Influence of Reported Study Design Characteristics on Intervention Effect Estimates From Randomized, Controlled Trials

TLDR

Published evidence suggests that aspects of trial design can bias intervention effect estimates, but findings are inconsistent, and this study is limited by incomplete trial reporting that may confound results. The authors pooled 234 unique meta‑analyses from seven meta‑epidemiologic studies (1973 trials), classified outcomes into mortality, objective, and subjective categories, and applied Bayesian hierarchical models to estimate associations between trial characteristics and average bias and heterogeneity. The analysis found that inadequate or unclear random‑sequence generation, allocation concealment, and lack of double‑blinding exaggerated intervention effect estimates (OR ratios 0.89, 0.93, and 0.87 respectively) and increased between‑trial heterogeneity, with these biases primarily driven by subjective outcomes and minimal impact on objective or mortality outcomes.

Abstract

Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.