BACKGROUND It is not uncommon for investigators to conduct further analyses of subgroups, using data collected in a nested case-control design. Since the sampling of the participants is related to the outcome of interest, the data at hand are not a representative sample of the population, and subgroup analyses need to be carefully considered for their validity and interpretation. METHODS We performed simulation studies, generating cohorts within the proportional hazards model framework and with covariate coefficients chosen to mimic realistic data and more extreme situations. From the cohorts we sampled nested case-control data and analysed the effect of a binary exposure on a time-to-event outcome in subgroups defined by a covariate (an independent risk factor, a confounder or an effect modifier) and compared the estimates with the corresponding subcohort estimates. Cohort analyses were performed with Cox regression, and nested case-control samples or restricted subsamples were analysed with both conditional logistic regression and weighted Cox regression. RESULTS For all studied scenarios, the subgroup analyses provided unbiased estimates of the exposure coefficients, with conditional logistic regression being less efficient than the weighted Cox regression. CONCLUSIONS For the study of a subpopulation, analysis of the corresponding subgroup of individuals sampled in a nested case-control design provides an unbiased estimate of the effect of exposure, regardless of whether the variable used to define the subgroup is a confounder, effect modifier or independent risk factor. Weighted Cox regression provides more efficient estimates than conditional logistic regression.

中文翻译：

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使用嵌套的病例对照数据进行有效和有效的亚组分析。

背景技术研究人员使用嵌套的病例对照设计中收集的数据进行亚组的进一步分析并不少见。由于参与者的抽样与所关注的结果相关，因此手头的数据并非人群的代表性样本，因此需要仔细考虑亚组分析的有效性和解释性。方法我们进行了模拟研究，在比例风险模型框架内生成了队列，并选择了协变量系数来模拟现实数据和更极端的情况。我们从队列中抽取了嵌套的病例对照数据，并分析了二元暴露对协变量（独立风险因素，混杂因素或效果修饰符），并将估算值与相应的同类群组估算值进行比较。使用Cox回归进行队列分析，并使用条件逻辑回归和加权Cox回归分析嵌套病例对照样本或受限子样本。结果对于所有研究的情景，亚组分析均提供了暴露系数的无偏估计，而条件逻辑回归的效率低于加权Cox回归。结论对于亚群的研究，对嵌套病例对照设计中抽样的相应个体亚群的分析提供了对暴露影响的无偏估计，无论用于定义亚群的变量是混杂因素，效应修饰因子还是独立的危险因素。