Evidence map›Paper›PMID 32450909›Full record

ArticleTrials2020

Analysis of responder-based endpoints: improving power through utilising continuous components.

James Wason, Martina McMenamin, Susanna Dodd

Abstract read
In one paragraph

Article in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Augmented binary method for basket trials (ABBA).Statistical methods in medical research · 2026
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  9. 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.

James WasonPopulation Health Sciences Institute, Newcastle University, Baddiley-Clark Building, Newcastle upon Tyne, NE2 4BN, UK. james.wason@newcastle.ac.uk.ORCID http://orcid.org/0000-0002-4691-126X
Martina McMenaminMRC Biostatistics Unit, University of Cambridge, Institute of Public Health, Robinson Way, Cambridge, CB2 0SR, UK.
Susanna DoddDepartment of Biostatistics, University of Liverpool (a member of Liverpool Health Partners), 1-5 Brownlow Street, Liverpool, L69 3GL, UK.

Funding

Cancer Research UK 18113Cancer Research UK C48553/A1811Medical Research Council MC_UU_00002/6
6 · The paper itself

Abstract

backgroundClinical trials and other studies commonly assess the effectiveness of an intervention through the use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by > 30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied.

methodsWe reviewed a database of core outcome sets (COSs) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power.

resultsOut of the 287 COSs reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified) and cardiovascular (8 identified).

conclusionsThe augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoints.

Indexed as

Endpoint DeterminationOutcome Assessment, Health CareClinical Trials as TopicData Interpretation, StatisticalHumansAugmented binary methodComposite endpointEfficiencyResponder analysisStatistical analysis

Identifiers

PMID32450909
PMCPMC7249409

What OpenQuestion holds

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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.