Abstract

A cost-effectiveness model was developed to evaluate use of ferric maltol (FM) to treat IDA in patients with IBD from a National Health Service perspective. A Markov model was developed to evaluate a hypothetical cohort of patients initiating therapy. FM was compared with ferric carboxymaltose (primary comparator), oral iron, iron isomaltoside, and iron sucrose in separate analyses. The model included four health states: on primary treatment, off primary treatment/on secondary therapy, discontinuation after secondary therapy, and mortality. In all living health states, patients could be in the following anaemia categories, based on their haemoglobin level: stable (non-anaemic), mild, moderate, and severe. As there was mixed evidence available, Bayesian network meta-analysis (NMA) of Phase 3 randomized controlled trials was performed. Overall cost calculations associated with each treatment included drug costs, routine medical care and hospitalization costs, adverse event related costs, and mortality costs. Utility values were obtained from FM’s AEGIS trials' patient-level data, and were mapped to EQ-5D values, which varied by health state (on and off treatment with stable, mild, moderate, or severe anaemia). The economic endpoint was quality-adjusted life years (QALYs). Overall, FM-treated patients showed slight dominance over the included comparators. In the base case analysis, FM was associated with a gain of 0.09 QALYs and cost savings of £2,212 versus ferric carboxymaltose. Deterministic and probabilistic sensitivity analyses generally showed consistency with base case findings. Deterministic sensitivity analysis exhibited greatest sensitivity to variations in utility values. When additional scenarios were explored, incremental cost effectiveness ratios were most sensitive to variations in time horizon and utility sources. NMA data were applied in the economic analysis, where ferric maltol appeared to be cost-saving and associated with a small QALYs gain versus the included comparators. Sensitivity analyses supported the findings, contributing to the robustness of the economic case.

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