Trends in the design of FDA registrational randomised clinical trials in haematology and oncology: a 20-year cohort study
Year: 2025
Type: article
Abstract: Introduction: Registrational trials are clinical trials which are used to justify regulatory approval of a new medication by the FDA. However, clinical trials may not be designed around patient-centered outcomes, like overall survival or quality of life. This disconnect raises concerns about whether current trial designs are truly aligned with the long-term needs and priorities of patients. A comprehensive analysis of trial designs and endpoints is necessary to ensure that future oncologic therapies deliver meaningful clinical improvements. Our objective was to describe types of clinical trial design and primary endpoints used for registrational trials, and their trends over time. Research Design and Methods: In this cohort study, the HemOnc database was used to identify registrational trials supporting cancer drug approval from 2004 through 2023.Clinical trial design (escalation, de-escalation, in-class switch, out-of-class switch) and primary endpoint (overall survival; time-to-event including progression free survival; response-based endpoint). Results: Escalation trial designs were more common than in-class switches or out-of-class switches. De-escalation and mixed designs were exceedingly rare. The most common primary endpoint was a composite time-to-event endpoint. Conclusion: Most clinical trials leading to FDA approval for cancer-directed therapies employ escalation designs with composite time-to-event endpoints. Designs reflecting paradigm shifts in therapy (in-class switches and out-of-class switches) are sparsely used. This approach raises the concern that trials may increase therapeutic toxicity without delivering meaningful improvements in overall survival or quality of life.
Source: BMJ Connections Oncology
Authors: Charles J Milrod, Aidan Petrovich, Wayne Haowei Liang, Elizabeth Davis, Carolyn Petersen, Talal Hilal, Peter Yang, Jeremy Lyle Warner, Samuel M Rubinstein
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416959803
