Evidence map›Paper›PMID 31454295›Full record

ArticleJournal of biopharmaceutical statistics2020

Response adaptive randomization procedures in seamless phase II/III clinical trials.

Hongjian Zhu, Jin Piao, J Jack Lee, Feifang Hu, Lixin Zhang

Abstract read
In one paragraph

Article in Journal of biopharmaceutical statistics, 2020. 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

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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Hongjian ZhuDepartment of Biostatistics and Data Science, University of Texas Health Science Center, Houston, TX, USA.
Jin PiaoKeck School of Medicine, University of Southern California, California, LA, USA.
J Jack LeeDepartment of Biostatistics, University of Texas MD Anderson Cancer Center.
Feifang HuDepartment of Statistics, George Washington University, Washington D.C., USA.
Lixin ZhangSchool of Mathematical Sciences, Zhejiang University, Hangzhou, China.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

It is desirable to work efficiently and cost effectively to evaluate new therapies in a time-sensitive and ethical manner without compromising the integrity and validity of the development process. The seamless phase II/III clinical trial has been proposed to meet this need, and its efficient, ethical and economic advantages can be strengthened by its combination with innovative response adaptive randomization (RAR) procedures. In particular, well-designed frequentist RAR procedures can target theoretically optimal allocation proportions, and there are explicit asymptotic results. However, there has been little research into seamless phase II/III clinical trials with frequentist RAR because of the difficulty in performing valid statistical inference and controlling the type I error rate. In this paper, we propose the framework for a family of frequentist RAR designs for seamless phase II/III trials, derive the asymptotic distribution of the parameter estimators using martingale processes and offer solutions to control the type I error rate. The numerical studies demonstrate our theoretical findings and the advantages of the proposed methods.

Indexed as

Adaptive Clinical Trials as TopicClinical Trials, Phase II as TopicClinical Trials, Phase III as TopicData Interpretation, StatisticalHumansModels, StatisticalRandomized Controlled Trials as TopicResearch DesignResponse adaptive randomizationseamless clinical trialstype I error

Identifiers

PMID31454295
PMCPMC6957739

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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.