Multiple Sclerosis Severity Score (MSSS) improves the accuracy of individualized prediction in MS
Jazyk angličtina Země Velká Británie, Anglie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
- Klíčová slova
- Multiple Sclerosis Severity Score (MSSS), Multiple sclerosis, prognostics, relapse prediction,
- MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- posuzování pracovní neschopnosti MeSH
- progrese nemoci MeSH
- prospektivní studie MeSH
- recidiva MeSH
- roztroušená skleróza * diagnóza MeSH
- stupeň závažnosti nemoci MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: The MSBase prediction model of treatment response leverages multiple demographic and clinical characteristics to estimate hazards of relapses, confirmed disability accumulation (CDA), and confirmed disability improvement (CDI). The model did not include Multiple Sclerosis Severity Score (MSSS), a disease duration-adjusted ranked score of disability. OBJECTIVE: To incorporate MSSS into the MSBase prediction model and compare model accuracy with and without MSSS. METHODS: The associations between MSSS and relapse, CDA, and CDI were evaluated with marginal proportional hazards models adjusted for three principal components representative of patients' demographic and clinical characteristics. The model fit with and without MSSS was assessed with penalized r2 and Harrell C. RESULTS: A total of 5866 MS patients were started on disease-modifying therapy during prospective follow-up (age 38.4 ± 10.6 years; 72% female; disease duration 8.5 ± 7.7 years). Including MSSS into the model improved the accuracy of individual prediction of relapses by 31%, of CDA by 23%, and of CDI by 24% (Harrell C) and increased the amount of variance explained for relapses by 49%, for CDI by 11%, and for CDA by 10% as compared with the original model. CONCLUSION: Addition of a single, readily available metric, MSSS, to the comprehensive MSBase prediction model considerably improved the individual accuracy of prognostics in MS.
Azienda Ospedaliera di Rilievo Nazionale San Giuseppe Moscati Avellino Avellino Italy
Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases Istanbul Turkey
Central Clinical School Monash University Melbourne VIC Australia
CISSS Chaudi're Appalache Levis QC Canada
Cliniques Universitaires Saint Luc UCLouvain Brussels Belgium
CSSS Saint Jérôme Saint Jerome QC Canada
Department of Biostatistics UAB School of Public Health Birmingham AL USA
Department of Medicine and Surgery University of Parma Parma Italy
Department of Neurology Charles University Prague Prague Czech Republic
Department of Neuroscience Imaging and Clinical Sciences University G d'Annunzio Chieti Italy
Division of Neurology Department of Medicine Amiri Hospital Sharq Kuwait
Dokuz Eylul University Izmir Turkey
GF Ingrassia Department University of Catania Catania Italy
Haydarpasa Numune Training and Research Hospital Istanbul Turkey
Hospital S João Porto Portugal; University Fernando Pessoa Porto Portugal
Hospital Universitario Virgen Macarena Sevilla Spain
IRCCS Mondino Foundation Pavia Italy
Isfahan University of Medical Sciences Isfahan Islamic Republic of Iran
KTU Medical Faculty Farabi Hospital Trabzon Turkey
Medical Faculty 19 Mayis University Samsun Turkey
Nemocnice Jihlava Jihlava Czech Republic
Neuro Rive Sud Greenfield Park QC Canada
Neurology NYU School of Medicine New York NY USA
Neurology Unit Department of Neuroscience Azienda Ospedaliera Universitaria Modena Italy
Neurology Unit Piazza S Maria di Gesù 5 Catania Italy
Ospedali Riuniti di Salerno Salerno Italy
School of Medicine and Public Health The University of Newcastle Newcastle NSW Australia
Universite de Montreal and CHUM Montreal QC Canada
UOC Neurologia Azienda Sanitaria Unica Regionale Marche AV3 Macerata Italy
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