By the same authors

From the same journal

Sensitivity of treatment recommendations to bias in network meta-analysis

Research output: Contribution to journalArticle

Author(s)

  • David Phillippo
  • Sofia Dias
  • Tony Ades
  • Vanessa Didelez
  • Nicky J. Welton

Department/unit(s)

Publication details

JournalJournal of the Royal Statistical Society: Series A (Statistics in Society)
DateAccepted/In press - 31 Oct 2017
DateE-pub ahead of print - 6 Dec 2017
DatePublished (current) - 1 Jun 2018
Issue number3
Volume181
Number of pages25
Pages (from-to)843-867
Early online date6/12/17
Original languageUndefined/Unknown

Abstract

Network meta-analysis (NMA) pools evidence on multiple treatments to estimate relative treatment effects. Included studies are typically assessed for risk of bias; however, this provides no indication of the impact of potential bias on a decision based on the NMA. We propose methods to derive bias adjustment thresholds which measure the smallest changes to the data that result in a change of treatment decision. The methods use efficient matrix operations and can be applied to explore the consequences of bias in individual studies or aggregate treatment contrasts, in both fixed and random-effects NMA models. Complex models with multiple types of data input are handled by using an approximation to the hypothetical aggregate likelihood. The methods are illustrated with a simple NMA of thrombolytic treatments and a more complex example comparing social anxiety interventions. An accompanying R package is provided.

Bibliographical note

© 2017 The Authors Journal of the Royal Statistical Society: Series A (Statistics in Society) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society.

    Research areas

  • Evidence synthesis, Influence matrix, Mixed treatment comparison, Quality of evidence, Risk of bias, Treshold analysis

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