Evaluating Matching‐Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention‐Deficit/Hyperactivity Disorder
Jason Shafrin,
Anshu Shrestha,
Amitabh Chandra,
M. Haim Erder and
Vanja Sikirica
Health Economics, 2017, vol. 26, issue 11, 1459-1466
Abstract:
Differences in patient characteristics across trials may bias efficacy estimates from indirect treatment comparisons. To address this issue, matching‐adjusted indirect comparison (MAIC) measures treatment efficacy after weighting individual patient data to match patient characteristics across trials. To date, however, there is no consensus on how best to implement MAIC. To address this issue, we applied MAIC to measure how two attention‐deficit/hyperactivity disorder (ADHD) treatments (guanfacine extended release and atomoxetine hydrochloride) affect patients' ADHD symptoms, as measured by the ADHD Rating Scale IV score. We tested MAIC sensitivity to: matched patient characteristics, matched statistical moments, weighting matrix, and placebo‐arm matching (i.e., matching on outcomes in the placebo arm). After applying MAIC, guanfacine and atomoxetine had similar reductions in ADHD symptoms (Δ: 0.4, p
Date: 2017
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https://doi.org/10.1002/hec.3408
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Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:26:y:2017:i:11:p:1459-1466
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