Pooling Biospecimens for Efficient Exposure Assessment When Using Case-Cohort Analysis in Cohort Studies

• Published in: Environmental health perspectives 2024-12, Vol.132 (12), p.127004
• Main Authors: Shi, Min, Umbach, David M, Weinberg, Clarice R
• Format: Article
• Language: English
• Subjects: Cohort Studies; Environmental Exposure - statistics & numerical data; Humans; Specimen Handling - methods
• ISSN: 0091-6765; 1552-9924; 1552-9924
• DOI: 10.1289/EHP14476

Large prospective cohort studies have been fruitful for identifying exposure-disease associations. In a cohort where biospecimens (e.g., blood, urine) were collected at enrollment, analysts can exploit a case-cohort approach: Biospecimens from a random sample of cohort participants, called the "subcohort," plus a sample of incident cases that were not part of the subcohort are assayed. Reusing subcohort data for multiple disease outcomes can reduce costs and conserve specimen archives. Pooling biospecimen samples before assay could both save money and reduce depletion of the archive but has not been studied for cohort studies. We develop and evaluate a biospecimen pooling strategy for case-cohort analyses that relate an exposure to risk of a rare disease. Our approach involves constructing pooling sets for cases not in the subcohort after grouping them according to time of diagnosis (e.g., age). In contrast, members of the subcohort are grouped by age at entry before constructing pooling sets. The analyst then fits a logistic regression model that jointly stratifies by age at risk and pooling set size and adjusts for confounders. We used simulations (288 sampling scenarios with 1,000 simulated datasets each) to evaluate the performance of this approach for several sizes of pooling sets and illustrated its application to environmental epidemiologic studies by reanalyzing Sister Study data. Parameter estimates were nearly unbiased, and 95% confidence intervals constructed using a bootstrap estimate of the standard error performed well. In statistical tests also based on the bootstrap standard error, pooling up to 8 specimens per pool caused only modest loss of power. Assigning more cohort members to the subcohort and commensurately increasing the number of specimens per pool improved power and precision substantially while reducing the number of assays. When using case-cohort analysis to study disease outcomes in relation to exposures assessed using biospecimens in a cohort study, epidemiologists should consider biospecimen pooling as a way to improve statistical power, conserve irreplaceable archives, and save money. https://doi.org/10.1289/EHP14476.