Drug approvals in crowded drug classes potentially reflect efficacy overestimates and false positivity: A portfolio analysis of immune checkpoint inhibitor trials
Abstract
Objectives: Institutions making decisions regarding drug development, approval, or insurance reimbursement require accurate estimates of drug efficacy that reflect the drug's true value. Stein estimation and multiplicity correction can be applied to trials for an entire class of drugs, minimizing random error in effect size estimates.
Study design and setting: We downloaded ClinicalTrials.gov registry entries for trials testing immune checkpoint inhibitor (ICI) drugs, including only trials with overall survival (OS) or progression-free survival (PFS) as a primary outcome, in phases 1-3, with 100 patients or more, at least one US site and primary completion date before January 1, 2023. Effect sizes and P values were recalculated for pivotal trials. A change was considered "meaningful" if the adjusted hazard ratio (HR) crossed the null or an European Society for Medical Oncology (ESMO)-Magnitude of Clinical Benefit Score (MCBS) cutoff.
Results: We included 14 ICIs, eight of which were approved by the Food and Drug Administration (FDA). These were tested in 111 trials, 45 of which led to FDA approvals. Among FDA-approved drugs, 82 distinct OS/PFS HRs were reported as primary outcomes supporting an FDA label approval/revision. After recalculation, estimates improved to a meaningful degree for one pivotal trial (1%) but diminished meaningfully for 29 (35%). Among OS/PFS HRs, 74 (90%) had an original P value that was less than 0.05. Among these, 20 (27%) had a corrected P value…
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