Literature DB >> 15824338

Multiple Sclerosis Severity Score: using disability and disease duration to rate disease severity.

R H S R Roxburgh1, S R Seaman, T Masterman, A E Hensiek, S J Sawcer, S Vukusic, I Achiti, C Confavreux, M Coustans, E le Page, G Edan, G V McDonnell, S Hawkins, M Trojano, M Liguori, E Cocco, M G Marrosu, F Tesser, M A Leone, A Weber, F Zipp, B Miterski, J T Epplen, A Oturai, P Soelberg Sørensen, E G Celius, N Téllez Lara, X Montalban, P Villoslada, A M Silva, M Marta, I Leite, B Dubois, J Rubio, H Butzkueven, T Kilpatrick, M P Mycko, K W Selmaj, M E Rio, M Sá, G Salemi, G Savettieri, J Hillert, D A S Compston.   

Abstract

BACKGROUND: There is no consensus method for determining progression of disability in patients with multiple sclerosis (MS) when each patient has had only a single assessment in the course of the disease.
METHODS: Using data from two large longitudinal databases, the authors tested whether cross-sectional disability assessments are representative of disease severity as a whole. An algorithm, the Multiple Sclerosis Severity Score (MSSS), which relates scores on the Expanded Disability Status Scale (EDSS) to the distribution of disability in patients with comparable disease durations, was devised and then applied to a collection of 9,892 patients from 11 countries to create the Global MSSS. In order to compare different methods of detecting such effects the authors simulated the effects of a genetic factor on disability.
RESULTS: Cross-sectional EDSS measurements made after the first year were representative of overall disease severity. The MSSS was more powerful than the other methods the authors tested for detecting different rates of disease progression.
CONCLUSION: The Multiple Sclerosis Severity Score (MSSS) is a powerful method for comparing disease progression using single assessment data. The Global MSSS can be used as a reference table for future disability comparisons. While useful for comparing groups of patients, disease fluctuation precludes its use as a predictor of future disability in an individual.

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Year:  2005        PMID: 15824338     DOI: 10.1212/01.WNL.0000156155.19270.F8

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  239 in total

1.  Custom CGH array profiling of copy number variations (CNVs) on chromosome 6p21.32 (HLA locus) in patients with venous malformations associated with multiple sclerosis.

Authors:  Alessandra Ferlini; Matteo Bovolenta; Marcella Neri; Francesca Gualandi; Alessandra Balboni; Anton Yuryev; Fabrizio Salvi; Donato Gemmati; Alberto Liboni; Paolo Zamboni
Journal:  BMC Med Genet       Date:  2010-04-28       Impact factor: 2.103

2.  Rationing and deprivation: disease-modifying therapies for multiple sclerosis in the United Kingdom.

Authors:  Trudy Owens; Nikos Evangelou; David K Whynes
Journal:  Eur J Health Econ       Date:  2012-01-24

3.  Identifying patient subtypes in multiple sclerosis and tailoring immunotherapy: challenges for the future.

Authors:  Philip L De Jager
Journal:  Ther Adv Neurol Disord       Date:  2009-11       Impact factor: 6.570

4.  Progression of non-age-related callosal brain atrophy in multiple sclerosis: a 9-year longitudinal MRI study representing four decades of disease development.

Authors:  Juha Martola; Leszek Stawiarz; Sten Fredrikson; Jan Hillert; Jakob Bergström; Olof Flodmark; Maria Kristoffersen Wiberg
Journal:  J Neurol Neurosurg Psychiatry       Date:  2006-11-21       Impact factor: 10.154

5.  Does long-term partial sodium channel blockade alter disease progression in MS? Evidence from a retrospective study.

Authors:  T J Counihan; J A Duignan; G Gormley; S Saidha; C Dooley; J Newell
Journal:  Ir J Med Sci       Date:  2013-11-28       Impact factor: 1.568

6.  Effect of Nonmyeloablative Hematopoietic Stem Cell Transplantation vs Continued Disease-Modifying Therapy on Disease Progression in Patients With Relapsing-Remitting Multiple Sclerosis: A Randomized Clinical Trial.

Authors:  Richard K Burt; Roumen Balabanov; Joachim Burman; Basil Sharrack; John A Snowden; Maria Carolina Oliveira; Jan Fagius; John Rose; Flavia Nelson; Amilton Antunes Barreira; Kristina Carlson; Xiaoqiang Han; Daniela Moraes; Amy Morgan; Kathleen Quigley; Kimberly Yaung; Regan Buckley; Carri Alldredge; Allison Clendenan; Michelle A Calvario; Jacquelyn Henry; Borko Jovanovic; Irene B Helenowski
Journal:  JAMA       Date:  2019-01-15       Impact factor: 56.272

7.  Altered neural signatures of interoception in multiple sclerosis.

Authors:  Paula C Salamone; Sol Esteves; Vladimiro J Sinay; Indira García-Cordero; Sofía Abrevaya; Blas Couto; Federico Adolfi; Miguel Martorell; Agustín Petroni; Adrián Yoris; Kathya Torquati; Florencia Alifano; Agustina Legaz; Fátima P Cassará; Diana Bruno; Andrew H Kemp; Eduar Herrera; Adolfo M García; Agustín Ibáñez; Lucas Sedeño
Journal:  Hum Brain Mapp       Date:  2018-08-04       Impact factor: 5.038

8.  Oligoclonal bands and age at onset correlate with genetic risk score in multiple sclerosis.

Authors:  Hanne F Harbo; Noriko Isobe; Pål Berg-Hansen; Steffan D Bos; Stacy J Caillier; Marte W Gustavsen; Inger-Lise Mero; Elisabeth Gulowsen Celius; Stephen L Hauser; Jorge R Oksenberg; Pierre-Antoine Gourraud
Journal:  Mult Scler       Date:  2013-10-07       Impact factor: 6.312

9.  A longitudinal observational study of brain atrophy rate reflecting four decades of multiple sclerosis: a comparison of serial 1D, 2D, and volumetric measurements from MRI images.

Authors:  Juha Martola; Jakob Bergström; Sten Fredrikson; Leszek Stawiarz; Jan Hillert; Yi Zhang; Olof Flodmark; Anders Lilja; Anders Ekbom; Peter Aspelin; Maria Kristoffersen Wiberg
Journal:  Neuroradiology       Date:  2009-09-23       Impact factor: 2.804

10.  Disability in multiple sclerosis: a reference for patients and clinicians.

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

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