A Proposal for Post Hoc Subgroup Analysis in Support of Regulatory Submission.

Loading...

Date

2023-03

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

1
views
1
downloads

Citation Stats

Attention Stats

Abstract

Background

In clinical trials, it is not uncommon that the primary analysis fails to achieve the study objective for demonstrating the safety and efficacy of a test treatment under investigation, while a specific sub-population analysis shows a significant positive result. In this case, whether the observed positive sub-population analysis results can be used in support of regulatory submission of the test treatment under investigation is an interesting question to both the investigator(s) and the regulatory medical/statistical reviewers.

Methods

In this article, several statistical evaluations for confirming the integrity and validity of the observed sub-population analysis results were proposed in support of the regulatory submission. Selection bias caused by looking at one subgroup is adjusted before all statistical evaluations, including reproducibility, consistency between sub-population and the entire population, generalizability between the promising sub-population and other sub-populations, and sensitivity index when there are shifts in mean and/or variability between sub-populations. The multiplicity issue is also addressed in measuring generalizability.

Results

A numerical example of a global (multi-regional) clinical trial was presented for illustration purposes. The choice of applying which estimation approach relies on the scale of test statistics. Recommendations for incorporating statistical evaluations in measuring sub-population analysis are provided. Finally, we proposed possible solutions such as real-world data and real-world evidence for regulatory concerns, which may increase the insufficient power.

Conclusion

Sub-population analysis can contribute to regulatory submission if it passes the evaluation. This analysis can also support hypothesis generation and the planning of future clinical trials, though it fails to pass the measurement process.

Department

Description

Provenance

Subjects

Reproducibility of Results, Selection Bias, Clinical Trials as Topic, Statistics as Topic

Citation

Published Version (Please cite this version)

10.1007/s43441-022-00459-0

Publication Info

Liu, Jiajun, and Shein-Chung Chow (2023). A Proposal for Post Hoc Subgroup Analysis in Support of Regulatory Submission. Therapeutic innovation & regulatory science, 57(2). pp. 196–208. 10.1007/s43441-022-00459-0 Retrieved from https://hdl.handle.net/10161/34873.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Liu

Jiajun Liu

Student
Chow

Shein-Chung Chow

Professor of Biostatistics & Bioinformatics

My research interest includes statistical methodology development and application in the area of biopharmaceutical/clinical statistics such as bioavailability and bioequivalence, clinical trials, bridging studies, medical devices, and translational research/medicine. Most recently, I am interested in statistical methodology development for the use of adaptive design methods in clinical trials and methodology development for assessment of biosimilarity of follow-on biologics. In addition, I am also interested in methodology development for statistical evaluation of traditional Chinese medicine (TCM) clinical trials.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.