Literature DB >> 3835484

A Markov model of the natural history of multiple sclerosis.

C Wolfson, C Confavreux.   

Abstract

Prior research into multiple sclerosis prognosis has produced conflicting results. This paper presents an original approach in which the disease course is described by the movements of patients through well-defined disease states. A Markov model is proposed to describe these movements and to evaluate the effect of prognostic factors on transitions from state to state. The feasibility and applicability of this model is determined using data on the course of disease in 278 diagnosed patients from Lyon. Patients with older age at onset, females, and those with monosymptomatic onset are found to be at a higher risk of transition to a worse disease state.

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Year:  1985        PMID: 3835484     DOI: 10.1159/000110234

Source DB:  PubMed          Journal:  Neuroepidemiology        ISSN: 0251-5350            Impact factor:   3.282


  2 in total

1.  Quantitative risk-benefit analysis of natalizumab.

Authors:  J P Thompson; K Noyes; E R Dorsey; S R Schwid; R G Holloway
Journal:  Neurology       Date:  2008-07-29       Impact factor: 9.910

2.  Exploration of machine learning techniques in predicting multiple sclerosis disease course.

Authors:  Yijun Zhao; Brian C Healy; Dalia Rotstein; Charles R G Guttmann; Rohit Bakshi; Howard L Weiner; Carla E Brodley; Tanuja Chitnis
Journal:  PLoS One       Date:  2017-04-05       Impact factor: 3.240

  2 in total

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