breast cancer treatment case study

Case Study in Breast Cancer: Primary Treatment of HR-positive, HER2-negative Advanced Breast Cancer

—this case illustrates the current treatment paradigm for postmenopausal, hr-positive, her2-negative, advanced breast cancer that has not been previously treated..

By Pooja Murthy, MD Reviewed by Francisco J. Esteva, MD, PhD

Patient history and assessment

A 65-year-old woman with no previous medical history of breast cancer was referred to the medical oncology clinic for newly diagnosed metastatic breast cancer. Three months ago, she developed left breast pain and a palpable breast mass. Mammogram and ultrasound revealed a 5.2-cm left breast mass with an enlarged ipsilateral axillary lymph node. Core biopsy of the mass showed invasive ductal carcinoma, estrogen receptor (ER) 95% positive, progesterone receptor 85% positive, and HER2 negative. Fine needle aspiration of the axillary lymph node was positive for adenocarcinoma. Positron emission tomography/computed tomography was obtained, and revealed multiple 1- to 2-cm, positron emission tomography-avid pulmonary nodules and enlarged mediastinal and hilar lymph nodes, suspicious for metastases. Interventional radiology was consulted for core biopsy of one of the pulmonary nodules. The biopsy confirmed metastatic breast cancer, ER 95% positive, progesterone receptor 90% positive, and HER2 negative.

The patient presents to clinic feeling well today. She denies shortness of breath, pain, or fatigue. She works as a high school teacher and has good energy at work. There is no family history of breast, ovarian, or other cancers. She has no medical problems and takes no medications. Menarche was at age 11 and menopause was at age 50. There is no history of hormone replacement therapy. She has two children, with her first pregnancy at age 29.

On physical exam, her height is 62 inches (157 cm), and her weight is 148 lbs (67 kg). Her body mass index is 27. A large, 6-cm left breast mass is palpable with some overlying skin puckering. Nipples are everted bilaterally with no nipple discharge. Enlarged left axillary lymph nodes are also palpable. Lungs are clear to auscultation. Otherwise, results of the exam are unremarkable.

Laboratory results include an unremarkable comprehensive metabolic panel and complete blood count.

In summary, the patient is a 65-year-old postmenopausal woman with newly diagnosed, de novo, HR-positive, HER2-negative metastatic breast cancer. Metastatic sites include pulmonary nodules and lymph nodes, and metastatic disease has been biopsy proven. She has an excellent performance status and no comorbidities.

Treatment recommendations

At this initial medical oncology visit, the patient was placed on the combination regimen of letrozole 2.5 mg by mouth daily and palbociclib 125 mg by mouth daily for 21 days followed by a 7 day rest period (to complete a 28-day cycle). This regimen is supported by the National Comprehensive Cancer Network guidelines as first-line therapy for postmenopausal women with HR-positive metastatic breast cancer. Letrozole is an aromatase inhibitor, and palbociclib is a small-molecule inhibitor of the CDKs 4 and 6. The combination of these medications was evaluated in a randomized phase II trial (PALOMA-1), in which letrozole plus palbociclib was compared with letrozole plus placebo as first-line treatment for postmenopausal, HR-positive, HER2-negative, advanced breast cancer. Results showed a significantly improved progression-free survival (PFS) in the palbociclib group (20.2 months versus 10.2 months). There was a trend towards improved overall survival in this group, but it was not statistically significant. 1

Prior to prescribing letrozole plus palbociclib, the physician discussed the diagnosis of metastatic breast cancer, and that the goal of treatment is to slow the progression of disease, improve quality of life, and prolong survival. The patient was informed that metastatic breast cancers are rarely cured, but rather are managed like chronic disease with sequential therapy as the mainstay of treatment.

Common adverse effects of letrozole, including joint pains, hot flashes, and increased risk of osteoporosis, were discussed with the patient. Adequate vitamin D and calcium supplementation, as well as regular exercise, were strongly recommended as measures to protect against osteoporosis and improve overall health.

The common adverse effects of palbociclib include neutropenia, leucopenia, and fatigue. The medication is also associated with an increased risk of venous thromboembolism (1%–5% of patients treated with the medication). The patient was made aware of these potential adverse effects, and that regular monitoring of blood counts is necessary (every 2 weeks for the first two cycles, then prior to each cycle).

More than 1.5 million new cases of breast cancer are reported worldwide each year, of which 60% are HR-positive. Hormonal therapy has been the mainstay of treatment for HR-positive, HER2-negative advanced breast cancers. However, resistance to hormonal therapy eventually develops, which has prompted increasing interest in modulating the mechanisms of resistance. Disruptions in cell cycle regulation are one of the possible mechanisms of resistance to hormonal therapy, with orderly progression through the cell cycle controlled by a group of proteins that include CDKs.

Palbociclib is a reversible, oral, small molecule inhibitor of CDK 4 and 6. CDK 4 and 6 have a critical role in the regulation of the G1 to S transition, therefore inhibition of their activity can cause cell cycle arrest. 2 Preclinical data suggested that palbociclib has activity in HR-positive breast cancers in conjunction with antiestrogen medications. The PALOMA-1 trial was a randomized phase II study evaluating the safety and efficacy of palbociclib in combination with letrozole as first-line treatment of patients with advanced, ER-positive, HER2-negative breast cancer. 1 165 patients were randomized to palbociclib plus letrozole versus letrozole alone (plus placebo). Median PFS was 20.2 months in the palbociclib plus letrozole group and 10.2 months in the letrozole alone group (hazard ratio 0.49, P = .0004). There was a trend towards improved overall survival in the palbociclib group, but it was not statistically significant. Grade 3 to 4 neutropenia was reported in 54% of the patients in the palbociclib group versus 1% in the letrozole group, but no patients treated with palbociclib developed febrile neutropenia. Other significant adverse effects in the palbociclib group include pulmonary embolism (4%), back pain (2%), and diarrhea (2%). 1

Previous to the PALOMA-1 results, the preferred first-line treatment for advanced, HR-positive, HER2-negative breast cancer had been a nonsteroidal aromatase inhibitor or fulvestrant. Now, with the compelling PFS results from PALOMA-1, we would treat first line with palbociclib plus letrozole instead. As before, chemotherapy instead of hormonal therapy is recommended for patients with HR-positive, HER2-negative advanced breast cancer who have rapidly progressive disease and/or visceral crisis. 3

Palbociclib was also evaluated in the setting of endocrine-resistant advanced breast cancer (PALOMA-3). Postmenopausal patients with advanced HR-positive, HER2-negative breast cancer who had progressed on prior endocrine therapy were treated with palbociclib plus fulvestrant versus fulvestrant plus placebo. Similar to the PALOMA-1 results, the palbociclib group had a significantly improved PFS compared with the fulvestrant-alone group. This data therefore support the use of palbociclib plus fulvestrant for patients who have not yet been treated with palbociclib and have progressed on an aromatase inhibitor. 4

Investigational agents

Other CDK 4/6 inhibitors are also in development, including ribociclib and abemaciclib, with promising results so far. MONALEESA-2 is a phase III randomized, double-blind, multicenter trial involving 668 postmenopausal women with HR-positive, HER2-negative advanced breast cancer who had received no prior therapy for their advanced breast cancer. 5 The patients were randomized to ribociclib (600 mg daily, 3 weeks on and 1 week off), or placebo, in combination with letrozole 2.5 mg daily. 5 Results from a preplanned interim analysis showed a significantly improved PFS for the ribociclib group; therefore the Independent Data Monitoring Committee recommended stopping the trial early. Full results are pending. 6 MONALEESA-3 is an ongoing trial evaluating ribociclib in combination with fulvestrant compared with fulvestrant alone in men and postmenopausal women with HR-positive, HER2-negative advanced breast cancer who had received no or a maximum of one prior line of endocrine therapy. 6,7 Abemaciclib is another investigational CDK 4/6 inhibitor which is being evaluated in the MONARCH-1 trial trial as a single agent (in contrast to the PALOMA and MONALEESA-2 trials) in patients with HR-positive, HER2-negative metastatic breast cancer. 8 This is a phase II trial involving patients who were endocrine resistant and heavily pretreated for advanced disease. Abemaciclib induced a response rate of nearly 20% with a median PFS of 6 months in these patients. 9

Treatment outcomes

A follow-up complete blood count 4 weeks after treatment initiation was remarkable for an absolute neutrophil count (ANC) of 1200/mm 3 (grade 2 neutropenia). The patient was feeling well and was afebrile, so palbociclib was continued. Four weeks later, ANC had decreased to 800/mm 3 , and the patient remained afebrile. Since this was grade 3 neutropenia, palbociclib was held for 1 week and was resumed when ANC was >1000/mm 3 . Otherwise, she tolerated the treatment well with no other adverse effects. Computed tomography scans of the chest, abdomen, and pelvis were done 3 months after treatment initiation, and showed significant decrease in size of the breast mass, lymph nodes, and pulmonary nodules.

CDK 4/6 inhibitors, including palbociclib, ribociclib, and abemaciclib, are emerging as promising therapies for advanced, HR-positive, HER2-negative breast cancer, possibly through mediation of endocrine resistance. Palbociclib plus letrozole is approved for use in the first-line setting for advanced, postmenopausal, HR-positive breast cancer, backed by the PALOMA-1 trial results showing a significantly improved PFS in the palbociclib group. The combination of ribociclib and letrozole was also evaluated as first-line treatment in a similar patient population of postmenopausal women with advanced HR-positive, HER2-negative breast cancer, and showed a significantly improved PFS based on a preplanned interim analysis; final results from this trial are still pending.

Patient education

For patient education materials, visit:

• Metastatic Breast Cancer Network: Guide for the Newly Diagnosed
• Susan G. Komen’s Facts for Life: Clinical Trials

Published: December 20, 2016

• 1. Finn RS, Crown JP, Lang I, et al. The cyclin-dependent kinase 4/6 inhibitor palbociclib in combination with letrozole versus letrozole alone as first-line treatment of oestrogen receptor-positive, HER2-negative, advanced breast cancer (PALOMA-1/TRIO-18): a randomised phase 2 study. Lancet Onco l. 2015;16:25-35.
• 2. Finn RS, Aleshin A, Slamon DJ. Targeting the cyclin-dependent kinases (CDK) 4/6 in estrogen receptor-positive breast cancers. Breast Cancer Res . 2016;18:17.
• 3. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Breast Cancer, Version 2.2016. 5/6/16.
• 4. Turner NC, Ro J, André F, et al; PALOMA3 Study Group. Palbociclib in hormone-receptor-positive advanced breast cancer. N Engl J Med . 2015;373:209-219.
• 5. ClinicalTrials.gov. Study of efficacy and safety of LEE011 in postmenopausal women with advanced breast cancer (MONALEESA-2).
• 7. ClinicalTrials.gov. Study of efficacy and safety of LEE011 in men and postmenopausal women with advanced breast cancer. (MONALEESA-3).
• 8. ClinicalTrials.gov. A study of abemaciclib (LY2835219) in participants with previously treated breast cancer that has spread (MONARCH 1).
• 9. Dickler MN, Tolaney SM, Rugo HS, et al. MONARCH1: results from a phase II study of abemaciclib, a CDK4 and CDK6 inhibitor, as monotherapy, in patients with HR+/HER2- breast cancer, after chemotherapy for advanced disease. In: 2016 ASCO Annual Meeting; abstract number 510.

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• Patient Care & Health Information
• Diseases & Conditions
• Breast cancer

Receiving a mammogram

During a mammogram, you stand in front of an X-ray machine designed for mammography. A technician places your breast on a platform and positions the platform to match your height. The technician helps you position your head, arms and torso to allow an unobstructed view of your breast.

Getting a breast MRI involves lying face down on a padded scanning table. The breasts fit into a hollow space in the table. The hollow has coils that get signals from the MRI . The table slides into the large opening of the MRI machine.

Core needle biopsy

A core needle biopsy uses a long, hollow tube to obtain a sample of tissue. Here, a biopsy of a suspicious breast lump is being done. The sample is sent to a lab for testing and evaluation by doctors, called pathologists. They specialize in analyzing blood and body tissue.

Breast cancer diagnosis often begins with an exam and a discussion of your symptoms. Imaging tests can look at the breast tissue for anything that's not typical. To confirm whether there is cancer or not, a sample of tissue is removed from the breast for testing.

Breast exam

During a clinical breast exam, a healthcare professional looks at the breasts for anything that's not typical. This might include changes in the skin or to the nipple. Then the health professional feels the breasts for lumps. The health professional also feels along the collarbones and around the armpits for lumps.

A mammogram is an X-ray of the breast tissue. Mammograms are commonly used to screen for breast cancer. If a screening mammogram finds something concerning, you might have another mammogram to look at the area more closely. This more-detailed mammogram is called a diagnostic mammogram. It's often used to look closely at both breasts.

Breast ultrasound

Ultrasound uses sound waves to make pictures of structures inside the body. A breast ultrasound may give your healthcare team more information about a breast lump. For example, an ultrasound might show whether the lump is a solid mass or a fluid-filled cyst. The healthcare team uses this information to decide what tests you might need next.

MRI machines use a magnetic field and radio waves to create pictures of the inside of the body. A breast MRI can make more-detailed pictures of the breast. Sometimes this method is used to look closely for any other areas of cancer in the affected breast. It also might be used to look for cancer in the other breast. Before a breast MRI , you usually receive an injection of dye. The dye helps the tissue show up better in the images.

Removing a sample of breast cells for testing

A biopsy is a procedure to remove a sample of tissue for testing in a lab. To get the sample, a healthcare professional puts a needle through the skin and into the breast tissue. The health professional guides the needle using images created with X-rays, ultrasound or another type of imaging. Once the needle reaches the right place, the health professional uses the needle to draw out tissue from the breast. Often, a marker is placed in the spot where the tissue sample was removed. The small metal marker will show up on imaging tests. The marker helps your healthcare team monitor the area of concern.

Testing cells in the lab

The tissue sample from a biopsy goes to a lab for testing. Tests can show whether the cells in the sample are cancerous. Other tests give information about the type of cancer and how quickly it's growing. Special tests give more details about the cancer cells. For example, tests might look for hormone receptors on the surface of the cells. Your healthcare team uses the results from these tests to make a treatment plan.

Staging breast cancer

Once your healthcare team diagnoses your breast cancer, you may have other tests to figure out the extent of the cancer. This is called the cancer's stage. Your healthcare team uses your cancer's stage to understand your prognosis.

Complete information about your cancer's stage may not be available until after you undergo breast cancer surgery.

Tests and procedures used to stage breast cancer may include:

• Blood tests, such as a complete blood count and tests to show how well the kidneys and liver are working.
• Positron emission tomography scan, also called a PET scan.

Not everyone needs all of these tests. Your healthcare team picks the right tests based on your specific situation.

Breast cancer stages range from 0 to 4. A lower number means the cancer is less advanced and more likely to be cured. Stage 0 breast cancer is cancer that is contained within a breast duct. It hasn't broken out to invade the breast tissue yet. As the cancer grows into the breast tissue and gets more advanced, the stages get higher. A stage 4 breast cancer means that the cancer has spread to other parts of the body.

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Breast cancer care at Mayo Clinic

• Breast cancer staging
• Breast cancer types
• 3D mammogram
• BRCA gene test
• Breast cancer risk assessment
• Breast self-exam for breast awareness
• Chest X-rays
• Complete blood count (CBC)
• Molecular breast imaging
• Positron emission tomography scan
• Sentinel node biopsy

Breast cancer treatment often starts with surgery to remove the cancer. Most people with breast cancer will have other treatments after surgery, such as radiation, chemotherapy and hormone therapy. Some people may have chemotherapy or hormone therapy before surgery. These medicines can help shrink the cancer and make it easier to remove.

Your treatment plan will depend on your particular breast cancer. Your healthcare team considers the stage of the cancer, how quickly it's growing and whether the cancer cells are sensitive to hormones. Your care team also considers your overall health and what you prefer.

There are many options for breast cancer treatment. It can feel overwhelming to consider all the options and make complex decisions about your care. Consider seeking a second opinion from a breast specialist in a breast center or clinic. Talk to breast cancer survivors who have faced the same decision.

• Breast cancer surgery

A lumpectomy involves removing the cancer and some of the healthy tissue that surrounds it. This illustration shows one possible incision that can be used for this procedure, though your surgeon will determine the approach that's best for your particular situation.

During a total mastectomy, the surgeon removes the breast tissue, nipple, areola and skin. This procedure also is known as a simple mastectomy. Other mastectomy procedures may leave some parts of the breast, such as the skin or the nipple. Surgery to create a new breast is optional. It may be done at the same time as mastectomy surgery or it can be done later.

Sentinel node biopsy identifies the first few lymph nodes into which a tumor drains. The surgeon uses a harmless dye and a weak radioactive solution to locate the sentinel nodes. The nodes are removed and tested for signs of cancer.

Breast cancer surgery typically involves a procedure to remove the breast cancer and a procedure to remove some nearby lymph nodes. Operations used to treat breast cancer include:

Removing the breast cancer. A lumpectomy is surgery to remove the breast cancer and some of the healthy tissue around it. The rest of the breast tissue isn't removed. Other names for this surgery are breast-conserving surgery and wide local excision. Most people who have a lumpectomy also have radiation therapy.

Lumpectomy might be used to remove a small cancer. Sometimes you can have chemotherapy before surgery to shrink the cancer so that lumpectomy is possible.

Removing all of the breast tissue. A mastectomy is surgery to remove all breast tissue from a breast. The most common mastectomy procedure is total mastectomy, also called simple mastectomy. This procedure removes all of the breast, including the lobules, ducts, fatty tissue and some skin, including the nipple and areola.

Mastectomy might be used to remove a large cancer. It also might be needed when there are multiple areas of cancer within one breast. You might have a mastectomy if you can't have or don't want radiation therapy after surgery.

Some newer types of mastectomy procedures might not remove the skin or nipple. For instance, a skin-sparing mastectomy leaves some skin. A nipple-sparing mastectomy leaves the nipple and the skin around it, called the areola. These newer operations can improve the look of the breast after surgery, but they aren't options for everyone.

• Removing a few lymph nodes. A sentinel node biopsy is an operation to take out some lymph nodes for testing. When breast cancer spreads, it often goes to the nearby lymph nodes first. To see if the cancer has spread, a surgeon removes some of the lymph nodes near the cancer. If no cancer is found in those lymph nodes, the chance of finding cancer in any of the other lymph nodes is small. No other lymph nodes need to be removed.
• Removing several lymph nodes. Axillary lymph node dissection is an operation to remove many lymph nodes from the armpit. Your breast cancer surgery might include this operation if imaging tests show the cancer has spread to the lymph nodes. It also might be used if cancer is found in a sentinel node biopsy.
• Removing both breasts. Some people who have cancer in one breast may choose to have their other breast removed, even if it doesn't have cancer. This procedure is called a contralateral prophylactic mastectomy. It might be an option if you have a high risk of getting cancer in the other breast. The risk might be high if you have a strong family history of cancer or have DNA changes that increase the risk of cancer. Most people with breast cancer in one breast will never get cancer in the other breast.

