MSR31 Applying Multi-Level Network Meta-Regression (ML-NMR) to a Case Study in Triple-Class Exposed (TCE) Relapsed/Refractory Multiple Myeloma (RRMM)

Abstract

BACKGROUND: ML-NMR provides a framework for defining an individual-level regression model, which is integrated over aggregate populations to form an aggregate-level model. ML-NMR avoids aggregation bias and produces estimates in any target population. ML-NMR has been published and applied to binary outcomes, but not time-to-event outcomes.