Using pooled exposure assessment to improve efficiency in case-control studies
Using pooled exposure assessment to improve efficiency in case-control studies
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DOI：
10.1111/j.0006-341x.1999.00718.x
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发表时间：
1999-09-01
期刊：
影响因子：
1.9
通讯作者：
Umbach, DM
中科院分区：
文献类型：
--
作者：
Weinberg, CR;Umbach, DM
化验可能非常昂贵，以至于有趣的假设在流行病学研究中变得不切实际。然而，人们不需要为每个提供生物标本的人进行化验。我们建议从随机分组的病例集合和随机分组的对照集合中合并等体积等分，然后分析较少数量的合并样本。如果关注某个效果修饰符，则可以在该变量定义的层内进行合并。对于对个体(例如，问卷数据)进行评估的协变量，通过将每个集合中的个体的值相加来计算基于集合的对应物。然后，池集合成为统计分析的单位。我们表明，如果乘法公式是正确的，标准软件在适当指定基于集合的逻辑模型的情况下，可以产生有效的暴露比估计值。汇集可最大限度地减少不可替代的生物标本的消耗，并能以经济的方式研究更多的暴露。与通常的基于个人的分析相比，统计权力几乎没有受到什么影响。在高昂的化验成本限制了研究人员能够承担的研究人数的情况下，样本池可以使研究更多的人成为可能，从而在不增加成本的情况下提高研究的统计能力。
Assays can be so expensive that interesting hypotheses become impractical to study epidemiologically. One need not, however, perform an assay for everyone providing a biological specimen. We propose pooling equal-volume aliquots from randomly grouped sets of cases and randomly grouped sets of controls, and then assaying the smaller number of pooled samples. If an effect modifier is of concern, the pooling can be done within strata defined by that variable. For covariates assessed on individuals (e.g., questionnaire data), set-based counterparts are calculated by adding the values for the individuals in each set. The pooling set then becomes the unit of statistical analysis. We show that, with appropriate specification of a set-based logistic model, standard software yields a valid estimated exposure odds ratio, provided the multiplicative formulation is correct. Pooling minimizes the depletion of irreplaceable biological specimens and can enable additional exposures to be studied economically. Statistical power suffers wry little compared with the usual, individual-based analysis. In settings where high assay costs constrain the number of people an investigator can afford to study, specimen pooling can make it possible to study more people and hence improve the study's statistical power with no increase in cost.