For case–control studies, pooling biologic specimens (cases with cases and controls with controls) can make it affordable to study a biomarker that is expensive to assay, while conserving quantities of archived specimens. For a fixed number of participants, pooling designs incur little loss of estimation precision, and they can even improve precision by enabling inclusion of more participants with the same number of assays. A limitation that has discouraged the use of these methods in environmental epidemiology, however, is the lack of a valid way to adjust for creatinine (urinary dilution) when assaying a biomarker in urine or to adjust for serum lipids when assaying a lipophilic biomarker in serum.
We aimed to develop practical strategies to accomplish those adjustments.
Our strategies either differentially dilute specimens before pooling equal aliquots or, alternatively, pool deliberately unequal aliquots from each specimen, where prior determinations of the adjustment factor in each individual specimen inform their differential dilution or unequal aliquot volumes. In addition, we show how to modify these strategies if, instead of just adjusting for creatinine per se, one needs to account for factors that influence creatinine. We carry out simulations under several causal scenarios.
We demonstrate that the proposed strategies perform well in estimating the same adjusted association parameter as would be estimated by using individually-assayed specimens.
By implementing the proposed strategies when forming specimen pools, one can greatly improve the efficiency of case–control studies that involve an expensive-to-assay exposure measured in biospecimens.
aBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (CRW, MS, DMU)
bEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (KMO)
ACKNOWLEDGMENTS: We thank Drs. Kelly Ferguson and Kristen Upson for helpful comments on an earlier draft of the paper. This research was carried out in the Intramural Research Program at the National Institute of Environmental Health Research, under project ES040006-22.
Conflicts of Interest: The authors have no actual or potential competing financial interests.
Corresponding author: C.R. Weinberg, MD A3-03, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, Weinber2@niehs.nih.gov, 984-287-3697, Text words: 3990,