Complications of breast cancer surgery depend on the procedures you choose. All operations have a risk of pain, bleeding and infection. Removing lymph nodes in the armpit carries a risk of arm swelling, called lymphedema.

You may choose to have breast reconstruction after mastectomy surgery. Breast reconstruction is surgery to restore shape to the breast. Options might include reconstruction with a breast implant or reconstruction using your own tissue. Consider asking your healthcare team for a referral to a plastic surgeon before your breast cancer surgery.

• Radiation therapy

External beam radiation uses high-powered beams of energy to kill cancer cells. Beams of radiation are precisely aimed at the cancer using a machine that moves around your body.

Radiation therapy treats cancer with powerful energy beams. The energy can come from X-rays, protons or other sources.

For breast cancer treatment, the radiation is often external beam radiation. During this type of radiation therapy, you lie on a table while a machine moves around you. The machine directs radiation to precise points on your body. Less often, the radiation can be placed inside the body. This type of radiation is called brachytherapy.

Radiation therapy is often used after surgery. It can kill any cancer cells that might be left after surgery. The radiation lowers the risk of the cancer coming back.

Side effects of radiation therapy include feeling very tired and having a sunburn-like rash where the radiation is aimed. Breast tissue also may look swollen or feel more firm. Rarely, more-serious problems can happen. These include damage to the heart or lungs. Very rarely, a new cancer can grow in the treated area.

• Chemotherapy

Chemotherapy treats cancer with strong medicines. Many chemotherapy medicines exist. Treatment often involves a combination of chemotherapy medicines. Most are given through a vein. Some are available in pill form.

Chemotherapy for breast cancer is often used after surgery. It can kill any cancer cells that might remain and lower the risk of the cancer coming back.

Sometimes chemotherapy is given before surgery. The chemotherapy might shrink the breast cancer so that it's easier to remove. Chemotherapy before surgery also might control cancer that spreads to the lymph nodes. If the lymph nodes no longer show signs of cancer after chemotherapy, surgery to remove many lymph nodes might not be needed. How the cancer responds to chemotherapy before surgery helps the healthcare team make decisions about what treatments might be needed after surgery.

When the cancer spreads to other parts of the body, chemotherapy can help control it. Chemotherapy may relieve symptoms of an advanced cancer, such as pain.

Chemotherapy side effects depend on which medicines you receive. Common side effects include hair loss, nausea, vomiting, feeling very tired and having an increased risk of getting an infection. Rare side effects can include premature menopause and nerve damage. Very rarely, certain chemotherapy medicines can cause blood cell cancer.

Hormone therapy

Hormone therapy uses medicines to block certain hormones in the body. It's a treatment for breast cancers that are sensitive to the hormones estrogen and progesterone. Healthcare professionals call these cancers estrogen receptor positive and progesterone receptor positive. Cancers that are sensitive to hormones use the hormones as fuel for their growth. Blocking the hormones can cause the cancer cells to shrink or die.

Hormone therapy is often used after surgery and other treatments. It can lower the risk that the cancer will come back.

If the cancer spreads to other parts of the body, hormone therapy can help control it.

Treatments that can be used in hormone therapy include:

• Medicines that block hormones from attaching to cancer cells. These medicines are called selective estrogen receptor modulators.
• Medicines that stop the body from making estrogen after menopause. These medicines are called aromatase inhibitors.
• Surgery or medicines to stop the ovaries from making hormones.

Hormone therapy side effects depend on the treatment you receive. The side effects can include hot flashes, night sweats and vaginal dryness. More-serious side effects include a risk of bone thinning and blood clots.

Targeted therapy

Targeted therapy uses medicines that attack specific chemicals in the cancer cells. By blocking these chemicals, targeted treatments can cause cancer cells to die.

The most common targeted therapy medicines for breast cancer target the protein HER2 . Some breast cancer cells make extra HER2 . This protein helps the cancer cells grow and survive. Targeted therapy medicine attacks the cells that are making extra HER2 and doesn't hurt healthy cells.

Many other targeted therapy medicines exist for treating breast cancer. Your cancer cells may be tested to see whether these medicines might help you.

Targeted therapy medicines can be used before surgery to shrink a breast cancer and make it easier to remove. Some are used after surgery to lower the risk that the cancer will come back. Others are used only when the cancer has spread to other parts of the body.

Immunotherapy

Immunotherapy is a treatment with medicine that helps the body's immune system to kill cancer cells. The immune system fights off diseases by attacking germs and other cells that shouldn't be in the body. Cancer cells survive by hiding from the immune system. Immunotherapy helps the immune system cells find and kill the cancer cells.

Immunotherapy might be an option for treating triple-negative breast cancer. Triple-negative breast cancer means that the cancer cells don't have receptors for estrogen, progesterone or HER2 .

Palliative care

Palliative care is a special type of healthcare that helps you feel better when you have a serious illness. If you have cancer, palliative care can help relieve pain and other symptoms. A team of healthcare professionals provides palliative care. The team can include doctors, nurses and other specially trained professionals. Their goal is to improve quality of life for you and your family.

Palliative care specialists work with you, your family and your care team to help you feel better. They provide an extra layer of support while you have cancer treatment. You can have palliative care at the same time as strong cancer treatments, such as surgery, chemotherapy or radiation therapy.

When palliative care is used along with all of the other appropriate treatments, people with cancer may feel better and live longer.

• Brachytherapy
• Breast cancer supportive therapy and survivorship
• Chemotherapy for breast cancer
• Hormone therapy for breast cancer
• Precision medicine for breast cancer
• Radiation therapy for breast cancer
• Common questions about breast cancer treatment
• Paulas story A team approach to battling breast cancer

Clinical trials

Explore Mayo Clinic studies testing new treatments, interventions and tests as a means to prevent, detect, treat or manage this condition.

Alternative medicine

No alternative medicine treatments have been found to cure breast cancer. But complementary and alternative medicine therapies may help you cope with side effects of treatment.

Alternative medicine for fatigue

Many people with breast cancer have fatigue during and after treatment. This feeling of being very tired and worn down can continue for years. When combined with care from your healthcare team, complementary and alternative medicine therapies may help relieve fatigue.

Talk with your healthcare team about:

• Expressing your feelings. Find an activity that allows you to write about or discuss your emotions. Examples include writing in a journal, participating in a support group or talking to a counselor.
• Gentle exercise. If you get the OK from your healthcare team, start with gentle exercise a few times a week. Add more exercise, as you feel up to it. Consider walking, swimming, yoga and tai chi.
• Managing stress. Take control of the stress in your daily life. Try stress-reduction techniques such as muscle relaxation, visualization, and spending time with friends and family.

Coping and support

Some breast cancer survivors say their diagnosis felt overwhelming at first. It can be stressful to feel overwhelmed at the same time you need to make important decisions about your treatment. In time, you'll find ways to cope with your feelings. Until you find what works for you, it might help to:

Learn enough about your breast cancer to make decisions about your care

If you'd like to know more about your breast cancer, ask your healthcare team for the details of your cancer. Write down the type, stage and hormone receptor status. Ask for good sources of information where you can learn more about your treatment options.

Knowing more about your cancer and your options may help you feel more confident when making treatment decisions. Still, some people don't want to know the details of their cancer. If this is how you feel, let your care team know that too.

Talk with other breast cancer survivors

You may find it helpful and encouraging to talk to others who have been diagnosed with breast cancer. Contact a cancer support organization in your area to find out about support groups near you or online. In the United States, you might start with the American Cancer Society.

Find someone to talk with about your feelings

Find a friend or family member who is a good listener. Or talk with a clergy member or counselor. Ask your healthcare team for a referral to a counselor or other professional who works with people who have cancer.

Keep your friends and family close

Your friends and family can provide a crucial support network for you during your cancer treatment.

As you begin telling people about your breast cancer diagnosis, you'll likely get many offers for help. Think ahead about things you may want help with. Examples include listening when you want to talk or helping you with preparing meals.

Preparing for your appointment

Make an appointment with a doctor or other healthcare professional if you have any symptoms that worry you. If an exam or imaging test shows you might have breast cancer, your healthcare team will likely refer you to a specialist.

Specialists who care for people with breast cancer include:

• Breast health specialists.
• Breast surgeons.
• Doctors who specialize in diagnostic tests, such as mammograms, called radiologists.
• Doctors who specialize in treating cancer, called oncologists.
• Doctors who treat cancer with radiation, called radiation oncologists.
• Genetic counselors.
• Plastic surgeons.

What you can do to prepare

• Write down any symptoms you're experiencing, including any that may seem unrelated to the reason for which you scheduled the appointment.
• Write down key personal information, including any major stresses or recent life changes.
• Write down your family history of cancer. Note any family members who have had cancer. Note how each member is related to you, the type of cancer, the age at diagnosis and whether each person survived.
• Make a list of all medicines, vitamins or supplements that you're taking.
• Keep all of your records that relate to your cancer diagnosis and treatment. Organize your records in a binder or folder that you can take to your appointments.
• Consider taking a family member or friend along. Sometimes it can be difficult to absorb all the information provided during an appointment. Someone who accompanies you may remember something that you missed or forgot.
• Write down questions to ask your healthcare professional.

Questions to ask your doctor

Your time with your healthcare professional is limited. Prepare a list of questions so that you can make the most of your time together. List your questions from most important to least important in case time runs out. For breast cancer, some basic questions to ask include:

• What type of breast cancer do I have?
• What is the stage of my cancer?
• Can you explain my pathology report to me? Can I have a copy for my records?
• Do I need any more tests?
• What treatment options are available for me?
• What are the benefits from each treatment you recommend?
• What are the side effects of each treatment option?
• Will treatment cause menopause?
• How will each treatment affect my daily life? Can I continue working?
• Is there one treatment you recommend over the others?
• How do you know that these treatments will benefit me?
• What would you recommend to a friend or family member in my situation?
• How quickly do I need to make a decision about cancer treatment?
• What happens if I don't want cancer treatment?
• What will cancer treatment cost?
• Does my insurance plan cover the tests and treatment you're recommending?
• Should I seek a second opinion? Will my insurance cover it?
• Are there any brochures or other printed material that I can take with me? What websites or books do you recommend?
• Are there any clinical trials or newer treatments that I should consider?

In addition to the questions that you've prepared, don't hesitate to ask other questions you think of during your appointment.

What to expect from your doctor

Be prepared to answer some questions about your symptoms and your health, such as:

• When did you first begin experiencing symptoms?
• Have your symptoms been continuous or occasional?
• How severe are your symptoms?
• What, if anything, seems to improve your symptoms?
• What, if anything, appears to worsen your symptoms?

Living with breast cancer?

Connect with others like you for support and answers to your questions in the Breast Cancer support group on Mayo Clinic Connect, a patient community.

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• Cancer facts and figures 2023. American Cancer Society. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2023-cancer-facts-figures.html. Accessed Aug. 9, 2023.
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Behind the Breakthroughs: How Can We Better Treat Younger Breast Cancer Patients?

BCRF investigator Dr. Sherene Loi talks about the landmark SOFT trial, international collaboration, and how breast cancer is affecting younger women

When younger women are diagnosed with breast cancer, they generally have poorer outcomes than older women. Incidence is on the rise for young women in the U.S.: In the last 10 years alone, there has been an eight percent increase in diagnoses in women under 40—underscoring the need for research focused on these patients. 

Researchers like Dr. Sherene Loi , a BCRF investigator since 2015, are working to uncover why this is happening—and how we can better treat the disease, reduce recurrence, and prevent it entirely. Through the landmark BCRF-supported SOFT trial, Dr. Loi and her colleagues have already developed treatment strategies that have improved outcomes for women under 40. Now, she’s working to understand the immune microenvironment of breasts cancers in younger women—including the role of tumor-infiltrating lymphocytes—and continue to improve treatment.

Below is an edited transcript of Dr. Loi’s conversation with BCRF staffer and breast cancer thriver Sadia Zapp.

Let's start with tumor-infiltrating lymphocytes (TILs), a major focus of your research. What are they?

TILs are immune cells. When a pathologist looks down the microscope they can see the breast cancer and all the surrounding tissue in a row that surrounds the breast cancer. And they can also see lots of different cells apart from cancer cells, and some of these cells are immune cells. And we call these cells tumor-infiltrating lymphocytes or TILs.

How are TILs being used in breast cancer?

A long time ago we looked at the quantity of immune cells [for people with cancer] and correlated that to whether they had recurrences from their breast cancer in the future. And it was actually quite remarkable, because we did find in these first studies that the amount of immune cells did predict whether you did better from your breast cancer. So, the more immune cells you had, we [realized] that your immune system was actively fighting the cancer. And then once you remove the tumor, your immune system was able to, with the one or the other treatment you receive, mop up the rest of the cancer cells and protect you from cancer recurrence in the long term. So that's subsequently been reproduced by many other investigators, and it really seems to be particular for patients with triple-negative breast cancer (TNBC) , [which is more common in younger patients]. This also seems to be the case with certain types of hormone receptor–positive breast cancer. We're exploring that in more detail, using the [BCRF-supported] SOFT trial .

But getting back to TNBC. We’re in an era now of immunotherapy. We've done quite a lot of work with other investigators that we know that your level of TIL does suggest that you might have a higher rate of pathological complete response [with a drug called] Keytruda and a shorter duration of chemotherapy. So, my belief at the moment is that if we can see your immune system is active, we can enhance that with agents such as Keytruda. And ultimately, we will be able to safely shorten the type of chemotherapy that you require. At the moment, everyone requires a big, intensive chemotherapy regimen. But I think for patients who have existing immune cells or evidence that the immune systems are really active, then they won't need that much additional chemotherapy. The Keytruda will kind of do the job for us.

Why is hormone-receptor positive cancer more aggressive in younger women?

I have a number of theories. So, for younger people to develop cancer, it has to be a little bit more aggressive to get through the natural barriers that we all have to prevent cancer from occurring. For women who are young, they're potentially of childbearing age. They'd have very strong menstrual cycle, and the breast changes during that cycle. So, you have your menstrual cycles, and every month you've got this growth in your breast. And then you have cells die, but a cell that's learned to not die every month is getting this strong growth signal. Naturally women’s fertility drops after the age of 40. We see that breast cancers seem to be a little bit less aggressive in women as they reach their mid-40s and move into a natural menopause.

There are other things that we don't really know, but we suspect. In countries such as America and Australia, women are having children later. There are also some issues with obesity, alcohol, etc. So that probably contributes as well. They're not breastfeeding for long, and we know that breastfeeding particularly does attenuate the risk of triple-negative breast cancer. And other things that we don't really understand like pollution or our environment may be contributing to some of the increased rates or younger onset breast cancer we're seeing. And also, maybe why they're a little bit more aggressive. So, there's potentially lots of reasons there. And no one really knows the answer. It's probably multifactorial, unfortunately, but with trying to study the individual parts to see if making a difference to one of those parts will help a lot.

The SOFT trial and its sister trial TEXT are happening on this massive international scale with more than 5,000 women enrolled from across 500 hospitals and 27 countries. Why is global collaboration so important in breast cancer research?

These studies, which were managed by the International Breast Cancer Study Group are a collaboration between Europe, America, Australia, and many countries in the world. It was really a remarkable feat for the global breast cancer community to answer an important question that is still highly relevant today. Most premenopausal women will receive concurrent ovarian function [to suppress estrogen]. If a woman’s cancer is high risk, that makes a huge difference to their outcomes, even though we are trying to obviously deal with some of the side effects. International collaboration is essential for all good breast cancer research. Getting people together in the one room is really important, and BCRF does that well.

What is your biggest hope for your work and for the future of breast cancer?

I'm hoping in the future, we might incorporate more biomarkers, because I feel we have a lot of biomarkers, but we don't really look to incorporate [them all] in routine practice. I'm hoping in the future, we will be able to incorporate TIL, tumor size, liquid biopsies and more to really understand who needs lesser treatment. We'll be able to individualize therapies for our patients in the future. And, I really do think that hopefully, we will understand a lot more about how we can prevent breast cancer in the future with some of the factors I’ve been talking about. We don't want to just treat, we want to prevent.

Why is BCRF funding specifically so important to your work?

BCRF gives you a lot of freedom to try out some riskier ideas. Fortunately for me, we did one of the first papers on single-cell RNA sequencing. And that was very successful, but at the time, it was extremely expensive. So, BCRF allowed us to work that technique up and apply that to human TILs. So that was very labor intensive and very expensive. But if I didn't have BCRF funding, no one would have given me money to do that. So that was really very helpful and helped us understand a lot about the TIL and certain subsets of the TIL. The whole community is lovely, and there's lots of interaction and networking and discussion about science. The annual meetings are really very motivational. From a scientific and research point of view, you really come back thinking, “I need to do this and this and this.” And [BCRF] gives you the freedom to explore a few things that you think might pay off. I've been very grateful for the support of BCRF. They're just such a fantastic organization.

If there's one takeaway from our conversation, or if there's one thing you hope patients walk away with, what would that be?

I think the cure is near for breast cancer. So hopefully the next generation of women won't have to suffer as much as ours.

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Case 1: 48-Year-Old Patient With HER2+ Metastatic Breast Cancer

EP: 1 . Best Practices: HER2+ MBC With Brain Mets

EP: 2 . Frontline Standards of Care for HER2+ MBC

EP: 3 . Case 1: 48-Year-Old Patient With HER2+ Metastatic Breast Cancer

EP: 4 . Treatment Strategies for Relapsed/Refractory HER2+ MBC

EP: 5 . Case 2: 61-Year-Old Patient With R/R HER2+ MBC

EP: 6 . Cancer Network Around the Practice: Relapsed/Refractory HER2+ Metastatic Breast Cancer

Adam M. Brufsky, MD, PhD: Let’s talk about this case. This is a 48-year-old woman who presented to her primary care physician a number of years ago with a lump in her breast. She had a 4.4-cm left breast mass and 3 palpable axillary lymph nodes. Her ultrasound and mammogram confirmed these physical findings.

