Anat Achiron1. 1. Multiple Sclerosis, Center Sheba Medical Center (affiliated to Tel-Aviv University, Sackler School of Medicine, Israel), Tel-Hashomer, Israel. achiron@post.tau.ac.il
Abstract
BACKGROUND AND OBJECTIVE: Multiple sclerosis (MS) is a chronic, progressive disease of the central nervous system that generally occurs in adults under the age of 40 years and ultimately leads to severe neurological disability. Following the progression of MS by monitoring changes in disability levels can facilitate treatment decisions taken by physicians. The aim of this review is to present longitudinal disability curves enabling the assessment of disease progression in patients with relapsing-remitting (RR)MS. METHODS: Patients with a definite diagnosis of MS and an RR disease course were identified using the Multiple Sclerosis Center computerised database. Patients were stratified into major percentile groups based on their Expanded Disability Status Scale (EDSS) score 1 year after disease onset. Model disability curves for each percentile were constructed using mean consecutive EDSS scores for 10 years after disease onset. Model curves were generated by smoothing (parametric and non-parametric regression) and curve approximation (linear regression and moving averages). The predictive ability of model curves was validated by superimposing data from a separate group of patients with RRMS. RESULTS: Disability curves were constructed using data from 1001 patients. A significant difference between the initial percentile assignment and disability progression was indicated by the log-rank test (p < 0.001). Kaplan-Meier and life table analyses demonstrated the validity of the model in predicting disease progression. The probability of experiencing more severe disability than predicted (i. e. deviating from the initial percentile to a higher percentile over time) ranged from 6.5 % (50th percentile) to 15.4 % (75th percentile), while the probability of experiencing less severe disability than predicted (i. e. deviating from the initially assigned percentile to a lower percentile over time) ranged from 6.9% (50th percentile) to 1.6 % (75th percentile). Both suggest reasonable predictive validity. CONCLUSION: In MS, longitudinal disability curves can help to assess individual patient disability, map the effects of immunomodulatory treatments over time, and generally build on the overall clinical impression of disease progression. Such models can act as a tool to aid and support the clinical decision-making process. This review is based on the study published in Multiple Sclerosis (2003) 9:486-491.
BACKGROUND AND OBJECTIVE:Multiple sclerosis (MS) is a chronic, progressive disease of the central nervous system that generally occurs in adults under the age of 40 years and ultimately leads to severe neurological disability. Following the progression of MS by monitoring changes in disability levels can facilitate treatment decisions taken by physicians. The aim of this review is to present longitudinal disability curves enabling the assessment of disease progression in patients with relapsing-remitting (RR)MS. METHODS:Patients with a definite diagnosis of MS and an RR disease course were identified using the Multiple Sclerosis Center computerised database. Patients were stratified into major percentile groups based on their Expanded Disability Status Scale (EDSS) score 1 year after disease onset. Model disability curves for each percentile were constructed using mean consecutive EDSS scores for 10 years after disease onset. Model curves were generated by smoothing (parametric and non-parametric regression) and curve approximation (linear regression and moving averages). The predictive ability of model curves was validated by superimposing data from a separate group of patients with RRMS. RESULTS: Disability curves were constructed using data from 1001 patients. A significant difference between the initial percentile assignment and disability progression was indicated by the log-rank test (p < 0.001). Kaplan-Meier and life table analyses demonstrated the validity of the model in predicting disease progression. The probability of experiencing more severe disability than predicted (i. e. deviating from the initial percentile to a higher percentile over time) ranged from 6.5 % (50th percentile) to 15.4 % (75th percentile), while the probability of experiencing less severe disability than predicted (i. e. deviating from the initially assigned percentile to a lower percentile over time) ranged from 6.9% (50th percentile) to 1.6 % (75th percentile). Both suggest reasonable predictive validity. CONCLUSION: In MS, longitudinal disability curves can help to assess individual patient disability, map the effects of immunomodulatory treatments over time, and generally build on the overall clinical impression of disease progression. Such models can act as a tool to aid and support the clinical decision-making process. This review is based on the study published in Multiple Sclerosis (2003) 9:486-491.