Evidence map›Paper›PMID 24085774›Full record

ArticleClinical trials (London, England)2014

Marker Sequential Test (MaST) design.

Boris Freidlin, Edward L Korn, Robert Gray

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  5. A Problematic Biomarker Trial Design.Journal of the National Cancer Institute · 2022
    Article
  6. Statistical Considerations for Subgroup Analyses.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2021
    Article
  7. Article
  8. Review
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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.

Boris FreidlinaBiometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA.
Edward L Korn
Robert Gray

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

backgroundNew targeted anticancer therapies often benefit only a subset of patients with a given cancer. Definitive evaluation of these agents may require phase III randomized clinical trial designs that integrate evaluation of the new treatment and the predictive ability of the biomarker that putatively determines the sensitive subset. PURPOSE: We propose a new integrated biomarker design, the Marker Sequential Test (MaST) design, that allows sequential testing of the treatment effect in the biomarker subgroups and overall population while controlling the relevant type I error rates.

methodsAfter defining the testing and error framework for integrated biomarker designs, we review the commonly used approaches to integrated biomarker testing. We then present a general form of the MaST design and describe how it can be used to provide proper control of false-positive error rates for biomarker-positive and biomarker-negative subgroups. The operating characteristics of the MaST design are compared by analytical methods and simulations to the sequential subgroup-specific design that sequentially assesses the treatment effect in the biomarker subgroups. Practical aspects of MaST design implementation are discussed.

resultsThe MaST design is shown to have higher power relative to the sequential subgroup-specific design in situations where the treatment effect is homogeneous across biomarker subgroups, while preserving the power for settings where treatment benefit is limited to biomarker-positive subgroup. For example, in the time-to-event setting considered with 30% biomarker-positive prevalence, the MaST design provides up to a 30% increase in power in the biomarker-positive and biomarker-negative subgroups when the treatment benefits all patients equally, while sustaining less than a 2% loss of power against alternatives where the benefit is limited to the biomarker-positive subgroup. LIMITATIONS: The proposed design is appropriate for settings where it is reasonable to assume that the treatment will not be effective in the biomarker-negative patients unless it is effective in the biomarker-positive patients.

conclusionThe MaST trial design is a useful alternative to the sequential subgroup-specific design when it is important to consider the treatment effect in the biomarker-positive and biomarker-negative subgroups.

Indexed as

BiomarkersResearch DesignAntineoplastic AgentsClinical Trials as TopicFalse Positive ReactionsHumansModels, StatisticalNeoplasmsPredictive Value of TestsAntineoplastic AgentsBiomarkers

Identifiers

PMID24085774
PMCPMC11406163

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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.