She was referred to a medical oncologist and had a core needle biopsy that showed ER- [estrogen receptor-negative]/PR- [progesterone receptor-negative], HER2 [human epidermal growth factor receptor 2]-positive by IHC [immunohistochemistry score] that was 3+. A CT scan of the chest, abdomen, and pelvis showed 3 liver lesions, the largest being 3.1 cm. This is the de novo patient we always talk about. She had an MRI of the brain and it was negative for metastasis. She received 6 cycles of THP [docetaxel, trastuzumab, pertuzumab], followed by HP [trastuzumab, pertuzumab] for another 12 months. That’s 18 months of therapy.

She had a partial response in her breast mass, and her liver lesions fully responded. Later, she suddenly began to have rapid unexplained weight loss. The CT scan only showed 2 new liver lesions, so not quite the symptom I would imagine. She then got a brain MRI that showed about 30 widely scattered lesions, the largest being about 0.5 or 0.6 [cm]. They have all these little punctate ones; you’ve all seen those.

The question is: what treatment would you give this person? Let’s say the brain MRI shows 3 lesions, all in the frontal cortex, with the largest being 1.5 cm. That makes it a little bit of a different question because if there are widely scattered lesions, we’re not going to want to do SRS [stereotactic radiosurgery]. We are probably going to want to do whole brain radiation. Let’s say she’s asymptomatic with no edema. The polling question is: what treatment would you recommend? T-DM1 [trastuzumab emtansine], tucatinib/trastuzumab/capecitabine, SRS to the brain metastases, clinical trial, or other.

You guys could answer that question. Let me start with Sara. How would you approach this?

Sara A. Hurvitz, MD, FACP: They’re not totally mutually exclusive, right? You could do SRS and switch systemic therapy. She is progressing systemically in the liver, so I think switching systemic therapy makes sense. I like tucatinib because it does penetrate the blood-brain barrier, but I would still be tempted and would probably talk to my radiation oncology and neurosurgery colleagues. We’d probably end up doing both the SRS and tucatinib-based therapy.

Adam M. Brufsky, MD, PhD: That’s reasonable. VK, do you have any other comments on this?

VK Gadi, MD, PhD: Yes, I agree. The tolerability of the regimen is good. You might even give this lady an opportunity to fly without SRS and have that in your back pocket. If you’re not seeing control, you can go to SRS at a later time. I don’t think there’s a wrong answer here. You could probably do it both ways.

Adam M. Brufsky, MD, PhD: Neil, do you have something to add?

Neil M. Iyengar, MD: No. She fits perfectly into the HER2CLIMB population, so I agree with everything that has been said because there is demonstrated activity of the tucatinib-based regimen in terms of CNS [central nervous system] response. Coupling that with SRS is reasonable. This is the patient we were talking about earlier with whom we would discuss foregoing local therapy to the brain. That’s a reasonable discussion here. It’s a tricky poll question because my kneejerk response would be to put her on a clinical trial. We should all be trying to prioritize clinical trials, but in the absence of that clinical availability, tucatinib plus or minus radiation is a reasonable option.

Adam M. Brufsky, MD, PhD: There’s a clinical trial that’s great; it’s not scientifically spectacular, but clinically, it’s fabulous. I believe it’s called DESTINY. In fact, I put a patient on it today with trastuzumab deruxtecan and tucatinib together. That’s a great trial that’s going to accrue quickly. If we could put as many people as we can on that, we can answer the clinical question quickly. I would agree.

I have 1 last question before we go on to the last 25 minutes and the last segment. What do you tell people about [adverse] effects? Are you seeing a lot of [adverse] effects with tucatinib? Do you have to dose reduce it at all when you give it? These are questions people who haven’t had a lot of experience with it usually ask. I’ll start with Neil. Do you see a lot of diarrhea? Do you have to dose reduce with tucatinib?

Neil M. Iyengar, MD: In my experience, this regimen is quite tolerable. We all, as oncologists, have unfortunately become very comfortable with managing diarrhea, along with oncology nursing and so forth. What I have found with the tucatinib-based regimen is that with the initiation of antidiarrheal agents, the diarrhea usually resolves or improves pretty quickly. People have to know about it and be prepared to deal with it immediately. It does come on early, usually within the first cycle.

The other consideration to keep in mind with tucatinib is that many of the [adverse] effects are likely related to capecitabine. We’re all very comfortable with managing capecitabine-related toxicity and dose modifying capecitabine as needed. We see in the HER2CLIMB data that patients in the tucatinib arm stayed on study longer and were therefore exposed to capecitabine for longer than those in the placebo arm. I think a lot of the toxicities are familiar ones that are related to capecitabine and are quite manageable.

Adam M. Brufsky, MD, PhD: Great. VK and Sara, do you have any other comments about this toxicity? Do you see any toxicity at all with this, more than you’d expect?

Sara A. Hurvitz, MD, FACP: It’s well tolerated. About 13% had grade 3/4 diarrhea. Before getting on this call, I had to dose reduce a patient on this therapy. It’s hard to tell. On the clinical trial we enrolled patients, and I had a patient on who had severe colitis, hospitalization, etc, and I was sure she was getting tucatinib. When she was unblinded after the data came out, it turned out that she wasn’t on tucatinib. She was on placebo. I completely agree that these are [adverse] effects we’re used to with capecitabine. There’s not a whole lot of difference. Tucatinib is pretty well tolerated.

VK Gadi, MD, PhD: I agree. I think the capecitabine is the real culprit. The people on the trial were actually on it for so much longer that the toxicities from capecitabine emerged ongoing on the study. That has been my experience. Something important we don’t yet have is the PRO [patient-reported outcomes] data from these studies. A lot of my colleagues, especially those in communities where patients come in from a long way away, know that this is a tremendous pill burden with this regimen. Sometimes a parenteral regimen that you’re giving every 3 weeks is better for patients. I’m curious to see what those data look like when they come out. From our perspective as physicians, this is a slam dunk and it’s easy to give, but that’s not always the perspective that matters.

Adam M. Brufsky, MD, PhD: I agree.

Sara A. Hurvitz, MD, FACP: Yes, I think the quality of life PRO data were presented at the San Antonio [Breast Cancer Symposium]. I’m trying to pull it up. I don’t have it right at my fingertips, but my recollection was that it looked fairly good, that the quality of life was maintained.

Adam M. Brufsky, MD, PhD: Right, but they’re not going to tell you that they’re struggling to take all those pills. It’s a lot.

Sara A. Hurvitz, MD, FACP: That’s true.

Adam M. Brufsky, MD, PhD: It’s about 9 pills a day, which is a lot.

Neil M. Iyengar, MD: The quality of life data are always interesting because the end point of choice is time to deterioration and whether we are avoiding that. I think that’s a fairly low bar.

Adam M. Brufsky, MD, PhD: Exactly. Women are going to do anything they can.

Transcript edited for clarity.

Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model

Affiliations.

• 1 General Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
• 2 Department of Breast Surgery (Surgical Oncology), Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
• 3 Rehabilitation Medicine Center, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
• PMID: 36387193
• PMCID: PMC9659609
• DOI: 10.3389/fonc.2022.897984

Breast cancer is one of the most common tumors in women. Despite various treatments, the survival of patients with advanced breast cancer is still disappointing. Furthermore, finding an effective individualized treatment for different kinds of patients is a thorny problem. Patient-derived tumor-like cell clusters were reported to be used for personalized drug testing in cancer therapy and had a prediction accuracy of 93%. However, there is still a lack of case reports about its application in the individualized treatment of breast cancer patients. Here, we described four cases of individualized treatment for advanced breast cancer using the patient-derived tumor-like cell cluster model (PTC model). In these four cases, the PTC model showed a good predictive effect. The tumor size was reduced significantly or even disappeared completely through clinical, radiological, or pathological evaluation with the help of the PTC model for selecting an individualized therapy regimen. Furthermore, the drug sensitivity test results of the PTC model were consistent with pathological molecular typing and the actual clinical drug resistance of the patients. In summary, our case report first evaluated the application value of the PTC model in advanced breast cancer, and the PTC model might be used as an efficient tool for drug resistance screening and for selecting a better personalized treatment, although further study is needed to prove the validity and stability of the PTC model in drug screening.

Keywords: breast cancer; case report; drug testing; individualized treatment; patient-derived tumor model.

Copyright © 2022 Xia, Chen, Fang, Wu, Zhang and Yuan.

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• Case Reports

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Case report article, case report: young adults with breast cancer: a case series of fertility preservation management and literature review.

• 1 Department of Obstetrics and Gynecology, St. Marianna University School of Medicine, Kawasaki, Japan
• 2 Department of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
• 3 Laboratory of Cancer and Reproductive Science, Department of Frontier Medicine, St. Marianna University, School of Medicine, Kawasaki, Japan
• 4 Department of Obstetrics and Gynecology, Jikei University School of Medicine, Tokyo, Japan

Breast cancer comprised at least 21.8% of the overall cancer among young adult (YA) women and became the leading cancer in this group in Japan, with 50% adolescent and YAs being diagnosed and 15–44-year-old women showing excellent 5-year survival. Surgical-chemoradiation therapy often results in excellent survivorship with an increased incidence of treatment-induced subfertility. Therefore, adding fertility preservation (FP) to the primary cancer treatment is necessary. Herein, we reported a series of cases of YA women with breast cancer who opted for FP, where their option was tailored accordingly. To date, the selection of oocytes, embryos and ovarian tissue is widely available as an FP treatment. PGT could reduce the risk of BRCA mutation transmission amongst BRCA carriers before pregnancy planning. Otherwise, gonadotropin-releasing hormone analog has no gonadoprotective effect and thus should not be considered as an FP option.

Introduction

Breast cancer comprised at least 21.8% of the overall cancer among young adult (YA) women and became the leading cancer in this group in Japan, followed by cervical cancer at 12.8% and malignant germ cells and other gonadal tumors at 8.5% ( 1 ). Overall, 50% of breast cancer cases were among adolescent and YAs (AYA); in addition, the age group of 15–44 years old showed an excellent 5-year survival rate of almost 90% in localized cancer group, 80% in regional cancer group, and 35% in distant metastasis cancer group ( 2 ). The combination of surgical and chemoradiation therapy in managing breast cancer often results in excellent survivorship. However, it could also lead to a reduction in fecundity. Therefore, considering the increased incidence of chemotherapy-induced subfertility that leads to a devastating quality of life, adding fertility preservation (FP) to the primary cancer treatment is deemed essential in oncofertility services ( 3 ). A prompt strategy is paramount to evaluate FP's best option tailored to age, cancer stage age, and marital status. Herein, we reported a series of cases of YA women with breast cancer who opted for FP, where their option was tailored accordingly.

Case Series

Our first case is a 31-year-old single and nulliparous woman with newly diagnosed stage I of right breast cancer (T1N0M0). Her hormone receptors were found positive (ER+/PR+) with HERS2-ve and Ki67 < 10%. Therefore, she was planned for right mastectomy and sentinel axillary lymph nodes biopsy, followed by possible chemotherapy (Taxane-based group if the nodes were positive). She was also planned for tamoxifen (TAM) therapy for at least 10 years. Therefore, she was referred to us for FP with an interval of 10 weeks before operation intervention. Her level of anti-Mullerian hormone (AMH) was 4.51 ng/dL. Given that she was single with applicable timeframe, a choice of oocyte cryopreservation was deemed appropriate. She was keen to start controlled ovarian stimulation (COS) as soon as possible; thus, the random start (RS) protocol with an aromatase inhibitor (AI) was offered. She managed to cryopreserve 10 oocytes and is currently still ongoing second COS before embarking on surgery next month. Although the chemotherapy is not yet planned, she was referred for possible long-term endocrine therapy for 10 years. By the time of treatment completion, the AMH could decline due to aging. Given that she has a borderline AMH level, the prediction of a further decrease in AMH level made the FP essential in managing her condition. However, oocyte cryopreservation could help motivate compliance to the primary treatment disease as her fertility ability has been covered.

Our second case is a 28-year-old married woman with preliminary diagnosis of left breast cancer upon tissue biopsy. Unfortunately, her lymph nodes tissue was found to be positive. Thus, she was categorized as T2N1M0. However, her hormonal subtype was ER/PR+. HERS2 was also positive and Ki67 > 20% (luminar B-like tumor). She was counseled for a left mastectomy with unilateral axillary lymph node clearance, followed by chemotherapy; anthracycline-based group or combination with taxane-based regime depending on the final histopathology examination and immunochemistry assessment of post-surgical specimen. She was also counseled regarding the possibility of anti-HER2 therapy for 1 year, followed by TAM for at least 5 years. Her current AMH level was 2.32 ng/dL. Therefore, she was counseled for FP treatment because the chemotherapeutic agent is gonadotoxic and long-term therapy because she is married. The option of embryo cryopreservation was an excellent choice. The interval before the primary cancer treatment was 6 weeks. Thus, adequate time was available for her FP. Fortunately, she was on her second day of menses; thus, conventional COS was initiated. To date, she had eight embryos cryopreserved (blastocyst stage) following two cycles of conventional COS. She is currently receiving chemotherapy and was planned for years for a cryopreservation update. She responded well with the chemotherapy (doxorubicin + cyclophosphamide), and she is currently on trastuzumab. Her latest AMH was 0.08 ng/dL. She experienced amenorrhea after 6 months of chemotherapy. Due to the FP strategy, she secured her chance for pregnancy in the future despite having a poor ovarian reserve due to her primary cancer treatment.

Our third case is a 37-year-old single and nulliparous woman diagnosed with right breast cancer 6 years ago. She was referred to us previously for FP treatment. She was diagnosed as triple negative because all her hormonal receptors were negative. However, her BRCA status was unknown due to financial constraints for testing. Her AMH level was 3.18 ng/dL. The timeframe for stimulation was limited at that time as her chemotherapy was scheduled a week after the FP counseling. Thus, the ovarian tissue cryopreservation (OTC) opted to follow FP counseling. She underwent laparoscopic left oophorectomy for OTC in November 2013. We obtained 23 pieces of ovarian tissue (1 mm 3 per piece) and 13 MII oocytes after in-vitro maturation; both were cryopreserved. To date, she completed her chemotherapy (doxorubicin + cyclophosphamide and olaparib), and she is currently in remission. Her latest AMH was 0.96 ng/dL. Given that she is still single, she had no plan to fertilize the oocytes and continue follow-up yearly to update her cryopreservation status.

The last case is a 33-year-old nulliparous married woman with grade III intraductal carcinoma of the right breast, with ER/PR+, HERS2+, and Ki67 > 20%. Her current AMH level was 2.54 ng/dL. She was diagnosed in February 2018, and she underwent right mastectomy with ipsilateral axillary lymph node clearance a month later. She was referred to us within 6 weeks before the initiation of chemotherapy. We offered embryo cryopreservation but were only able to pursue a single COS cycle. She managed to preserve three good-quality embryos at that time (blastocyst stage). She received four cycles of doxorubicin and trastuzumab for 1 year and completed 3 years of TAM. Given that she is now in remission, she is keen to embark on pregnancy, with clearance obtained from her breast oncologist. She was planned for frozen embryo transfer (FET), with natural cycles for at least 3 months following the last dose of TAM as the “wash-out” period. Tentatively, her FET was planned for September 2021. Although the period was regular, her AMH level 6 months ago was 0.07 ng/dL, confirming the chemotherapy's gonadotoxic effect on her ovarian reserve. Thus, FP was an appropriate choice in her case.

All these cases represented the current scenario of managing breast cancer among YA women, where FP is deemed essential to be incorporated into the primary disease management. The gonadotoxic effect of the chemo-regime in breast cancer is contemplating, and recommendations seem to be inconclusive. Therefore, a proactive strategy in adding FP as a wise strategy in managing young women with breast cancer is appropriate. The summary of the cases is tabulated in Table 1 .

Table 1 . The summary of main characteristics and reproductive outcomes.

As known, at least 15–25% of breast cancer cases affected premenopausal women, with 7% below 40 years old, which is categorized as AYA group ( 3 ). This group usually has a poorer prognosis than the post-menopausal group. However, the surviving rate increased by up to 80–90% in locoregional type due to the efficient breast cancer treatment at present ( 2 , 3 ). At least 60% of the overall breast cancer among the AYA group is stage II, and above with highly associated with hormonal receptor-positive and high-grade variant. Thus, they highly likely require cytotoxic chemotherapy with prolonged endocrine therapy, which leads to low fecundity ( 4 ). Therefore, the FP treatment among AYA group is paramount. The types of cryopreservation among breast cancer varies in accordance with women's preference, marital status, and the availability of the interval timeframe for FP treatment, as suggested in the FP for breast cancer referral workflow ( Figure 1 ). Embryo cryopreservation is an established method worldwide ( 5 ). It is cost-effective and it reduces the interval of time for pregnancy because the embryo is ready to be transferred once pregnancy is desired. However, it is only permitted for women with a steady partner or those legally married, as elaborated in our second case. This treatment is the best choice among YA women as the majority had an established relationship in their life.

Figure 1 . The suggested referral work flow for oncofertility referral for breast cancer cases.

Oocyte cryopreservation is also recommended as the first line of treatment among single YA women, because it was no longer considered as experimental starting from 2013 ( 5 , 6 ). However, the number of oocytes is a key to determine the prediction of successful pregnancy concerning age. Among YA women, at least 15 oocytes are required to predict a 50% chance of successful pregnancy ( 6 ). Therefore, repeat COS is needed to ensure that a justified number of oocytes could be cryopreserved prior to chemotherapy. Likewise, in our first case, the patient already managed to secure 10 oocytes and continued to collect more oocytes in a given timeframe to ensure good pregnancy outcome in the future. Impromptu initiation of COS and its safety among breast cancer had been overcome by the implementation of random start (RS) protocol with a combination of AI in supplementing conventional COS. The usage of AI is well-known to stabilize the estradiol level to reduce the risk of activating estrogen-driven cancer cell ( 7 – 10 ). Meanwhile, the RS protocol helps overcome the delay in starting COS in the follicular phase, thus reducing the waiting time for FP treatment ( 10 , 11 ). Both of these measures have been proven as an effective strategy among cancer women without jeopardizing the numbers and quality of oocytes compared with conventional COS ( 8 ). Therefore, in our first case, we managed initiating the COS and RS-AI, and she successfully cryopreserved 10 oocytes. The subsequent cycles are still ongoing, with the aim of more oocytes to be cryopreserved.

