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Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis

Authors :
Signori, A
Izquierdo, G
Lugaresi, A
Hupperts, R
Grand'Maison, F
Sola, P
Horakova, D
Havrdova, E
Prat, A
Girard, M
Duquette, P
Boz, C
Grammond, P
Terzi, M
Singhal, B
Alroughani, R
Petersen, T
Ramo, C
Oreja-Guevara, C
Spitaleri, D
Shaygannejad, V
Butzkueven, H
Kalincik, T
Jokubaitis, V
Slee, M
Fernandez Bolanos, R
Luis Sanchez-Menoyo, J
Pucci, E
Granella, F
Lechner-Scott, J
Iuliano, G
Hughes, S
Bergamaschi, R
Taylor, B
Verheul, F
Rio, ME
Amato, MP
Sajedi, SA
Majdinasab, N
Van Pesch, V
Sormani, MP
Trojano, M
Signori, A
Izquierdo, G
Lugaresi, A
Hupperts, R
Grand'Maison, F
Sola, P
Horakova, D
Havrdova, E
Prat, A
Girard, M
Duquette, P
Boz, C
Grammond, P
Terzi, M
Singhal, B
Alroughani, R
Petersen, T
Ramo, C
Oreja-Guevara, C
Spitaleri, D
Shaygannejad, V
Butzkueven, H
Kalincik, T
Jokubaitis, V
Slee, M
Fernandez Bolanos, R
Luis Sanchez-Menoyo, J
Pucci, E
Granella, F
Lechner-Scott, J
Iuliano, G
Hughes, S
Bergamaschi, R
Taylor, B
Verheul, F
Rio, ME
Amato, MP
Sajedi, SA
Majdinasab, N
Van Pesch, V
Sormani, MP
Trojano, M
Publication Year :
2018

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.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1315674966
Document Type :
Electronic Resource