Clinical trial design and treatment effects: a meta-analysis of randomised controlled and single-arm trials supporting 437 FDA approvals of cancer drugs and indications.

Abstract

Objectives: This study aims to analyse the association between clinical trial design and treatment effects for cancer drugs with US Food and Drug Administration (FDA) approval.

Design: Cross-sectional study and meta-analysis.

Setting: Data from Drugs@FDA, FDA labels, ClincialTrials.gov and the Global Burden of Disease study.

Participants: Pivotal trials for 170 drugs with FDA approval across 437 cancer indications between 2000 and 2022.

Main outcome measures: Treatment effects were measured in HRs for overall survival (OS) and progression-free survival (PFS), and in relative risk for tumour response. Random-effects meta-analyses and meta-regressions explored the association between treatment effect estimates and clinical trial design for randomised 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 tumour 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 tumour response (ß=-2.91, p=0.004) outcomes were greater in trials with fewer centres. HRs for PFS (0.54 vs 0.62, p=0.011) were lower in trials testing the new drug to an inactive (placebo/no treatment) rather than an active comparator. The analysed efficacy population (intention-to-treat, per-protocol, or as-treated) was 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-centre trials testing a new drug compared with an inactive rather than an active comparator could overstate treatment outcomes. Future studies should verify results in unsuccessful trials, adjust for further confounders and examine other therapeutic areas. The FDA, manufacturers and trialists must strive to conduct robust clinical trials with a low risk of bias.