No inexplicable disagreements between real-world data-based nonrandomized controlled studies and randomized controlled trials were found

Objectives: We assessed disagreements between nonrandomized controlled studies based on real-world data (NRCS-RWDs) and randomized controlled trials (RCTs). Study Design and Setting: We systematically searched for studies that compared treatment effect estimates from NRCS-RWDs and RCTs on the same clinical question. We assessed the potential difference between NRCS-RWDs and RCTs related to internal and external validity. We calculated various meta-epidemiological measures to assess agreement. In case of disagreements, we tried to identify the probable causes of disagreements. Results: We included 12 studies comparing 15 treatment effect estimates of NRCS-RWDs and RCTs. There were many potential causes of disagreement. Ninety-five percent confidence intervals overlapped for 12 of 15 treatment effect estimates. Our analysis on predicted vs. observed overlap showed that there were no more disagreements than expected by chance. We observed only two substantial differences between the 15 treatment effect estimates. In both cases, we identified risk of bias in the NRCS-RWDs as the most probable cause of disagreement. Conclusion: Our findings suggest that there are clinical questions where the difference in risk of bias between a well-conducted NRCS-RWD and an RCT is negligible. In our analysis, threats to external validity appeared to have no or only a weak impact on the disagreements of treatment effect estimates. (C) 2020 Elsevier Inc. All rights reserved.

Automated summary

The study compared treatment effect estimates between nonrandomized controlled studies based on real-world data and randomized controlled trials, finding that in most cases there was overlap, with disagreements mainly attributed to bias risk in NRCS-RWDs.