Biomarkers and Breast Cancer Risk Prediction in Younger Women

描述（由申请人提供）：背景：本提案的目标是通过添加生物标志物（睾酮或游离睾酮和/或苗勒管抑制物质（MIS）），改善Gail乳腺癌风险预测模型2在35-49岁女性中的性能。MIS仅在绝经前女性中可检测到，在迄今为止唯一的前瞻性研究中，MIS与绝经前和绝经后乳腺癌风险的大幅增加相关（最高与最低四分位数的OR = 9.8，95%CI = 3.3至28.9）。绝经前的睾酮和游离睾酮水平也一直被证明与绝经前和绝经后乳腺癌的风险增加呈正相关。所有三种生物标志物在月经周期中变化很小，可以相对便宜地测量，并且具有良好的时间可靠性，即单一测量合理地代表了女性的长期平均水平，使其成为纳入风险预测模型的良好候选者。目的：1）评估绝经前MIS水平与乳腺癌风险的相关性; 2）评估将生物标志物（睾酮或游离睾酮和/或MIS）添加到Gail模型2中包含的因素中是否改善了模型对35-49岁女性的预测性能。研究方法：本研究将使用8个前瞻性队列的资源，这些队列采集健康年轻女性的血清或血浆，并随访其乳腺癌发病率（突破世代研究; CLUE II;哥伦比亚，MO血清库;根西岛队列;护士健康研究II;纽约大学妇女健康研究;北方瑞典乳腺筛查研究; ORDET）。对于目标1，将进行1：2巢式病例：对照研究（2500例病例）。对于目标2，除了Gail模型2中包括的因素（年龄、初潮年龄、首次活产年龄、既往乳腺活检次数和有乳腺癌病史的一级亲属数量）外，还将包括一种或两种生物标志物的风险预测模型的性能与Gail模型2的校准和判别准确性进行比较。影响：改进的风险预测模型将帮助女性在乳腺癌筛查和化学预防方面做出更明智的决定。这对年轻妇女尤其重要，因为她们的筛查指南不一致。此外，他莫昔芬在美国被批准用于预防乳腺癌风险增加的35岁及以上女性的乳腺癌，最有可能使年轻女性受益，因为他们比老年女性更低风险他莫昔芬的不良反应。

DESCRIPTION (provided by applicant): Background: The goal of this proposal is to improve the performance of the Gail breast cancer risk prediction model 2 for women 35-49 years of age, by the addition of biomarkers (testosterone or free testosterone, and/or Mullerian Inhibiting Substance (MIS)). MIS, which is detectable only in premenopausal women, was associated with a large increase in risk of both pre- and post-menopausal breast cancer in the only prospective study to date (OR = 9.8, 95% CI = 3.3 to 28.9 for the highest vs. lowest quartile). Premenopausal levels of testosterone and free testosterone have also been consistently shown to be positively associated with increased risk of both pre- and post-menopausal breast cancer. All three biomarkers vary little during the menstrual cycle, can be measured relatively inexpensively, and have good temporal reliability, i.e. a single measurement is reasonably representative of a woman's long-term average level, making them good candidates for inclusion in a risk prediction model. Aims: 1) To evaluate the association of premenopausal levels of MIS with breast cancer risk; 2) To assess whether adding biomarkers (testosterone or free testosterone, and/or MIS) to the factors included in the Gail model 2 improves the prediction performance of the model for women 35-49 years of age. Methods: The study will use the resources of eight prospective cohorts which collected serum or plasma from healthy young women and followed them up for incidence of breast cancer (Breakthrough Generations Study; CLUE II; Columbia, MO Serum Bank; Guernsey Cohort; Nurses' Health Study II; New York University Women's Health Study; Northern Sweden Mammary Screening Study; ORDET). For aim 1, a 1:2 nested case:control study (2500 cases) will be conducted. For aim 2, the performance of risk prediction models including one or two biomarkers, in addition to factors included in the Gail model 2 (age, age at menarche, age at first live birth, number of previous breast biopsies and number of first degree relatives with a history of breast cancer), will be compared to the Gail model 2 with respect to calibration and discriminatory accuracy. Impact: An improved risk prediction model will help women make more informed decisions regarding breast cancer screening and chemoprevention. This is particularly relevant to younger women for whom guidelines on screening are inconsistent. Further, tamoxifen, which is approved in the US for prevention of breast cancer in women age 35 and older who are at increased risk of breast cancer, is most likely to benefit younger women because they are at lower risk than older women of the adverse effects of tamoxifen.