Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.

BACKGROUND Women and their clinicians are increasingly encouraged to use risk estimates derived from statistical models, primarily that of Gail et al., to aid decision making regarding potential prevention options for breast cancer, including chemoprevention with tamoxifen. METHODS We evaluated both the goodness of fit of the Gail et al. model 2 that predicts the risk of developing invasive breast cancer specifically and its discriminatory accuracy at the individual level in the Nurses' Health Study. We began with a cohort of 82 109 white women aged 45-71 years in 1992 and applied the model of Gail et al. to these women over a 5-year follow-up period to estimate a 5-year risk of invasive breast cancer. All statistical tests were two-sided. RESULTS The model fit well in the total sample (ratio of expected [E] to observed [O] numbers of cases = 0.94; 95% confidence interval [CI] = 0.89 to 0.99). Underprediction was slightly greater for younger women (<60 years), but in most age and risk factor strata, E/O ratios were close to 1.0. The model fit equally well (E/O ratio = 0.93; 95% CI = 0.87 to 0.99) in a subset of women reporting recent screening (i.e., within 1 year before the baseline); among women with an estimated 5-year risk of developing invasive breast cancer of 1.67% or greater, the E/O ratio was 1.04 (95% CI = 0.96 to 1.12). The concordance statistic, which indicates discriminatory accuracy, for the Gail et al. model 2 when used to estimate 5-year risk was 0.58 (95% CI = 0.56 to 0.60). Only 3.3% of the 1354 cases of breast cancer observed in the cohort arose among women who fell into age-risk strata expected to have statistically significant net health benefits from prophylactic tamoxifen use. CONCLUSIONS The Gail et al. model 2 fit well in this sample in terms of predicting numbers of breast cancer cases in specific risk factor strata but had modest discriminatory accuracy at the individual level. This finding has implications for use of the model in clinical counseling of individual women.

[1]  J. Manson,et al.  Plasma sex steroid hormone levels and risk of breast cancer in postmenopausal women. , 1998, Journal of the National Cancer Institute.

[2]  M H Gail,et al.  Weighing the risks and benefits of tamoxifen treatment for preventing breast cancer. , 1999, Journal of the National Cancer Institute.

[3]  J Benichou,et al.  Validation studies for models projecting the risk of invasive and total breast cancer incidence. , 1999, Journal of the National Cancer Institute.

[4]  J. Benichou,et al.  Validation studies on a model for breast cancer risk. , 1994, Journal of the National Cancer Institute.

[5]  H. Tongaonkar,et al.  Cancer prevention. , 1998, Indian journal of medical sciences.

[6]  J. Benichou,et al.  Epidemiology and Biostatistics Program of the National Cancer Institute , 1994 .

[7]  G. Colditz,et al.  The nurses' health study: a cohort of US women followed since 1976. , 1995, Journal of the American Medical Women's Association.

[8]  P. Strax,et al.  A prospective study of endogenous estrogens and breast cancer in postmenopausal women. , 1995, Journal of the National Cancer Institute.

[9]  M. Coughlin,et al.  Radial Scars in Benign Breast‐Biopsy Specimens and the Risk of Breast Cancer , 2000 .

[10]  F. Harrell,et al.  Regression models in clinical studies: determining relationships between predictors and response. , 1988, Journal of the National Cancer Institute.

[11]  R. Hoover,et al.  Breast cancer risk factors among screening program participants. , 1979, Journal of the National Cancer Institute.

[12]  Spratt Js,et al.  Assessing the risk of breast cancer. , 2000 .

[13]  D Spiegelman,et al.  Validation of the Gail et al. model for predicting individual breast cancer risk. , 1994, Journal of the National Cancer Institute.

[14]  W. Willett,et al.  Validation of questionnaire information on risk factors and disease outcomes in a prospective cohort study of women. , 1986, American journal of epidemiology.

[15]  R F Nease,et al.  Perceptions of breast cancer risk and screening effectiveness in women younger than 50 years of age. , 1995, Journal of the National Cancer Institute.

[16]  C. Byrne,et al.  Studying mammographic density: implications for understanding breast cancer. , 1997, Journal of the National Cancer Institute.

[17]  G. Friedman,et al.  Screening in chronic disease , 2004, Cancer Causes & Control.

[18]  C K Redmond,et al.  Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1 Study. , 1999, Journal of the National Cancer Institute.

[19]  N Risch,et al.  Autosomal dominant inheritance of early‐onset breast cancer. Implications for risk prediction , 1994, Cancer.

[20]  J. Mandel,et al.  Screening in Chronic Disease , 1985 .

[21]  M. Gail,et al.  Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. , 1989, Journal of the National Cancer Institute.

[22]  Godfrey Fowler,et al.  THE STRATEGY OF PREVENTIVE MEDICINE , 1992 .

[23]  E. Lustbader,et al.  Validation of a breast cancer risk assessment model in women with a positive family history. , 1994, Journal of the National Cancer Institute.

[24]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.