Evidence map›Paper›PMID 35191780›Full record

Trial reportStatistical methods in medical research2022

A Bayesian phase I/II biomarker-based design for identifying subgroup-specific optimal dose for immunotherapy.

Beibei Guo, Yong Zang

Abstract readClinical Trial, Phase IClinical Trial, Phase II
In one paragraph

Trial report in Statistical methods in medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Commentary: EDFrontiers in medicine · 2025
    Article
  5. Review
  6. Review
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.

Beibei GuoDepartment of Experimental Statistics, 5779Louisiana State University, Baton Rouge, USA.ORCID 0000-0001-9921-5535
Yong ZangDepartment of Biostatistics and Health Data Science, Indiana University, Indianapolis, USA.ORCID 0000-0001-5036-5815

Funding

Tumor Microenvironment and Metastasis ProgramP30CA082709 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI Jun Wan · 1999 to 2026
$59.3M
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 CA264257
6 · The paper itself

Abstract

Immunotherapy is an innovative treatment that enlists the patient's immune system to battle tumors. The optimal dose for treating patients with an immunotherapeutic agent may differ according to their biomarker status. In this article, we propose a biomarker-based phase I/II dose-finding design for identifying subgroup-specific optimal dose for immunotherapy (BSOI) that jointly models the immune response, toxicity, and efficacy outcomes. We propose parsimonious yet flexible models to borrow information across different types of outcomes and subgroups. We quantify the desirability of the dose using a utility function and adopt a two-stage dose-finding algorithm to find the optimal dose for each subgroup. Simulation studies show that the BSOI design has desirable operating characteristics in selecting the subgroup-specific optimal doses and allocating patients to those optimal doses, and outperforms conventional designs.

Indexed as

ImmunotherapyResearch DesignBayes TheoremBiomarkersComputer SimulationDose-Response Relationship, DrugHumansBiomarkersBayesian adaptive designbiomarkerdose findingimmune responseImmunotherapyphase I/II trialrisk–benefit tradeoffsubgroups

Identifiers

PMID35191780
PMCPMC9305985

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.