MATCHING-ADJUSTED INDIRECT COMPARISONS TO ASSESS COMPARATIVE EFFECTIVENESS- A SYSTEMATIC REVIEW OF APPLICATION IN SCIENTIFIC LITERATURE AND HEALTH TECHNOLOGY APPRAISALS
Author(s)
Thom H1, Jugl SM2, Nikoglou E3, Jawla S4
1University of Bristol, Bristol, UK, 2Novartis Pharma AG, Basel, Switzerland, 3Product Lifecycle Services - NBS, Novartis Global Service Center Dublin, Dublin, Ireland, 4Novartis Healthcare Pvt. Ltd., Hyderabad, India
OBJECTIVES: In the absence of head-to-head studies, indirect comparisons are being recommended and widely used to estimate comparative effectiveness. Matching-Adjusted Indirect Comparison (MAIC) re-weights Individual Patient Data from one study to match the distribution of baseline characteristics of another, reducing heterogeneity due to observed trial differences compared with conventional meta-analytic methods. The objective of this study was to review the application of MAIC in the scientific literature and in Health Technology Assessments (HTA). METHODS: A systematic literature review was conducted using Ovid (Medline, Cochrane Library) and Embase (Embase, Medline) platforms from years 2010 through October 2016. In addition, assessment documents from key HTA bodies (England, Scotland, Canada and Australia) were reviewed. Publications from conferences where the authors of this study have been involved were also targeted for evidence. RESULTS: A total of 61 publications (manuscripts, posters or abstracts) reported the use of MAIC across different therapeutic areas: auto-immune and rheumatology(23), oncology(22), infectious diseases(7), neuroscience(4), hematology(2), metabolic diseases(1), respiratory(1) and unspecified disease(1). An increasing trend in MAIC publications was observed as 29 publications were released alone in 2016, compared to 6 in 2010. Differences were observed in the methodologies employed regarding placebo effects and variable matching between publications. The MAIC methodology was part of 21 HTA submissions with the first submission in 2012. Comments on MAICs were inconsistent across HTA bodies, with some requesting MAIC analyses, others questioning them. This diversity in quality and acceptability is likely explained by unclear standards of application, reporting and interpretation of the MAIC analyses. CONCLUSIONS: The current study found that the use of MAIC has been increasing across different therapeutic areas, and so has its acceptability by HTA bodies even though many MAICs have not been reported adequately. If applied, reported and interpreted correctly, MAIC can be a valid technique for comparative effectiveness research.
Conference/Value in Health Info
2017-05, ISPOR 2017, Boston, MA, USA
Value in Health, Vol. 20, No. 5 (May 2017)
Code
PRM159
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Multiple Diseases