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| Home > Publications database > Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. > print |
| 001 | 132495 | ||
| 005 | 20240229105019.0 | ||
| 024 | 7 | _ | |a 10.1093/aje/kwx243 |2 doi |
| 024 | 7 | _ | |a pmid:28633381 |2 pmid |
| 024 | 7 | _ | |a 0002-9262 |2 ISSN |
| 024 | 7 | _ | |a 1476-6256 |2 ISSN |
| 024 | 7 | _ | |a altmetric:22219436 |2 altmetric |
| 037 | _ | _ | |a DKFZ-2018-00182 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Liu, Gang |b 0 |
| 245 | _ | _ | |a Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. |
| 260 | _ | _ | |a Oxford |c 2018 |b Oxford Univ. Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1521206779_1744 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. |
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| 700 | 1 | _ | |a Mukherjee, Bhramar |b 1 |
| 700 | 1 | _ | |a Lee, Seunggeun |b 2 |
| 700 | 1 | _ | |a Lee, Alice W |b 3 |
| 700 | 1 | _ | |a Wu, Anna H |b 4 |
| 700 | 1 | _ | |a Bandera, Elisa V |b 5 |
| 700 | 1 | _ | |a Jensen, Allan |b 6 |
| 700 | 1 | _ | |a Rossing, Mary Anne |b 7 |
| 700 | 1 | _ | |a Moysich, Kirsten B |b 8 |
| 700 | 1 | _ | |a Chang-Claude, Jenny |0 P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253 |b 9 |u dkfz |
| 700 | 1 | _ | |a Doherty, Jennifer A |b 10 |
| 700 | 1 | _ | |a Gentry-Maharaj, Aleksandra |b 11 |
| 700 | 1 | _ | |a Kiemeney, Lambertus |b 12 |
| 700 | 1 | _ | |a Gayther, Simon A |b 13 |
| 700 | 1 | _ | |a Modugno, Francesmary |b 14 |
| 700 | 1 | _ | |a Massuger, Leon |b 15 |
| 700 | 1 | _ | |a Goode, Ellen L |b 16 |
| 700 | 1 | _ | |a Fridley, Brooke L |b 17 |
| 700 | 1 | _ | |a Terry, Kathryn L |b 18 |
| 700 | 1 | _ | |a Cramer, Daniel W |b 19 |
| 700 | 1 | _ | |a Ramus, Susan J |b 20 |
| 700 | 1 | _ | |a Anton-Culver, Hoda |b 21 |
| 700 | 1 | _ | |a Ziogas, Argyrios |b 22 |
| 700 | 1 | _ | |a Tyrer, Jonathan P |b 23 |
| 700 | 1 | _ | |a Schildkraut, Joellen M |b 24 |
| 700 | 1 | _ | |a Kjaer, Susanne K |b 25 |
| 700 | 1 | _ | |a Webb, Penelope M |b 26 |
| 700 | 1 | _ | |a Ness, Roberta B |b 27 |
| 700 | 1 | _ | |a Menon, Usha |b 28 |
| 700 | 1 | _ | |a Berchuck, Andrew |b 29 |
| 700 | 1 | _ | |a Pharoah, Paul D |b 30 |
| 700 | 1 | _ | |a Risch, Harvey |b 31 |
| 700 | 1 | _ | |a Pearce, Celeste Leigh |b 32 |
| 700 | 1 | _ | |a Consortium, Ovarian Cancer Association |b 33 |e Collaboration Author |
| 773 | _ | _ | |a 10.1093/aje/kwx243 |g Vol. 187, no. 2, p. 366 - 377 |0 PERI:(DE-600)2030043-8 |n 2 |p 366 - 377 |t American journal of epidemiology |v 187 |y 2018 |x 1476-6256 |
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