Literature DB >> 18767896

Use of indirect and mixed treatment comparisons for technology assessment.

Alex Sutton1, A E Ades, Nicola Cooper, Keith Abrams.   

Abstract

Indirect and mixed treatment comparison (MTC) approaches to synthesis are logical extensions of more established meta-analysis methods. They have great potential for estimating the comparative effectiveness of multiple treatments using an evidence base of trials that individually do not compare all treatment options. Connected networks of evidence can be synthesized simultaneously to provide estimates of the comparative effectiveness of all included treatments and a ranking of their effectiveness with associated probability statements. The potential of the use of indirect and MTC methods in technology assessment is considerable, and would allow for a more consistent assessment than simpler alternative approaches. Although such models can be viewed as a logical and coherent extension of standard pair-wise meta-analysis, their increased complexity raises some unique issues with far-reaching implications concerning how we use data in technology assessment, while simultaneously raising searching questions about standard pair-wise meta-analysis. This article reviews pair-wise meta-analysis and indirect and MTC approaches to synthesis, clearly outlining the assumptions involved in each approach. It also raises the issues that the National Institute for Health and Clinical Excellence (NICE) needed to consider in updating their 2004 Guide to the Methods of Technology Appraisal, if such methods are to be used in their technology appraisals.

Mesh:

Year:  2008        PMID: 18767896     DOI: 10.2165/00019053-200826090-00006

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  28 in total

1.  Validity of indirect comparison for estimating efficacy of competing interventions: empirical evidence from published meta-analyses.

Authors:  Fujian Song; Douglas G Altman; Anne-Marie Glenny; Jonathan J Deeks
Journal:  BMJ       Date:  2003-03-01

2.  Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes.

Authors:  Jonathan J Deeks
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

3.  Network meta-analysis for indirect treatment comparisons.

Authors:  Thomas Lumley
Journal:  Stat Med       Date:  2002-08-30       Impact factor: 2.373

4.  Using mixed treatment comparisons and meta-regression to perform indirect comparisons to estimate the efficacy of biologic treatments in rheumatoid arthritis.

Authors:  R M Nixon; N Bansback; A Brennan
Journal:  Stat Med       Date:  2007-03-15       Impact factor: 2.373

5.  Mixed treatment comparison with multiple outcomes reported inconsistently across trials: evaluation of antivirals for treatment of influenza A and B.

Authors:  N J Welton; N J Cooper; A E Ades; G Lu; A J Sutton
Journal:  Stat Med       Date:  2008-11-29       Impact factor: 2.373

6.  Indirect comparisons of competing interventions.

Authors:  A M Glenny; D G Altman; F Song; C Sakarovitch; J J Deeks; R D'Amico; M Bradburn; A J Eastwood
Journal:  Health Technol Assess       Date:  2005-07       Impact factor: 4.014

7.  Practical methodology of meta-analyses (overviews) using updated individual patient data. Cochrane Working Group.

Authors:  L A Stewart; M J Clarke
Journal:  Stat Med       Date:  1995-10-15       Impact factor: 2.373

8.  Correction: interpretation of random effects meta-analysis in decision models.

Authors:  N J Welton; I R White; G Lu; J P T Higgins; J Hilden; A E Ades
Journal:  Med Decis Making       Date:  2007 Mar-Apr       Impact factor: 2.583

Review 9.  Simultaneous comparison of multiple treatments: combining direct and indirect evidence.

Authors:  Deborah M Caldwell; A E Ades; J P T Higgins
Journal:  BMJ       Date:  2005-10-15

10.  Bias modelling in evidence synthesis.

Authors:  Rebecca M Turner; David J Spiegelhalter; Gordon C S Smith; Simon G Thompson
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2009-01       Impact factor: 2.483

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  122 in total

Review 1.  Frequency of treatment-effect modification affecting indirect comparisons: a systematic review.

Authors:  Michael Coory; Susan Jordan
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

Review 2.  Effectiveness of psychotherapeutic, pharmacological, and combined treatments for chronic depression: a systematic review (METACHRON).

Authors:  Levente Kriston; Alessa von Wolff; Lars Hölzel
Journal:  BMC Psychiatry       Date:  2010-11-23       Impact factor: 3.630

Review 3.  Critical evaluation of mixed treatment comparison meta-analyses using examples assessing antidepressants and opioid detoxification treatments.

Authors:  Alexander Schacht; Yulia Dyachkova; Richard James Walton
Journal:  Int J Methods Psychiatr Res       Date:  2013-06-06       Impact factor: 4.035

4.  Comparative efficacy of vildagliptin and sitagliptin in Japanese patients with type 2 diabetes mellitus: a matching-adjusted indirect comparison of randomized trials.

Authors:  James E Signorovitch; Eric Q Wu; Elyse Swallow; Evan Kantor; Liangyi Fan; Jean-Bernard Gruenberger
Journal:  Clin Drug Investig       Date:  2011       Impact factor: 2.859

5.  NICE Methodology for Technology Appraisals: cutting edge or tried and trusted?

Authors:  Louise Longworth; Carole Longson
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

6.  NICE's 2008 Methods Guide: sensible consolidation or opportunities missed?

Authors:  Mark Sculpher
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

7.  Exploring uncertainty in cost-effectiveness analysis.

Authors:  Karl Claxton
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

8.  NICE Guide to the Methods of Technology Appraisal: pharmaceutical industry perspective.

Authors:  Julia Earnshaw; Gavin Lewis
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

Review 9.  Systematic review and meta-analysis: techniques and a guide for the academic surgeon.

Authors:  Kevin Phan; David H Tian; Christopher Cao; Deborah Black; Tristan D Yan
Journal:  Ann Cardiothorac Surg       Date:  2015-03

10.  Is It Necessary to Perform the Pharmacological Interventions for Intrahepatic Cholestasis of Pregnancy? A Bayesian Network Meta-Analysis.

Authors:  Yi Shen; Jie Zhou; Sheng Zhang; Xu-Lin Wang; Yu-Long Jia; Shu He; Yuan-Yuan Wang; Wen-Chao Li; Jian-Guo Shao; Xun Zhuang; Yuan-Lin Liu; Gang Qin
Journal:  Clin Drug Investig       Date:  2019-01       Impact factor: 2.859

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