OBJECTIVES: In the absence of head-to-head trials, indirect comparisons are being increasingly utilized to analyze the comparative effectiveness of interventions. Matching-Adjusted Indirect Comparison (MAIC) is a novel technique allowing for a robust comparison, by re-weighting Individual Patient Data (IPD) from one study to the baseline summary statistics of another, to provide greater adjustment for observed trial differences compared to conventional meta-analytic methods. The objective of this study was to review the applications of MAIC by analyzing published literature across therapeutic areas, including Health Technology Assessments (HTA).  METHODS: To capture the use of MAIC in literature and HTA, electronic literature databases (Medline, Embase and the Cochrane Library) were queried via Ovid and data was also extracted from the websites of the national HTA bodies of England, Scotland, Canada and Australia. A checklist was developed to assess the methodology, strengths and limitations of each publication. RESULTS: A total of 23 publications (manuscripts, posters or abstracts) reported the use of MAIC across different therapeutic areas: Auto-immune and Rheumatology (7), Infectious Diseases (6), Oncology (5), Neuroscience (4) & Metabolic Diseases (1), although differences were observed in the methodologies employed regarding placebo effects and variable matching. MAIC methodology has been part of 12 HTA submissions with the first submission in 2012. Opinion on MAIC was inconsistent across HTA bodies and committees, with some requesting MAIC analyses, others questioning their general validity and some being particularly critical of inadequately reported analyses. CONCLUSIONS: The current study found that even though it is a new method, the use of MAIC in the absence of direct comparisons between treatments has been increasing across different therapeutic areas, and so has its acceptability by HTA bodies, although questions about its validity and correct application remain. If applied, reported and interpreted correctly, MAIC is a valid technique for comparative effectiveness research.