Amyotrophic lateral sclerosis regional progression intervals change according to time of involvement of different body regions.

Abstract

The prediction of disease course is one of the main targets of amyotrophic lateral sclerosis (ALS) research, particularly considering its wide phenotypic heterogeneity. Despite many attempts to classify patients into prognostic categories according to the different spreading patterns at diagnosis, a precise regional progression rate and the time of involvement of each region has yet to be clarified. The aim of our study was to evaluate the functional decline in different body regions according to their time of involvement during disease course. In a population-based dataset of ALS patients, we analysed the functional decline in different body regions according to time and order of regional involvement. We calculated the regional progression intervals (RPIs) between initial involvement and severe functional impairment using the ALS Functional Rating Scale revised (ALSFRS-r) subscores for the bulbar, upper limb, lower limb and respiratory/thoracic regions. Time-to-event analyses, adjusted for age, sex, ALSFRS-r pre-slope (ΔALSFRS-R), cognitive status, and mutational status were performed. The duration of RPI differed significantly among ALS phenotypes, with the RPI of the first region involved being significantly longer than the RPIs of regions involved later. Cox proportional hazard models showed that in fact a longertime between disease onset and initial regional involvement was related to a reduced duration of the RPI duration in each different body region (bulbar region: hazard ratio [HR] 1.11, 95% confidence interval [CI] 1.06-1.16, p < 0.001; upper limb region: HR 1.16, 95% CI 1.06-1.28, p=0.002; lower limb region: HR 1.11, 95% CI 1.03-1.19, p=0.009; respiratory/thoracic region: HR 1.10, 95% CI 1.06-1.14, p=0.005). We found that the progression of functional decline accelerates in regions involved later during disease course. Our findings can be useful in patient management and prognosis prediction.