Schmidt S, Schaid D J
Division of Epidemiology, German Cancer Research Center, Heidelberg.
Am J Epidemiol. 1999 Oct 15;150(8):878-85. doi: 10.1093/oxfordjournals.aje.a010093.
Novel epidemiologic study designs are often required to assess gene-environment interaction. A design using only cases, without controls, is one of several approaches that have been proposed as more efficient alternatives to the typical random sampling of cases and controls. However, it has not been pointed out that a case-only analysis estimates a different interaction parameter than does a traditional case-control analysis: The latter typically estimates departure from multiplicative population odds or rate ratios, depending on the method of control selection, while the former estimates departure from multiplicative risk ratios if genotype and environmental exposure are not associated in the population. These parameters are approximately equal if the disease risk is small at all levels of the study variables. The authors quantify the impact of allowing for higher disease risk among gene carriers, a relevant situation when the gene under study is highly penetrant. Their findings show that the cross-product ratio computed from case-only data may be substantially smaller than the odds ratio computed from case-control data and may therefore underestimate either the population odds or the rate ratio. Thus, to avoid misinterpretation of interaction parameters estimated from case-only data, the definition of multiplicative interaction should be made explicit.
评估基因-环境相互作用通常需要新颖的流行病学研究设计。仅使用病例而无对照的设计是已被提出的几种方法之一，作为对典型的病例与对照随机抽样的更有效替代方法。然而，尚未有人指出，仅病例分析所估计的相互作用参数与传统病例对照分析所估计的不同：后者通常估计相对于相乘性总体优势比或率比的偏离，这取决于对照选择方法，而前者如果基因型与环境暴露在总体中不相关，则估计相对于相乘性风险比的偏离。如果在研究变量的所有水平上疾病风险都较小，这些参数近似相等。作者们量化了基因携带者中较高疾病风险所产生的影响，这是所研究基因具有高度外显率时的一种相关情况。他们的研究结果表明，从仅病例数据计算出的交叉乘积比可能远小于从病例对照数据计算出的优势比，因此可能低估总体优势比或率比。因此，为避免对从仅病例数据估计出的相互作用参数产生误解，应明确相乘性相互作用的定义。
