A hierarchical meta-analysis for settings involving multiple outcomes across multiple cohorts

• Type of Material: Article
• Authors: Tugba Akkaya Hocagil, University of Waterloo; Louise M. Ryan, University of Technology Sydney; Richard J. Cook, University of Waterloo; Sandra W. Jacobson, Wayne State University; Gale A. Richardson, University of Pittsburgh; Nancy L. Day, University of Pittsburgh; Claire Coles, Emory University; Heather Carmichael Olson, University of Washington, Seattle; Joseph L. Jacobson, Wayne State University
• Language: English
• Date: 2022-01-31
• Publisher: John Wiley and Sons
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2022 John Wiley & Sons, Ltd.
• Final Published Version (URL): https://doi.org/10.1002/sta4.462
• Title of Journal or Parent Work: Stat
• Volume: 11
• Issue: 1
• Start Page: e462
• Grant/Funding Information: This research was funded by grants to Sandra W. Jacobson and Joseph L. Jacobson from the National Institutes of Health/National Institute on Alcohol Abuse and Alcoholism (NIH/NIAAA; R01-AA025905) and the Lycaki-Young Fund from the State of Michigan. Louise Ryan received support from the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (Grant No. CE140100049). Richard J. Cook was supported by Natural Sciences and Engineering Research Council of Canada RGPIN 155849 and RGPIN 04207. Data collection for the Detroit cohort was supported by NIAAA/NIH grants R01-AA06966, R01-AA09524, and P50-AA07606 and National Institute on Drug Abuse (NIDA)/NIH grant R21-DA021034; for the Pittsburgh cohorts, by NIAAA/NIH grants R01-AA06390, R01-AA06666, R01-AA14215, and R01-AA18116, National Institute on Child Health and Human Development/NIH grant HD036890, and NIDA/NIH grants R01-DA00090, R01-DA03209, R01-DA03874, and R01-DA17786, R01-DA05460, R01-DA06839, R01-DA08916, and R01-DA12401; for the Atlanta cohorts, by NIAAA/NIH grants R01-AA08105, R01-AA10108, and R01-AA13272, NIDA/NIH grants R01-DA0737362 and R01-DA0737362, and Georgia State Contract DHR 427-93-05050762; and for the Seattle cohort, by NIAAA/NIH grant R01-AA01455.
• Keywords: multiple outcomes; fetal alcohol syndrome; two-stage estimation; Cognition; prenatal alcohol exposure; synthesis of evidence; hierarchical model
• Research Categories: Health Sciences, Public Health; Health Sciences, Epidemiology

Abstract

Evidence from animal models and epidemiological studies has linked prenatal alcohol exposure (PAE) to a broad range of long-term cognitive and behavioural deficits. However, there is a paucity of evidence regarding the nature and levels of PAE associated with increased risk of clinically significant cognitive deficits. To derive robust and efficient estimates of the effects of PAE on cognitive function, we have developed a hierarchical meta-analysis approach to synthesize information regarding the effects of PAE on cognition, integrating data on multiple outcomes from six U.S. Iongitudinal cohort studies. A key assumption of standard methods of meta-analysis, effect sizes are independent, is violated when multiple intercorrelated outcomes are synthesized across studies. Our approach involves estimating the dose–response coefficients for each outcome and then pooling these correlated dose–response coefficients to obtain an estimated “global” effect of exposure on cognition. In the first stage, we use individual participant data to derive estimates of the effects of PAE by fitting regression models that adjust for potential confounding variables using propensity scores. The correlation matrix characterizing the dependence between the outcome-specific dose–response coefficients estimated within each cohort is then run, while accommodating incomplete information on some outcome. We also compare inferences based on the proposed approach to inferences based on a full multivariate analysis.