Evidence map›Paper›PMID 38923150›Full record

ArticlePharmaceutical statistics

T3 + 3: 3 + 3 Design With Delayed Outcomes.

Jiaying Guo, Mengyi Lu, Isabella Wan, Yumin Wang, Leng Han, Yong Zang

Abstract read
In one paragraph

Article in Pharmaceutical statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jiaying GuoDepartment of Biostatistics and Health Data Science, Indiana University, Indianapolis, Indiana, USA.
Mengyi LuDepartment of Biostatistics, Nanjing Medical University, Nanjing, China.
Isabella WanFaculty of Arts and Science, University of Toronto, Toronto, Canada.
Yumin WangChengdu University, Chengdu, China.
Leng HanDepartment of Biostatistics and Health Data Science, Indiana University, Indianapolis, Indiana, USA.
Yong ZangDepartment of Biostatistics and Health Data Science, Indiana University, Indianapolis, Indiana, USA.

Funding

Tumor Microenvironment and Metastasis ProgramP30CA082709 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI David W Clapp · 1999 to 2026
$59.3M
Use Bayesian methods to facilitate the data integration for complex clinical trialsR01GM150808 · NIGMS · INDIANA UNIVERSITY INDIANAPOLIS · PI Yong Zang · 2023 to 2026
$1.3M
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 CA264257NIGMS NIH HHS R01 GM150808NIH HHS P30 CA082709NIH HHS R01 GM150808NIH HHS R21 CA264257Ralph W. and Grace M. Showalter Research Trust award
6 · The paper itself

Abstract

Delayed outcome is common in phase I oncology clinical trials. It causes logistic difficulty, wastes resources, and prolongs the trial duration. This article investigates this issue and proposes the time-to-event 3 + 3 (T3 + 3) design, which utilizes the actual follow-up time for at-risk patients with pending toxicity outcomes. The T3 + 3 design allows continuous accrual without unnecessary trial suspension and is costless and implementable with pretabulated dose decision rules. Besides, the T3 + 3 design uses the isotonic regression to estimate the toxicity rates across dose levels and therefore can accommodate for any targeted toxicity rate for maximum tolerated dose (MTD). It dramatically facilitates the trial preparation and conduct without intensive computation and statistical consultation. The extension to other algorithm-based phase I dose-finding designs (e.g., i3 + 3 design) is also studied. Comprehensive computer simulation studies are conducted to investigate the performance of the T3 + 3 design under various dose-toxicity scenarios. The results confirm that the T3 + 3 design substantially shortens the trial duration compared with the conventional 3 + 3 design and yields much higher accuracy in MTD identification than the rolling six design. In summary, the T3 + 3 design addresses the delayed outcome issue while keeping the desirable features of the 3 + 3 design, such as simplicity, transparency, and costless implementation. It has great potential to accelerate early-phase drug development.

Indexed as

Clinical Trials, Phase I as TopicComputer SimulationDose-Response Relationship, DrugMaximum Tolerated DoseResearch DesignAlgorithmsAntineoplastic AgentsHumansNeoplasmsTime FactorsTreatment OutcomeAntineoplastic Agents3 + 3 designBayesian adaptive designdelayed outcomeoptimal designphase I clinical trials

Identifiers

PMID38923150
PMCPMC11602947

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.