Evidence map›Paper›PMID 33478274›Full record

ArticleClinical trials (London, England)2021

A modular framework for early-phase seamless oncology trials.

Philip S Boonstra, Thomas M Braun, Elizabeth C Chase

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

3 authors.

Philip S BoonstraDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0001-8545-9133
Thomas M BraunDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Elizabeth C ChaseDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-0452-2976

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THEODORE S LAWRENCE · 1988 to 2026
$178.2M
Biostatistics Training Program in Cancer ResearchT32CA083654 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Veerabhadran Baladandayuthapani, Kelley McLain Kidwell · 2002 to 2026
$4.3M
NCI NIH HHS P30 CA046592NCI NIH HHS T32 CA083654
6 · The paper itself

Abstract

backgroundAs our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now "seamless," meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (1) what is the probability that the design will identify an acceptable, that is., safe and efficacious, dose level? or (2) how many patients will be assigned to an acceptable dose level on average?

methodsIn this manuscript, we propose a new modular framework for designing and evaluating seamless oncology trials. Each module is comprised of either a dose assignment step or a dose-response evaluation, and multiple such modules can be implemented sequentially. We develop modules from existing phase I/II designs as well as a novel module for evaluating dose-response using a Bayesian isotonic regression scheme.

resultsWe also demonstrate a freely available R package called seamlesssim to numerically estimate, by means of simulation, the operating characteristics of these modular trials.

conclusionsTogether, this design framework and its accompanying simulator allow the clinical trialist to compare multiple different candidate designs, more rigorously assess performance, better justify sample sizes, and ultimately select a higher quality design.

Indexed as

Clinical Trials as TopicNeoplasmsResearch DesignBayes TheoremComputer SimulationDose-Response Relationship, DrugHumansMaximum Tolerated Dosedose escalationPhase Iphase IIrecommended phase II dose

Identifiers

PMID33478274
PMCPMC8382494

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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.