Evidence map›Paper›PMID 40169075›Full record

ArticleContemporary clinical trials2025

Dose-finding designs for cell therapy cancer clinical trials evaluating drug-combinations.

Evan M Bagley, Nolan A Wages

Abstract read
In one paragraph

Article in Contemporary clinical trials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Evan M BagleyDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. Electronic address: bagleye@musc.edu.
Nolan A WagesDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.

Funding

Virus Vector Shared ResourceP30CA016059 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI Kim Felder Rhoads · 1985 to 2026
$51.0M
Translational Science Laboratory Shared ResourceP30CA138313 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Jian Ouyang · 2009 to 2026
$42.7M
Dose finding designs for late-onset toxicitiesR01CA247932 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI WAGES, NOLAN · 2021 to 2023
$1.0M
NCI NIH HHS P30 CA016059NCI NIH HHS P30 CA138313NCI NIH HHS R01 CA247932
6 · The paper itself

Abstract

Cell therapies have taken hold as a promising modality of treatment for multiple types of cancer. Despite this, their efficacy as a monotherapy has been limited, driving interest in their possible role as part of a drug combination. This paper introduces a novel dose-finding design for phase I cancer trials assessing drug combinations where one of the drugs is a cell therapy. Our design adapts the partial order continual reassessment method (POCRM) to account for late-onset dose-limiting toxicities (DLT) and feasibility concerns due to complexities related to manufacturing the cell therapy product. We illustrate our design on a proposed trial to assess the combination of a Rituximab-based bispecific antibody activated T cell product and Nivolumab for the treatment of high-grade B-cell lymphoma. We also provide simulation results that demonstrate our design's ability to accurately identify the feasible maximum tolerated dose combination (FMTDC) while managing late-onset DLTs and feasibility concerns. Our methodology aims to improve the phase I drug combination landscape for cell therapy cancer clinical trials.

Indexed as

Cell- and Tissue-Based TherapyClinical Trials, Phase I as TopicLymphoma, B-CellAntibodies, BispecificDose-Response Relationship, DrugHumansMaximum Tolerated DoseNeoplasmsNivolumabResearch DesignRituximabAntibodies, BispecificNivolumabRituximabCancer clinical trialsCell therapyDose-feasibilityDose-findingDrug combinationsLate-onset toxicity

Identifiers

PMID40169075
PMCPMC13213886

What OpenQuestion holds

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Registered trials

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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.