Rockhill B, Spiegelman D, Byrne C, Hunter D J, Colditz G A
B. Rockhill, C. Byrne, Channing Laboratory, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA.
J Natl Cancer Inst. 2001 Mar 7;93(5):358-66. doi: 10.1093/jnci/93.5.358.
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.
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.
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.
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.
越来越多的女性及其临床医生被鼓励使用统计模型得出的风险评估值，主要是盖尔等人的模型，以辅助做出关于乳腺癌潜在预防方案的决策，包括使用他莫昔芬进行化学预防。
我们评估了盖尔等人的模型2在预测侵袭性乳腺癌发生风险方面的拟合优度及其在护士健康研究中个体层面的鉴别准确性。我们从1992年的82109名年龄在45 - 71岁的白人女性队列开始，在5年的随访期内将盖尔等人的模型应用于这些女性，以估计侵袭性乳腺癌的5年风险。所有统计检验均为双侧检验。
该模型在总样本中拟合良好（预期病例数[E]与观察病例数[O]的比值 = 0.94；95%置信区间[CI] = 0.89至0.99）。年轻女性（<60岁）的预测不足略多，但在大多数年龄和风险因素分层中，E/O比值接近1.0。在报告近期筛查（即基线前一年内）的女性子集中，该模型拟合同样良好（E/O比值 = 0.93；95%CI = 0.87至0.99）；在估计5年发生侵袭性乳腺癌风险为1.67%或更高的女性中，E/O比值为(1.04)（95%CI = 0.96至1.12）。用于估计5年风险时，盖尔等人的模型2的一致性统计量（表明鉴别准确性）为(0.58)（95%CI = 0.56至0.60）。在该队列中观察到的1354例乳腺癌病例中，只有3.3%发生在预期从预防性使用他莫昔芬中获得统计学显著净健康益处的年龄 - 风险分层的女性中。
就预测特定风险因素分层中的乳腺癌病例数而言，盖尔等人的模型2在该样本中拟合良好，但在个体层面的鉴别准确性一般。这一发现对该模型在个体女性临床咨询中的应用具有启示意义。