OTC is not considered as the first line for YA women with breast cancer. It is usually reserved for women with limited timeframe, because FP treatment is squeezed prior to early chemotherapy schedule or in between ongoing chemotherapy cycle, thus making the combination of oocyte and embryo cryopreservation impossible. To date, OTC is still considered as experimental ( 12 – 14 ). The selection of OTC candidates is currently based on Edinburg's criteria to ensure a good outcome ( Table 2 ). Majority of the YA group who selected for FP treatment required cytotoxic chemotherapy, followed by long term hormonal suppression treatment, mainly TAM ( 1 , 11 , 12 ). By the time when ovarian tissue transplantation (OTT) is the aim, most of the women already had a low fertility potential due to the nature of the aging process. Fortunately, in women who received OTC, the possibility of harvesting immature oocytes simultaneously during the procedure could allow enhanced pregnancy outcome. The implementation of in-vitro maturation (IVM) made the maturation process possible, thus improving the FP outcome, because we managed to combine both oocytes and OTC ( 6 , 14 ). This scenario was reflected in our third case, where the patient received OTC due to the limited timeframe and managed to secure 13 oocytes via IVM during the procedure.

Table 2 . The Edinburg criteria for ovarian tissue cryopreservation ( 1 , 11 , 12 ).

By contrast, the implementation of gonadotropin-releasing hormone analog (GnRHa) as gonadal protection among women with breast cancer is still inconclusive ( 15 ). Most centers utilize it as a shield to reduce the direct effect of chemotherapy by creating a transient resting follicle environment. Theatrically, the resting follicles are more resistant to chemotherapeutic agents, thereby reducing the risk of ovarian damage. Surprisingly, most of the data concluded that the level of GnRHa suppression was not sufficient to protect the ovarian tissue from chemotherapeutic damage. Therefore, most of the international bodies do not recommend the usage of GnRHa as one of the FP strategies ( 15 , 16 ). Currently, GnRHa is mainly used to create the transient amenorrhea period to reduce the risk of heavy menstrual bleeding while on treatment compared with FP treatment. However, GnRHa is reserved as an FP option in centers where the established FP options, such as embryo, oocyte, or ovarian cryopreservation, were not available. Therefore, GnRHa was not offered for any of our cases ( 11 , 15 , 16 ).

Concerning germline mutation, at least 10% of young women with breast cancer were related to BRCA1 or BRCA2 gene. An increased risk of BC was seen in BRCA1 (20%) and BRCA2 (10%). Implementing these gene screenings has become an excellent strategy ( 17 ). However, they are still not widely available due to cost. Evidence did show that the BRCA-related BC ovarian reserve was lower than the non-BRCA BC ( 11 , 18 ). Therefore, FP should be offered before primary cancer treatment. The choice of FP should be carefully discussed as OTC may have the risk of reintroducing ovarian cancer (OC) following OTT. The risk of OC is 40% for BRCA1 compared to that for BRCA2 at 15% ( 17 ). Therefore, a lengthy discussion should be offered before OTC. Furthermore, following OTC, BRCA mutation BC has a lower number of oocytes per ovarian tissue piece than non-BRCA BC, leading to lower pregnancy chance following OTT. Thus, oocyte and embryo cryopreservation is considered as a better option in terms of inadequate FP timeframe for stimulation. The use of COS-AI is also recommended to reduce the risk of breast tissue stimulation ( 7 , 9 ). However, the risk of transferring to the offspring needs to be highlighted as an autosomal dominant (AD) link ( 17 , 18 ). It could be carried in cryopreserved oocytes or embryos. Thus, pre-implantation genetic testing (PGT) should be offered before embryo transfer or the usage of oocytes to determine the status of BRCA mutation ( 18 , 19 ). PGT could be a good FP strategy among BRCA BC women aiming for healthy offspring. The current limitation is the awareness and cost of testing that both lead to low uptake of FP among BRCA BC women. In our cases, none of the women was offered BRCA mutation screening due to cost, because it was not covered by insurance. As a proper FP strategy, BRCA mutation screening should be offered to young women with breast cancer to ensure good FP outcome.

In addition, most of the single women among breast cancer survivors in the YA group who received FP treatment have an increased possibility to remain single upon completion of the treatment ( 20 ). Therefore, the indefinite allowable duration of cryopreservation therapy and its effect on pregnancy outcome are still inconclusive. Previously published literature concluded that the duration of storage does not influence pregnancy outcome in cryopreserved material; thus, no timeframe was currently allocated for the duration of cryopreservation ( 21 ). The scenario is applicable to our first and third cases, as the cryopreservation will be renewed until they embark in a stable relationship and had a desire to conceive. Meanwhile, pregnancy in women with breast cancer was proven to be safe with no additional risk of recurrence with potentially more favorable prognosis compared with non-pregnant women with breast cancer ( 22 , 23 ). However, the timing of pregnancy is essential. To date, no evidence that recommends a proper timeframe from the diagnosis to pregnancy could be found. Most of the centers depend on the molecular subtype, histological grade, and stage of cancer when anticipating the risk of recurrence following pregnancy. The first 2–3 years is mostly vital to ensure no pregnancy due to an increased risk of recurrence, particularly in estrogen receptor-positive cases. Some of the centers tend to defer up to 5 years, especially in luminal-type and in women with positive lymph nodes, to ensure no late relapse ( 24 ). Regarding the subtype of BC with FP outcome, triple-negative BC was reported to have decreased oocyte yield and pregnancy rates ( 19 ). Therefore, the urgency of FP should be highlighted to this group to ensure that an adequate number of oocytes or embryos could be cryopreserved before chemotherapy. Our triple-negative case opted for OTC due to limited time for stimulation. Fortunately, with the IVM, she was able to secure 13 MII oocytes. Thus, the combination of OTC and OC improved her future fertility outcome.

In our center, we practice a conjoint decision with breast oncologist in determining the overall patient status before allowing pregnancy. On the basis of standard rules, most of our cases are considered for conception at least after 24 months of endocrine therapy with no evidence of relapse. Currently, our center is included in the clinical trial for “Pregnancy Outcome and Safety of Interrupting Therapy for Women with Endocrine Responsive Breast Cancer” (The POSITIVE Trial, NCT02308085). This trial is recruiting women from the YA group with breast cancer who are willing to embark in pregnancy after receiving adjuvant endocrine therapy, either selective estrogen receptor modulator (SERM) alone or GnRHa + SERM or AI for ≥ 18 months but ≤ 30 months for early breast cancer ( 25 ). The study completed its first phase of recruitment and is now waiting for the analysis of the results. The estimated time for the completion of study recruitment is December 2028. Therefore, we allowed our fourth case to proceed with FET as she already finished the 2 years of TAM and deferred FET for at three 3 months following the last dose of TAM for “wash-out” period to ensure a good pregnancy outcome.

Management of breast cancer women in the YA group is complex, from the variant of molecular cancer subtype to the requirement of cytotoxic chemotherapy and desire for fertility. Therefore, a proper selection of cryopreservation type and targeted timeframe for pregnancy based on a joint decision from oncofertility specialist and breast oncologist is needed to facilitate the FP treatment. To date, the selection of oocytes, embryos, and ovarian tissue is widely available as an FP treatment. However, the risk of BRCA mutation transmission should be considered among BRCA BC women, and PGT should cooperate to ensure enhanced FP outcomes. GnRHa has no gonadoprotective effect and thus should not be considered as an FP option.

Data Availability Statement

The datasets presented in this article are not readily available because there are no data for this case series. Requests to access the datasets should be directed to nao@marianna-u.ac.jp .

Ethics Statement

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author Contributions

YS, MA, YS-T, and NS: conceptualization. YS, MA, YH-O, ST, SS, HI, ES, and YS-T: data curation. YS, MA, YH-O, YS-T, and ST: formal analysis. YS, MA, YH-O, YS-T, ST, and NS: methodology and project administration. YH-O, YS-T, ST, and NS: supervision. ES, MA, and YS-T: writing—original draft. YS, MA, YH-O, YS-T, ST, and NS: writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We would like to thank all the staff in reproductive outpatient clinic and reproductive center who contributed to this study.

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Keywords: breast cancer, cryopreservation, fertility preservation, oncofertility, young adult

Citation: Ahmad MF, Sugishita Y, Suzuki-Takahashi Y, Sawada S, Iwahata H, Shiraishi E, Takae S, Horage-Okutsu Y and Suzuki N (2021) Case Report: Young Adults With Breast Cancer: A Case Series of Fertility Preservation Management and Literature Review. Front. Med. 8:670872. doi: 10.3389/fmed.2021.670872

Received: 22 February 2021; Accepted: 13 July 2021; Published: 06 August 2021.

Reviewed by:

Copyright © 2021 Ahmad, Sugishita, Suzuki-Takahashi, Sawada, Iwahata, Shiraishi, Takae, Horage-Okutsu and Suzuki. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Nao Suzuki, nao@marianna-u.ac.jp

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• Published: 23 November 2020

Clinical Study

A case-control study to evaluate the impact of the breast screening programme on mortality in England

• Roberta Maroni   ORCID: orcid.org/0000-0001-6420-2881 1   na1 ,
• Nathalie J. Massat   ORCID: orcid.org/0000-0002-1095-994X 1   na1 ,
• Dharmishta Parmar 1 ,
• Amanda Dibden   ORCID: orcid.org/0000-0002-0599-9840 1 ,
• Jack Cuzick 1 ,
• Peter D. Sasieni   ORCID: orcid.org/0000-0003-1509-8744 2   na2 &
• Stephen W. Duffy   ORCID: orcid.org/0000-0003-4901-7922 1   na2  

British Journal of Cancer volume  124 ,  pages 736–743 ( 2021 ) Cite this article

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• Breast cancer
• Cancer screening

Over the past 30 years since the implementation of the National Health Service Breast Screening Programme, improvements in diagnostic techniques and treatments have led to the need for an up-to-date evaluation of its benefit on risk of death from breast cancer. An initial pilot case-control study in London indicated that attending mammography screening led to a mortality reduction of 39%.

Based on the same study protocol, an England-wide study was set up. Women aged 47–89 years who died of primary breast cancer in 2010 or 2011 were selected as cases (8288 cases). When possible, two controls were selected per case (15,202 controls) and were matched by date of birth and screening area.

Conditional logistic regressions showed a 38% reduction in breast cancer mortality after correcting for self-selection bias (OR 0.62, 95% CI 0.56–0.69) for women being screened at least once. Secondary analyses by age group, and time between last screen and breast cancer diagnosis were also performed.

Conclusions

According to this England-wide case-control study, mammography screening still plays an important role in lowering the risk of dying from breast cancer. Women aged 65 or over see a stronger and longer lasting benefit of screening compared to younger women.

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Following an evaluation of several randomised controlled trials (RCT) 1 that showed an overall reduction in mortality from breast cancer in women undergoing mammography screening, the National Health Service Breast Screening Programme (NHS BSP) was launched in the United Kingdom (UK) in 1988. At the time, it aimed to offer free routine screening to every woman aged 50–64 once every three years. It now invites women aged 50–70, with an age extension to younger and older women (47–73 years) being trialled. 2

Over the last thirty years, major advances have been made in the fields of cancer screening, treatment, and management (including effective adjuvant systemic therapies 3 and two-view mammography 3 , 4 ), with resulting lengthening of survival times after a breast cancer diagnosis. 5 Despite recent reductions in breast cancer mortality, breast cancer is still the cancer with the highest incidence 6 and the second most common cause of cancer death 7 in females in the UK.

Case-control studies are a useful tool to evaluate screening programmes in settings where lack of equipoise would mean that RCTs would be unethical, or as in this case, where the RCTs have already been done, but there remains a need to ensure that the service is delivering the expected clinical benefit. Case-control studies also overcome some limitations associated with other observational designs by taking into account changes in cancer incidence and use of treatments over time and adjusting for any imbalances in other factors that could affect breast cancer mortality.

Taking as an example a case-control study 8 that resulted in policy change within the NHS cervical screening programme by altering age at first screen and the screening interval, we designed a similar study focussing on the NHS BSP with the aim of:

Evaluating the effect of mammography screening in the NHSBSP on breast cancer mortality

Evaluating the effect of mammography screening on breast cancer incidence, and incidence of late stage disease

Estimating overdiagnosis

Analysing the interplay of early detection, pathology, and treatment on fatality of breast cancer.

The study protocol and results from two pilot studies have been published previously. 9 , 10 , 11 This paper reports on the first objective above (breast cancer mortality), making use of England-wide data. Effects on incidence etc. will be reported in future papers.

Definition of cases and controls

As the main objective was to evaluate the effect of mammography screening on breast cancer mortality, cases were defined as women whose primary cause of death was breast cancer, who were diagnosed at age 47 years or older and died at age 89 years or younger in 2010–2011. We chose the lower limit of 47 as there is a major trial of screening in ages 47–49 ongoing, 2 so substantial numbers of women have been screened in this age group. We chose the upper limit of 89 because above this age we would not expect a major effect of screening taking place mainly at ages 50–70, because we were less confident of the cause of death in the very old, and because screening is essentially aimed at preventing premature mortality, which one might reasonably interpret as death below age 90 years. Only diagnoses occurring after 1990 were included in the analysis. Their matched controls were women sampled from the general population of those invited for screening (99.9% of women eligible for screening in England 12 ) and alive at the time of their corresponding case’s death. Controls may have been diagnosed with breast cancer, but not before their case’s date of diagnosis. Where possible, two controls were selected per case and matched on date of birth (within one month of the case’s) and screening area at date of diagnosis.

For the purposes of the statistical analysis, controls were assigned a date of pseudodiagnosis, equal to the diagnosis date of their corresponding matched case. To be eligible as a case or a control, a woman had to have had at least one invitation to screening prior to the date of diagnosis/pseudodiagnosis.

The primary endpoint was to estimate, among those invited to breast screening, the effect of ever attending breast screening on mortality from breast cancer. Changes in this effect over time were also investigated. Secondary endpoints included the effect of measures of screening intensity, such as time between last screen and diagnosis/pseudodiagnosis, and their estimations in different age subgroups.

Data selection and linkage

Cases were identified from the National Cancer Registration and Analysis Service (NCRAS) database accessed through the Office for Data Release of Public Health England (PHE). This database contains Office for National Statistics date and cause of death data. NHS Digital used the National Health Application and Infrastructure Services (NHAIS) system to identify matched controls and provided breast and cervical screening histories within.

We excluded any breast screens occurring outside the usual call/recall system of the national screening programme. All the screening histories of the study subjects were considered up to and including their date of diagnosis/pseudodiagnosis.

The data were processed according to the NHS Information Governance guidelines. 13

Sample size

Sample size calculations for the pilot study showed that, assuming an OR for breast cancer mortality of 0.7 and a number of discordant pairs of 33%, two controls per case with 800 breast cancer deaths and 1600 controls would confer more than 90% power to detect such an effect size at the 5% significance level using a two-sided test. 10 As the data for this main phase encompassed the whole of England, we had ample power, not only for the primary outcome (8288 cases and 15,202 controls after exclusions), but also for subgroup analyses.

Statistical analysis

Data were analysed using Stata version 13 14 by matched (conditional) logistic regression with death from primary breast cancer as the outcome. Date of birth and screening area were accounted for by the matching process.

Ineligible subjects were excluded (see Fig.  1 ). For some of these, this resulted in a matched set containing only a case, or only controls, which could then no longer be used in the matched logistic regression. Sensitivity analyses using unmatched logistic regression and controlling for age at diagnosis/pseudodiagnosis and screening area were performed on the same dataset with fewer exclusions; in this case, the inclusion criteria considered were the same, but the fact that a case or a control was excluded did not imply discarding that matched set.

Asterisk indicates that these records were excluded for being in a 1:1 matched set where the case or the control was excluded or for being in a 1:2 matched set where the case or both controls were excluded. Hash indicates that these become 1:1 matched sets in the final dataset. Note: some records may be excluded for more than one reason.

Case-control studies used to evaluate population screening programmes are subject to a type of bias known as non-compliance or self-selection bias, which is based on the assumption that people who are already ill may be less likely to attend screening and those who do attend may be more health conscious, and therefore healthier, than those who do not take up the invitation. This may confer an artificially greater protective effect for screening, which was corrected in our analyses using a variant of the method by Duffy et al. 15

The effect of self-selection bias was estimated using data available on cervical screening attendance for the women in the study, on the basis that any observed protective effect of cervical screening on breast cancer death cannot be due to cervical screening (which does not include breast examination) and is therefore likely to be caused by self-selection bias. In particular, the odds ratio (OR) uncorrected for self-selection is an estimate of the relative risk:

An unbiased estimate of the effect of screening on risk of dying from breast cancer would be (refer to Duffy et al. 15 ):

The OR for death from breast cancer associated with attendance at cervical screening, i.e. the self-selection correction factor, can be considered an approximate estimate of the relative risk:

Therefore, we obtain an estimate of θ by dividing γ by φ . The fundamental assumption here is that the populations choosing to attend or not to attend cervical cancer screening have the same risk of dying of breast cancer a priori as those choosing or not choosing to attend breast cancer screening. We do not assume that the effects of self-selection are the same in the two programmes. This is referred to as our first method of correction in the Results section.

As there is considerable uncertainty in the extent of self-selection, and of course decisions to attend at two separate screening programmes are likely to be confounded with each other, we also corrected for this using the method of Duffy et al. 15 . This method estimates the effect of participation in screening in those who would participate if invited as:

where p is the proportion of the invited population who participate in screening and D r is the a priori relative risk of dying of breast cancer for someone who chooses not to attend compared to an uninvited general population member. We estimated D r as 1.19 (95% CI 1.11–1.27), from the cohort study of Johns et al. 16 Thus, this correction was based on a prospective estimate of the extent of self-selection bias in a cohort of 988,090 women in the NHS Breast Screening Programme. We estimated p as 73.4% from the annual report of the National Programme. 12 This method, referred to as our second method of correction in the Results section, also yields an estimate of the effect of invitation to screening as follows: 15

More details on the methods are available in the published study protocol 9 and pilot study analysis. 10

The study dataset had a total of 9550 cases and 17,993 controls. There were 1107 sets with matching ratio 1:1 (1 case to 1 control) and 8443 sets with matching ratio 1:2 (1 case to 2 controls). Records of 1262 cases and 2791 controls (15% of the total) were excluded for various reasons before the statistical analysis (see study flow diagram in Fig.  1 ). This left a final dataset of 8288 cases and 15,202 controls, divided into 1,374 matched sets of size 1:1 and 6914 of size 1:2.

Sensitivity analyses using unconditional logistic regression were performed including subjects without a matched case or control, leaving us with 8479 cases and 16,794 controls.

Table  1 shows patient demographics and screening histories. Median age at first diagnosis was 64 years for both cases and controls and median age at death for cases was 71 years. Whilst the distributions of the number of screening invitations in the two study groups were comparable, differences can be noted in screening attendance, with 72% of the cases versus 82% of the controls attending their first screening invitation; 64% of the cases versus 76% of the controls attending their last screening invitation before diagnosis/pseudodiagnosis; and 21% of the cases versus 12% of the controls never being screened. Median time between last screen and date of diagnosis/pseudodiagnosis for compliers was also slightly longer for cases. From the data available on cervical screening history up to the date of diagnosis/pseudodiagnosis, it can be noted that 22% of the cases compared with 19% of the controls never had a cervical screen.

