Evidence map›Paper›PMID 41212869›Full record

ArticlePloS one2025

crm12comb: Phase I/II adaptive design for drug combinations based on CRM design through R.

Junying Wang, Song Wu, Jie Yang

Abstract read
In one paragraph

Article in PloS one, 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

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Junying WangDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, United States of America.
Song WuDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, United States of America.
Jie YangDepartment of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, United States of America.ORCID https://orcid.org/0000-0003-3469-5931

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adaptive designs for integrated phase I/II trials of drug combinations are increasingly utilized to speed up the drug development process and enhance drug efficacy, particularly in the realm of cancer therapy. The model-based Continual Reassessment Method (CRM) for dose-finding is widely used to leverage accumulated data in guiding patient allocation, drawing on principles from the Bayesian framework. In this paper, we present crm12Comb, an R package we developed to streamline the Phase I/II adaptive design process for drug combinations using the CRM approach. This package supports patients' assignment guidance in a single trial based on existing data, as well as simulation studies for conducting extensive simulations with multiple trial parameters to evaluate operating characteristics and create visual representations. It accounts for toxicity and efficacy as binary outcomes, applying partial orderings to the dose-toxicity and dose-efficacy relationships for drug combinations. crm12Comb allows for a wide range of user-specified parameters, including maximum number of patients, cohort size, drug combinations, and a variety of link functions with prior distributions, offering flexibility to accommodate diverse clinical scenarios.

Indexed as

Clinical Trials, Phase I as TopicClinical Trials, Phase II as TopicSoftwareBayes TheoremComputer SimulationDose-Response Relationship, DrugDrug CombinationsHumansNeoplasmsResearch DesignDrug Combinations

Identifiers

PMID41212869
PMCPMC12599976

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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.