AI Article Synopsis
- Mixed treatment comparisons (MTC) extend traditional meta-analysis by allowing indirect comparisons among various interventions, addressing the lack of direct head-to-head data.
- The article discusses MTC with a focus on examples of drug treatments for rheumatoid arthritis, highlighting the use of patient-reported outcomes.
- It contrasts traditional meta-analysis with Bayesian methods and offers insights on effectively presenting MTC results to engage clinicians and decision-makers in the healthcare market.
Article Abstract
Recently, mixed treatment comparisons (MTC) have been presented as an extension of traditional meta-analysis by including multiple different pairwise comparisons across a range of different interventions. MTC allow for indirect comparisons and can therefore provide very useful information for clinical and reimbursement decision-making in the absence of head-to-head data. In this article, we provide an introductory overview of MTC illustrated with example analyses of different drug treatments in rheumatoid arthritis using a continuous patient-reported end point. As a background, we start with an overview of the traditional meta-analyses for pairwise trials, and the difference between a traditional approach and a Bayesian approach. Next, the Bayesian MTC for continuous outcomes are presented. We finish with a discussion of how MTC can best be presented in order to maximize acceptance by target audiences, i.e., clinicians and market access decision-makers.
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| http://dx.doi.org/10.1111/j.1524-4733.2008.00347.x | DOI Listing |
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