Evidence map›Paper›PMID 28219326›Full record

ArticleBMC medical research methodology2017

Estimation of treatment preference effects in clinical trials when some participants are indifferent to treatment choice.

Stephen D Walter, Robin M Turner, Petra Macaskill, Kirsten J McCaffery, Les Irwig

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In one paragraph

Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Stephen D WalterDepartment of Clinical Epidemiology and Biostatistics, McMaster University, CRL 233, Hamilton, ON, Canada, L8N 3Z5. walter@mcmaster.ca.
Robin M TurnerSchool of Public Health and Community Medicine, University of New South Wales, Sydney,, NSW 2052, Australia.
Petra MacaskillScreening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia.
Kirsten J McCafferyScreening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia.
Les IrwigScreening and Test Evaluation Program, Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the two-stage randomised trial design, a randomly sampled subset of study participants are permitted to choose their own treatment, while the remaining participants are randomised to treatment in the usual way. Appropriate analysis of the data from both arms of the study allows investigators to estimate the impact on study outcomes of treatment preferences that patients may have, in addition to evaluating the usual direct effect of treatment. In earlier work, we showed how to optimise this design by making a suitable choice of the proportion of participants who should be assigned to the choice arm of the trial. However, we ignored the possibility of some participants being indifferent to the treatments under study. In this paper, we extend our earlier work to consider the analysis of two-stage randomised trials when some participants have no treatment preference, even if they are assigned to the choice arm and allowed to choose.

methodsWe compare alternative characterisations of the response profiles of the indifferent or undecided participants, and derive estimates of the treatment and preference effects on study outcomes. We also present corresponding test statistics for these parameters. The methods are illustrated with data from a clinical trial contrasting medical and surgical interventions.

resultsExpressions are obtained to estimate and test the impact of treatment choices on study outcomes, as well as the impact of the actual treatment received. Contrasts are defined between patients with stated treatment preferences and those with no preference. Alternative assumptions concerning the outcomes of undecided participants are described, and an approach leading to unbiased estimation and testing is identified.

conclusionsUse of the two-stage design can provide important insights into determinants of study outcomes that are not identifiable with other designs. The design can remain attractive even in the presence of participants with no stated treatment preference.

Indexed as

Randomized Controlled Trials as TopicFemaleHumansMenstruationMenstruation DisturbancesPatient PreferencePatient SatisfactionTreatment OutcomeDesignEstimationParticipant preferencesRandomised trials

Identifiers

PMID28219326
PMCPMC5319089

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.