Literature DB >> 20106349

Prognosis of the individual course of disease: the elements of time, heterogeneity and precision.

Martin Daumer1, Anneke Neuhaus, Joseph Herbert, George Ebers.   

Abstract

There is no gold standard in monitoring disease activity for clinical trials in multiple sclerosis. Various outcome measures, including relapses, disability and magnetic resonance imaging (MRI) measures have been used to demonstrate the efficacy of the different available therapies for multiple sclerosis. Recently, the potential limitations of these measures have received increasing attention, and these have stimulated research into more appropriate and sensitive outcome measures for clinical trials. For example, it has been shown that widely-used MRI measures add little, if any, independent information to that provided by more clinically relevant measures such as relapses and disability. Similarly, the Expanded Disability status Scale (EDSS), which is the most widely-used measure of disability related to multiple sclerosis, is insufficiently sensitive to detect robust changes in disability over the timeframes usually used in clinical trials. An alternative to the EDSS is the Multiple Sclerosis Severity Score (MSSS), a severity scale which relates clinical disability to disease duration. The MSSS was originally developed from a database of nearly ten thousand patients from eleven European countries and Australia and has since been reproduced in an independent dataset of 1134 patients from the placebo arms of randomised clinical trials. Based on the MSSS score, disease severity can be defined, which shows stability over time and may provide evidence-based decision support for patient management. Another alternative to measure disability is the objective quantification of physical activity. There is evidence that recent developments in pervasive computing using tiny accelerometers may have the potential to increase the reliability and precision of motor assessment, especially in the mid-range of the EDSS. The outcome measures discussed have potential use as online tools for evidence-based decision support which are increasingly being used in medical research and clinical decision-making. Copyright 2009 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2009        PMID: 20106349     DOI: 10.1016/S0022-510X(09)71301-2

Source DB:  PubMed          Journal:  J Neurol Sci        ISSN: 0022-510X            Impact factor:   3.181


  10 in total

1.  Genome-wide association study of severity in multiple sclerosis.

Authors: 
Journal:  Genes Immun       Date:  2011-06-09       Impact factor: 2.676

Review 2.  Precision medicine in myasthenia graves: begin from the data precision.

Authors:  Hai-Feng Li; Yu Hong; Yanchen Xie; Hong-Jun Hao; Ren-Cheng Sun
Journal:  Ann Transl Med       Date:  2016-03

3.  Longitudinal changes of cerebral glutathione (GSH) levels associated with the clinical course of disease progression in patients with secondary progressive multiple sclerosis.

Authors:  In-Young Choi; Phil Lee; Abbey J Hughes; Douglas R Denney; Sharon G Lynch
Journal:  Mult Scler       Date:  2016-09-12       Impact factor: 6.312

Review 4.  Clinical correlates of grey matter pathology in multiple sclerosis.

Authors:  Dana Horakova; Tomas Kalincik; Jana Blahova Dusankova; Ondrej Dolezal
Journal:  BMC Neurol       Date:  2012-03-07       Impact factor: 2.474

5.  Patterns of Objective and Subjective Burden of Informal Caregivers in Multiple Sclerosis.

Authors:  E Bayen; C Papeix; P Pradat-Diehl; C Lubetzki; M E Joël
Journal:  Behav Neurol       Date:  2015-05-20       Impact factor: 3.342

Review 6.  Multiple sclerosis: clinical profiling and data collection as prerequisite for personalized medicine approach.

Authors:  Tjalf Ziemssen; Raimar Kern; Katja Thomas
Journal:  BMC Neurol       Date:  2016-08-02       Impact factor: 2.474

Review 7.  Multiple sclerosis: integration of modeling with biology, clinical and imaging measures to provide better monitoring of disease progression and prediction of outcome.

Authors:  Shikha Jain Goodwin
Journal:  Neural Regen Res       Date:  2016-12       Impact factor: 5.135

8.  Three distinct physical behavior types in fatigued patients with multiple sclerosis.

Authors:  H E M Braakhuis; M A M Berger; G A van der Stok; J van Meeteren; V de Groot; H Beckerman; J B J Bussmann
Journal:  J Neuroeng Rehabil       Date:  2019-08-23       Impact factor: 4.262

9.  Study design of PANGAEA 2.0, a non-interventional study on RRMS patients to be switched to fingolimod.

Authors:  Tjalf Ziemssen; Raimar Kern; Christian Cornelissen
Journal:  BMC Neurol       Date:  2016-08-08       Impact factor: 2.474

10.  Regarding the publication The Multiple Sclerosis Severity Score: Fluctuations and prognostic ability in a longitudinal cohort of patients with MS authored by RH Gross et al.

Authors:  Richard Roxburgh; Ernest Willoughby; Shaun Seaman
Journal:  Mult Scler J Exp Transl Clin       Date:  2020-05-22
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.