1544MO - Clinical trial design and treatment effects: A meta-analysis of randomized-controlled and single-arm trials supporting 437 FDA approvals of cancer drugs and indications

Background

The design of clinical trials may influence measured treatment effect estimates. However, the Food and Drug Administration (FDA) approval of new cancer drugs ought to be supported by unbiased and robust clinical trials. In this study, we analyze the association between clinical trial design characteristics and treatment effect estimates for FDA-approved cancer drugs.

Methods

Clinical trial evidence supporting the FDA approval of 170 new anti-cancer drugs across 437 indications was collected from Drugs@FDA and clincialtrials.gov between 2000-2022. Treatment effects were measured in hazard ratios (HR) for overall survival (OS) and progression-free survival (PFS), and in relative risk (RR) for tumor response. Random-effects meta-analyses and meta-regressions explored the association between treatment effect estimates and clinical trial design for randomized-controlled trials (RCTs) and single-arm trials.

Results

Across RCTs, greater effect estimates were observed in smaller trials for OS (ß=0.06, p<0.001), PFS (ß=0.15, p<0.001), and tumor response (ß=-3.61, p<0.001). Effect estimates were larger in shorter trials for OS (ß=0.08, p<0.001) and PFS (ß=0.09, p=0.002). OS (ß=0.04, p=0.006), PFS (ß=0.10, p<0.001), and tumor response (ß=-2.91, p=0.004) outcomes were greater in trials with fewer centers. HRs for PFS (0.54 vs. 0.62, p=0.011) were lower in trials testing the new drugs to an inactive (placebo/no treatment) rather than an active comparator. The analyzed efficacy population, e.g. intention-to-treat (ITT), per-protocol (PP), or as-treated (AT), were not consistently associated with treatment effects. Results were consistent for single-arm trials and in multivariable analyses.

Conclusions

Pivotal trial design is significantly associated with measured treatment effects. Particularly small, short, single-center trials testing a new drug compared to an inactive rather than an active comparator could overstate treatment outcomes. The FDA, manufacturers, and trialists must strive to conduct robust clinical trials with a low risk of bias.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.