EconPapers    
Economics at your fingertips  
 

A novel Phase II single-arm hybrid design to minimize trial duration and enhance subsequent Phase III trial success rate

Jun Lu, Yuzi Zhang, Ying Cui, Limin Peng and Zhengjia Chen

Journal of Applied Statistics, 2025, vol. 52, issue 3, 578-594

Abstract: Many Phase III trials fail for lack of significant efficacy for the testing agents although their success has been demonstrated in preceding Phase II trials. One of the major reasons for this discordance is the use of different endpoints in Phase II and III trials, respectively. In oncology clinical trials, tumor response (surrogate endpoint) can be determined quickly whereas survival estimation (direct endpoint) requires a long period of follow-up. To better bridge the gap between two endpoints, we propose a novel two-stage single-arm hybrid design for Phase II trials whereby the percent of tumor size change is used as an initial screening to select potentially effective agents within a short time interval followed by a second screening stage where survival is estimated to confirm the efficacy of agents. This design can improve trial efficiency and reduce cost by early stopping the evaluation of an ineffective agent based on the low percent of tumor size change. The second survival endpoint screening will substantially increase the success rate of the follow-up Phase III trial by using the same endpoint. Simulation studies demonstrated that our novel design has improved in terms of trial efficiency, trial length, and the success rate of following Phase III trials.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2024.2382135 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:52:y:2025:i:3:p:578-594

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664763.2024.2382135

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-22
Handle: RePEc:taf:japsta:v:52:y:2025:i:3:p:578-594