Evidence map›Paper›PMID 36870476›Full record

ArticleContemporary clinical trials2023

Modified isotonic regression based phase I/II clinical trial design identifying optimal biological dose.

Yingjie Qiu, Yi Zhao, Hao Liu, Sha Cao, Chi Zhang, Yong Zang

Abstract readClinical Trial Protocol
In one paragraph

Article in Contemporary clinical trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Yingjie QiuDepartment of Biostatistics and Health Data Science, Indiana University, USA.
Yi ZhaoDepartment of Biostatistics and Health Data Science, Indiana University, USA.
Hao LiuDepartment of Biostatistics and Epidemiology, Cancer Institute of New Jersey, Rutgers University, USA.
Sha CaoDepartment of Biostatistics and Health Data Science, Indiana University, USA; Center of Computational Biology and Bioinformatics, Indiana University, USA.
Chi ZhangCenter of Computational Biology and Bioinformatics, Indiana University, USA; Department of Medical and Molecular Genetics, Indiana University, USA.
Yong ZangDepartment of Biostatistics and Health Data Science, Indiana University, USA; Center of Computational Biology and Bioinformatics, Indiana University, USA. Electronic address: zangy@iu.edu.

Funding

Tumor Microenvironment and Metastasis ProgramP30CA082709 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI Sara K Quinney · 1999 to 2026
$59.3M
S-nitrosylation signaling in asthmaP01HL158507 · NHLBI · INDIANA UNIVERSITY INDIANAPOLIS · PI LAHM, TIM · 2021 to 2025
$12.0M
Curve-free phase I/II clinical trial designs for molecularly targeted agents and immunotherapyR21CA264257 · NCI · INDIANA UNIVERSITY INDIANAPOLIS · PI ZANG, YONG · 2021 to 2022
$277k
NCI NIH HHS P30 CA082709NCI NIH HHS R21 CA264257NHLBI NIH HHS P01 HL158507
6 · The paper itself

Abstract

Conventional phase I/II clinical trial designs often use complicated parametric models to characterize the dose-response relationships and conduct the trials. However, the parametric models are hard to justify in practice, and the misspecification of parametric models can lead to substantially undesirable performances in phase I/II trials. Moreover, it is difficult for the physicians conducting phase I/II trials to clinically interpret the parameters of these complicated models, and such significant learning costs impede the translation of novel statistical designs into practical trial implementation. To solve these issues, we propose a transparent and efficient phase I/II clinical trial design, referred to as the modified isotonic regression-based design (mISO), to identify the optimal biological doses for molecularly targeted agents and immunotherapy. The mISO design makes no parametric model assumptions on the dose-response relationship and yields desirable performances under any clinically meaningful dose-response curves. The concise, clinically interpretable dose-response models and dose-finding algorithm make the proposed designs highly translational from the statistical community to the clinical community. We further extend the mISO design and develop the mISO-B design to handle the delayed outcomes. Our comprehensive simulation studies show that the mISO and mISO-B designs are highly efficient in optimal biological dose selection and patients allocation and outperform many existing phase I/II clinical trial designs. We also provide a trial example to illustrate the practical implementation of the proposed designs. The software for simulation and trial implementation are available for free download.

Indexed as

Antineoplastic AgentsBayes TheoremClinical Trials as TopicClinical Trials, Phase I as TopicClinical Trials, Phase II as TopicComputer SimulationDose-Response Relationship, DrugHumansMaximum Tolerated DoseResearch DesignAntineoplastic AgentsDelayed outcomeImmunotherapyIsotonic regressionMolecularly targeted agentsPhase I/II clinical trials

Identifiers

PMID36870476
PMCPMC10065963

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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.