Survival outcomes are commonly analyzed in studies with data from patients with progressive, neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS). Given the fast progression of ALS, survival analyses are, however, often difficult to perform and interpret. In this methodological article we demonstrate on real-world data how the choices we make in the study design, data collection, and analysis could influence the results. The factors we consider in this study are length of follow-up, sample size, timing of sample collection, and choice of covariables adjusted for in the models. We further discuss the importance of each of these contributing factors and about how to avoid mistakes in interpreting and reporting survival data in ALS and other rare, progressive diseases.
Yazdani et al. (2026) studied this question.