A Pointwise Approach to Dose-Response Meta-Analysis of Aggregated Data

Abstract

In a two-stage dose-response meta-analysis a common functional relationship is applied to each study and an overall curve is obtained by combining study-specific dose-response coefficients. Possible limitations are: 1) a common dose-response model may have a poor fit in some of the studies; 2) combining dose-response coefficients discard information about study-specific exposure range. A pointwise approach for meta-analysis may overcome those limitations by combining predicted relative risks for a fine grid of exposure values based on potentially different dose-response models.We described how to flexibly model the dose-response association in a single study using fractional polynomials and spline, and how to present the combined results from study-specific analyses.The strategy is illustrated using aggregated data derived from the Surveillance, Epidemiology, and End Results program, with results compared to the corresponding analysis based on individual data.Another example on milk consumption and all-cause mortality is used to show the advantages of the pointwise approach regarding flexibility in the dose-response analyses, limitations of extrapolations, and informativeness in presenting pooled results.Application of the proposed strategy may improve dose-response meta-analysis of observational studies in case of particularly heterogeneous exposure distributions.