Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
Department of Public Health, California State University, Fullerton, Fullerton, CA, USA.
J Natl Cancer Inst. 2023 Nov 8;115(11):1420-1426. doi: 10.1093/jnci/djad137.
Generally, risk stratification models for cancer use effect estimates from risk/protective factor analyses that have not assessed potential interactions between these exposures. We have developed a 4-criterion framework for assessing interactions that includes statistical, qualitative, biological, and practical approaches. We present the application of this framework in an ovarian cancer setting because this is an important step in developing more accurate risk stratification models. Using data from 9 case-control studies in the Ovarian Cancer Association Consortium, we conducted a comprehensive analysis of interactions among 15 unequivocal risk and protective factors for ovarian cancer (including 14 non-genetic factors and a 36-variant polygenic score) with age and menopausal status. Pairwise interactions between the risk/protective factors were also assessed. We found that menopausal status modifies the association among endometriosis, first-degree family history of ovarian cancer, breastfeeding, and depot-medroxyprogesterone acetate use and disease risk, highlighting the importance of understanding multiplicative interactions when developing risk prediction models.
一般来说，癌症风险分层模型使用风险/保护因素分析的效应估计值，而这些分析并未评估这些暴露之间的潜在相互作用。我们已经开发了一个用于评估相互作用的四标准框架，其中包括统计、定性、生物学和实际方法。我们在卵巢癌环境中介绍了该框架的应用，因为这是开发更准确的风险分层模型的重要步骤。我们使用卵巢癌协会联盟中的 9 项病例对照研究的数据，对 15 个明确的卵巢癌风险和保护因素（包括 14 个非遗传因素和一个 36 变体多基因评分）与年龄和绝经状态之间的相互作用进行了全面分析。还评估了风险/保护因素之间的两两相互作用。我们发现，绝经状态改变了子宫内膜异位症、一级卵巢癌家族史、母乳喂养和 depot-medroxyprogesterone 醋酸酯使用与疾病风险之间的关联，突出了在开发风险预测模型时理解乘法相互作用的重要性。
