Evidence map›Paper›PMID 41428975›Full record

ArticleJCO precision oncology2025

Master Protocol Design With Hybrid Control for Efficient Early-Phase Trial Consolidation.

Alexander M Kaizer, Xiaojiang Zhan, Eric Baron, Rui Sammi Tang, David S Hong, Brian P Hobbs

Abstract read
In one paragraph

Article in JCO precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexander M KaizerDepartment of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO.ORCID 0000-0003-2334-5514
Xiaojiang ZhanGlobal Biometrics, Servier, Boston, MA.
Eric BaronGlobal Biometrics, Servier, Boston, MA.ORCID 0000-0003-1934-1932
Rui Sammi TangAstellas Pharma Inc, Northbrook, IL.
David S HongDivision of Cancer Medicine, Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-8721-1609
Brian P HobbsTelperian Inc, Austin, TX.ORCID 0009-0004-3855-7434

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMaster protocols represent transformations, enabling multiple therapies or diseases under a single protocol. These designs streamline therapeutic development by reducing redundancies. Suited for evolving fields such as oncology and global emergencies such as the COVID-19 pandemic, master protocols have been exemplified by studies such as RECOVERY, Solidarity, and I-SPY 2, which accelerated effective treatment identification (with I-SPY 2 focused on molecular subtypes). Recent oncology examples, such as MORPHEUS, evaluate immunotherapy combinations with shared controls. Despite advantages, their application in early-phase oncology remains underutilized amid growing regulatory emphasis on randomization for robust evidence.

methodsUS Food and Drug Administration (FDA) Oncology Center of Excellence (OCE) initiatives, such as Project Optimus and Project FrontRunner, emphasize randomization in early-phase oncology trials. However, these initiatives pose challenges, including larger sample sizes, patient and physician reluctance to randomization, and high failure rates from poor accrual. To address these, this article adapts master protocol designs to consolidate early-phase trials for novel therapeutics sharing a common backbone therapy, integrating hybrid controls from published standard-of-care data to minimize randomization to the control arm.

resultsBy consolidating trials under a shared standard-of-care control arm, the proposed master protocol design reduces total sample size by as much as 55% when compared with independent trials (with control arm sizes 2.4-2.9 times lower), lowers costs and duration, and enhances enrollment through reduced randomization to controls. Incorporating hybrid controls from prior studies and sharing information among arms with common background standard-of-care further improve efficiency, increasing power (reaching 90% overall) while controlling type I error rates acceptable levels.

conclusionMaster protocol designs with hybrid controls and Bayesian information sharing enable the efficient integration of randomization into early-phase oncology trials, enhancing efficiency, cost-effectiveness, and patient-centricity while aligning with FDA OCE initiatives.

Indexed as

COVID-19NeoplasmsRandomized Controlled Trials as TopicResearch DesignHumansSARS-CoV-2United States

Identifiers

PMID41428975
PMCPMC12727066

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.