Breast Cancer HealthRisk Assessment

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Medically Reviewed By: Expert-24 Medical Review Board on March 27, 2014 | References

HEALTHTOOLS™ (HEALTHRISK™ AND HEALTHAGE™) DOES NOT PROVIDE MEDICAL ADVICE. It is intended for informational purposes only. It is not a substitute for professional medical advice, diagnosis or treatment. Never ignore professional medical advice in seeking treatment because of something you have read on the site. If you think you may have a medical emergency, immediately call your doctor or dial 911.

Expert Review Panel – Expert-24 Ltd

Terms of reference

The aim of the Expert Review Panel is to ensure that all Expert-24 clinical and epidemiological content is robust, independent and up to date.


Medical Director and Editor

Dr. Timothy Dudley

Chairman of the Expert Review Panel

Dr. Robin Christie

Current authors and reviewers for the Health Risk Assessment

Dr. Martin Dawes

Dr. Jonathan Mant

Emeritus authors and reviewers for the Health Risk Assessment

The following individuals were deeply involved in the creation of the health risk assessment at its inception, but are no longer active reviewers on the panel:

Dr. John Fletcher

Dr. Emma Boulton

Professor Larry Ramsay

Professor Klim McPherson

Patient-centered health risk using an Evidence Based Medicine approach

Who created it and how often is it reviewed and updated?

This health risk assessment is brought to you by Expert-24 Limited. Expert-24 Ltd has full editorial control over content and strives to ensure that the content is: 

  • Robust - All information used is derived from reputable, referenced sources and subject to rigorous expert review. The content is written by the medical staff of Expert-24 and reviewed by an independent Expert Review Panel. All content is subject to regular review and updated to incorporate the latest evidence. Oxford Health Consulting was commissioned to conduct independent research to determine the model for disease and mortality-specific risks, the contents and its assumptions. The research and statistical modeling behind the risk assessment has been led by Dr. John Fletcher. Dr. Fletcher is deputy editor of the Canadian Medical Association Journal. He holds a Masters degree in Public Health Quantitative Methods and is a member of the Royal College of General Practitioners. 
  • Independent - The content on the site is provided by Expert-24 Limited, an independent UK company providing knowledge automation and decision support tools to improve health and wellbeing. No member of the Expert Review Panel has any financial stake in Expert-24 Ltd. Content creation and ongoing Quality Assurance is provided by Expert-24 Ltd and its Expert Review Panel. 
  • Up to date - All clinical material is subject to review by Expert-24 and its Expert Review Panel at least annually.

Why is this health risk assessment different than others?

Most health risk assessments say if a person is at high, medium or low risk of either dying from or developing a given medical condition. Most also indicate what lifestyle factors contribute to this risk. What they do not say is the magnitude of each risk for an individual and how much that person’s risk will decrease if they change their lifestyle. For example, if one is at moderate risk of two diseases, say bowel cancer and heart disease, most people would be unaware that their risk of heart disease is still five times higher than their risk of bowel cancer. 

In order to construct an electronic risk assessment tool for health and disease states, it is necessary to provide supporting research evidence and a method of encapsulating the best estimate of relative risk. For each medical condition, it is necessary to present credible estimates of risk, based on evidence from relevant, peer reviewed medical research. Important features of the risk assessment tool are: 
  • The tool gives numerical estimates of risk, rather than an imprecise statement such as "increased risk" or "reduced risk". 
  • The tool has the capability for interaction, allowing users to explore the impact on their personal risk of changing individual risk factors. 
  • The tool utilizes best available medical evidence 

The aim of this project is to provide healthy people with a quantitative assessment of their personal risk of developing some important diseases and some of the factors that influence their risk. This is an ambitious task and we would not claim to have produced the definitive approach. Although we believe this is the most informative collection of disease prediction equations available at the present time they do have limitations. The ones we are aware of are outlined below.

What exactly does a given percentage risk mean?

Someone looking at their risk of lung cancer until the age of 50 should read this model as saying, "Assuming survival to age 50 the chance of developing lung cancer during that time would be (some predicted value)". This approach has the appeal that changing risk factors will have the expected impact on cumulative risk and the mathematics remains transparent. We chose the risk of developing a certain condition rather than the risk of dying from it because for many people the fear of living and dealing with a disabling disease is as frightening as dying from it. 

