B Rockhill1, D Spiegelman, C Byrne, D J Hunter, G A Colditz. 1. B. Rockhill, C. Byrne, Channing Laboratory, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA. beverly.rockhill@channing.harvard.edu
Abstract
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.
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.
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