» Articles » PMID: 36313987

Design and Analysis of Umbrella Trials: Where Do We Stand?

Overview
Specialty General Medicine
Date 2022 Oct 31
PMID 36313987
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.

Methods: We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.

Findings: We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.

Conclusions: Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.

Citing Articles

Tumor-Agnostic Therapies in Practice: Challenges, Innovations, and Future Perspectives.

Wu S, Thawani R Cancers (Basel). 2025; 17(5).

PMID: 40075649 PMC: 11899253. DOI: 10.3390/cancers17050801.


The Role of Molecular Profiling in De-Escalation of Toxic Therapy in Breast Cancer.

Khan S, Bah T, Layeequr Rahman R Int J Mol Sci. 2025; 26(3).

PMID: 39941099 PMC: 11818289. DOI: 10.3390/ijms26031332.


The effect of estimating prevalences on the population-wise error rate.

Luschei R, Brannath W Stat Methods Med Res. 2025; 34(2):390-404.

PMID: 39828909 PMC: 11874581. DOI: 10.1177/09622802241307237.


Importance of clinical trials and contributions to contemporary medicine: commentary.

Zhang H, Jiang X Ann Med. 2025; 57(1):2451190.

PMID: 39781895 PMC: 11721763. DOI: 10.1080/07853890.2025.2451190.

References
1.
Middleton G, Fletcher P, Popat S, Savage J, Summers Y, Greystoke A . The National Lung Matrix Trial of personalized therapy in lung cancer. Nature. 2020; 583(7818):807-812. PMC: 7116732. DOI: 10.1038/s41586-020-2481-8. View

2.
Gerber D, Oxnard G, Govindan R . ALCHEMIST: Bringing genomic discovery and targeted therapies to early-stage lung cancer. Clin Pharmacol Ther. 2015; 97(5):447-50. PMC: 4839167. DOI: 10.1002/cpt.91. View

3.
Bateman R, Benzinger T, Berry S, Clifford D, Duggan C, Fagan A . The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model. Alzheimers Dement. 2016; 13(1):8-19. PMC: 5218895. DOI: 10.1016/j.jalz.2016.07.005. View

4.
Saville B, Berry S . Efficiencies of platform clinical trials: A vision of the future. Clin Trials. 2016; 13(3):358-66. DOI: 10.1177/1740774515626362. View

5.
Grinsztejn B, Hughes M, Ritz J, Salata R, Mugyenyi P, Hogg E . Third-line antiretroviral therapy in low-income and middle-income countries (ACTG A5288): a prospective strategy study. Lancet HIV. 2019; 6(9):e588-e600. PMC: 6857629. DOI: 10.1016/S2352-3018(19)30146-8. View