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Fox Foundation for Parkinson\u2019s Research","award":["MJFF-021683"],"award-info":[{"award-number":["MJFF-021683"]}]},{"name":"Biostatistic\/Informatics Junior Faculty","award":["BI-2107-38160"],"award-info":[{"award-number":["BI-2107-38160"]}]},{"DOI":"10.13039\/100000890","name":"National Multiple Sclerosis Society","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000890","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>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 \u223c50 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 \u223c30 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 \u2018outlier\u2019 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, P &amp;lt; 0.0001), a higher prevalence of males (61.1% versus 48.5%, P = 0.013) and a higher lesion volumes both in T1 (4.1 versus 0.6, P &amp;lt; 0.0001) and T2 (16.5 versus 7.9, P &amp;lt; 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\u20132.62, P &amp;lt; 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\u20137.68 years, P &amp;lt; 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.<\/jats:p>","DOI":"10.1093\/braincomms\/fcae434","type":"journal-article","created":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T18:26:36Z","timestamp":1734200796000},"source":"Crossref","is-referenced-by-count":5,"title":["A data-driven model of disability progression in progressive multiple sclerosis"],"prefix":"10.1093","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3583-3630","authenticated-orcid":false,"given":"Sara","family":"Garbarino","sequence":"first","affiliation":[{"name":"Life Science Computational laboratory, IRCCS Ospedale Policlinico San Martino , 16132 Genoa ,","place":["Italy"]},{"name":"MIDA, Dipartimento di Matematica, Universit\u00e0 di Genova , 16146 Genoa 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Ospedale Policlinico San Martino , 16132 Genoa ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michele","family":"Piana","sequence":"additional","affiliation":[{"name":"Life Science Computational laboratory, IRCCS Ospedale Policlinico San Martino , 16132 Genoa ,","place":["Italy"]},{"name":"MIDA, Dipartimento di Matematica, Universit\u00e0 di Genova , 16146 Genoa ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2008-6038","authenticated-orcid":false,"given":"Antonio","family":"Uccelli","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Universit\u00e0 di Genova , 16132 Genoa ,","place":["Italy"]},{"name":"IRCCS Ospedale Policlinico San Martino , 16132 Genoa ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Douglas L","family":"Arnold","sequence":"additional","affiliation":[{"name":"McGill University , H3A0G4 Montr\u00e9al ,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce A C","family":"Cree","sequence":"additional","affiliation":[{"name":"UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco , 94143 San Francisco ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria Pia","family":"Sormani","sequence":"additional","affiliation":[{"name":"IRCCS Ospedale Policlinico San Martino , 16132 Genoa ,","place":["Italy"]},{"name":"Department of Health Sciences (DISSAL), Universit\u00e0 di Genova , 16132 Genoa ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Bovis","sequence":"additional","affiliation":[{"name":"Department of Health Sciences (DISSAL), Universit\u00e0 di Genova , 16132 Genoa 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