Validating the Assumptions of Population Adjustment: Application of Multilevel Network Meta-regression to a Network of Treatments for Plaque Psoriasis.

ABSTRACT:

Background

Network meta-analysis (NMA) and indirect comparisons combine aggregate data (AgD) from multiple studies on treatments of interest but may give biased estimates if study populations differ. Population adjustment methods such as multilevel network meta-regression (ML-NMR) aim to reduce bias by adjusting for differences in study populations using individual patient data (IPD) from 1 or more studies under the conditional constancy assumption. A shared effect modifier assumption may also be necessary for identifiability. This article aims to demonstrate how the assumptions made by ML-NMR can be assessed in practice to obtain reliable treatment effect estimates in a target population.

Methods

We apply ML-NMR to a network of evidence on treatments for plaque psoriasis wi

SUBMITTER: Phillippo DM 

PROVIDER: S-EPMC9742635 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature