The paper outlines four considerations for improving covariate adjustment in indirect treatment comparisons, focusing on bias-robustness, extrapolation needs, data-adaptive challenges, and doubly-robust methods.
Population adju stment methods for indirect comparisons: a review of national institute for health and care excellence technology appraisals
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Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons
The paper outlines four considerations for improving covariate adjustment in indirect treatment comparisons, focusing on bias-robustness, extrapolation needs, data-adaptive challenges, and doubly-robust methods.