OBJECTIVES: Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disease affecting voluntary muscle control. While no cure exists for ALS, treatments may slow its progression, as measured by clinical scales and staging systems (e.g., Fine’til 9, MiToS). Thakore et al. (2020) developed a Markov model (MM) with health states based on Fine’til 9 stages to assess the cost-effectiveness of ALS treatments. This approach has been leveraged in subsequent health technology assessments (HTAs) in ALS. In 2022, Amylyx conducted an advisory board with leading health economists, representing six European countries. The advisors recommended a partitioned survival model (PSM) as it may better capture the different clinical benefits of treatment and better represents the ALS disease course. This study considers how to best conceptualize ALS and treatment effects in a cost-effectiveness model.

METHODS: The PSM approach involved a single partition based on time-to-hospitalization. A targeted literature review (TLR) was conducted to assess data availability for cost-effectiveness analysis, and an early PSM was developed.

RESULTS: In previous HTAs in ALS, Markov transition probabilities were based on published evidence, and treatments effects were applied using relative risks. Whereas, a PSM allows inclusion of cross-over adjusted survival from trial data in a technically robust manner, which is crucial to understanding life years (LYs) and therefore quality-adjusted life years (QALYs). A potential limitation of the PSM approach is that information on subsequent worsening may be lost by dichotimizing progression. However, the TLR findings suggested little differentiation in utility and healthcare resource use between later disease stages (as defined by MiToS 2-4), which could be pooled for post-progression inputs.

CONCLUSIONS: Overall, time-to-hospitalization is important to people living with ALS and clinicians, and a PSM seems to be a more optimal approach to represent the ALS disease course and capture the value of novel ALS interventions.