Table  2 summarises the main results without and with correction for self-selection bias. Using data from cervical screening attendance, the self-selection correction factor was estimated to be 0.78 (95% CI 0.73–0.84). The primary endpoint, the association between attending one or more screens and death from breast cancer, had a resulting OR = 0.49 (95% CI 0.45–0.53) and, when corrected for self-selection, had OR = 0.62 (95% CI 0.56–0.69) by our first method and OR = 0.63 (95% CI 0.55–0.71) by our second. Using the second method, the estimate of the effect of invitation to screening was a 26% reduction in breast cancer mortality (OR = 0.74, 95% CI 0.68-0.81). The unmatched logistic regression on the larger dataset for sensitivity analyses showed a similar effect of screening on breast cancer mortality both before and after controlling for age at diagnosis/pseudodiagnosis and screening area (in both cases, uncorrected OR = 0.55, 95% CI 0.51–0.59).

In order to analyse changes of the effect of screening over time, we excluded women diagnosed before year 2000 (13% of the total records), which led to a corrected OR of 0.56 (95% CI 0.51–0.63) for the effect of ever attending mammographic screening on breast cancer mortality. Women diagnosed from year 2003 onwards had an even larger benefit from being screened (OR corrected by first method = 0.53, 95% CI 0.47–0.59). The estimated effect continued to increase as we restricted the year of diagnosis/pseudodiagnosis further in time (Supplementary Fig.  1 ).

Table  3 shows how the effect of screening varies depending on how much time has passed between a woman’s last screen and her diagnosis/pseudodiagnosis. Screen-detected cancers (assumed to be cancers diagnosed within three months of screening) showed a positive association with breast cancer fatality, after self-selection bias correction by our first method (OR = 1.93, 95% CI 1.68–2.22), while women screened in any other time interval were at reduced risk of dying from breast cancer. This was lowest for women screened in the last year (OR corrected by our first method = 0.19, 95% CI 0.17–0.23) and gradually increased, while still conferring a beneficial effect to screening, for women screened further back in time with respect to their date of diagnosis/pseudodiagnosis. Results using our alternative correction for self-selection were very similar (Table  3 ). Note that the time is from screening to diagnosis, not to death. The Table shows risk of subsequently dying of breast cancer increasing by the time between the screen and diagnosis/pseudodiagnosis.

A similar analysis is shown in Table  4 and Fig.  2 for different time intervals after stratifying for three different age categories at diagnosis/pseudodiagnosis (younger than 60 years, between 60 and 64 years, and 65 years or older). The results show that the protective effect of a screen is greater and lasts longer in the oldest group. The benefit of attending screening in the three years prior to diagnosis/pseudodiagnosis, the recommended interval for screening in the NHS BSP, is shown in the final row of Table  4 , and shows close to a halving of risk with screening within the recommended interval, following self-selection correction by our first method (OR = 0.51, 95% CI 0.46–0.57). Results using our second method of correction were very similar to those using the first (Supplementary Table  1 ). The estimated effect of invitation to screening within the last 36 months using our second method was a 33% reduction in breast cancer mortality (OR = 0.67, 95% CI 0.61–0.73).

Note: the coordinates on the x -axis are the midpoints of the time intervals: 0–3, 3–6, 6–18, 18–36, 36–54 and 54–72 months.

Despite the many improvements in treatments, diagnostic procedures and technologies over the last thirty years, and changes in baseline rate of breast cancer mortality, our data showed an overall reduction in the risk of dying from breast cancer of ~38% for women attending at least one mammography screen, after adjusting for self-selection bias. This is in line with the results obtained from the pilot phase of the study, 10 in which a mortality reduction of 39% was seen for women attending screening in London (deaths occurring in 2008–2009). Using the same calculation method as in the review by the Independent UK Panel on Breast Cancer Screening UK Independent Review, 17 this would correspond to approximately nine breast cancer deaths prevented for every 1,000 women attending screening at ages 50–69 years, larger than but in the same general scale as the six deaths estimated from the UK Independent review.

It should be noted that there is a wide range of estimates of the absolute mortality benefit of mammography screening 18 , 19 , 20 , 21 some finding considerably smaller benefits than above. The size of the estimated effect depends on sources used and assumptions made. However, it has been shown to depend more crucially on whether the effect pertains to screening per se or to invitation to screening only, and on the timescale envisaged. 22 Screening prevents deaths not this year or next, but 5, 10, 15 or 20 years from now. Considering the effect of screening on 10-year mortality will considerably underestimate the absolute benefit. Nevertheless, it should be acknowledged that while the body of evidence, randomised and observational, points to a substantial reduction in breast cancer mortality with screening, there is sufficient variation that different views are still possible.

Our first method of correction for self-selection caused a decrease of about 25% in the estimated protective effect of screening for women having at least one mammogram. The second method yielded similar results. This is a greater correction than the one estimated in the pilot phase, 10 where self-selection only played a minor role, despite the fact that the final risk reduction is very similar. London has a lower coverage than the rest of England for both breast and cervical screening, which is largely explained by factors like deprivation and ethnicity. 23 Such variations in coverage might be one of the causes for the different impact of self-selection between the two phases of the study. For example, a larger population of non-participants, such as in London, may be less different in health status than a smaller population. In the Swedish two-County trial, 24 where only 15% of the population were non-participants, the rate of death from breast cancer in this population was very high. It is also worth noting that, during the early 21st century, breast screening attendance was rapidly increasing in London, and the socioeconomic gradient in attendance was reducing with time nationally. 25 , 26

Case-control studies tend to give higher estimates of benefit than other evaluations, largely because they assess the effect of actually being screened rather than simply being invited to screening. 19 , 27 It should be noted that with our second correction for self-selection bias, we were able to estimate the effect of invitation, giving a 26% breast cancer mortality reduction, similar to the effect observed in the randomised trials in this age group and to the prospectively estimated effect of a 25% reduction in the Copenhagen screening programme. 28 As a comparison, in the review by the Independent UK Panel on Breast Cancer Screening, 17 a meta-analysis of 11 RCTs found that the relative risk reduction of breast cancer mortality for women invited to screening was 20%. Furthermore, in the same report, the panel stated that the case-control studies that they had analysed seemed to inflate the benefit of screening compared to the trials and postulated that this may have been caused by some residual bias unaccounted for by the authors. We believe that our adjustments for self-selection bias has largely accounted for this and that the greater effect of screening in this study is due to technical improvements in mammography since the RCTs were carried out, accompanied by improved treatment and strong quality assurance measures in the NHS BSP. 11

The greater benefit of screening observed for women diagnosed after year 2000 was similar to the pilot study, 10 but here we were able to restrict the analysis to later years of diagnosis and see the benefit getting larger (data not shown). We could conjecture that this improvement was due to the introduction of better procedures in the NHS BSP, such as two-view mammography at every attendance in year 2000 4 ; however, there may be a bias in comparing different times since diagnosis as we only have data on deaths in years 2010–2011. In the first place, cases diagnosed before 2000 have a long survival by definition, and there might therefore be an over-representation of screen-detected cancers. In other words, it is more likely that a case diagnosed before year 2000, for example, who had a breast cancer for more than 10–11 years before dying from it, had a screen-detected cancer rather than a symptomatic one. This confers a bias against screening in the analysis of cancers diagnosed prior to the year 2000. In the second place, there will be a bias in favour of screening if the analysis is restricted to cancers diagnosed within a short time before death, i.e. if we only consider women (pseudo)diagnosed a few years before 2010–2011. We are therefore unable to make any definitive conclusions on the impact of any improvements in the NHS BSP over time.

As shown in RCTs of breast screening, 24 measures of the benefit of screening are largely influenced by the consequent reduction in mortality from symptomatic cancers. This is due to the fact that screen-detected cancers (defined as the ones diagnosed within three months of a screen), despite being less fatal overall, represent a larger proportion of the cancer-related deaths in the immediate period after a screen as it can be seen from the spike in excess mortality in Fig.  2 .

The duration of the benefit of attending screening appears to be greater in older women (Table  4 and Fig.  2 ). Women aged 65 or more see the greatest and longer lasting benefit, which might suggest that they could be screened less often than younger women. This result is in agreement with the impact of ageing on breast cancer biology 29 and is also potentially important in light of the recent incident in the NHS BSP, where a number of women aged 69 and 70 years did not receive the scheduled invitation to their last screening appointment. 30 The exact number affected has been debated but an Independent Review concluded that 5000 women were not invited as scheduled, and that a further 62,000 could be interpreted as having missed their final invitation as defined in the service specification. 30 Our findings suggest that the effect of a delayed screen in older women has a lesser consequence for increased risk of breast cancer mortality than it would have had in younger women. While three years is a longer interval than other programmes in Europe and North America, and further slippage of the interval should be avoided if at all possible, these results could also be used as guidelines for screening units at times of capacity constraints, with the provision that all women receive an opportunity for a final screen around or shortly after age 70. There is interest in stratified screening and these results may inform further thinking on this subject.

A limitation of the study is the retrospective design and the potential for self-selection bias. We have corrected for this in two different ways and for one of these, an effect of invitation to screening was derived which was consistent with trials results and prospective studies for this age group. However, it must be acknowledged that there remains some uncertainty about the extent of self-selection bias. Furthermore, case-control studies for cancer screening programmes are subject to an inherent type of anti-screening bias known as screening opportunity bias. 27 As most of the controls do not have a breast cancer diagnosis, the only way they can be exposed to screening is if they attended a mammography appointment in the past. Cases, on the other hand, may have had a screen in the past, but some of them will also have an additional screen for when their cancer was diagnosed. This induces an artificially higher retrospective probability of screening exposure among cases. Screening opportunity bias was corrected for in the pilot study, 10 where a 10–15% increase in mortality reduction was seen following this, but here we preferred to keep a conservative approach and not adjust for it. To minimise biases with respect to age and opportunity to be screened, we matched very closely for age. This meant that in 1107 cases out of 9550, we could only find one control.

Although the effect of the NHS BSP in preventing breast cancer mortality has been assessed several times, 31 , 32 , 33 , 34 we are aware of only one other case-control study conducted using national data. 34 The latter relies on data up to year 2005 (diagnoses and deaths took place between 1991 and 2005), while ours uses more recent data up to year 2012, arguably more in the epoch of effective adjuvant systemic therapies. It is of interest that our more recent case base shows similar results in terms of the reduction in risk of breast cancer death with screening. In any case, we suggest that it would be of interest to repeat this type of analysis for years thereafter, to ensure that the programme continues to deliver its aims even with the introduction of new diagnostic technologies (e.g. digital mammography). Before the establishment of the NHS BSP in 1987, it was suggested that a routine case-control assessment could and should be part of an ongoing evaluation of a mass screening programme. 35 For this reason, we believe that this exercise should be held on a two-yearly basis.

The results of further national case-control studies (1) evaluating the effect of the NHS BSP on breast cancer incidence and incidence of late stage disease, (2) estimating overdiagnosis, and (3) analysing the interplay of early detection, pathology and treatment on fatality of breast cancer will be published shortly.

To conclude, this study showed that the breast screening programme in England continues to play an important role in the control of breast cancer. The effect of screening within the NHS BSP in England is stronger and longer lasting in women aged 65 or over, but it remains highly relevant for younger women.

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Acknowledgements

Data for this study is based on information collected and quality assured by the PHE National Cancer Registration and Analysis Service. Access to the data was facilitated by the PHE Office for Data Release. We would like to thank Rachael Brannan from the PHE Office for Data Release and David Graham from NHS Digital for their help with the data selection and matching of cases and controls. This work uses data provided by patients and collected by the NHS as part of their care and support.

Author information

These authors contributed equally: Roberta Maroni, Nathalie J Massat

These authors jointly supervised this work: Peter D Sasieni, Stephen W Duffy

Authors and Affiliations

Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK

Roberta Maroni, Nathalie J. Massat, Dharmishta Parmar, Amanda Dibden, Jack Cuzick & Stephen W. Duffy

Faculty of Life Sciences and Medicine, Cancer Prevention Group, School of Cancer and Pharmaceutical Sciences, King’s College London, Guy’s Campus, Great Maze Pond, London, SE1 9RT, UK

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Contributions

R.M. oversaw the first draft of the manuscript draft and submission. N.J.M., J.C., P.D.S. and S.W.D. designed the study. D.P. contributed to data collection and cleaning. A.D. assisted with data interpretation. R.M. and S.W.D. analysed the data and produced the figures. All the authors critically reviewed the paper.

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Correspondence to Stephen W. Duffy .

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Ethics approval and consent to participate.

The study protocol was reviewed and approved by the Department of Health. Ethical approval was obtained from the London Research Ethics Committee of the National Research Ethics Service (reference: 12/LO/1041), and by the National Information Governance Board Ethics and Confidentiality Committee (reference: ECC 6–05 (e)/2012). The ethics committee agreed that informed consent to participate for the study subjects was not necessary. The study was performed in accordance with the Declaration of Helsinki.

Data availability

Data were saved on the servers of the Barts Cancer Institute, Queen Mary University of London, in a folder with restricted access to D.P. A clean, anonymised version of the data was produced and made available to R.M., A.D. and S.W.D. with restricted access to the staff of the Policy Research Unit in Cancer Awareness, Screening and Early Diagnosis at Queen Mary University of London. The data were obtained via the Office for Data Release at Public Health England. We do not have authority to share the data with others, but requests for access to data will be forwarded to the Office for Data Release.

Competing interests

P.D.S. reports personal fees from GRAIL Bio outside the submitted work. J.C. and S.W.D. are members of the editorial board of the British Journal of Cancer. The remaining authors declare no competing interests.

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his research is funded by the National Institute for Health Research (NIHR) Policy Research Programme, conducted through the Policy Research Unit (PRU) in Cancer Awareness, Screening and Early Diagnosis, PR-PRU-1217-21601. The PRU is a collaboration between researchers from seven institutions (Queen Mary University of London, University College London, King’s College London, London School of Hygiene and Tropical Medicine, Hull York Medical School, Durham University, and Peninsula Medical School). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funding body was not involved in design, data collection, analysis or interpretation. The funding body had sight of the paper prior to publication but has not had input to its content.

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Maroni, R., Massat, N.J., Parmar, D. et al. A case-control study to evaluate the impact of the breast screening programme on mortality in England. Br J Cancer 124 , 736–743 (2021). https://doi.org/10.1038/s41416-020-01163-2

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Received : 18 March 2020

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Accepted : 28 October 2020

Published : 23 November 2020

Issue Date : 16 February 2021

DOI : https://doi.org/10.1038/s41416-020-01163-2

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Some postmenopausal women with HR-positive, HER2-negative breast cancer may not benefit from chemotherapy and can safely forgo the treatment, according to clinical trial results presented at the San Antonio Breast Cancer Symposium.

A heart-related event, like a heart attack, may make breast cancer grow faster, a new study suggests. In mice, heart attacks accelerated breast tumor growth and human studies linked cardiac events with breast cancer recurrence, researchers reported.

FDA has approved sacituzumab govitecan (Trodelvy) for the treatment of triple-negative breast cancer that has spread to other parts of the body. Under the approval, patients must have already undergone at least two prior treatment regimens.

Women with high-risk breast cancer who engaged in regular exercise before their cancer diagnosis and after treatment were less likely to have their cancer return or to die compared with women who were inactive, a recent study found.

Researchers have developed a “microscaled” approach to analyze the proteins and genetic changes (proteogenomics) of a tumor that uses tissue from a core needle biopsy. The analyses can provide important information that may help guide treatment.

Tucatinib improved survival for women in the HER2CLIMB trial, including some whose cancer had spread to the brain. Trastuzumab deruxtecan improved survival and shrank many tumors in the DESTINY-Breast01 trial, which led to its accelerated approval.

A TAILORx analysis shows women with early-stage breast cancer and high recurrence scores on the Oncotype DX who received chemotherapy with hormone therapy had better long-term outcomes than what would be expected from hormone therapy alone.

Men with breast cancer may be more likely to die of the disease than women, particularly during the first 5 years after diagnosis, a new study suggests. The higher likelihood of death was linked in part to undertreatment and later diagnosis.

In a survey of nearly 600 breast cancer survivors, researchers found that the cost of care factored into the decisions the women made about what type of surgery to get. Many women also reported never discussing costs with their physicians.

FDA has expanded the approved use of the drug ado-trastuzumab emtansine (Kadcyla), also called T-DM1, to include adjuvant treatment in some women with early-stage HER2-positive breast cancer.

Many women diagnosed with ovarian and breast cancer are not undergoing tests for inherited genetic mutations that can provide important information to help guide decisions about treatment and longer-term cancer screening, a new study has found.

FDA has approved atezolizumab (Tecentriq) in combination with chemotherapy for the treatment of some women with advanced triple-negative breast cancer. This is the first FDA-approved regimen for breast cancer to include immunotherapy.

The build-up of connective tissue around some types of cancer can act as a barrier to immunotherapy. A new study uses a bone marrow transplant drug, plerixafor, to break down this barrier and improve the efficacy of immune checkpoint inhibitors in animal models of breast cancer.

A new study in mice shows that disrupting the relationship between breast cancer cells that spread to bone and normal cells surrounding them makes the cancer cells sensitive to treatment.

In women with early-stage breast cancer, two clinical trials have shown that both whole- and partial-breast radiation therapy are effective at preventing the cancer from returning after breast-conserving surgery.

Researchers are testing a topical-gel form of the drug tamoxifen to see if it can help prevent breast cancer as effectively as the oral form of the drug but with fewer side effects.

Findings from a clinical study and a mouse study may shed light on genetic risk factors for developing cancer-related cognitive problems in older breast cancer survivors. The results suggest a gene associated with Alzheimer’s disease may play a role.

Arsenic trioxide and retinoic acid work together to target the master regulator protein Pin1, a new study shows. In cancer cell lines and mice, the drug combination slowed the growth of triple-negative breast cancer tumors.

FDA has expanded the approved uses of ribociclib (Kisqali) for women with advanced breast cancer, including new uses in pre- and postmenopausal women. It’s the first approval under a new FDA program to speed the review of cancer drugs.

Using a liquid biopsy to test for tumor cells circulating in blood, researchers found that, in women with breast cancer, the presence of these cells could identify women at risk of their cancer returning years later.

Findings from the TAILORx clinical trial show chemotherapy does not benefit most women with early breast cancer. The new data, released at the 2018 ASCO annual meeting, will help inform treatment decisions for many women with early-stage breast cancer.

