Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis. (April 2018)

• Record Type: Journal Article
• Authors: Signori, Alessio; Izquierdo, Guillermo; Lugaresi, Alessandra; Hupperts, Raymond; Grand'Maison, Francois; Sola, Patrizia; Horakova, Dana; Havrdova, Eva; Prat, Alexandre; Girard, Marc; Duquette, Pierre; Boz, Cavit; Grammond, Pierre; Terzi, Murat; Singhal, Bhim; Alroughani, Raed; Petersen, Thor; Ramo, Cristina; Oreja-Guevara, Celia; Spitaleri, Daniele; Shaygannejad, Vahid; Butzkueven, Helmut; Kalincik, Tomas; Jokubaitis, Vilija; Slee, Mark; Fernandez Bolaños, Ricardo; Sanchez-Menoyo, Jose Luis; Pucci, Eugenio; Granella, Franco; Lechner-Scott, Jeannette; Iuliano, Gerardo; Hughes, Stella; Bergamaschi, Roberto; Taylor, Bruce; Verheul, Freek; Edite Rio, Maria; Amato, Maria Pia; Sajedi, Seyed Aidin; Majdinasab, Nastaran; Van Pesch, Vincent; Sormani, Maria Pia; Trojano, Maria;
• Is Part Of: Multiple sclerosis. Volume 24:Number 5(2018)
• Page Start: 642
• Page End: 652
• Publication Date: 2018-04
• Subjects: Primary progressive multiple sclerosis -- disability -- long-term -- trajectories -- clinical trials -- heterogeneity; Central nervous system -- Diseases -- Periodicals; Myelin sheath -- Diseases -- Periodicals; Inflammation -- Periodicals; Multiple sclerosis -- Periodicals; Central Nervous System Diseases -- Periodicals; Demyelinating Diseases -- Periodicals; Inflammation -- Periodicals; Multiple Sclerosis -- Periodicals; Système nerveux central -- Maladies -- Périodiques; Gaine de myéline -- Maladies -- Périodiques; Inflammation (Pathologie) -- Périodiques; Sclérose en plaques -- Périodiques; Electronic journals; 616.834005
• DOI: 10.1177/1352458517703800
• Languages: English
• ISSNs: 1352-4585

Abstract

Background: Several natural history studies on primary progressive multiple sclerosis (PPMS) patients detected a consistent heterogeneity in the rate of disability accumulation. Objectives: To identify subgroups of PPMS patients with similar longitudinal trajectories of Expanded Disability Status Scale (EDSS) over time. Methods: All PPMS patients collected within the MSBase registry, who had their first EDSS assessment within 5 years from onset, were included in the analysis. Longitudinal EDSS scores were modeled by a latent class mixed model (LCMM), using a nonlinear function of time from onset. LCMM is an advanced statistical approach that models heterogeneity between patients by classifying them into unobserved groups showing similar characteristics. Results: A total of 853 PPMS (51.7% females) from 24 countries with a mean age at onset of 42.4 years (standard deviation (SD): 10.8 years), a median baseline EDSS of 4 (interquartile range (IQR): 2.5–5.5), and 2.4 years of disease duration (SD: 1.5 years) were included. LCMM detected three different subgroups of patients with a mild ( n = 143; 16.8%), moderate ( n = 378; 44.3%), or severe ( n = 332; 38.9%) disability trajectory. The probability of reaching EDSS 6 at 10 years was 0%, 46.4%, and 81.9% respectively. Conclusion: Applying an LCMM modeling approach to long-term EDSS data, it is possible to identify groups of PPMS patients with different prognosis.