TY - JOUR
T1 - A framework for assessing interactions for risk stratification models
T2 - the example of ovarian cancer
AU - Australian Ovarian Cancer Study Group
AU - Ovarian Cancer Association Consortium
AU - Phung, Minh Tung
AU - Lee, Alice W.
AU - McLean, Karen
AU - Anton-Culver, Hoda
AU - Bandera, Elisa V.
AU - Carney, Michael E.
AU - Chang-Claude, Jenny
AU - Cramer, Daniel W.
AU - Doherty, Jennifer Anne
AU - Fortner, Renee T.
AU - Goodman, Marc T.
AU - Harris, Holly R.
AU - Jensen, Allan
AU - Modugno, Francesmary
AU - Moysich, Kirsten B.
AU - Pharoah, Paul D.P.
AU - Qin, Bo
AU - Terry, Kathryn L.
AU - Titus, Linda J.
AU - Webb, Penelope M.
AU - Wu, Anna H.
AU - Zeinomar, Nur
AU - Ziogas, Argyrios
AU - Berchuck, Andrew
AU - Cho, Kathleen R.
AU - Hanley, Gillian E.
AU - Meza, Rafael
AU - Mukherjee, Bhramar
AU - Pike, Malcolm C.
AU - Pearce, Celeste Leigh
AU - Trabert, Britton
N1 - Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press. All rights reserved.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85176507896
U2 - 10.1093/jnci/djad137
DO - 10.1093/jnci/djad137
M3 - Article
C2 - 37436712
SN - 0027-8874
VL - 115
SP - 1420
EP - 1426
JO - Journal of the National Cancer Institute
JF - Journal of the National Cancer Institute
IS - 11
ER -