Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

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

View ORCID ProfileGeorgia Salanti, View ORCID ProfileAdriani Nikolakopoulou, Alex J Sutton, Stephan Reichenbach, Sven Trelle, Huseyin Naci, Matthias Egger
doi: https://doi.org/10.1101/324871
Georgia Salanti
1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, , ,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Georgia Salanti
  • For correspondence: georgia.salanti@ispm.unibe.ch adriani.nikolakopoulou@ispm.unibe.ch matthias.egger@ispm.unibe.ch
Adriani Nikolakopoulou
1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, , ,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Adriani Nikolakopoulou
  • For correspondence: georgia.salanti@ispm.unibe.ch adriani.nikolakopoulou@ispm.unibe.ch matthias.egger@ispm.unibe.ch
Alex J Sutton
2Department of Health Sciences, College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, UK,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ajs22@leicester.ac.uk
Stephan Reichenbach
1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, , ,
3Department of Rheumatology, Immunology and Allergiology, University Hospital, University of Bern, Bern, Switzerland,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: georgia.salanti@ispm.unibe.ch adriani.nikolakopoulou@ispm.unibe.ch matthias.egger@ispm.unibe.ch stephan.reichenbach@ispm.unibe.ch
Sven Trelle
4CTU Bern, University of Bern, Bern, Switzerland,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: sven.trelle@ctu.unibe.ch
Huseyin Naci
5LSE Health, Department of Health Policy, London School of Economics and Political Science, London, UK,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: H.Naci@lse.ac.uk
Matthias Egger
1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland, , ,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: georgia.salanti@ispm.unibe.ch adriani.nikolakopoulou@ispm.unibe.ch matthias.egger@ispm.unibe.ch
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

ABSTRACT

Background: The 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.

Methods: Network meta-analyses can also be used to plan future trials. We introduce a four-steps framework to plan a new trial that aims to identify the optimal new design that will update the existing evidence to best serve timely clinical and public health decision making. 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.

Results: A 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 in the approach include the complexity of the methodology and the need for a coherent network meta-analysis of previous trials with little heterogeneity.

Conclusions: When used judiciously, conditional trial design could significantly reduce waste in clinical research.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted May 17, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Planning a future randomized clinical trial based on a network of relevant past trials
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
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
bioRxiv 324871; doi: https://doi.org/10.1101/324871
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
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
bioRxiv 324871; doi: https://doi.org/10.1101/324871

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Epidemiology
Subject Areas
All Articles
  • Animal Behavior and Cognition (2646)
  • Biochemistry (5259)
  • Bioengineering (3671)
  • Bioinformatics (15788)
  • Biophysics (7247)
  • Cancer Biology (5624)
  • Cell Biology (8088)
  • Clinical Trials (138)
  • Developmental Biology (4763)
  • Ecology (7510)
  • Epidemiology (2059)
  • Evolutionary Biology (10571)
  • Genetics (7727)
  • Genomics (10125)
  • Immunology (5187)
  • Microbiology (13896)
  • Molecular Biology (5383)
  • Neuroscience (30754)
  • Paleontology (215)
  • Pathology (876)
  • Pharmacology and Toxicology (1524)
  • Physiology (2253)
  • Plant Biology (5017)
  • Scientific Communication and Education (1040)
  • Synthetic Biology (1384)
  • Systems Biology (4145)
  • Zoology (812)