Amyotrophic lateral sclerosis disease progression model

• Published in: Amyotrophic lateral sclerosis and frontotemporal degeneration Vol. 15; no. 1-2; pp. 119 - 129
• Main Authors: Gomeni, Roberto, Fava, Maurizio
• Format: Journal Article
• Language: English
• Published: England Informa Healthcare 01.03.2014; Taylor & Francis
• Subjects: Adolescent; Adult; Aged; ALS; Amyotrophic Lateral Sclerosis - epidemiology; Amyotrophic Lateral Sclerosis - physiopathology; cluster analysis; Databases, Factual - statistics & numerical data; Disease Progression; disease progression model; Female; Humans; Longitudinal Studies; Male; Middle Aged; Models, Statistical; placebo response; Predictive Value of Tests; Software; Young Adult
• ISSN: 2167-8421; 2167-9223
• DOI: 10.3109/21678421.2013.838970

Abstract Our objective was to develop: 1) a longitudinal model to describe amyotrophic lateral sclerosis (ALS) disease progression using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R); and 2) a probabilistic model to estimate the presence of clusters of trajectories in ALS progression over 12 months of treatment. Three hundred and thirty-eight patients treated with placebo from the PRO-ACT database were included in the analyses. A non-linear Weibull model best described the ALS disease progression, and a stepwise logistic regression approach was used to select the variables predicting a slow or fast disease progression. Results identified two clusters of trajectories: 1) slow disease progressors (46% of patients with a change from baseline of 13%); 2) fast disease progressors (54% of patients with a change from baseline of 49%). ROC curve analysis estimated the optimal cut-off for classifying patients as slow or fast disease progressors given ALSFRS-R measurements at 2-4 weeks. Results showed that the degree of ALS disease progression quantified by the ALSFRS-R symptomatic change on placebo is highly heterogeneous. In conclusion, this finding indicates the potential interest of disease progression models for implementing a population enrichment strategy to control the level of heterogeneity in the patients included in new trials.