Journal Article

Prevalence of and factors associated with potentially redundant randomized controlled trials: a cross-sectional study

Jia, Yuanxi, Zhang, Jiayue, Sha, Feng, Yang, Zuyao, Tang, Jinling, Yun, Qingping, Wang, Yuxin, Lin, Minqing

2024

Overview

To investigate the prevalence of meta-analyses containing potentially redundant randomized controlled trials (RCTs) and the factors associated with the presence of redundancy. This is a cross-sectional study, based on a random sample of references (n = 4500) that were published during 2020 and 2021, indexed in PubMed, Embase, or the Cochrane Database of Systematic Reviews, and retrieved through comprehensive searches using terms about systematic reviews and meta-analysis. From each systematic review, one meta-analysis fulfilling all the following criteria, if available, was included in this study: (1) assessing the effect of the intervention on a primary outcome of the systematic review; (2) combining RCTs only. The primary outcome was prevalence of meta-analyses containing potentially redundant RCTs. Potentially redundant RCTs referred to the trials that started 1 year after the overall effect estimate from cumulative meta-analysis had been statistically robust, as determined by trial sequential analysis when appropriate. The number of potentially redundant trials (if any) in each eligible meta-analysis and the number of participants involved in those trials were documented and contrasted across groups. Logistic regression analysis was conducted to explore the factors associated with presence of potential redundancy. Of the 448 eligible meta-analyses, 57 (12.7%, 95% confidence interval (CI) 9.8–16.2%) contained potentially redundant RCTs. When limited to the 333 low-heterogeneity meta-analyses, the prevalence was 17.1% (95% CI 13.5–21.5%). The total number of potentially redundant RCTs was 295 (involving 85,385 participants), accounting for 38.5% of the RCTs (and 30.3% of the participants) included in the 57 meta-analyses. In these meta-analyses, the median number of potentially redundant RCTs and the participants involved were 2 (range: 1–50) and 352 (range: 17–26997), respectively. Potentially redundant RCTs were more likely to be present in the meta-analyses evaluating pharmaceutical intervention (odds ratio [OR] 2.31, 95% CI 1.16–4.49), assessing efficacy outcomes (OR 7.25, 95% CI 0.85–61.87), containing more than 5 RCTs (OR 6.47, 95% CI 3.22–12.99), or with the earliest RCT reporting statistically significant effect estimate (OR 5.30, 95% CI 2.64–10.64). This study found that 12.7% to 17.1% of recently published meta-analyses contained potentially redundant RCTs, highlighting the importance of conducting or examining systematic reviews of existing evidence to justify new RCTs. More importantly, the study identified some scenarios in which redundancy was more likely to occur and thus has implications for trialists, funding agencies, ethics committees, and journal editors. •Of the selected meta-analyses, 12.7%–17.1% contained potentially redundant randomized controlled trials (RCTs).•The 295 potentially redundant RCTs (with 85,385 participants) accounted for 38.5% of the RCTs (and 30.3% of the participants) included in the 57 meta-analyses.•The potentially redundant RCTs were more prevalent in the meta-analyses evaluating pharmaceutical interventions, assessing efficacy outcomes, including more than 5 RCTs, or with the earliest RCT reporting statistically significant effect estimate.

• Publisher: Elsevier Inc,Elsevier Limited
• Subject: Clinical trials / Confidence intervals / Cross-Sectional Studies / Cross-sectional study / Heterogeneity / Humans / Internal Medicine / Intervention / Meta-analysis / Meta-Analysis as Topic / Meta-epidemiology / Prevalence / Randomized Controlled Trials as Topic - methods / Randomized Controlled Trials as Topic - standards / Randomized Controlled Trials as Topic - statistics & numerical data / Redundancy / Regression analysis / Research waste / Sequential analysis / Software / Statistical analysis / Systematic review / Systematic Reviews as Topic - methods / Trial sequential analysis