Evidence map›Paper›PMID 29996869›Full record

ArticleTrials2018

Planning a future randomized clinical trial based on a network of relevant past trials.

Georgia Salanti, Adriani Nikolakopoulou, Alex J Sutton, Stephan Reichenbach, Sven Trelle, Huseyin Naci, Matthias Egger

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Trials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  19. Network meta-analysis reaches nutrition research.European journal of nutrition · 2019
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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

7 authors.

Georgia SalantiInstitute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland. georgia.salanti@ispm.unibe.ch.ORCID http://orcid.org/0000-0002-3830-8508
Adriani NikolakopoulouInstitute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Alex J SuttonDepartment of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK.
Stephan ReichenbachInstitute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Sven TrelleCTU Bern, University of Bern, Bern, Switzerland.
Huseyin NaciLSE Health, Department of Health Policy, London School of Economics and Political Science, London, UK.
Matthias EggerInstitute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.

Funding

H2020 Marie Skłodowska-Curie Actions 703254
6 · The paper itself

Abstract

backgroundThe important role of network meta-analysis of randomized clinical trials in health technology assessment and guideline development is increasingly recognized. This approach has the potential to obtain conclusive results earlier than with new standalone trials or conventional, pairwise meta-analyses.

methodsNetwork meta-analyses can also be used to plan future trials. We introduce a four-step framework that aims to identify the optimal design for a new trial that will update the existing evidence while minimizing the required sample size. The new trial designed within this framework does not need to include all competing interventions and comparisons of interest and can contribute direct and indirect evidence to the updated network meta-analysis. We present the method by virtually planning a new trial to compare biologics in rheumatoid arthritis and a new trial to compare two drugs for relapsing-remitting multiple sclerosis.

resultsA trial design based on updating the evidence from a network meta-analysis of relevant previous trials may require a considerably smaller sample size to reach the same conclusion compared with a trial designed and analyzed in isolation. Challenges of the approach include the complexity of the methodology and the need for a coherent network meta-analysis of previous trials with little heterogeneity.

conclusionsWhen used judiciously, conditional trial design could significantly reduce the required resources for a new study and prevent experimentation with an unnecessarily large number of participants.

Indexed as

Network Meta-Analysis as TopicResearch DesignArthritis, RheumatoidHumansMultiple Sclerosis, Relapsing-RemittingRandomized Controlled Trials as TopicSample SizeConditional powerEvidence synthesisHistorical dataRheumatoid arthritisSample size

Identifiers

PMID29996869
PMCPMC6042258

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.