Rate and Shape of Functional Decline in Amyotrophic Lateral Sclerosis Identify Clinically Distinct Amyotrophic Lateral Sclerosis Phenotypes
Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: The ALS Functional Rating Scale-Revised decline rate compresses trajectory shape into a single number, potentially missing distinct phenotypes. We tested whether shape identifies phenotypes that rate does not distinguish, and whether post-hoc analysis recovers a hidden ultrarapid subgroup. METHODS: From the Piemonte and Valle d'Aosta register (2000-2022), we applied 2 models to 1,686 amyotrophic lateral sclerosis patients: a Gaussian mixture model (GMM; rate axis) and a latent-class mixed model (LCMM) with cubic splines (shape axis). Concordance, prognostic performance, calibration, and clinical utility were assessed at 24 months. External validation used the Emilia-Romagna register. RESULTS: The rate model identified 4 classes (GMM-Slow 31%, GMM-Inter-slow 46%, GMM-Inter-fast 17%, GMM-Catastrophic 6%; slopes -0.44 to -3.52 points/month); the shape model 4 (LCMM-SlowLinear 46%, LCMM-PlateauFall 23%, LCMM-LateDecline 15%, LCMM-RapidEarly 16%). Concordance was modest (kappa = 0.273). Adding shape to rate changed discrimination negligibly (C-index 0.761 vs 0.755), but separated subgroups within rate classes (within GMM-Catastrophic, 30.1 vs 12.0 months). LCMM-LateDecline combined moderate early decline with reduced respiratory reserve (median forced vital capacity 83.5%) and 22.7-month median survival. The combined model gave the greatest net benefit for the composite outcome. Of 945 patients excluded for sparse sampling, 367 were ultrarapid progressors with shorter survival than LCMM-RapidEarly; findings replicated in the Emilia-Romagna register. INTERPRETATION: Rate and shape describe partially overlapping aspects of the disease. LCMM-LateDecline, with moderate early decline yet occult respiratory compromise, is clinically challenging, and the 3-visit criterion hides over half of ultrarapid patients. Rate predicts the overall burden of progression, whereas shape predicts the timing of deterioration. ANN NEUROL 2026.
Source: Annals of Neurology
DOI: 10.1002/ana.78394
Authors: Andrea Calvo, Cristina Moglia, Antonio Canosa, Umberto Manera, Elisabetta Zucchi, Giulia Gianferrari, Ilaria Martinelli, Gabriele Mora, Sara Cabras, Francesca Palumbo, Enrico Matteoni, Giorgio Pellegrino, Emilio Minerva, Daniela Pascariu, Stefano Callegaro, Fabrizio D'Ovidio, Rosario Vasta, Letizia Mazzini, Fabiola De Marchi, Jessica Mandrioli, Adriano Chiò
Institutions: Azienda Ospedaliera Citta' della Salute e della Scienza di Torino, University of Turin, Azienda Ospedaliero-Universitaria di Modena, University of Modena and Reggio Emilia, Università degli Studi del Piemonte Orientale “Amedeo Avogadro”, Azienda Ospedaliero Universitaria Maggiore della Carita
Language: English
Subfield: Clinical Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,700
Awards: G1707306367, G2903992827, G5415030073, BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis, HetERogeneous sEmantic Data integratIon for the guT-bRain interplaY, European multidisciplinary ALS network identification to cure motor neuron degeneration
OpenAlex ID: W7223940320
