A data-driven model of disability progression in progressive multiple sclerosis
This study applies the Gaussian process progression model, a Bayesian data-driven disease progression model, to analyse the evolution of primary progressive multiple sclerosis. Utilizing data from 1521 primary progressive multiple sclerosis participants collected within the International Progressive Multiple Sclerosis Alliance Project, the analysis includes 18 581 longitudinal time-points (average follow-up time: 28.2 months) of disability assessments including the expanded disability status scale, symbol digit modalities, timed 25-foot-walk, 9-hole-peg test and of MRI metrics such as T1 and T2 lesion volume and normalized brain volume. From these data, Gaussian process progression model infers a data-driven description of the progression common to all individuals, alongside scores measuring the individual progression rates relative to the population, spanning ∼50 years of disease duration. Along this timeline, Gaussian process progression model identifies an initial steep worsening of the expanded disability status scale that stabilizes after ∼30 years of disease duration, suggesting its diminished utility in monitoring disease progression beyond this time. Conversely, it underscores the slower evolution of normalized brain volume across the disease duration. The individual progression rates estimated by Gaussian process progression model can be used to identify three distinct sub-groups within the primary progressive multiple sclerosis population: a normative group (76% of the population) and two 'outlier' sub-groups displaying either accelerated (13% of the population) or decelerated (11%) progression compared to the normative one. Notably, fast progressors exhibit older age at symptom onset (38.5 versus 35.0, <i>P</i> < 0.0001), a higher prevalence of males (61.1% versus 48.5%, <i>P</i> = 0.013) and a higher lesion volumes both in T1 (4.1 versus 0.6, <i>P</i> < 0.0001) and T2 (16.5 versus 7.9, <i>P</i> < 0.0001) compared to slow progressors. Prognostically, fast progressors demonstrate a significantly worse prognosis, with double the risk of experiencing a 3-month confirmed disease progression on expanded disability status scale compared to the normative population according to Cox proportional hazard modelling (HR = 2.09, 95% CI: 1.66-2.62, <i>P</i> < 0.0001) and a shorter median time from the onset of disease symptoms to reaching a confirmed expanded disability status scale 6 (95% CI: 5.83-7.68 years, <i>P</i> < 0.0001). External validation on a test set comprising 227 primary progressive multiple sclerosis participants from the SPI2 trial produced consistent results, with slow progressors exhibiting a reduced risk of experiencing 3-month confirmed disease progression determined through expanded disability status scale (HR = 0.21), while fast progressors facing an increased risk (HR = 1.45). This study contributes to our understanding of disability accrual in primary progressive multiple sclerosis, integrating diverse disability assessments and MRI measurements. Moreover, the identification of distinct sub-groups underscores the heterogeneity in progression rates among patients, offering invaluable insights for patient stratification and monitoring in clinical trials, potentially facilitating more targeted and personalized interventions.
Authors
- Francesca Bovis (ORCID: https://orcid.org/0000-0002-3823-4000)
- Bruce Cree (ORCID: https://orcid.org/0000-0001-7689-2533)
- Carmen Tur (ORCID: https://orcid.org/0000-0003-1849-3184)
- Sara Garbarino (ORCID: https://orcid.org/0000-0002-3583-3630)
- Antonio Uccelli (ORCID: https://orcid.org/0000-0002-2008-6038)
- Maria Pia Sormani (ORCID: https://orcid.org/0000-0001-6892-104X)
- Marco Lorenzi (ORCID: https://orcid.org/0000-0003-0521-2881)
- Douglas Lorne Arnold (ORCID: https://orcid.org/0000-0003-4266-0106)
- Matteo Pardini (ORCID: https://orcid.org/0000-0002-4740-1982)
- Michele Piana (ORCID: https://orcid.org/0000-0003-1700-991X)
Institutions
- Universitat Autònoma de Barcelona (ES)
- Institut national de recherche en sciences et technologies du numérique (FR)
- University of California, San Francisco (US)
- Université Côte d'Azur (FR)
- Ospedale Policlinico San Martino (IT)
- McGill University (CA)
- University of Genoa (IT)
Publication Details
- Journal
- Brain Communications
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1093/braincomms/fcae434
- Citations
- 3
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.27
Funders
- National Multiple Sclerosis Society
- Biogen
- Teva Pharmaceutical Industries
- Istituto Nazionale di Alta Matematica "Francesco Severi"
- International Progressive MS Alliance
- Ministero della Salute
- Ministerio de Ciencia e Innovación
- MedDay Pharmaceuticals
- Genentech
- Gruppo Nazionale per il Calcolo Scientifico
- Instituto de Salud Carlos III