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@ARTICLE{Phung:277473,
      author       = {M. T. Phung and A. W. Lee and K. McLean and H. Anton-Culver
                      and E. V. Bandera and M. E. Carney and J. Chang-Claude$^*$
                      and D. W. Cramer and J. A. Doherty and R.
                      Turzanski-Fortner$^*$ and M. T. Goodman and H. R. Harris and
                      A. Jensen and F. Modugno and K. B. Moysich and P. D. P.
                      Pharoah and B. Qin and K. L. Terry and L. J. Titus and P. M.
                      Webb and A. H. Wu and N. Zeinomar and A. Ziogas and A.
                      Berchuck and K. R. Cho and G. E. Hanley and R. Meza and B.
                      Mukherjee and M. C. Pike and C. L. Pearce and B. Trabert},
      collaboration = {A. O. C. S. Group and O. C. A. Consortium},
      title        = {{A} framework for assessing interactions for risk
                      stratification models: the example of ovarian cancer.},
      journal      = {Journal of the National Cancer Institute},
      volume       = {115},
      number       = {11},
      issn         = {0027-8874},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2023-01394},
      pages        = {1420-1426},
      year         = {2023},
      note         = {2023 Nov 8;115(11):1420-1426},
      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 four-criterion framework for assessing
                      interactions which includes statistical, qualitative,
                      biological, and practical approaches. Using ovarian cancer,
                      we present the application of the framework as this is an
                      important step in developing more accurate risk
                      stratification models. Using data from nine case-control
                      studies in the Ovarian Cancer Association Consortium, we
                      conducted a comprehensive analysis of interactions between
                      15 unequivocal risk/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
                      between 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.},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37436712},
      doi          = {10.1093/jnci/djad137},
      url          = {https://inrepo02.dkfz.de/record/277473},
}