Contributions
Abstract: P897
Type: Poster
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Conversion to secondary progressive (SP) multiple sclerosis (MS) typically occurs after approximately 20 years of disease duration. This generally is a gradual process which is determined retroactively by a neurologist after examining clinical records over a period of several years. Improving prediction of secondary progressive disease and standardizing parameters which define this transition could benefit clinicians, patients and researchers. The aim of this study was to use clinical measures as a predictive tool to indicate SPMS.
Data included 11,234 MS patients from the Swedish MS registry (SMSReg), of whom 3904 had reached the secondary progressive stage as determined by a neurologist using patient records. These records contained clinical data such as the last EDSS measurement, age at last EDSS, date of disease diagnosis, date of disease onset, and sex. We used these measurements as inputs into a decision tree with SP as a binary output. The final variables included in the decision tree were last EDSS measurement and the age at last EDSS.
The model achieved 87.7% internal accuracy, and over 86% internally cross-validated accuracy. Furthermore, each of the resultant decision branches contains a certainty estimate which can be used clinically to make rapid judgements about whether a patient has reached secondary progressive disease. Since the last EDSS and corresponding age are readily available, this demonstrates that an easy method to accurately estimate patients" current SP status is possible. This has strong potential to be a clinically relevant tool which can both reduce required to evaluate the transition to secondary progress multiple sclerosis and also standardize the basis of SP across diverse clinical groups.
Disclosure: RR and AM have nothing to disclose
JH has received honoraria for serving on advisory boards for Biogen and Novartis and speaker"s fees from BiogenIdec, Merck-Serono, Bayer-Schering, Teva and Sanofi-Aventis. He has served as P.I. for projects, or received unrestricted research support from, Biogen, Merck-Serono, Sanofi-Genzyme and Novartis.
Abstract: P897
Type: Poster
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Conversion to secondary progressive (SP) multiple sclerosis (MS) typically occurs after approximately 20 years of disease duration. This generally is a gradual process which is determined retroactively by a neurologist after examining clinical records over a period of several years. Improving prediction of secondary progressive disease and standardizing parameters which define this transition could benefit clinicians, patients and researchers. The aim of this study was to use clinical measures as a predictive tool to indicate SPMS.
Data included 11,234 MS patients from the Swedish MS registry (SMSReg), of whom 3904 had reached the secondary progressive stage as determined by a neurologist using patient records. These records contained clinical data such as the last EDSS measurement, age at last EDSS, date of disease diagnosis, date of disease onset, and sex. We used these measurements as inputs into a decision tree with SP as a binary output. The final variables included in the decision tree were last EDSS measurement and the age at last EDSS.
The model achieved 87.7% internal accuracy, and over 86% internally cross-validated accuracy. Furthermore, each of the resultant decision branches contains a certainty estimate which can be used clinically to make rapid judgements about whether a patient has reached secondary progressive disease. Since the last EDSS and corresponding age are readily available, this demonstrates that an easy method to accurately estimate patients" current SP status is possible. This has strong potential to be a clinically relevant tool which can both reduce required to evaluate the transition to secondary progress multiple sclerosis and also standardize the basis of SP across diverse clinical groups.
Disclosure: RR and AM have nothing to disclose
JH has received honoraria for serving on advisory boards for Biogen and Novartis and speaker"s fees from BiogenIdec, Merck-Serono, Bayer-Schering, Teva and Sanofi-Aventis. He has served as P.I. for projects, or received unrestricted research support from, Biogen, Merck-Serono, Sanofi-Genzyme and Novartis.