This is different than lifetime risk calculations, which generally calculate the risk of dying from a given condition. Lifetime risk must take account of the fact that we all die of something in the end and calculating the relative contribution of common competing causes of death at various ages is difficult. Not only that, but the interpretation by users is complex. For example, a user of an interactive model predicting lifetime risk of lung cancer would see their individual risk of lung cancer fall with increasing cigarette consumption, because they would be dying of heart disease and chronic lung disease before they could get lung cancer.

How accurate are these percentages?

These models are good for illustrating the change in risk due to the presence or absence of single risk factors for prediction times of up to 5 years. They are likely to be reasonably good for 15 or 20 years and for combinations of several risk factors. For longer prediction times and varying more than, say, four risk factors the results should be regarded as illustrative rather than precise. The absolute level of risk for an individual may also be wide of the mark because the majority of overall risk remains unexplained in most research studies. This is why "confidence intervals" have not been included. That said these prediction equations do calculate the best estimate of risk that can be provided on the data given. 

Is this useful in the end? We believe it is. We believe that putting some quantification on risk allows users to explore the possible impact on their health of altering what they do. We find this approach more informative than a bland statement of "high risk" that is often value laden or that a certain action will "cut down" a risk without any indication of by how much.

Is risk really reversible?

This is a difficult question to answer, but in many cases the answer seems to be, "yes". This is good news for people with high risks who are older. Intuition might tell you that you are constantly doing damage to your body that accumulates over time, and in many cases that may be true. An example of this is in skin cancer, where the earlier and more often you are badly burned in life, the higher your risk of skin cancer. Staying out of the sun when you are old cannot reverse this risk. 
However, there is good evidence that for heart disease, for example, your risks can be significantly reduced no matter what your age. Cholesterol reduction by medications called "statins" reduces the risk of heart attack, angina or sudden death from heart problems by up to 30%, and this is entirely independent of age. Similarly, blood pressure reduction by drugs reduces the risk of stroke and heart disease by 25% - again entirely independent of age. Because in general it is older people who have the highest risks, they actually stand to benefit the most from treatment. 

The risk for developing heart disease in tobacco users has been shown to decline to a level comparable with a person who has never smoked within 2-3 years of giving up. Furthermore, the risk of having a stroke is reversed after 5-10 years of stopping. Studies have also shown that life expectancy improves even in people who stop smoking later in life (i.e. at 65 years or older). 

The reduction of risk that can be obtained from changing lifestyle habits such as diet, alcohol consumption and exercise is largely unknown. Therefore, the amount of risk reduction that can be expected from optimizing these habits needs to be viewed with caution. Certainly they should not take the place of blood pressure control, cholesterol control, and smoking cessation as goals.

How good is the evidence?

Our aim in searching for evidence was to identify up to ten high quality, relevant research studies for each topic. We used Medline to search using free text, MeSH terms and thesaurus search terms specific to each medical condition. To narrow the documents we used filters using "risk" and study design type; cohorts, case control, longitudinal, follow up. Searches were limited to studies published in English language and human studies. Although a comprehensive systematic review of the literature on each disease was not possible due to the scope of this project, we feel that the evidence used represents a reasonable cross-section of high-quality literature on the subjects in question. 
What we have done is to seek out plausible values of relative risk to use in the prediction equations. We have used an approach that searches for high quality research studies and have then applied our judgment tempered by Austin Bradford Hill's criteria for causation when selecting which risks to use. Hill's criteria are: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experimental evidence and analogy. 

If this sometimes appears somewhat subjective then that is because at times it is a matter of judgment. The judgments have seldom altered the relative risk by more than a small amount. For each risk factor we had to choose a value to use in the model and have been faced at times with a range from which to choose. While a meta-analysis may provide the best point estimate, one is not always available and would be spurious to conduct on the sample of studies we have used for each condition. Given the level of uncertainty surrounding an individual's absolute personal risk we are comfortable with a comparatively lesser degree of uncertainty regarding a risk factor's relative risk.

What is the mathematical model that is used?

