A framework for assessing interactions for risk stratification models: the example of ovarian cancer.

ABSTRACT: 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. Pair

SUBMITTER: Phung MT 

PROVIDER: S-EPMC10637032 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature