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Title: Development of mixed treatment comparison meta-analysis
Author: Lu, Guobing
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2013
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Mixed treatment comparison (MTC) meta-analysis, or network meta-analysis, is a methodology developed in the last decade for synthesizing both direct and indirect evidence on multiple treatments from randomised controlled trials available in a therapeutic area, while respecting the randomisation of the included trials. As a natural extension of ordinary pairwise comparison meta-analysis, MTC has increasingly been used in medical research and health technology assessment. The eleven papers (PI-PI 1) on MTC meta-analysis included in this thesis were published in peer-viewed journals from 2004 to early 2013, which was a period of rapid growth of this research topic_ These papers have substantially contributed to the development of MTC meta-analysis in both theory and applications_ They are organised into four chapters (Chapters 3-6) according to their roles in the development of MTC rather than the chronological order of publishing, which are the body of the commentary part of this thesis. In each of these chapters, my comments will be focused on the basic idea behind each included paper and its role in developing the MTC methodology_ Treated as a system of methodology on MTC meta-analysis, these included publications are intrinsically related in a connection network (Chapter 7), where three pivotal papers (P 1, P4 and P 11) provided fundamental concepts and models, four extension papers (P7 -PlO) generalised the basic models to more complex situations, and the rest were concerned with practical applications (P2-3) and issues on assessing evidence inconsistency (P5-6). The significance of the included published work on the development of MTC is discussed in the conclusion chapter around several statistical and methodological aspects of evidence synthesis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available