Do cancer study participants want to receive their genetic test results? A recent study involving women with a history of breast cancer tested an approach for returning genetic research results and evaluated the impact those results had on the women.

Researchers compared the risk of death for women with breast cancer who had low skeletal muscle mass, or sarcopenia, at the time of their cancer diagnosis and women who had adequate muscle mass.

Some people who have been treated for breast cancer or lymphoma have a higher risk of developing congestive heart failure than people who haven’t had cancer, results from a new study show.

FDA has approved the CDK4/6 inhibitor abemaciclib (Verzenio) as a first-line treatment in some women with advanced or metastatic breast cancer. Under the approval, the drug must be used in combination with an aromatase inhibitor.

A new study in mice raises the possibility that using microscopic, oxygen-carrying bubbles may improve the effectiveness of radiation therapy in the treatment of breast cancer.

The drug olaparib (Lynparza®) is the first treatment approved by the Food and Drug Administration for patients with metastatic breast cancer who have inherited mutations in the BRCA1 or BRCA2 genes.

Joint pain caused by aromatase inhibitors in postmenopausal women with breast cancer can cause some women to stop taking the drugs. Reducing their symptoms may translate into better adherence to therapy.

A new study suggests that the cells in treatment-resistant tumors in women with metastatic breast cancer share important characteristics that could potentially make tumors vulnerable to therapies that otherwise might not have been considered.

A large nationwide clinical trial called TMIST has been launched to compare two techniques used for mammograms: tomosynthesis, often called 3D mammography, and standard 2D digital mammography.

FDA approved abemaciclib (Verzenio™) for the treatment of some people with advanced or metastatic HR-positive, HER2-negative breast cancer whose disease has progressed after treatment with hormone therapy.

Long-term results from a large clinical trial confirm that, for some women with early-stage breast cancer who have lumpectomy as their surgical treatment, a less extensive lymph node biopsy approach is sufficient.

When given at the same time, two immune checkpoint inhibitors were ineffective against breast cancer growth in mice, a new study found. The combination was more effective and safer if the two inhibitors were given in a specific sequence.

FDA has expanded its approval of fulvestrant (Faslodex®) as a standalone treatment for postmenopausal women with advanced HR-positive, HER2-negative breast cancer who have not previously undergone endocrine therapy.

Many women who receive taxane-based chemotherapy to treat breast cancer experience long-term nerve damage, or peripheral neuropathy, data from a large clinical trial show.

Researchers recognized the potential of endoxifen as a treatment for breast cancer and, with NCI support, developed the compound into a drug now being tested in clinical trials.

Researchers have used modified stem cells to deliver a cancer drug selectively to metastatic breast cancer tumors in mice. The stem cells target metastatic tumors by homing in on the stiff environment that typically surrounds them.

FDA has approved neratinib for patients with early-stage HER2-positive breast cancer who have finished at least 1 year of adjuvant therapy with trastuzumab.

Many survivors of early-stage breast cancer prefer that their oncologist handle aspects of routine medical care usually overseen by primary care practitioners, leading to concerns about gaps in care.

Results from the first large prospective study of breast and ovarian cancer risk in women with inherited mutations in the BRCA 1 or BRCA2 genes confirm the high risks estimated from earlier, retrospective studies.

Two clinical trials show that trastuzumab emtansine (T-DM1) improves survival compared with other standard treatments for patients with HER2-positive metastatic breast cancer that has progressed after treatment with other HER2-targeted drugs.

Using one of the largest collections of tumor samples from African Americans with breast cancer, researchers tried to assess the extent to which the molecular characteristics on these tumors might help to explain breast cancer disparities.

A new study shows that the number of women in the United States living with distant metastatic breast cancer (MBC), the most severe form of the disease, is growing. This is likely due to the aging of the U.S. population and improvements in treatment.

In a randomized trial, low-income women who role-played talking with their doctor about their survivorship care plan in a counseling session reported receiving more of their recommended care than women who did not get counseling.

The FDA has approved a new targeted therapy, ribociclib, and expanded its earlier approval of another targeted therapy, palbociclib, for some women with metastatic breast cancer.

Researchers have found that duloxetine (Cymbalta®), a drug most commonly used to treat depression, may also reduce joint pain caused by aromatase inhibitors in some women being treated for early-stage breast cancer.

Most Women Can Have Successful Pregnancies After Breast Cancer Treatment

C HICAGO -- The vast majority of young breast cancer survivors who attempted pregnancy after treatment were able to become pregnant and have a live birth, according to a prospective cohort study.

With more than 10 years of follow-up, 73% of women who attempted pregnancy after treatment for stage 0 to III breast cancer became pregnant at least once, with 90% having at least one live birth, reported Kimia Sorouri, MD, MPH, of the Dana-Farber Cancer Institute in Boston.

The median time from breast cancer diagnosis to first pregnancy was 48 months, and older age at diagnosis was associated with lower odds of pregnancy (adjusted OR 0.82 per year increase, 95% CI 0.74-0.90, P <0.0001) and live birth (aOR 0.82 per year increase, 95% CI 0.76-0.90, P <0.0001).

On the other hand, financial comfort at time of diagnosis was predictive of pregnancy (aOR 2.04, 95% CI 1.01-4.12, P =0.047), and fertility preservation was predictive of live birth (aOR 2.78, 95% CI 1.29-6.00, P =0.009).

"Of note, fertility preservation prior to cancer treatment consisting of freezing eggs or embryos was predictive of live births," Sorouri said during a press briefing in advance of the American Society of Clinical Oncology (ASCO) annual meeting.

"This suggests that in this modern cohort, with a heightened awareness of fertility, access to fertility preservation can help to mitigate the damage from chemotherapy and other agents," she added. "This highlights the need for increased accessibility of fertility preservation services for women newly diagnosed with breast cancer who are interested in a future pregnancy."

Julie Gralow, MD, chief medical officer and executive vice president of ASCO, who moderated the press briefing, noted that while oncologists "can't do a lot to impact [younger age and financial comfort at diagnosis] ... we can impact fertility preservation prior to treatment."

"It is really critical that every patient be informed of the impact of a breast cancer diagnosis and treatment on future fertility," she said. "And that we actually offer all young patients ... fertility preservation prior to beginning their treatment, and that we should have equitable access for all."

"It is impressive that this is the first study with long-term follow-up to look at fertility in pregnancy in all subtypes of breast cancer," Gralow added. "It's also impressive that 68% of the patients in this study did receive chemotherapy, which is known to reduce future fertility."

"The conclusion is that pregnancy after a diagnosis of breast cancer is indeed possible for the majority who desire pregnancy, and it is safe," she said.

In explaining the rationale behind the study, Sorouri suggested that current research on the impact of breast cancer treatment on fertility and live birth is somewhat limited. For example, she pointed out that some studies, such as the POSITIVE study , only included select subgroups.

POSITIVE "provided excellent data on fertility outcomes, but only for women with estrogen receptor-positive breast cancer," she said. "Other studies have short-term follow-up and -- critically -- lack prospective assessment of attempt at conception, thus the results don't truly reflect who is trying to get pregnant."

This analysis used data from the Young Women's Breast Cancer Study, a prospective cohort study of women ages 40 and younger with newly diagnosed breast cancer who were enrolled across 13 sites in the U.S. and Canada from 2006 to 2016.

Of the 1,213 eligible participants, 197 reported an attempt to get pregnant over a median follow-up of 11 years.

Among those 197 women, median age at diagnosis was 32, 74% were white, 41% had stage I disease, 35% had stage II, 10% had stage III, and 14% had stage 0. About two-thirds (68%) received chemotherapy, 57% received endocrine therapy within 1 year, and 13% were BRCA1 / 2 carriers.

About half (51%) of patients reported financial comfort at baseline, 28% had undergone fertility preservation consisting of egg/embryo freezing at diagnosis, and 15% reported a history of infertility before breast cancer diagnosis.

The study was funded by the Breast Cancer Research Foundation and Susan G. Komen.

Sorouri reported no disclosures.

Co-authors reported relationships with Alston & Bird, AstraZeneca, Blue Note Therapeutics, Daiichi Sankyo, Elsevier, Exact Sciences, Gilead Sciences, GSK, Hall Matson, Included Health, Ipsen, Knight Therapeutics, Libbs, Lilly, M. Dalton Esq. and Associates, Medtronic, Menarini, Morrison, MSD, Novartis, Olema Oncology, Perla Therapeutics, Pfizer, Pierre Fabre, Roche, Rubedo Life Sciences, Seagen, Sandoz, Springer Nature, Takeda, and UpToDate.

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• v.371; 2020

Use of hormone replacement therapy and risk of breast cancer: nested case-control studies using the QResearch and CPRD databases

Yana vinogradova.

1 Division of Primary Care, University Park, University of Nottingham, Nottingham NG2 7RD, UK

Carol Coupland

Julia hippisley-cox.

2 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Associated Data

To assess the risks of breast cancer associated with different types and durations of hormone replacement therapy (HRT).

Two nested case-control studies.

UK general practices contributing to QResearch or Clinical Practice Research Datalink (CPRD), linked to hospital, mortality, social deprivation, and cancer registry (QResearch only) data.

Participants

98 611 women aged 50-79 with a primary diagnosis of breast cancer between 1998 and 2018, matched by age, general practice, and index date to 457 498 female controls.

Main outcome measures

Breast cancer diagnosis from general practice, mortality, hospital, or cancer registry records. Odds ratios for HRT types, adjusted for personal characteristics, smoking status, alcohol consumption, comorbidities, family history, and other prescribed drugs. Separate results from QResearch or CPRD were combined.

Overall, 33 703 (34%) women with a diagnosis of breast cancer and 134 391 (31%) controls had used HRT prior to one year before the index date. Compared with never use, in recent users (<5 years) with long term use (≥5 years), oestrogen only therapy and combined oestrogen and progestogen therapy were both associated with increased risks of breast cancer (adjusted odds ratio 1.15 (95% confidence interval 1.09 to 1.21) and 1.79 (1.73 to 1.85), respectively). For combined progestogens, the increased risk was highest for norethisterone (1.88, 1.79 to 1.99) and lowest for dydrogesterone (1.24, 1.03 to 1.48). Past long term use of oestrogen only therapy and past short term (<5 years) use of oestrogen-progestogen were not associated with increased risk. The risk associated with past long term oestrogen-progestogen use, however, remained increased (1.16, 1.11 to 1.21). In recent oestrogen only users, between three (in younger women) and eight (in older women) extra cases per 10 000 women years would be expected, and in oestrogen-progestogen users between nine and 36 extra cases per 10 000 women years. For past oestrogen-progestogen users, the results would suggest between two and eight extra cases per 10 000 women years.

This study has produced new generalisable estimates of the increased risks of breast cancer associated with use of different hormone replacement preparations in the UK. The levels of risks varied between types of HRT, with higher risks for combined treatments and for longer duration of use.

Introduction

Hormone replacement therapy (HRT) (also known as hormone therapy (HT) or menopausal hormonal therapy (MHT)) is prescribed to relieve the symptoms of menopause, which can be life changing. HRT is used by millions of women, sometimes over extended periods. A range of hormone combinations are available, each with different efficacy and side effects. HRT can bring several improvements to quality of life, and it can prevent osteoporosis. Concerns about adverse effects, particularly the increased risk of breast cancer associated with HRT, 1 has, however, resulted in a substantial decrease in HRT use over the past 17 years. 2 Breast cancer is the most common cancer in women, with more than 55 000 women in the UK affected each year, 3 so different drug use scenarios might result in substantial differences in the number of women who develop breast cancer, even though the risk differences between hormones might seem relatively small. Current clinical guidelines recommend use of HRT for no longer than five years and have signalled that more information is needed about the risks of breast cancer associated with different types of HRT. 4 5

Randomised trials using enrolled participants are now impractical to investigate the risks of breast cancer associated with HRT because of the numbers required and the length of follow-up. Trials would also be difficult to justify ethically, given the known harms that are associated with some types of HRT. Earlier trials have been limited, focusing on specific age groups possibly unrepresentative of women likely to request HRT or selecting specific types of HRT 6 (the largest being the Women’s Health Initiative trial), 7 or, because the design failed to distinguish between treatment types, looking only at overall effect or association. 8 9 10 Observational studies are more feasible but require access to large datasets covering lengthy time periods; so far only the Million Women Study has approached the requisite power. 10 A recent meta-analysis published after our study commenced, pooled information from 24 prospective observational studies to provide more comprehensive data on the details of exposure and breast cancer risks for the most commonly prescribed oestrogens and progestogens. 11 This meta-analysis reported that the risk of breast cancer is increased for both oestrogen only and oestrogen-progestogen current users, with, respectively, a 17% and 60% increase for 1-4 years of use and a 33% and 108% increase for 5-14 years of use. The results also showed a remaining increased risk even after discontinuation of HRT. As with many meta-analyses, however, the included studies were conducted in different settings, had different selection criteria, and had different definitions of exposure, so the data and original study designs were heterogeneous. The study provided information for the most commonly used HRT preparations, albeit with notably smaller statistical power for dydrogesterone—a progestogen previously found to be associated with a low increased risk of breast cancer. 12 At publication, the focus of publicity was the higher than expected associations with breast cancer risks than had been suggested by earlier trials. The Medicine and Healthcare products Regulatory Agency subsequently raised an HRT drug safety alert specific to breast cancer, but this has since been questioned as having caused “considerable anxiety,” particularly for women who might need HRT for reasons other than menopausal symptoms. 13

Our study focused on exposure to all the commonly prescribed types of HRT in the UK over the past 20 years in a representative primary care population. We assessed the differences in risks associated with the individual component hormones used in HRT, including dydrogesterone. Our findings are based on prospectively collected electronic health records from the two largest UK primary care databases linked to secondary care data sources. We analysed these separately and then combined the results. In contrast with data and analytical designs used in studies included in the recent meta-analysis, 11 our data were homogeneous, and the analytical approach was common. This has allowed us to gain a realistic picture of exposure in the UK to component hormones used in HRT, and the associations with increased breast cancer risk of specific treatments, providing consistently derived information for patients and doctors.

Study design

Full details for this study are available in the published protocol. 14 To summarise, we undertook a nested case-control study using the two largest UK primary care databases, QResearch and Clinical Practice Research Datalink (CPRD) GOLD, and utilised linked data from Hospital Episode Statistics (HES), Office for National Statistics (ONS) mortality data, and (QResearch only) cancer registry data. We included all general practices that had contributed data for at least three years and from these we identified two open cohorts of women aged between 50 and 79 and registered with the general practice between 1 January 1998 and 31 December 2018. We excluded women with already diagnosed breast cancer or records of mastectomy at the cohort entry date, and, to ensure completeness, any with fewer than three years of medical records.

Selection of cases and controls

Across both databases, we identified all cases between 1 January 1998 and 31 December 2018. From the QResearch database, we identified all cases of incident breast cancer using general practice, hospital admission, mortality, and cancer registry records. From CPRD, when practices were linked, we used general practice, hospital admission (up to 31 December 2017), and mortality data records (up to 13 February 2018) to identify cases, and, when not linked, general practice records only. Each case was matched to a maximum of five controls by year of birth and general practice using incidence density sampling. 15 For each case in any data source, the date of the first breast cancer record became the index date for their matched controls. QResearch and CPRD GOLD use different computer systems to collect records from practices, and as patients can be registered with only one practice, there was no overlap of cases and controls.

Exposure to HRT

We extracted prescription information for all oestrogens, progestogens, and tibolone from practice records. Symptoms indicative of developing breast cancer before diagnosis could have resulted in cessation of HRT. To minimise this source of possible protopathic bias, we excluded prescriptions issued in the year before the index date. 16

Exposure to HRT was taken as the date from when a woman received her first prescription containing systemic oestrogen (oral, subcutaneous, or transdermal) indicated to treat menopausal symptoms. If a woman received no prescription that contained a progestogen after this date, she was classified as an oestrogen only therapy user. If a woman received any prescription that contained a progestogen, she was classified as a combined therapy user. We also included topical oestrogen preparations (vaginal pessaries or cream) and tibolone, because both are commonly prescribed to menopausal women.

A large proportion of women switched between different combinations of oestrogens and progestogens, so we analysed each hormonal preparation as a separate exposure. For oestrogen only users, we distinguished between types, doses, and application method, whereas for combined therapy users we analysed combinations of any oestrogen, concentrating on progestogen type and application method. If combined therapy users had also used oestrogen only therapy, we analysed the women as oestrogen-progestogen users but adjusted the combined exposure results to account for periods of oestrogen only treatment. For all treatments, the reference category was no exposure (never users) to HRT.

At the time of our study, two types of oestrogen (conjugated equine oestrogen and estradiol) and four types of progestogen (norethisterone acetate, levonorgestrel, medroxyprogesterone, and dydrogesterone) were commonly prescribed in the UK and were included in our analyses. Of these, sufficient data were available for estradiol, estradiol-norethisterone, and oestrogen-levonorgestrel to facilitate separate analysis of application methods—oral, transdermal, or injection, and (for levonorgestrel) intrauterine. We investigated two daily dosage levels of oestrogen: low (0.625 mg/day or less for oral conjugated equine oestrogen, 1 mg/day or less for oral estradiol, and 50 mg or less for transdermal estradiol) and high (all other dosage levels). Median dosages for each oestrogen and for each woman were also calculated and analysed.

We have not specified the type of oestrogen for combinations with progestogens, but in our data conjugated equine oestrogen was by far the most commonly prescribed drug in combination with medroxyprogesterone (only 16% of prescriptions included estradiol) and levonorgestrel (only 5% included estradiol). Estradiol was the only oestrogen prescribed in combination with norethisterone and dydrogesterone.

Our data showed that HRT prescriptions were frequently issued for three months, so we assessed the durations of use by summing the lengths of prescriptions in days, including gaps of fewer than 90 days between prescriptions. Most (79%) repeated prescriptions were, however, issued within 30 days. We then categorised durations of use as never (0), less than 1 year, 1-2 years (≥1 and <3), 3-4 years (≥3 and <5), 5-9 years (≥5 and <10), and 10 years or more. Excluding prescriptions in the past year, the gap between the end of the last prescription and the index date was categorised as 1-2 years (>1 and <2), 2-4 years (≥2 and <4), 5-9 years (≥5 and <10), and 10 years or more.

Because some women discontinued HRT more than a year before the index date, and associated breast cancer risks might have diminished noticeably, we investigated two recency related exposures: recent, if the women had a prescription more than one year and less than five years before the index date (this includes current users of HRT at one year before the index date), and past, if their last prescription ended before that period (≥5 years before). Using these, we analysed different durations of exposures in relation to the recency of the last prescription.

