BACKGROUND AND PURPOSE: We sought to identify predictive clinical factors of disability during initial course in multiple sclerosis (MS) patients. METHODS: A total of 2871 MS patients from the LORSEP (Lorraine Multiple Sclerosis) population-based cohort were analyzed. The relationships between baseline demographic, clinical predictors and time to assignment of Expanded Disability Status Scale (EDSS) scores of 3, 4 and 6 were assessed using a Cox regression model. RESULTS: Multivariate analysis showed that, for relapsing-remitting patients, a shorter time to assignment of an EDSS score of 4 was associated with an older age of onset of MS and incomplete recovery from the first relapse. Median times were not influenced by gender or the time between the first two relapses. The results also demonstrated that MS progression is independent of the initial clinical data once an EDSS score of 4 is reached rather than a score of 3 because the time from EDSS 3 to assignment of EDSS 4 were correlated with predicting variables. The data were very different for the time between assignment of scores of 4 and 6 because the median times were not influenced by any of the predicting variables.
BACKGROUND AND PURPOSE: We sought to identify predictive clinical factors of disability during initial course in multiple sclerosis (MS) patients. METHODS: A total of 2871 MSpatients from the LORSEP (Lorraine Multiple Sclerosis) population-based cohort were analyzed. The relationships between baseline demographic, clinical predictors and time to assignment of Expanded Disability Status Scale (EDSS) scores of 3, 4 and 6 were assessed using a Cox regression model. RESULTS: Multivariate analysis showed that, for relapsing-remitting patients, a shorter time to assignment of an EDSS score of 4 was associated with an older age of onset of MS and incomplete recovery from the first relapse. Median times were not influenced by gender or the time between the first two relapses. The results also demonstrated that MS progression is independent of the initial clinical data once an EDSS score of 4 is reached rather than a score of 3 because the time from EDSS 3 to assignment of EDSS 4 were correlated with predicting variables. The data were very different for the time between assignment of scores of 4 and 6 because the median times were not influenced by any of the predicting variables.
Authors: M Mateo Paz Soldán; Martina Novotna; Nuhad Abou Zeid; Nilufer Kale; Melih Tutuncu; Daniel J Crusan; Elizabeth J Atkinson; Aksel Siva; B Mark Keegan; Istvan Pirko; Sean J Pittock; Claudia F Lucchinetti; Brian G Weinshenker; Moses Rodriguez; Orhun H Kantarci Journal: Neurology Date: 2014-11-14 Impact factor: 9.910
Authors: Simon Gamraoui; Guillaume Mathey; Marc Debouverie; Catherine Malaplate; René Anxionnat; Francis Guillemin; Jonathan Epstein Journal: J Neurol Date: 2019-02-01 Impact factor: 4.849
Authors: Gil Benedek; Roberto Meza-Romero; Kelley Jordan; Ying Zhang; Ha Nguyen; Gail Kent; Jia Li; Edwin Siu; Jenny Frazer; Marta Piecychna; Xin Du; Antoine Sreih; Lin Leng; Jack Wiedrick; Stacy J Caillier; Halina Offner; Jorge R Oksenberg; Vijayshree Yadav; Dennis Bourdette; Richard Bucala; Arthur A Vandenbark Journal: Proc Natl Acad Sci U S A Date: 2017-09-18 Impact factor: 11.205
Authors: W Oliver Tobin; Chiara Costanzi; Yong Guo; Joseph E Parisi; Stephen D Weigand; Claudia F Lucchinetti Journal: Mult Scler Date: 2016-10-19 Impact factor: 6.312
Authors: Ilya Kister; Eric Chamot; Amber R Salter; Gary R Cutter; Tamar E Bacon; Joseph Herbert Journal: Neurology Date: 2013-02-20 Impact factor: 9.910