Use of Indirect and Mixed Treatment Comparisons for Technology Assessment
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.
- 1.Hierarchy of evidence and grading of recommendations. Thorax 2004; 59 (Suppl. 1): 13Google Scholar
- 2.Egger M, Davey Smith G, Altman DG. Systematic reviews in health care: meta-analysis in context. London: BMJ Books, 2000Google Scholar
- 3.Higgins JPT, Green S, editors. Cochrane handbook for systematic reviews of interventions, 4.2.5 [updated May 2005]. In: The Cochrane Library. Issue 3. Chichester: John Wiley & Sons, Ltd, 2005Google Scholar
- 10.National Institute for Health and Clinical Excellence (NICE). Guide to the methods of technology appraisal. London: NICE 2004Google Scholar
- 12.Sutton AJ, Abrams KR, Jones DR, et al. Methods for meta-analysis in medical research. London: John Wiley, 2000Google Scholar
- 24.Turner RM, Spiegelhalter DJ, Smith GCS, et al. Bias modelling in evidence synthesis. J R Stat Soc Ser A Stat Soc. In pressGoogle Scholar
- 26.Barrio V. Actual methodological controversies on the controlled clinical trials and on meta-analysis. Nefrologia 1998; 18: 32–39Google Scholar
- 30.Spiegelhalter DJ, Thomas A, Best NG. WinBUGS version 1.2 user manual. Cambridge (UK): MRC Biostatistics Unit, 1999Google Scholar
- 32.Efron B, Tibshirani RJ. An introduction to the bootstrap. 1st ed. New York: Chapman & Hall, 1993Google Scholar
- 36.Welton N, Cooper NJ, Ades A, et al. Mixed treatment comparison with multiple outcomes reported inconsistently across trials: evaluation of antivirals for treatment of influenza A and B. Stat Med. In pressGoogle Scholar