Confounders

Analyses were all adjusted by the same factors—those that might have affected a doctor’s prescribing decision for HRT or might have affected a woman’s decision to take HRT or are associated with an increased breast cancer risk. 3 11 14 The data for confounders were derived from practice or hospital records, and data for drugs were from practice records only. To minimise protopathic bias, records of confounders had to be from at least a year before the index date. Confounders included lifestyle factors (smoking status, alcohol consumption, body mass index (BMI), and Townsend fifth as a measure of deprivation (in QResearch only)), self-assigned ethnicity (based on practice and hospital data), family history of cancers and osteoporosis, history of other cancers, records of early and late menopause, oophorectomy or hysterectomy, uptake of mammography or scanning, menopausal symptoms, comorbidities, and use, or when possible, duration of use of other drugs. Comorbidities included benign breast disease, diabetes, and bipolar disorder or schizophrenia. 14 Other drugs included combined and progestogen only contraceptive drugs, aspirin, non-steroidal anti-inflammatory drugs, tamoxifen, and raloxifene. When numbers permitted, we categorised duration of use of other drugs up to one year before the index date as never, less than 1 year, 1-2 years, 3-4 years, and 5 years or more. Early menopause was estimated from records of menopausal symptoms or of oophorectomy or hysterectomy before age 45 years. Late menopause was considered if the first menopause related record was after 55 years for women older than 55 at the index date. For all other women we assumed onset of menopause was between age 50 and 55 years.

Statistical analysis

As data from QResearch and CPRD cannot be pooled, for all analyses we processed extracted datasets in parallel as similarly as possible. To calculate associations between breast cancer risk and different exposures to HRT, we used conditional logistic regression to estimate odds ratios with 95% confidence intervals. A small proportion of women had missing values for BMI, smoking status, and alcohol consumption, which we assumed to be missing at random. We imputed these separately for each dataset using chained equations over 10 imputed datasets, where the imputation model included all listed confounders, exposures, and case-control status indicators, and we combined the odds ratios obtained from the imputed datasets using Rubin’s rule. 17

We considered duration of exposure both in the form of defined categories of exposure and as a continuous variable. For ease of comparability with other studies and to simplify interpretation, our main results are presented using defined categories of exposure, with duration of HRT expressed in years. We used a meta-analytical technique to combine the obtained odds ratios from the separate analyses run on each database. 18 A fixed effect model with inverse variance weights was used for the main analysis and a random effect model as a sensitivity analysis. In the main tables and text we only include the combined results; the separate results for QResearch and CPRD are in the supplementary tables.

To model exposures as continuous variables, we ran separate analyses on each database using fractional polynomials to explore non-linear risk associations for durations of exposure, measured in days. 19 This was done for both recent and past exposures to all the types of HRT under investigation. Variables found to have non-linear associations were then transformed into the suggested powers, the separate analyses were rerun, and the resulting coefficients and standard errors were combined.

Additional and sensitivity analyses

To assess possible age related differences in risks associated with exposures to hormone, we performed additional analyses for different age categories at the index date: 50-59 years, 60-69 years, and 70-79 years. We ran another subgroup analysis for women in three different BMI groups: less than 25, 25 up to 30, and 30 or more. In this analysis, we included only controls in the same body mass category as their matched case.

For the main analysis, we considered women to have recently used HRT if they had a prescription between one and five years before the index date. The risk associated with HRT has been found to decrease rapidly after discontinuation, 20 so we needed a measure showing excess of risk for the most recently exposed women. To assess this, we repeated the analysis, defining recent use as exposure between one and two years before the index date.

It is possible that some women were classified as never exposed only because they were not registered with the practice at the time when they had used HRT. Although any systematic difference between cases and controls is unlikely, we addressed this possible misclassification of exposure by repeating the analysis in a subgroup of women with at least 10 years of medical records. Another sensitivity analysis dealt with unknown adherence to HRT, because it is possible that some women with apparent gaps between prescriptions had in fact spread their HRT supply over longer periods. In this analysis, we defined duration of HRT use as the period between the first HRT prescription and the last one prior to one year before the index date.

The main analysis was run on women aged 50 to 79, which may include some premenopausal and perimenopausal women who have a higher risk of breast cancer. 21 To deal with this and provide comparability of our results with those of a meta-analysis, 11 we also ran an additional analysis restricting our sample to women aged 55 to 79.

To check our assumption of missing at random for some confounders, we compared patterns of missingness in exposed and non-exposed women and repeated the analyses, including only cases and controls with recorded values. In the final sensitivity analysis, we dealt with problems that might have arisen from the different levels of linkage in QResearch and CPRD. All QResearch practices were linked to deprivation, hospital, mortality, and cancer registry data, so cases could be identified using all sources of data. For CPRD, however, only 60% of practices were linked to deprivation, hospital, and mortality data, so to include data from all usable practices, we were limited to identifying cases from all available data. To assess the possible effect on our results, we ran an analysis using only fully linked CPRD practices.

To estimate the excess of breast cancer cases associated with different HRT exposures we calculated the incidence rate in the unexposed female population for different age categories (50-59, 60-69, and 70-79) using the underlying cohort from CPRD. The rate in the exposed population was derived by multiplying the baseline rate by relevant odds ratios obtained from the combined analysis.

We used Stata v16 for all analyses. A 1% level of statistical significance was used to allow for multiple comparisons. To facilitate comparison with other studies, however, we present the results as odds ratios with 95% confidence intervals.

Patient and public involvement

This epidemiological study investigated a research question recommended by a National Institute for Health and Care Excellence committee, which included lay members. 5 It used routinely collected data and appropriate statistical techniques. The grant application process and the publication process of The BMJ both had lay involvement. No other lay people were involved in setting or extending the research question or the outcome measures in our study, nor were they involved in developing plans for the design or implementation of the study. However, to better understand motivations for starting HRT and possible adherence issues related to prescribed treatment, formal and informal conversations with some women taking HRT were also organised. In these, women generally reported high levels of adherence, regardless of whether they had sought treatment themselves or were recommended it by a doctor. Some of the women involved have also agreed to help further with interpretation and dissemination of the results through women’s menopausal forums.

Overall, 59 999 cases of breast cancer were identified in QResearch between 1 January 1998 and 31 July 2018, using general practice, hospital admissions, mortality, and cancer registry records. In total, 38 612 breast cancer cases were identified in CPRD between 1 January 1998 and 31 December 2018, using general practice records and, for linked practices, also using hospital admission records (until 31 December 2017) and mortality records (until 13 February 2018) ( fig 1 ).

Flow chart of included cases and controls

Table 1 shows the characteristics of the cases and matched controls from QResearch and CPRD. Cases were more likely than controls to be overweight or obese (53% v 50%), to be former smokers (29% v 27%), to have a record of benign breast disease (9% v 6%) or other cancers (3.1% v 2.6%), or to have a family history of breast cancer (4% v 2.5%).

Characteristics of women with breast cancer and matched controls one year before index date by database (QResearch and CPRD). Values are percentages (numbers) of participants unless stated otherwise

MRI=magnetic resonance imaging; CT=computed tomography.

Across both databases, 33 703 (34%) cases and 142 391 (31%) controls had ever been exposed to HRT. Of those, 8860 (26%) cases and 42 799 (30%) controls had been exposed to oestrogen only therapy and 24 843 (74%) cases and 99 592 (70%) controls had been exposed to oestrogen-progestogen therapy (supplementary eTable 1). Women in the 60-69 age category were relatively more exposed to oestrogen only (47% in cases and controls) and oestrogen-progestogen therapies (48% in cases and controls). A high proportion of women using oestrogen only therapy had undergone oophorectomy or hysterectomy (89% cases and 90% controls), but, overall, users of oestrogen only and oestrogen-progestogen therapies had characteristics broadly similar to those of never users for most confounders. Some women switched between hormones during HRT exposure. About 20% of oestrogen only users had exposure to both oestrogens. About 57% of combined therapy users had only one oestrogen-progestogen combination recorded. About 0.6% of cases and controls started HRT in the year before the index date, but these are considered as never users in the analyses.

Overall exposure

Overall (or ever) exposure to HRT was associated with an increased risk of breast cancer (adjusted odds ratio 1.21, 95% confidence interval 1.19 to 1.23). The increased risk was mostly attributable to oestrogen-progestogen therapy (1.26, 1.24 to 1.29), with oestrogen only therapy showing a small increased risk (1.06, 1.03 to 1.10), both compared with never users (supplementary eTable 2). No increased risk was associated with oestrogen cream or vaginal preparations (supplementary eTable 3). The risks associated with HRT increased with duration of use, but the associations were less strong for oestrogen only therapy and for tibolone than for oestrogen-progestogen therapy, apart from estradiol-dydrogesterone preparations. Norethisterone, levonorgestrel, and medroxyprogesterone were associated with similar risks, increasing across all duration categories longer than one year. For all exposure durations, the combined treatment with the lowest associated risk increase was estradiol-dydrogesterone. No differences were found between low and high doses of oestrogens or between different application methods for estradiol, norethisterone, or levonorgestrel (supplementary eTable 4).

Associations between use of HRT and risk of breast cancer rapidly decreased with increasing years of discontinuation (supplementary eFigure 1 and eTable 5). For oestrogen only, estradiol combined with norethisterone and dydrogesterone, and tibolone, no significantly increased risk was found from two years after discontinuation. For medroxyprogesterone, the risk was reduced after two years but remained raised until after five years; for levonorgestrel until after 10 years.

Duration of recent and past exposures as categorical variables

Recent users of HRT (ie, those with prescriptions more than one year and less than five years before the index date) comprised 56% (18 879) of cases and 50% (70 931) of controls ever exposed to HRT. Figure 2 and figure 3 (supplementary eTable 6) show the associations between categorised durations of HRT and risks of breast cancer in women with recent and past exposures. The patterns of risks for recently exposed women were similar to those for overall exposures, but the risks were consistently higher and more pronounced, particularly for oestrogen-progestogen therapy. For women with past exposures, risks associated with longer durations of use of oestrogen-progestogen, particularly longer use of levonorgestrel (>3 years) and norethisterone (>5 years), remained high, but for other hormones the risks were not statistically significant. Findings for recent exposures to different doses and applications also had similar patterns to the overall exposure analysis, but with higher odds ratios (supplementary eTable 7).

Recent and past use of oestrogen, oestrogen-progestogen, and tibolone in association with breast cancer risk. Odds ratios are with reference to never users and adjusted for smoking status, alcohol consumption, Townsend fifth (QResearch only), body mass index, ethnicity, history of other cancers, oophorectomy or hysterectomy, records of early and late menopause, menopausal symptoms, mammography or scans, family history, comorbidities, other drugs, and years of data. Cases are matched to controls by age, general practice, and index date

Recent and past use of different hormones in association with breast cancer risk. Odds ratios are with reference to never users and adjusted for smoking status, alcohol consumption, Townsend fifth (QResearch only), body mass index, ethnicity, history of other cancers, oophorectomy or hysterectomy, records of early and late menopause, menopausal symptoms, mammography or scans, family history, comorbidities, other drugs, and years of data. Cases are matched to controls by age, general practice, and index date

A further restriction to recency (defined now as one prescription or more in the period 1-2 years before the index date) resulted in fewer women in each category of exposure, but the increased risks associated with longer exposures were even more pronounced (supplementary eFigure 2). In HRT users, 40% (13 463) of cases and 32% (44 972) of controls ever exposed to HRT had one or more prescriptions in the period 1-2 years before the index date. The patterns of risks for these recently exposed women were similar to those of overall exposures, but the risks were consistently higher and more pronounced for progestogens. For women with a last exposure more than two years before the index date, risks associated with long exposures to levonorgestrel (>3 years) remained high, but for other hormones the risks were not statistically significant (supplementary eFigure 3 and eTable 8).

Duration of recent and past exposures as continuous variables

Figure 4 (supplementary eTable 6) shows the associations between duration of different types of HRT and risks of breast cancer for recent (1-5 years before index date) and past users (prescriptions ≥5 years previously). A linear relation was found between duration of exposure as a continuous variable for most types of HRT, with risk increasing uniformly over time. However, for recent exposure to oestrogen-progestogen or to estradiol-norethisterone, and for past exposure to oestrogen-medroxyprogesterone, square root transformations gave the best fit for an association with breast cancer risk, showing that risk for these treatments increased faster earlier in the exposure. Additions of further fractional polynomial terms were not statistically significant.

Adjusted odds ratios for different durations of recent and past exposures to hormone replacement therapies in association with breast cancer risk. Odds ratios are with reference to never users and adjusted for smoking status, alcohol consumption, Townsend fifth (QResearch only), body mass index, ethnicity, history of other cancers, oophorectomy or hysterectomy, records of early and late menopause, menopausal symptoms, mammography or scans, family history, comorbidities, other drugs, and years of data. Cases are matched to controls by age, general practice, and index date. Model includes fractional polynomial terms for recent use of oestrogen-progestogen (power 0.5), estradiol-norethisterone (power 0.5), past use of oestrogen-levonorgestrel (power 0.5), and linear terms (1) for all other exposures

Risk increases for recent users were more pronounced than for past users, and different types of HRT showed different patterns of increase as the durations of exposure increased. Oestrogen-medroxyprogesterone and oestrogen-levonorgestrel formulations showed the greatest increases with duration. Oestrogen only (including separately conjugated equine oestrogen and estradiol), tibolone, and estradiol-dydrogesterone formulations showed the smallest increases with duration.

Subgroup analyses

The subgroup analyses for different age categories showed similar patterns in magnitudes of risk for recent and past exposures ( fig 5 , supplementary eFigure 4 and eTables 9 and 10). The oldest age group (70-79) had a smaller number of recent (1-5 years before the index date) users and, although odds ratios appeared to be higher than for the younger age groups, the confidence intervals were too wide to reach statistical significance for oestrogen only users. The younger age group (50-59) had the lowest odds ratios, which could reflect shorter durations of exposure, particularly in the category of five years or more (supplementary eTables 9 and 10). The mean duration for the category of 1-4 years, however, was only slightly lower for the younger group but similar between the older groups.

Use of oestrogen only, oestrogen-progestogen, and tibolone in women of different ages in association with breast cancer risk. Odds ratios are with reference to never users and adjusted for smoking status, alcohol consumption, Townsend fifth (QResearch only), body mass index, ethnicity, history of other cancers, oophorectomy or hysterectomy, records of early and late menopause, menopausal symptoms, mammography or scans, family history, comorbidities, other drugs, and years of data. Cases are matched to controls by age, general practice, and index date

Figure 6 presents the associations with breast cancer risk for recent and past exposures in different BMI categories (supplementary eFigure5 and eTables 11 and 12). Overall, the pattern of risks in the subgroups were similar to those of the main analyses. For women with a higher BMI (>30), however, the risks associated with HRT for recent users appeared slightly lower than in women with a lower BMI, both for oestrogen only and for oestrogen-progestogen therapies. For oestrogen only therapy and more than five years of use, the association with risk of breast cancer was statistically significant only in the lowest BMI group (1.24, 1.11 to 1.35) compared with never use. For oestrogen-progestogen, more than five years of use was associated with the highest adjusted odds ratio in the lowest BMI group and the lowest adjusted odds ratio in the highest BMI group (1.93, 1.80 to 2.05 for BMI <25; 1.71, 1.58 to 1.85 for BMI 25-30; and 1.38, 1.23 to 1.55 for BMI >30). For past use, no difference between BMI groups was observed.

Use of oestrogen-only, oestrogen-progestogen, and tibolone in women of different body mass index in association with breast cancer risk. Odds ratios are with reference to never users and adjusted for smoking status, alcohol consumption, Townsend fifth (QResearch only), body mass index, ethnicity, history of other cancers, oophorectomy or hysterectomy, records of early and late menopause, menopausal symptoms, mammography or scans, family history, comorbidities, other drugs, and years of data. Cases are matched to controls by age, general practice, and index date

Excess numbers in HRT users

The crude incidence rate of breast cancer in the underlying CPRD cohort was 33.0 (95% confidence interval 32.7 to 33.3) per 10 000 women years, whereas the crude incidence rate in women not exposed to HRT was 31.5 (31.1 to 31.7) per 10 000 women years. The rate for unexposed women varied with age, with the lowest rate in younger women (28.2, 27.6 to 28.7 in women aged 50-59; 34.1, 33.4 to 34.8 in women aged 60-69; and 33.3, 32.6 to 34.0 in women aged 70-79). The highest rate in the 60-69 years group was consistent with national data from cancer registration statistics in England. 22

Table 2 and fig 7 contain incidence rates and excess rates of breast cancer in users of HRT at different ages and for different durations. The number of extra cases is consistently larger for older women for all exposures. Compared with never users, the estimated number of excess cases per 10 000 women years in recent long term (≥5 years) users of oestrogen only treatment was three in women aged 50-59, four in women aged 60 to 69, and eight in women aged 70-79. Compared with never users, the number of excess cases per 10 000 women years in recent long term users of oestrogen-progestogen treatment was 15 in women aged 50-59, 26 in women aged 60-69, and 36 in women aged 70-79. For tibolone in recent long term users, the numbers exposed in younger women were too small to provide sufficient data, but within the older groups there are an estimated nine extra cases per 10 000 women years in women aged 60 to 69 and 15 extra cases per 10 000 women years in women aged 70 to 79.

Incidence rates and excess of cases of breast cancer compared with never use per 10 000 women years by different age categories and different durations and recency of hormone replacement therapy (HRT) use

Rates were estimated using rates in unexposed populations from Clinical Practice Research Datalink multiplied by adjusted odds ratios derived from subgroup analyses for different age categories (see fig 5 ). Extra cases were reported only for statistically significant findings. Recent use is within one and five years; past use is five years before the index date.

Incident breast cancer rate per 10 000 women years for women unexposed and exposed for different durations to different hormone replacement therapies by age range. Rates were estimated using rates in unexposed populations multiplied by adjusted odds ratios derived from subgroup analyses for different age categories (see fig 5 )

Sensitivity analyses

The sensitivity analysis run on women with at least 10 years of recorded data showed similar patterns of risks associated with different durations of HRT use, but the risks appeared slightly higher, particularly for exposure to oestrogen-progestogen combinations of between five and 10 years (supplementary eFigure 6 and eTable 13). The sensitivity analysis on the subgroup of women aged 55 to 79 showed similar patterns of risks, with all values consistent with the subgroup analyses for different age groups (supplementary eFigure 6 and eTable 14). The sensitivity analysis with duration of exposure defined as from the first prescription of HRT to the end of the last prescription showed results similar to those of the main analysis (supplementary eTable 15). The results of analyses run on cases and controls without missing data for smoking status, alcohol consumption, and BMI were similar to those of the main analyses—as were the analysis restricted to CPRD cases and controls with linked data.

