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Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.

Abstract : BACKGROUND: A design combining both related and unrelated controls, named the case-combined-control design, was recently proposed to increase the power for detecting gene-environment (GxE) interaction. Under a conditional analytic approach, the case-combined-control design appeared to be more efficient and feasible than a classical case-control study for detecting interaction involving rare events. METHODS: We now propose an unconditional analytic strategy to further increase the power for detecting gene-environment (GxE) interactions. This strategy allows the estimation of GxE interaction and exposure (E) main effects under certain assumptions (e.g. no correlation in E between siblings and the same exposure frequency in both control groups). Only the genetic (G) main effect cannot be estimated because it is biased. RESULTS: Using simulations, we show that unconditional logistic regression analysis is often more efficient than conditional analysis for detecting GxE interaction, particularly for a rare gene and strong effects. The unconditional analysis is also at least as efficient as the conditional analysis when the gene is common and the main and joint effects of E and G are small. CONCLUSIONS: Under the required assumptions, the unconditional analysis retains more information than does the conditional analysis for which only discordant case-control pairs are informative leading to more precise estimates of the odds ratios.
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https://www.hal.inserm.fr/inserm-00122280
Contributor : Marie-Gabrielle Dondon <>
Submitted on : Monday, July 2, 2007 - 10:06:40 AM
Last modification on : Tuesday, July 21, 2020 - 3:58:18 AM
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Alisa Goldstein, Marie-Gabrielle Dondon, Nadine Andrieu. Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.. International Journal of Epidemiology, Oxford University Press (OUP), 2006, 35, pp.1067-73. ⟨10.1093/ije/dyl048⟩. ⟨inserm-00122280⟩

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