The actual mathematical and statistical models and risk coefficients that are used to determine risk are proprietary at this time, but have been validated by the authors and reviewers to be appropriate for use in this setting. 

References: Breast Cancer

Most recently reviewed:

  1. Gonzalez CA and Riboli E. Diet and Cancer Prevention: Contributions from the European Prospective Investigation into Cancer and Nutrition Study. Euro J Cancer 46 (2010) 2555 –2562.
  2. Chen, WY et al. Moderate Alcohol Consumption During Adult Life, Drinking Patterns, and Breast Cancer Risk. JAMA 2011; 306(17): 1884-1890.
  3. Petracci E, Gail M, et al. Risk Factor Modification and Projections of Absolute Breast Cancer Risk. J Natl Cancer Inst 2011; 03:1037-1048.
  4. World Cancer Research Fund and the American Institute for Cancer Prevention. Recommendations based on the Second Expert Report. Food, Nutrition, Physical Activity and the Prevention of Cancer: A Global Perspective. 2007

Guidelines reviewed annually:

  1. American Cancer Society Guidelines for the early detection of cancer at
  2. NHS Cancer screening programmes at
  3. National Institute for Health and Clinical Excellence at
  4. Risk of breast cancer at
  5. United States Preventive Services Task Force at

Selected articles from previous reviews:

