Application of Multilevel Network Meta-Regression in the NICE Technology Appraisal of Quizartinib for induction, consolidation and maintenance treatment of newly diagnosed FLT3-ITD-positive acute myeloid leukaemia: an External Assessment Group perspective

Matching-adjusted indirect comparisons (MAICs)[1] are increasingly popular within National Institute for Health and Care Excellence (NICE) Single Technology Appraisals (STAs) as a method to adjust for cross-study differences in patient characteristics which are treatment-effect modifiers (TEMs)[2, 3]. MAICs are applicable only in a two-study indirect treatment comparison (ITC) scenario where individual participant data (IPD) is available from a study comparing treatment A vs treatment C and aggregate data (AD) from a second study comparing B vs C, to obtain the indirect comparison of A vs B. An inherent limitation is that MAICs provide comparative effect estimates which are applicable only to the population of the AD study and cannot be transposed to different populations [4]. Multilevel network meta-regression (ML-NMR) overcomes these limitations, allowing flexibility to generate population-adjusted ITC estimates from any number of treatments and studies, which are applicable to any specified target population [4-6]. In this commentary, we describe observations and key learnings from an External Assessment Group (EAG) perspective of the first use of ML-NMR for survival outcomes in an STA submitted to NICE for treatment of newly diagnosed FMS-like tyrosine kinase 3 internal tandem duplication positive (FLT3-ITD+) acute myeloid leukaemia (AML) [TA1013][7].