OBJECTIVES: The objective of this study was to assess feasibility of using Milano-Torino staging (MiToS) for developing a Markov model to conduct economic analysis in ALS.

METHODS: A hypothetical treatment was compared with usual supportive care for ALS using MiToS staging based on a 6-health-state Markov model. Health utilities, transition probabilities and costs were derived from the literature. One, 5, 10-year and lifetime time horizons with 3 months cycle length and ½ cycle correction were examined. The treatment effect was risk reduction in transition in MiToS staging: 20%, 25%, 30% and 35%. For patient distribution, three scenarios were tested: (1) 100% of the patients starting in Stage 0 and (2) and (3) were patient mix based on Real-world evidence (RWE). Quality-adjusted life years (QALYs) and Life years (LYs) with a 3% discount rate were reported.

RESULTS: The model shows it is feasible to use MiToS staging for developing a Markov transition state model in ALS. Comparison of 1, 5, 10 and 20 years horizon shows 10 years might be an optimal time horizon to capture treatment effect. The estimated incremental QALY and LY gains for a treatment with 20-35% reduction in progression are significant for a rare and serious disease such as ALS. For 10-year time horizon, in RWE settings, the incremental QALYs and LYs range was 0.16-0.41 and 0.35-0.79, respectively; for a hypothetical patient mix, the incremental QALYs and LYs range was 0.22-0.45 and 0.41-0.83, respectively. Analysis of QALYs by MiToS stages shows the majority of gains occur in earlier stages, especially stages 0, 1 and 2. There are some evidence gaps for US costs and health utilities.

CONCLUSIONS: MiToS-based staging can be used for developing Markov models for economic analysis in ALS. A hypothetical new treatment with 20-35% risk reduction using MiToS can lead to significant QALYs and LYs gains in ALS.