Prognosis of the individual course of disease - steps in developing a decision support tool for Multiple Sclerosis

For a given patient the most similar patients of the SLCMSR database are intelligently selected by a model-based matching algorithm integrated into an OLAP-tool to enable real time, web-based statistical analyses. The underlying database (last update April 2005) contains 1,059 patients derived from 30 placebo arms of controlled clinical trials. Demographic information on the entire database and the portion selected for comparison are displayed. The result of the statistical comparison is provided as a display of the course of Expanded Disability Status Scale (EDSS) for individuals in the database with regions of probable progression over time, along with their mean relapse rate. Kaplan-Meier curves for time to sustained progression in the EDSS and time to requirement of constant assistance to walk (EDSS 6) are also displayed. The software-application OLAP anticipates the input MS patient's course on the basis of baseline values and the known course of disease for similar patients who have been followed in clinical trials.This simulation could be useful for physicians, researchers and other professionals who counsel patients on therapeutic options. The application can be modified for studying the natural history of other chronic diseases, if and when similar datasets on which the OLAP operates exist.Multiple sclerosis (MS) is an inflammatory disease of the central nervous system. Currently there is no cure for MS, but there are treatments for its relapsing forms that reduce the short and mid-range impact of the disease. It remains impossible to accurately predict the prognosis of individual patients, which could be important for patient counselling and in weighing therapeutic options. The Sylvia Lawry Centre for MS Research in Munich (SLCMSR) uses data from clinical trials and natural history studies to develop mathematical models for the course of the disease which might assist in the efforts to accurately determine short, mid and long-range prognosis. The "individu