Poole C
Am J Epidemiol. 1986 Feb;123(2):352-8. doi: 10.1093/oxfordjournals.aje.a114244.
Efficient control of confounding is well recognized as a legitimate motive for restriction, matching, and conditional analysis in case-control studies. Some investigators, however, have advocated use of the same techniques for another purpose: to achieve a balance of "opportunity" or "potential" for past exposure between cases and controls. This paper shows that disparities of exposure opportunity between cases and controls exert no bias on estimates of the incidence rate ratio. The precision of rate ratio estimates is lessened when case-control studies are reduced in size by the exclusion of people with no opportunity for exposure. Matching and conditional analysis with respect to indicators of exposure opportunity also reduce precision without enhancing validity. Such indicators, which are correlates of exposure but not determinants of disease, are not confounders; therefore, they do not need to be controlled in the design or analysis of case-control studies.
在病例对照研究中,有效控制混杂因素被公认为是进行限制、匹配和条件分析的合理动机。然而,一些研究者主张将这些相同的技术用于另一个目的:在病例组和对照组之间实现过去暴露的“机会”或“可能性”的平衡。本文表明,病例组和对照组之间的暴露机会差异不会对发病率比的估计产生偏差。当通过排除没有暴露机会的人来缩小病例对照研究的规模时,发病率比估计的精度会降低。针对暴露机会指标进行匹配和条件分析也会降低精度,而不会提高有效性。这些指标是暴露的相关因素,但不是疾病的决定因素,不是混杂因素;因此,在病例对照研究的设计或分析中不需要对它们进行控制。