<p>Comparing and combining reports from different publication is of interest to many when conducting meta-analyses. However, challenges can arise with reports using transformations of the exposure data. A recent publication, Linakis et al. (BMC Med Res Methodol 24:6, 2024), compared methods for re-expression with the conclusion that the re-expression methods examined are not reliable. In their analysis, they treated the estimated effect estimates, which are random variables, as if they were constants, which have no inherent variability. This letter describes two places where this assumption was made and how it affected their conclusions. While the re-expression methods demonstrate potential room for refinement in terms of estimating the observed point estimate, with the statistically appropriate consideration of variability, use of re-expression for small to moderate sample sizes (up to approximately 5000) seems appropriate. That contrasts with the author’s conclusion that use of re-expression methods is not suitable for meta-analyses.</p>

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The importance of considering variability in re-expression of effect estimates for use in meta-analyses

  • Leonid Kopylev,
  • Michael Dzierlenga

摘要

Comparing and combining reports from different publication is of interest to many when conducting meta-analyses. However, challenges can arise with reports using transformations of the exposure data. A recent publication, Linakis et al. (BMC Med Res Methodol 24:6, 2024), compared methods for re-expression with the conclusion that the re-expression methods examined are not reliable. In their analysis, they treated the estimated effect estimates, which are random variables, as if they were constants, which have no inherent variability. This letter describes two places where this assumption was made and how it affected their conclusions. While the re-expression methods demonstrate potential room for refinement in terms of estimating the observed point estimate, with the statistically appropriate consideration of variability, use of re-expression for small to moderate sample sizes (up to approximately 5000) seems appropriate. That contrasts with the author’s conclusion that use of re-expression methods is not suitable for meta-analyses.