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

Alessio Signori; Guillermo Izquierdo; Alessandra Lugaresi; Raymond Hupperts; Francois Grand'Maison; Patrizia Sola; Dana Horakova; Eva Havrdova; Alexandre Prat; Marc Girard; Pierre Duquette; Cavit Boz; Pierre Grammond; Murat Terzi; Bhim Singhal; Raed Alroughani; Thor Petersen; Cristina Ramo; Celia Oreja-Guevara; Daniele Spitaleri; Vahid Shaygannejad; Helmut Butzkueven; Tomas Kalincik; Vilija Jokubaitis; Mark Slee; Ricardo Fernandez-Bolaños; Jose Luis Sanchez-Menoyo; Eugenio Pucci; Franco Granella; Jeannette Lechner-Scott; Gerardo Iuliano; Stella E. Hughes; Roberto Bergamaschi; Bruce Taylor; Freek Verheul; Maria Edite Rio; Maria Pia Amato; Seyed Aidin Sajedi; Nastaran Majdinasab; Vincent Van Pesch; Maria Pia Sormani; Maria Trojano

doi:10.1177/1352458517703800

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

Alessio Signori, Guillermo Izquierdo, Alessandra Lugaresi, Raymond Hupperts, Francois Grand'Maison, Patrizia Sola, Dana Horakova, Eva Havrdova, Alexandre Prat, Marc Girard, Pierre Duquette, Cavit Boz, Pierre Grammond, Murat Terzi, Bhim Singhal, Raed Alroughani, Thor Petersen, Cristina Ramo, Celia Oreja-Guevara, Daniele SpitaleriVahid Shaygannejad, Helmut Butzkueven, Tomas Kalincik, Vilija Jokubaitis, Mark Slee, Ricardo Fernandez-Bolaños, Jose Luis Sanchez-Menoyo, Eugenio Pucci, Franco Granella, Jeannette Lechner-Scott, Gerardo Iuliano, Stella E. Hughes, Roberto Bergamaschi, Bruce Taylor, Freek Verheul, Maria Edite Rio, Maria Pia Amato, Seyed Aidin Sajedi, Nastaran Majdinasab, Vincent Van Pesch, Maria Pia Sormani, Maria Trojano

Istituto Scienze Neurologiche

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	1352458517703800
Journal	Multiple Sclerosis
DOIs	https://doi.org/10.1177/1352458517703800
Publication status	E-pub ahead of print - Apr 1 2017

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Journal Article

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10.1177/1352458517703800

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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., ... Trojano, M. (2017). Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis. Multiple Sclerosis, 1352458517703800. https://doi.org/10.1177/1352458517703800

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-Bolaños, R, Sanchez-Menoyo, JL, Pucci, E, Granella, F, Lechner-Scott, J, Iuliano, G, Hughes, SE, Bergamaschi, R, Taylor, B, Verheul, F, Edite Rio, M, Amato, MP, Sajedi, SA, Majdinasab, N, Pesch, VV, Sormani, MP & Trojano, M 2017, 'Long-term disability trajectories in primary progressive MS patients: A latent class growth analysis', Multiple Sclerosis, pp. 1352458517703800. https://doi.org/10.1177/1352458517703800

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

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.",

keywords = "Journal Article",

author = "Alessio Signori and Guillermo Izquierdo and Alessandra Lugaresi and Raymond Hupperts and Francois Grand'Maison and Patrizia Sola and Dana Horakova and Eva Havrdova and Alexandre Prat and Marc Girard and Pierre Duquette and Cavit Boz and Pierre Grammond and Murat Terzi and Bhim Singhal and Raed Alroughani and Thor Petersen and Cristina Ramo and Celia Oreja-Guevara and Daniele Spitaleri and Vahid Shaygannejad and Helmut Butzkueven and Tomas Kalincik and Vilija Jokubaitis and Mark Slee and Ricardo Fernandez-Bola{\~n}os and Sanchez-Menoyo, {Jose Luis} and Eugenio Pucci and Franco Granella and Jeannette Lechner-Scott and Gerardo Iuliano and Hughes, {Stella E.} and Roberto Bergamaschi and Bruce Taylor and Freek Verheul and {Edite Rio}, Maria and Amato, {Maria Pia} and Sajedi, {Seyed Aidin} and Nastaran Majdinasab and Pesch, {Vincent Van} and Sormani, {Maria Pia} and Maria Trojano",

note = "Ricercatore distaccato presso IRCCS a seguito Convenzione esclusiva con Universit{\`a} di Bologna (Lugaresi Alessandra). La Prof.ssa Alessandra Lugaresi viene da altro Istituto e lavori con affiliazioni diverse usciranno ancora nei prossimi anni. ",

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doi = "10.1177/1352458517703800",

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journal = "Multiple Sclerosis",

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TY - JOUR

T1 - Long-term disability trajectories in primary progressive MS patients

T2 - A latent class growth analysis

AU - Signori, Alessio

AU - Izquierdo, Guillermo

AU - Lugaresi, Alessandra

AU - Hupperts, Raymond

AU - Grand'Maison, Francois

AU - Sola, Patrizia

AU - Horakova, Dana

AU - Havrdova, Eva

AU - Prat, Alexandre

AU - Girard, Marc

AU - Duquette, Pierre

AU - Boz, Cavit

AU - Grammond, Pierre

AU - Terzi, Murat

AU - Singhal, Bhim

AU - Alroughani, Raed

AU - Petersen, Thor

AU - Ramo, Cristina

AU - Oreja-Guevara, Celia

AU - Spitaleri, Daniele

AU - Shaygannejad, Vahid

AU - Butzkueven, Helmut

AU - Kalincik, Tomas

AU - Jokubaitis, Vilija

AU - Slee, Mark

AU - Fernandez-Bolaños, Ricardo

AU - Sanchez-Menoyo, Jose Luis

AU - Pucci, Eugenio

AU - Granella, Franco

AU - Lechner-Scott, Jeannette

AU - Iuliano, Gerardo

AU - Hughes, Stella E.

AU - Bergamaschi, Roberto

AU - Taylor, Bruce

AU - Verheul, Freek

AU - Edite Rio, Maria

AU - Amato, Maria Pia

AU - Sajedi, Seyed Aidin

AU - Majdinasab, Nastaran

AU - Pesch, Vincent Van

AU - Sormani, Maria Pia

AU - Trojano, Maria

N1 - Ricercatore distaccato presso IRCCS a seguito Convenzione esclusiva con Università di Bologna (Lugaresi Alessandra). La Prof.ssa Alessandra Lugaresi viene da altro Istituto e lavori con affiliazioni diverse usciranno ancora nei prossimi anni.

PY - 2017/4/1

Y1 - 2017/4/1

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1177/1352458517703800

DO - 10.1177/1352458517703800

M3 - Article

C2 - 28382837

SN - 1352-4585

SP - 1352458517703800

JO - Multiple Sclerosis

JF - Multiple Sclerosis

ER -

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

Abstract

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