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Evaluating Matching‐Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention‐Deficit/Hyperactivity Disorder

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  • Jason Shafrin
  • Anshu Shrestha
  • Amitabh Chandra
  • M. Haim Erder
  • Vanja Sikirica

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

Suggested Citation

  • Jason Shafrin & Anshu Shrestha & Amitabh Chandra & M. Haim Erder & Vanja Sikirica, 2017. "Evaluating Matching‐Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention‐Deficit/Hyperactivity Disorder," Health Economics, John Wiley & Sons, Ltd., vol. 26(11), pages 1459-1466, November.
    • Handle: RePEc:wly:hlthec:v:26:y:2017:i:11:p:1459-1466
    DOI: 10.1002/hec.3408
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    References listed on IDEAS

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    1. K. Ishak & Irina Proskorovsky & Agnes Benedict, 2015. "Simulation and Matching-Based Approaches for Indirect Comparison of Treatments," PharmacoEconomics, Springer, vol. 33(6), pages 537-549, June.
    2. M. Erder & Jipan Xie & James Signorovitch & Kristina Chen & Paul Hodgkins & Mei Lu & Eric Wu & Vanja Sikirica, 2012. "Cost Effectiveness of Guanfacine Extended-Release versus Atomoxetine for the Treatment of Attention-Deficit/Hyperactivity Disorder," Applied Health Economics and Health Policy, Springer, vol. 10(6), pages 381-395, November.
    3. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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