  1. Duffy, SW et al. Absolute numbers of lives saved and over diagnosis in breast cancer screening, from a randomized trial and from the Breast Screening Programme in England. J. Med. Screen 2010; 17:25-30
  2. Canadian Expert Panel on Tobacco Smoke and Breast Cancer Risk, April 2009 at
  3. Schreer, I. Dense breast tissue as an important risk factor for breast cancer and implications for early detection. Breast Care 2009; 4(2): 89-92.
  4. Gøtzsche PC, Nielsen M. Screening for breast cancer with mammography. Cochrane Database of Systematic Reviews 2009, Issue 4. Art. No.: CD001877.
  5. Tosteson AN, Stout NK, Fryback DG, for the DMIST Investigators. Cost-effectiveness of digital mammography breast cancer screening. Ann Intern Med 2008;148(1):1-10.
  6. Sweeney C, Baumgartner KB, Byers T, Giuliano AR, Herrick JS, Murtaugh MA, et al. Reproductive history in relation to breast cancer risk among Hispanic and non-Hispanic white women. Cancer Causes Control. 2008 May ;19(4):391-401.
  7. International Menopause Society concensus statement on HRT and risk of cancer at:
  8. Benetou, V. et al. Conformity to traditional Mediterranean diet and cancer incidence: Greek EPIC cohort. British J. Ca. (1 July, 2008) 99, 191-195
  9. Kushi, L.H. et al. American Cancer Society Guidelines on Nutrition and Physical Activity for Cancer Prevention: Reducing the Risk of Cancer With Healthy Food Choices and Physical Activity CA Cancer J. Clin. 2006; 56 (5):254-281
  10. Chlebowski RT, et al. Dietary fat reduction and breast cancer outcome: interim efficacy results from the Women's Intervention Nutrition Study. J Natl Cancer Inst. 2006 Dec 20;98(24):1767-76.
  11. Breast Cancer Management - alcohol consumption. Clinical Knowledge Summaries. Minor update May 2007 at:
  12. Takkouche B, et al. "Personal use of hair dyes and risk of cancer: a meta-analysis." JAMA May 25, 2005, 293(20):2516-252.
  13. Duijts SF, et al. "The association between stressful life events and breast cancer risk: a meta-analysis." Int J Cancer Dec. 20, 2003, 107(6):1023-9
  14. Boyd NF, et al. "Dietary fat and breast cancer risk revisited: a meta-analysis of the published literature." Br J Cancer Nov 2003, 89(9):1672-85
  15. McTiernan A, et al. "Recreational physical activity and the risk of breast cancer in postmenopausal women: the Women's Health Initiative Cohort Study." JAMA 10/09/
  16. Calle EE, et al. "Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults." N Engl J Med Apr 24, 2003, 348(17):1625-38
  17. Rossouw JE et al. "Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial." JAMA 2002 Jul 17 288(3):321-33.
  18. Ellison RC et al. "Exploring the relation of alcohol consumption to risk of breast cancer" Am J Epidemiol. Oct 15, 2001; 154(8):740-7.
  19. Key, T.J. et al, "Epidemiology of breast cancer." Lancet Oncology 01 Mar 2001; 2(3): 133-40
  20. Hamajima, N. et al, "Alcohol, tobacco and breast cancer--collaborative reanalysis of individual data from 53 epidemiological studies, including 58,515 women with breast cancer and 95,067 women without the disease." British Journal of Cancer, 18 Nov 2002; 87(11): 1234-45
  21. Bianchini, F., "Overweight, obesity, and cancer risk." Lancet Oncology 01Sep 2002; 3(9): 565-74
  22. Lahmann, P.H., "A prospective study of adiposity and postmenopausal breast cancer risk: The Malmö diet and cancer study." International Journal of Cancer 10 Jan 2003; 103(2): 246-52
  23. Boyd, N.F., "Heritability of mammographic density, a risk factor for breast cancer." New England Journal of Medicine 19 Sep 2002; 347(12): 886-94
  24. Lillberg, K., "Stressful life events and risk of breast cancer in 10,808 women: a cohort study." American Journal of Epidemiology 1 Mar 2003; 157(5): 415-23
  25. Kropp, S., "Active and passive smoking and risk of breast cancer by age 50 years among German women." American Journal of Epidemiology 1 Oct 2002; 156(7): 616-26
  26. Egan, K.M., "Active and passive smoking in breast cancer: prospective results from the Nurses' Health Study." Epidemiology 01 Mar 2002; 13(2): 138-45
  27. Band, P.R., "Carcinogenic and endocrine disrupting effects of cigarette smoke and risk of breast cancer." Lancet 5 Oct 2002; 360(9339): 1044-9
  28. Layde, P.M., "The independent associations of parity, age at first full term pregnancy, and duration of breastfeeding with the risk of breast cancer. Cancer and Steroid Hormone Study Group." Journal of Clinical Epidemiology 01 Jan 1989; 42(10): 963-73
  29. Lipworth, L., "History of breast-feeding in relation to breast cancer risk: a review of the epidemiologic literature." Journal of the National Cancer Institute, 16 Feb 2000; 92(4): 302-12
  30. Little, M.P., "Comparison of breast cancer incidence in the Massachusetts tuberculosis fluoroscopy cohort and in the Japanese atomic bomb survivors." Radiation Research, 01 Feb 1999; 151(2): 218-24
  31. Doody, M.M., "Mortality among United States radiologic technologists, 1926-90." Cancer Causes Control, 01 Jan 1998; 9(1): 67-75
  32. Evans, J.S., "The influence of diagnostic radiography on the incidence of breast cancer and leukemia." New England Journal of Medicine 25 Sep 1986; 315(13): 810-5
  33. Eunyoung, C., et al, "Premenopausal Fat Intake and Risk of Breast Cancer" Journal of the National Cancer Institute, Vol. 95, No. 14, 1079-1085, July 16, 2003
  34. Clavel-Chapelon, F., "Differential effects of reproductive factors on the risk of pre- and postmenopausal breast cancer. Results from a large cohort of French women." British Journal of Cancer 4 Mar 2002; 86(5): 723-7
  35. Holmes MD, et al. "Physical activity and survival after breast cancer diagnosis". JAMA 5 May 2005; 293(20):2479-86
  36. Key TJ, et al. "Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women" J Natl Cancer Inst. 20 Aug. 2003; 95(16):1218-26
  37. Duijts SF, et al. "The association between stressful life events and breast cancer risk: a meta-analysis." Int J Cancer 20 December 2003; 107(6):1023-9
  38. Collaborative group on hormonal factors in breast cancer, "Breast cancer and hormonal contraceptives: collaborative reanalysis of individual data on 53,297 women with breast cancer and 100,239 women without breast cancer from 54 epidemiological studies", Lancet, 1996 347:1713-1727
  39. Colditz, et al, "Family History, Age and Risk of Breast Cancer; Prospective data from the Nurses Health Study", JAMA 1993 270: 338-343
  40. Schairer, et al, "Menopausal Estrogen and Progestin-Estrogen Replacement therapy and Breast Cancer Risk", JAMA 2000 283: 485-491