98%
921
2 minutes
20
In a randomized controlled trial with time-to-event endpoint, some commonly used statistical tests to test for various aspects of survival differences, such as survival probability at a fixed time point, survival function up to a specific time point, and restricted mean survival time, may not be directly applicable when external data are leveraged to augment an arm (or both arms) of an RCT. In this paper, we propose a propensity score-integrated approach to extend such tests when external data are leveraged. Simulation studies are conducted to evaluate the operating characteristics of three propensity score-integrated statistical tests, and an illustrative example is given to demonstrate how these proposed procedures can be implemented.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/pst.2377 | DOI Listing |
J Biopharm Stat
August 2025
Department of Biostatistics, NHC Key Laboratory for Health Technology Assessment, Key Laboratory of Public Health Safety of Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
Propensity score-integrated Bayesian dynamic borrowing methods offer an effective approach for covariate adjustment when using external data to augment randomized controlled trials (RCTs). However, identifying the correct propensity score model can be challenging due to unknown treatment selection processes, potentially leading to model misspecification and biased estimates. To improve robustness to model misspecification, we propose an innovative Bayesian inference procedure that incorporates multiply robust weights into the construction of informative power priors.
View Article and Find Full Text PDFStat Med
August 2025
Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands.
The incorporation of real-world data to supplement the analysis of trials and improve decision-making has spurred the development of statistical techniques to account for introduced confounding. Recently, "hybrid" methods have been developed through which measured confounding is first attenuated via propensity scores and unmeasured confounding is addressed through (Bayesian) dynamic borrowing. Most efforts to date have focused on augmenting control arms with historical controls.
View Article and Find Full Text PDFJ Biopharm Stat
April 2025
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
There has been growing interest in incorporating historical data to improve the efficiency of randomized controlled trials (RCTs) or reduce their required sample size. A key challenge is that the patient characteristics of the historical data may differ from those of the current RCT. To address this issue, a well-known approach is to employ propensity score matching or inverse probability weighting to adjust for baseline heterogeneity, enabling the incorporation of historical data into the inference of RCT.
View Article and Find Full Text PDFPharm Stat
May 2025
Division of Biostatistics, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.
The method of power prior has long been used as a tool for leveraging external data to augment a traditional clinical study. More recently, it has been found that integrating propensity scoring into its application has the potential for improved operating characteristics. In this paper, we introduce a new propensity score-integrated power prior strategy which uses propensity score weighting and is distinctive from other such proposals in the literature.
View Article and Find Full Text PDFStat Med
February 2025
Division of Biostatistics, College of Public Health, The Ohio State University, Ohio, USA.
Leveraging external data information to supplement randomized clinical trials has been a popular topic in recent years, especially for medical device and drug discovery. In rare diseases, it is very challenging to recruit patients and run a large-scale randomized trial. To take advantage of real-world data from historical trials on the same disease, we can run a small hybrid trial and borrow historical controls to increase the power.
View Article and Find Full Text PDF