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

Author:

Signori Alessio1,Izquierdo Guillermo2,Lugaresi Alessandra3,Hupperts Raymond4,Grand’Maison Francois5,Sola Patrizia6,Horakova Dana7,Havrdova Eva7,Prat Alexandre8,Girard Marc8,Duquette Pierre8,Boz Cavit9,Grammond Pierre10,Terzi Murat11,Singhal Bhim12,Alroughani Raed13,Petersen Thor14,Ramo Cristina15,Oreja-Guevara Celia16,Spitaleri Daniele17,Shaygannejad Vahid18,Butzkueven Helmut19,Kalincik Tomas20,Jokubaitis Vilija20,Slee Mark21,Fernandez Bolaños Ricardo22,Sanchez-Menoyo Jose Luis23,Pucci Eugenio24,Granella Franco25,Lechner-Scott Jeannette26,Iuliano Gerardo27,Hughes Stella28,Bergamaschi Roberto29,Taylor Bruce30,Verheul Freek31,Edite Rio Maria32,Amato Maria Pia33,Sajedi Seyed Aidin34,Majdinasab Nastaran35,Van Pesch Vincent36,Sormani Maria Pia1,Trojano Maria37

Affiliation:

1. Department of Health Sciences (DISSAL), Section of Biostatistics, University of Genoa, Genova, Italy

2. Hospital Universitario Virgen Macarena, Sevilla, Spain

3. Department of Biomedical and Neuromotor Sciences(DIBINEM), Alma Mater Studiorum, University of Bologna, Italy/IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy

4. Zuyderland Ziekenhuis, Sittard, The Netherlands

5. Clinique Neuro Rive-Sud, Greenfield Park, QC, Canada

6. Nuovo Ospedale Civile S. Agostino-Estense, Modena, Italy

7. Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic

8. Hôpital Notre-Dame, Montreal, QC, Canada

9. KTU Medical Faculty Farabi Hospital, Trabzon, Turkey

10. Centre de Réadaptation En Déficience Physique Chaudière-Appalache, Levis, QC, Canada

11. Medical Faculty, Ondokuz Mayis University, Samsun, Turkey

12. Bombay Hospital Institute of Medical Sciences (BHIMS), Mumbai, India

13. Amiri Hospital, Kuwait City, Kuwait

14. Kommunehospitalet, Aarhus, Denmark

15. Hospital Germans Trias i Pujol, Badalona, Spain

16. Hospital Clinico San Carlos, Madrid, Spain

17. Azienda Ospedaliera di Rilievo Nazionale, San Giuseppe Moscati, Avellino, Italy

18. Isfahan University of Medical Sciences, Isfahan, Iran

19. Box Hill Hospital, Melbourne, VIC, Australia/Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia

20. Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia

21. Flinders University and Medical Centre, Adelaide, SA, Australia

22. Hospital Universitario Virgen de Valme, Seville, Spain

23. Hospital de Galdakao-Usansolo, Galdakao, Spain

24. UOC Neurologia, Azienda Sanitaria Unica Regionale Marche, Macerata, Italy

25. University of Parma, Parma, Italy

26. Hunter Medical Research Institute, The University of Newcastle, Newcastle, NSW, Australia

27. Ospedali Riuniti di Salerno, Salerno, Italy

28. Craigavon Area Hospital, Craigavon, UK

29. C. Mondino National Neurological Institute, Pavia, Italy

30. Royal Hobart Hospital, Hobart, TAS, Australia

31. Groene Hart Ziekenhuis, Gouda, The Netherlands

32. Hospital São João, Porto, Portugal

33. Department NEUROFARBA, Section Neuroscience, University of Florence, Florence, Italy

34. Department of Neurology, Golestan University of Medical Sciences, Gorgan, Iran/Golestan Hospital, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

35. Golestan Hospital, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

36. Cliniques Universitaires Saint-Luc, Brussels, Belgium

37. Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari, Bari, Italy

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.

Funder

MSBase Fellowship 2015

Publisher

SAGE Publications

Subject

Neurology (clinical),Neurology

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