Evidence map›Paper›PMID 36289451›Full record

Trial reportBMC medical research methodology2022

A stratified adaptive two-stage design with co-primary endpoints for phase II clinical oncology trials.

Bastien Cabarrou, Eve Leconte, Patrick Sfumato, Jean-Marie Boher, Thomas Filleron

Abstract readClinical Trial, Phase II
In one paragraph

Trial report in BMC medical research methodology, 2022. 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. Trial
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.

Bastien CabarrouBiostatistics & Health Data Science Unit, Institut Claudius Regaud - IUCT-O, 1 avenue Irène Joliot-Curie, 31059 Cedex 9, Toulouse, France.
Eve LeconteToulouse School of Economics, University of Toulouse Capitole, Toulouse, France.
Patrick SfumatoBiostatistics Unit, Institut Paoli-Calmettes, Marseille, France.
Jean-Marie BoherBiostatistics Unit, Institut Paoli-Calmettes, Marseille, France.
Thomas FilleronBiostatistics & Health Data Science Unit, Institut Claudius Regaud - IUCT-O, 1 avenue Irène Joliot-Curie, 31059 Cedex 9, Toulouse, France. filleron.thomas@iuct-oncopole.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the inherent challenges of conducting randomized phase III trials in older cancer patients, single-arm phase II trials which assess the feasibility of a treatment that has already been shown to be effective in a younger population may provide a compelling alternative. Such an approach would need to evaluate treatment feasibility based on a composite endpoint that combines multiple clinical dimensions and to stratify older patients as fit or frail to account for the heterogeneity of the study population to recommend an appropriate treatment approach. In this context, stratified adaptive two-stage designs for binary or composite endpoints, initially developed for biomarker studies, allow to include two subgroups whilst maintaining competitive statistical performances. In practice, heterogeneity may indeed affect more than one dimension and incorporating co-primary endpoints, which independently assess each individual clinical dimension, would therefore appear quite pertinent. The current paper presents a novel phase II design for co-primary endpoints which takes into account the heterogeneity of a population. 

methodsWe developed a stratified adaptive Bryant & Day design based on the Jones et al. and Parashar et al. algorithm. This two-stage design allows to jointly assess two dimensions (e.g. activity and toxicity) in two different subgroups. The operating characteristics of this new design were evaluated using examples and simulation comparisons with the Bryant & Day design in the context where the study population is stratified according to a pre-defined criterion.

resultsSimulation results demonstrated that the new design minimized the expected and maximum sample sizes as compared to parallel Bryant & Day designs (one in each subgroup), whilst controlling type I error rates and maintaining a competitive statistical power as well as a high probability of detecting heterogeneity.

conclusionsIn a heterogeneous population, this two-stage stratified adaptive phase II design provides a useful alternative to classical one and allows to identify a subgroup of interest without dramatically increasing sample size. As heterogeneity is not limited to older populations, this new design may also be relevant to other study populations such as children or adolescents and young adults or the development of targeted therapies based on a biomarker.

Indexed as

Medical OncologyNeoplasmsAgedBiomarkersHumansResearch DesignSample SizeBiomarkersAdaptive stratified designCo-primary endpointsHeterogeneityPhase II clinical oncology trials

Identifiers

PMID36289451
PMCPMC9608934

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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.