A study on ALS progression suggested that tollgate-related prognostic factors have a stronger effect on the time trajectories of passing ALS tollgates in comparison with standard prognostic factors.
Findings of a study using data from a cohort of 6366 patients suggests that ALS progression with tollgate-related prognostic factors have a stronger effect on the time trajectories of passing ALS tollgates in comparison with standard prognostic factors.1
The investigators noted that factors that affect the variability of ALS progression based on the time trajectories of ALS-related clinical events are important to understand for individualized ALS care. For example, patients with a normal speech at the tollgate level 0 had a less than 10% likelihood of losing speech within a year at the first visit.1 In comparison, patients with a tollgate level of 1 with affected speech, had a probability increase to 23% with early swallowing and leg impairment. In addition, there was also a probability increase to 50% with swallowing impairment and normal leg function for patients at tollgate level 1.
The findings were presented as an abstract at the 2022 American Association of Neuromuscular & Electrodiagnostic Medicine Annual Meeting, held September 21-24, in Nashville, Tennessee, by Haoran Wu, PhD, associate professor at University, Waterloo, and colleagues. At the first visit, the impairment level in a segment impacted the subsequent ALS progression in that segment. Furthermore, the characterized ALS progression speed revealed in the findings that the tollgates affected segment combination or the phenotype during the first visit.
The study focused on ALS progression based on the timing of several critical events, otherwise known as ALS tollgates, by augmenting the patients’ data with tollgate-passed information using binary classification. The patients’ data came from the Pooled Resource Open-Access ALS Clinical Trials database, and the time trajectories of passing ALS tollgates were derived using interval-censored Kaplan–Meier analyses. The researchers used a log-rank test to identify the significant prognostic factors in the ALS progression and its pathways. Furthermore, there was a decision-tree-based classification that was applied to specify the different types of ALS phenotypes. The classification through the tollgates also displayed the different disease progression aggressiveness.
Wu and colleagues wrote the future research should, “consider all risk factors for characterizing risk groups with different progression aggressiveness, which could better predict individualized ALS progression and facilitate shared decision-making.”
Previous research into the potential of ALS tollgate staging systems suggest similar benefits. In 2019, Dalgiç et al reported that this model of staging “can inform ALS patients about their individualized likelihood of having critical disabilities and assistive-device needs” such as wheelchair or ventilation dependence, or the necessitation of a walker, wheelchair, or communication devices.2 Additionally, their data suggested that patients with ALS showed nonuniform pathways, indicating that the likelihood of passing a tollgate differed based on the affected segments at the initial visit.