Influence of Sponsorship Bias on Treatment Effect Size Estimates in Randomized Trials of Oral Health Interventions: A Meta-epidemiological Study.
Saltaji H., Armijo-Olivo S., Cummings GG., Amin M., Major PW., da Costa BR., Flores-Mir C.
BACKGROUND: In this meta-epidemiological study, we aimed to examine associations between treatment effect size estimates and sponsorship bias in oral health randomized clinical trials. METHODS: We selected oral health related meta-analyses that included a minimum of five randomized controlled trials. We extracted data, in duplicate, related to influence of sponsorship bias. We quantified the extent of bias associated with influence of sponsorship on the magnitude of effect size estimates of continuous variables using a two-level meta-meta-analytic approach with random-effects models to allow for intra- and inter-meta-analysis heterogeneity. RESULTS: We initially identified 540 randomized trials included in 64 meta-analyses. Risk of sponsorship bias was judged as being "unclear" in 72.8% (n = 393) of the trials, while it was assessed as "low" in 16.7% (n = 90) and as "high" in 10.6% (n = 57) of the trials. Using a meta-epidemiological analysis (37 meta-analyses, including 328 trials that analyzed 85,934 patients), we identified statistically significant larger treatment effect size estimates in trials that had "high or unclear" risk of sponsorship bias (difference in treatment effect size estimates=0.10; 95% confidence intervals: 0.02 to 0.19) than in trials that had "low" risk of sponsorship bias. CONCLUSIONS: We identified significant differences in treatment effect size estimates between dental trials based on sponsorship bias. Treatment effect size estimates were 0.10 larger in trials with "high or unclear" risk of sponsorship bias. PRACTICAL IMPLICATIONS: Clinicians should have an adequate knowledge of sponsorship bias in a clinical trial and be able to estimate the degree to which the conclusions of a systematic review are synthesized and interpreted, based on trials with low risk of sponsorship bias.