Appropriateness of conducting and reporting random-effects meta-analysis in oncology

Abstract

A random-effects model is often applied in meta-analysis when considerable heterogeneity among studies is observed due to the differences in patient characteristics, timeframe, treatment regimens, and other study characteristics. Since 2014, the journals Research Synthesis Methods and the Annals of Internal Medicine have published a few noteworthy papers that explained why the most widely used method for pooling heterogeneous studies—the DerSimonian–Laird (DL) estimator—can produce biased estimates with falsely high precision and recommended to use other several alternative methods. Nevertheless, more than half of studies (55.7%) published in top oncology-specific journals during 2015–2022 did not report any detailed method in the random-effects meta-analysis. Of the studies that did report the methodology used, the DL method was still the dominant one reported. Thus, while the authors recommend that Research Synthesis Methods and the Annals of Internal Medicine continue to increase the publication of its articles that report on specific methods for handling heterogeneity and use random-effects estimates that provide more accurate confidence limits than the DL estimator, other journals that publish meta-analyses in oncology (and presumably in other disease areas) are urged to do the same on a much larger scale than currently documented.