Evidence map›Paper›PMID 34101217›Full record

ArticleStatistics in medicine2021

A Bayesian hierarchical monitoring design for phase II cancer clinical trials: Incorporating information on response duration into monitoring rules.

Jian Wang, Junsheng Ma, Chunyan Cai, Naval Daver, Jing Ning

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 43% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 1 country.

Jian WangDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-7104-0673
Junsheng MaDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Chunyan CaiMarketplace Data Science, Uber, San Francisco, California.
Naval DaverDepartment of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jing NingDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-5289-331X
The University of Texas MD Anderson Cancer Center · USUber AI (United States) · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Convalescent Plasma to Limit Coronavirus Associated ComplicationsUL1TR003167 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KARP, DANIEL D, MCPHERSON, DAVID D · 2019 to 2023
$45.3M
Consortium on Translational Research in Early Detection of Liver Cancer:Data Management and Coordinating Center (DMCC)U24CA230144 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Ziding Feng · 2018 to 2026
$5.8M
Comparative Effectiveness of Cancer Research: Use Data from Multiple SourcesR01CA193878 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI NING, JING · 2016 to 2019
$1.2M
NCATS NIH HHS UL1 TR003167NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA193878NCI NIH HHS U24 CA230144
6 · The paper itself

Abstract

We propose a Bayesian hierarchical monitoring design for single-arm phase II clinical trials of cancer treatments that incorporates the information on the duration of response (DOR) into the monitoring rules. To screen a new treatment by evaluating its preliminary therapeutic effect, futility monitoring rules are commonly used in phase II clinical trials to make "go/no-go" decisions timely and efficiently. These futility monitoring rules are usually focused on a single outcome (eg, response rate), although a single outcome may not adequately determine the efficacy of the experimental treatment. For example, targeted agents with a long response duration but a similar response rate may be worth further evaluation in cancer research. To address this issue, we propose Bayesian hierarchical futility monitoring rules to consider both the response rate and duration. The first level of monitoring evaluates whether the response rate provides evidence that the experimental treatment is worthy of further evaluation. If the evidence from the response rate does not support continuing the trial, the second level monitoring rule, which is based on the DOR, will be triggered. If both stopping rules are satisfied, the trial will be stopped for futility. We conducted simulation studies to evaluate the operating characteristics of the proposed monitoring rules and compared them to those of standard method. We illustrated the proposed design with a single-arm phase II cancer clinical trial to assess the safety and efficacy of combined treatment of nivolumab and azacitidine in patients with relapsed/refractory acute myeloid leukemia. The proposed design avoids an aggressive early termination for futility when the experimental treatment substantially prolongs the DOR but fails to improve the response rate.

Indexed as

Leukemia, Myeloid, AcuteResearch DesignBayes TheoremClinical Trials, Phase II as TopicComputer SimulationHumansMedical FutilityBayesian hierarchical futility monitoring rulesduration of responseresponse ratesingle-arm phase II clinical trial

Identifiers

PMID34101217
PMCPMC8376777
OpenAlexW3166664117

What OpenQuestion holds

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Read underepoch 390

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.