Applications of Personalized Estimates of Absolute Breast Cancer Risk
- 146 Downloads
Absolute risk is the probability that a given health outcome will be observed in a defined time period in the presence of competing causes of death. In this commentary I discuss some applications of models of absolute breast cancer risk that account for a woman’s particular risk factors. Such models can be useful in counseling by giving perspective on the level of risk, and as an aid to weighing risks and benefits, as in deciding whether or not to take tamoxifen to prevent breast cancer. Absolute risk models also have applications in public health, such as in designing intervention trials to prevent breast cancer and in assessing the potential reductions in absolute risk of disease that might result from reducing exposures. Other potential public health applications that require models with high discriminatory accuracy are to identify “high risk” subsets of the population that might benefit from a preventive intervention or screening, or to rank members of the population on risk to allocate preventive resources under cost constraints.
KeywordsAbsolute risk Breast cancer Crude risk Cumulative incidence Disease prevention Risk versus benefit
This work was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.
- 9.Gail MH, Costantino JP, Pee D, Bondy M, Newman L, Selvan M, Anderson GL, Malone KE, Marchbanks PA, McCaskill-Stevens W, Norman SA, Simon MS, Spirtas R, Ursin G, Bernstein L (2007) Projecting individualized absolute invasive breast cancer risk in African American women. J Natl Cancer Inst 99:1782–1792 CrossRefGoogle Scholar
- 23.Calonge N, Petitti DB, DeWitt TG, Dietrich AJ, Gregory KD, Grossman D, Isham G, LeFevre ML, Leipzig RM, Marion LN, Melnyk B, Moyer VA, Ockene JK, Sawaya GF, Schwartz JS, Wilt T (2009) T screening for breast cancer: US preventive services task force recommendation statement. Ann Intern Med 151:716–726 CrossRefGoogle Scholar
- 24.Gail M, Rimer B (1999) Risk-based recommendations for mammographic screening for women in their forties (vol 16, pg 3105, 1998). J Clin Oncol 17:740. Google Scholar
- 26.van Ravesteyn NT, Miglioretti DL, Stout NK, Lee SJ, Schechter CB, Buist DS, Huang H, Heijnsdijk EA, Trentham-Dietz A, Alagoz O, Near AM, Kerlikowske K, Nelson HD, Mandelblatt JS, de Koning HJ (2012) Tipping the balance of benefits and harms to favor screening mammography starting at age 40 years: a comparative modeling study of risk. Ann Intern Med 156:609–617 CrossRefGoogle Scholar
- 28.Fisher B, Costantino JP, Wickerham DL, Redmond CK, Kavanah M, Cronin WM, Vogel V, Robidoux A, Dimitrov N, Atkins J, Daly M, Wieand S, Tan-Chiu E, Ford L, Wolmark N (1998) Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 study. J Natl Cancer Inst 90:1371–1388 CrossRefGoogle Scholar
- 29.Vogel VG, Costantino JP, Wickerham DL, Cronin WM, Cecchini RS, Atkins JN, Bevers TB, Fehrenbacher L, Pajon ER, Wade JL, Robidoux A, Margolese RG, James J, Lippman SM, Runowicz CD, Ganz PA, Reis SE, McCaskill-Stevens W, Ford LG, Jordan VC, Wolmark N (2006) Effects of tamoxifen vs raloxifene on the risk of developing invasive breast cancer and other disease outcomes—the NSABP study of tamoxifen and raloxifene (STAR) p-2 trial. JAMA J Am Med Assoc 295:2727–2741 CrossRefGoogle Scholar
- 31.Rose GA (1992) The strategy of preventive medicine. Oxford University Press, Oxford Google Scholar