This large observational study found that exposure to most HRT drugs is associated with an increased risk of breast cancer. In comparison with a recent meta-analysis, however, our findings generally suggest lower increased risk associations between longer term HRT use and breast cancer, and we report a more noticeable decline in risks once HRT has stopped. Risk increases were mostly associated with oestrogen-progestogen treatments, but small increases were also associated with oestrogen only treatments. For all exposure durations, the combined treatment with the lowest associated risk increase was estradiol-dydrogesterone. Associations for all treatments depended on duration, with no increased risks for less than one year of treatment but increasing risks for longer exposures to medroxyprogesterone, norethisterone, and levonorgestrel. Associations were more pronounced for older women and less noticeable for obese women.

Strengths and weaknesses of this study

The main strengths of this original study are its size, consistent sources of primary care data, almost complete follow-up of diagnoses using linked data, consistent design, and resulting generalisability of the findings. Combining results from the two largest UK primary care research databases with national coverage has provided increased power, representiveness, and wide geographical coverage of included practices. The study relates to an important health problem and used only objective information on prescriptions for HRT in the UK, facilitating inclusion of the full range of preparations available within this national setting and presenting in detail the increased risk of breast cancer associated with usage patterns. The follow-up and validation of breast cancer diagnoses through linkages to hospital, mortality, and cancer registry (QResearch only) data reduced both ascertainment and recording bias. As our study was based on routinely collected data, it was also not susceptible to recall bias. Matching by general practice enabled consideration of possible differences in prescribing and recording patterns across practices. Differences in menopause onset and age at start of HRT were partially dealt with through matching by age. The results were also adjusted for information on lifestyle, comorbidities, and use of other drugs, and the study presents subgroup analyses for women in different age groups and in different BMI categories. Protopathic bias, from diagnostic and prescribing problems created by symptoms common to early breast cancer and onset of menopause, was minimised by excluding prescriptions issued in the year before the index date.

Some limitations of this study arise from inevitable shortfalls in completeness and accuracy within any routinely collected dataset. A small proportion of women had missing information on smoking status, alcohol consumption, and BMI, but these were dealt with by multiple imputation. As we did not have reliable data for age at onset of menopause for all women, we estimated onset from the first menopause specific record before the earliest HRT prescription. For women with no such record we assumed onset within the most common age range of 50 to 54 years. We did not investigate the differences between continuous and sequential HRT because these regimens are prescribed at different times after menopause. As our cases and controls were matched by age, they would likely have been prescribed similar regimens, making a comparison infeasible. Our primary focus, anyway, was recent long term exposure.

No reliable data were available for established risk factors for breast cancer, such as parity or time of the first pregnancy, but there is no evidence to show that these are related to HRT use. No data for physical activity were available, but a possible risk reduction for active women has been shown not to be influenced by menopausal status. 23 Some women might have joined their current practice after the onset of menopause, so records of past treatments might not have been available. The results from the subgroup restricted to women with at least 10 years of data, however, showed a similar pattern of risk associations to that of the main analysis. Use of HRT might have the side effect of increased breast density, possibly masking cancers and leading to diagnostic delays, 24 which could shift odds ratios for short duration towards unity. Also, although there was no information about adherence to HRT, any systematic differences between cases and controls seems unlikely because information was recorded prospectively before diagnosis. Conversations with lay women involved in this research also revealed a high adherence to HRT.

Strengths and weaknesses in relation to other studies

Our study used a nested case-control design, so it did not follow women prospectively from the start of HRT or assess average lifetime risks. Rather, it looked back at already recorded exposures to HRT for women with a diagnosis of breast cancer and matched controls in the age range 50 to 79 and produced comparisons of risks averaged across all time points at which diagnoses in the datasets occurred. The study is based on data derived from real world treatment settings, when women might not have had a constant supply of a preparation and might have needed to switch drugs during the study period. Including all exposures prescribed over time allowed us to present information for a wide range of common types of HRT.

Most trials produced results for a more restricted number of treatments. A meta-analysis of existing trials, 7 taken largely from the Women’s Health Initiative study, provided estimates only for the specific treatments of conjugated equine oestrogen with and without medroxyprogesterone. 6 In contrast to our estimates of a slightly increased risk for long term users of conjugated equine oestrogen (average duration for recent exposure of 5.6 years, odds ratio 1.07, 95% confidence interval 1.01 to 1.12), the meta-analysis found no difference in risk of breast cancer (relative risk 0.79, 95% confidence interval 0.61 to 1.02) after a mean duration of 7.2 years. The observed relative risk for the combined conjugated equine oestrogen with medroxyprogesterone therapy after a mean duration of 5.6 years (1.27, 1.03 to 1.56) was similar to our findings for recent exposure, with an average duration of 3.7 years (odds ratio 1.35, 1.30 to 1.41).

Our estimates were consistent with previous observational studies. 9 25 26 27 The Million Women Study 28 29 showed slightly higher risks than our study: for recent oestrogen only users a relative risk of 1.30 (95% confidence interval 1.21 to 1.40) compared with our odds ratio of 1.12 (1.08 to 1.16), and for recent oestrogen-progestogen users a relative risk of 2.00 (1.88 to 2.12) compared with our odds ratio of 1.51 (1.47 to 1.54). However, the Million Women Study only covered a selected population of women who had undergone mammography, and the initial study used just a single baseline questionnaire to collect information. 28 Taken together, the relatively high proportion of HRT users in the initial study (55% were ever users and 35% were current users) and the less than 65% response rate at three years of follow-up, which would be expected also to be skewed towards HRT users, would suggest that women who used HRT were more likely to have participated. 29

In general, some inconsistency was found between the proportions of women exposed to HRT in data used for our study and those used in the 2019 meta-analysis. 11 The predominant (40%) data source for the meta-analysis was from the Million Women Study, where, 51% of cases had ever been exposed to HRT and 18% of cases were current users (<5 years). The second largest data source, comprising 28% of the data used in the meta-analysis, was routinely collected CPRD data (one of the two data sources in our study), and here 40% of women with breast cancer had been exposed to HRT and 12% were current users. Both these exposure rates contrast with those in our study, which overall had 34% of cases ever exposed and 19% of cases with prescriptions within 1-5 years before diagnosis.

We cannot speculate on reasons for these differences in the CPRD data used because we do not have access to relevant information for the 2019 meta-analysis. That sample contained slightly older cases (mean age at diagnosis 66 v 63 in our sample) but no age range was reported. The estimations of risk for overall use of HRT in our CPRD analysis (odds ratio 1.21, 95% confidence interval 1.18, 1.25) were, however, similar to the CPRD specific estimations reported in the meta-analysis (relative risk 1.25, 95% confidence interval 1.20, 1.30). For recent use (prescriptions 1-2 years before the index date), when the proportions of HRT users in CPRD data used in our study and in the meta-analysis were closest, the estimates of risk were also similar. In our analysis of CPRD data on recent use, the odds ratios were 1.25 (1.17 to 1.34) for oestrogen only and 1.91 (1.83 to 1.99) for oestrogen-progestogen, whereas for the CPRD data used in the meta-analysis the corresponding findings were 1.36 (1.25 to 1.4) and 2.16 (2.02 to 2.31).

Comparative assessment of the findings from the 2019 meta-analysis is in general complicated by the heterogeneity of included studies and data sources. The meta-analysis included data from 24 differently designed prospective studies from around the world. Differences between findings from our large, consistently designed study and those from the meta-analysis might be related to the different periods covered by included studies or several problems relating to the different data sources. Some studies used routinely collected data with different definitions of exposure, 9 30 some used questionnaires with a single baseline assessment of exposure, 27 28 31 and others used repeated biennial questionnaires. 25 32 Some participants were recruited from different countries with ever exposure levels varying from 19% to 69%, 8 and some studies were from different profession related populations. 8 25

Overall, our results were broadly in line with those of the meta-analysis 11 but with slightly lower risks for long term exposures. This might partly be explained by almost half of the cases in the meta-analysis coming from the Million Women Study. For current use, however, the meta-analysis reported similar associations with risk of breast cancer, regardless of whether such use was restricted to HRT exposure within the past five years or within the past two years. By contrast, we found associations to be more pronounced for users with a prescription recency of 1-2 years before the index date, with higher odds ratios than for an exposure recency of 1-5 years. Our results with a recency definition of 1-2 years were broadly similar to those of the meta-analysis for either of their definitions of current use, whereas our findings for 1-5 years recency were lower. The difference in risk found by us seems to be more in line with previous expectations of declines in risk after cessation of HRT. 7

Our findings for oestrogen only users with recent (1-5 years) use of more than five years (odds ratio 1.15, 95% confidence interval 1.09 to 1.21) were lower than those from the meta-analysis (relative risk 1.33, 95% confidence interval 1.28 to 1.38). 11 Our study also found a marginally higher risk associated with estradiol than with conjugated equine oestrogen. For oestrogen-progestogen therapy, our finding for recent use of more than five years duration was also lower (1.79, 1.73 to 1.85) than the meta-analysis estimate (2.08, 2.02 to 2.15). Despite the similar average duration of exposures between our study and those in the meta-analysis, our findings for the different types of the most common progestogens and tibolone were consistently lower than those of the meta-analysis (supplementary eTable 16).

For dydrogesterone, our study found lower risks associated with more than five years of exposure than in the meta-analysis (1.24, 1.03 to 1.48 v 1.41, 1.17 to 1.71). 11 The risk from dydrogesterone was much lower than for any other progestogen, but one of our sensitivity analyses did show a statistically significant increased risk for a small subgroup of dydrogesterone users—those with a prescription 1-2 years before the index date and more than five years of use (112 cases, odds ratio 1.47, 1.19 to 1.83).

Our study showed differential risks associated with HRT use by age category. For recent exposures of more than five years’ duration, associated risks of breast cancer rose with increasing age category. This might partly be explained by generally longer usages in older age categories, although exposure of 1-4 years was similarly associated with increasing risk from younger to older age groups of women. Our findings for the 70-79 age group for oestrogen only use (1.25, 1.11 to 1.39) and for oestrogen-progestogen use (2.20, 2.02 to 2.39) are in line with findings from the meta-analysis 11 for women who started HRT at the age of 55-59 and continued treatment for 5-14 years : oestrogen only use of 1.26 (1.12 to 1.41) and oestrogen-progestogen use of 1.97 (1.81 to 2.15).

The adiposity of included women differed between our study and previous studies. Mean BMI in our study (27.7 in cases) was higher than in other observational studies (average 25) 33 but slightly lower than in the Women’s Health Initiative trial (28.5). 34 This could help to explain overall differences in associations between our findings and those of other studies, although the mean BMI in our study reflects the distribution within women with breast cancer diagnosed in the general UK population over the study period. Our findings for women matched by age and category of BMI are detailed and comprehensive estimations of duration dependent associations for HRT exposure and breast cancer risk. They are broadly similar to those from previous studies and the 2019 meta-analysis, 11 33 with the lowest associations between HRT use and risk of breast cancer in women in the highest BMI category. These concur with findings from the Million Women Study (which had relatively small numbers) and an earlier meta-analysis. 29 35 Some complex biological relation might exist between fat tissue and HRT, 36 although it might also be related to differences in timeliness of diagnoses between women with different body weights.

Implications for clinicians and policymakers

This study delivers more generalisable estimates of the different risks of breast cancer associated with specific progestogen components of HRT, while confirming no increased risks from short term use of oestrogen only, estradiol-dydrogesterone, and tibolone. Increasing duration of use was generally associated with increased risk, with tibolone and estradiol-dydrogesterone showing the smallest risks. The frequency of prescribing for treatments including dydrogesterone was, however, much lower than for those including norethisterone, medroxyprogesterone, or levonorgestrel.

Unanswered questions and future research

In our study protocol we did not prespecify analyses relating to cancer stage or tumour type because these lay outside the main question of interest. Although information on risk related to individual progestogens could be improved, previous studies have shown that the associated risks between HRT and tumour types might differ, with higher risks of developing oestrogen receptor positive tumours and lobular tumours. 11 Knowing the cancer stage could also address the question of risk differences between women of various body weights, to clarify whether systematic differences might exist in diagnostic delay. Other unknowns include questions about breast cancer survival rates and all cause mortality in women using HRT. 13

This large observational study of HRT and breast cancer risk based on two large primary care databases analysed in an identical manner has confirmed the excess risk to be attributable mostly to combined treatments, with the lowest risks associated with use of the least commonly prescribed dydrogesterone. Rarely prescribed tibolone also showed low increased risks.

Our findings of generally lower increased risks for combined HRT treatments and of more pronounced declines in risk once HRT has stopped, provide some counterbalance to the higher than expected risks reported in a recently published meta-analysis. 11 Our results add more evidence to the existing knowledge base and should help doctors and women to identify the most appropriate HRT formulation and treatment regimen, and provide more consistently derived information for women’s health experts, healthcare researchers, and treatment policy professionals.

What is already known on this topic

• Long term systemic use of hormone replacement therapy (HRT) is associated with increased risks of breast cancer, mostly attributable to the progestogens medroxyprogesterone, norethisterone, and levonorgestrel
• After discontinuation of treatment, the increased risks decline, but remain raised for some years
• A recent large meta-analysis has reported higher than expected breast cancer risks associated with HRT

What this study adds

• The study confirmed increased risks of breast cancer associated with long term use of oestrogen only therapy and combined oestrogen and progestogen therapy
• The combined treatment associated with the lowest risk increase was estradiol-dydrogesterone
• The findings suggest lower increased risks of breast cancer associated with longer term HRT use, and a more noticeable decline in risks once treatment is stopped compared with the meta-analysis

Acknowledgments

We acknowledge the contribution of EMIS practices who contribute to the QResearch database and EMIS and the University of Nottingham for expertise in establishing, developing, and supporting the QResearch database and the Chancellor masters and schools of the University of Oxford for continuing to develop and support the QResearch database. The Hospital Episode Statistics data used in this analysis are re-used by permission from the NHS Digital who retain the copyright. We thank the Office for National Statistics (ONS) for providing the mortality data. ONS and NHS Digital bear no responsibility for the analysis or interpretation of the data. This project involves data derived from patient level information collected by the NHS, as part of the care and support of patients with cancer. The data are collated, maintained, and quality assured by the National Cancer Registration and Analysis Service, which is part of Public Health England (PHE). Access to the data was facilitated by the PHE Office for Data Release. QResearch acknowledges funding from the National Institute for Health Research funded Nottingham Biomedical Research Centre until 31 January 2019 and the CRUK Cancer Centre and Wellcome Trust from 1 October 2019. Lauren Taylor (Division of Primary Care University of Nottingham) contributed clinical advice, in particular on the pharmacology of treatments and decisions made in the prescribing process, at the stage of interpreting the results and we should like to acknowledge these inputs with gratitude.

Web extra. 

Extra material supplied by authors

Supplementary information: Tables e1-e16 and figures e1-e7

Contributors: YV contributed to the study protocol, reviewed the literature, designed the study, organised the extraction of CPRD data, did the analysis on both datasets and wrote the draft of the manuscript. JHC initiated the study, undertook the original literature review, drafted the study protocol, organised the extraction of the QResearch data, advised on the design and clinical aspects of the study and interpretation of the results and drafting of the paper. CC contributed to the development of the idea and the study design and advised on the analysis and interpretation of the results. JHC and CC critically reviewed the paper. YV is the guarantor of the study. All authors have approved the submitted version. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: This work is partially funded by the National Institute for Health Research (NIHR) School for Primary Care Research (project reference 848619) and by Cancer Research UK (grant No C5255/A18085) through the cancer research UK Oxford Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare support from the National Institute for Health Research School for Primary Care Research and by Cancer Research UK through the cancer research UK Oxford Centre; JHC is professor of clinical epidemiology at the University of Oxford and unpaid director of QResearch, a not-for-profit organisation which is a joint partnership between the University of Oxford and EMIS (commercial IT supplier for 60% of general practices in the UK). JHC was a paid director of ClinRisk until 2019, which produces open and closed source software to ensure the reliable and updatable implementation of clinical risk algorithms within clinical computer systems to help improve patient care; no other relationships or activities that could appear to have influenced the submitted work.

Ethical approval: The protocol for QResearch has been published in ePrints and was reviewed in accordance with the requirements for the East Midlands Derby Research Ethic Committee (ref 03/4/021). The protocol for CPRD has been approved by the Independent Scientific Advisory Committee for MHRA Database Research (N 16_282).

Data sharing: To guarantee the confidentiality of personal and health information only the authors have had access to the data during the study in accordance with the relevant licence agreements. Access to the QResearch data are according to the information on the QResearch website ( www.qresearch.org ). CPRD linked data were provided under a licence that does not permit sharing.

The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted and that any discrepancies from the study as planned have been explained.

Dissemination to participants and related patient and public communities: The results of the study will be sent to University of Nottingham press office, to related patients, and to the funders. A lay summary will be created and published at SPCR NIHR and QResearch website.

Provenance and peer review: Not commissioned; externally peer reviewed.

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For more information, visit the National Cancer Institute's Breast Cancer Treatment Option Overview. This site can also help you find health care services.

Which treatment is right for me?

Talk to your cancer doctor about the treatment options available for your type and stage of cancer. Your doctor can explain the risks and benefits of each treatment and their side effects. Side effects are how your body reacts to drugs or other treatments.

Sometimes people get an opinion from more than one cancer doctor. This is called a "second opinion." Getting a second opinion may help you choose the treatment that is right for you.

Clinical trials

Clinical trials use new treatment options to see if they are safe and effective. If you have cancer, you may want to take part. Visit the sites listed below for more information.

• NIH Clinical Research Trials and You (National Institutes of Health)
• Learn About Clinical Trials (National Cancer Institute)
• Search for Clinical Trials (National Cancer Institute)
• ClinicalTrials.gov (National Institutes of Health)

Complementary and alternative medicine

Complementary and alternative medicine are medicines and health practices that are not standard cancer treatments. Complementary medicine is used in addition to standard treatments. Alternative medicine is used instead of standard treatments. Acupuncture and supplements like vitamins and herbs are some examples.

Many kinds of complementary and alternative medicine have not been tested scientifically and may not be safe. Talk to your doctor about the risks and benefits before you start any kind of complementary or alternative medicine.

• Types of Treatment for Breast Cancer (National Cancer Institute)
• Complementary and Alternative Medicine for Patients (National Cancer Institute)

Breast Cancer

Talk to your doctor about when to start and how often to get a mammogram.

For Everyone

Public health.