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05 June 2018

We compared methods for an indirect treatment comparison (ITC) of two marketed medicines in patients with diabetic macular edema. Post-stratification, inverse probability weighting based on simulated data, weight optimization, and regression model techniques were used to compare pooled individual patient-level data (IPD) from two phase III studies with summary-level data from two other phase III studies. The impact of adjusting for up to two important baseline characteristics was assessed. The weight optimisation method used is a new matching-adjusted indirect treatment comparison (MAIC) method we developed, which allows for more flexible and sophisticated matching compared with current MAIC approaches. We describe how this method works, how it can be applied (in both R and SAS), and how it compared with the other, more standard, methods.

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