Evidence map›Paper›PMID 35098585›Full record

ArticleStatistics in medicine2022

TITE-BOIN12: A Bayesian phase I/II trial design to find the optimal biological dose with late-onset toxicity and efficacy.

Yanhong Zhou, Ruitao Lin, J Jack Lee, Daniel Li, Li Wang, Ruobing Li, Ying Yuan

Abstract read
In one paragraph

Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Practical Considerations for Using the TITE-BOIN Design to Handle Late-Onset Toxicity or Fast Accrual in Phase I Trials.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
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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

7 authors.

Yanhong ZhouDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Ruitao LinDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-2244-131X
J Jack LeeDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Daniel LiJuno Therapeutics, Bristol-Myers Squibb Company, Seattle, Washington, USA.
Li WangData and Statistical Sciences, AbbVie Inc., North Chicago, Illinois, USA.
Ruobing LiThe Center for Drug Evaluation, The National Medical Products Administration, Beijing, China.
Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-3163-480X

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Tropism Enhanced Oncolytic Adenovirus for the Treatment of Brain TumorsP50CA127001 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Juan Fueyo · 2008 to 2026
$41.2M
Project 3: Inhibiting Oxidative Phosphorylation in Pancreatic CancerP50CA221707 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KOPETZ, SCOTT, MAITRA, ANIRBAN · 2019 to 2023
$11.0M
The University of Texas MD Anderson Cancer Center SPORE in MelanomaP50CA221703 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DAVIES, MICHAEL · 2019 to 2023
$10.3M
U.T. M. D. Anderson Cancer Center SPORE in Ovarian CancerP50CA217685 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BAST, ROBERT C, SOOD, ANIL K · 2017 to 2021
$7.9M
Bayesian Methods for Complex Precision Biotherapy Trials in OncologyR01CA261978 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIN, RUITAO, THALL, PETER F · 2021 to 2024
$1.4M
NCI NIH HHS 1R01CA261978NCI NIH HHS P30 CA016672NCI NIH HHS P30CA016672NCI NIH HHS P50 CA127001NCI NIH HHS P50CA127001NCI NIH HHS P50 CA217685NCI NIH HHS P50CA217685NCI NIH HHS P50 CA221703NCI NIH HHS P50CA221703NCI NIH HHS P50 CA221707NCI NIH HHS P50CA221707NCI NIH HHS R01 CA261978
6 · The paper itself

Abstract

In the era of immunotherapies and targeted therapies, the focus of early phase clinical trials has shifted from finding the maximum tolerated dose to identifying the optimal biological dose (OBD), which maximizes the toxicity-efficacy trade-off. One major impediment to using adaptive designs to find OBD is that efficacy or/and toxicity are often late-onset, hampering the designs' real-time decision rules for treating new patients. To address this issue, we propose the model-assisted TITE-BOIN12 design to find OBD with late-onset toxicity and efficacy. As an extension of the BOIN12 design, the TITE-BOIN12 design also uses utility to quantify the toxicity-efficacy trade-off. We consider two approaches, Bayesian data augmentation and an approximated likelihood method, to enable real-time decision making when some patients' toxicity and efficacy outcomes are pending. Extensive simulations show that, compared to some existing designs, TITE-BOIN12 significantly shortens the trial duration while having comparable or higher accuracy to identify OBD and a lower risk of overdosing patients. To facilitate the use of the TITE-BOIN12 design, we develop a user-friendly software freely available at http://www.trialdesign.org.

Indexed as

Clinical Trials, Phase I as TopicClinical Trials, Phase II as TopicResearch DesignBayes TheoremComputer SimulationDose-Response Relationship, DrugHumansImmunotherapyMaximum Tolerated DoseBayesian adaptive designdose findingdose optimizationrisk-benefit trade-off

Identifiers

PMID35098585
PMCPMC9199061

What OpenQuestion holds

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Registered trials

None linked

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.