Abstract
BackgroundMultiple sclerosis is a chronic disease of uncertain aetiology. Variations in its disease course make it difficult to impossible to accurately determine the prognosis of individual patients. The Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) developed an "online analytical processing (OLAP)" tool that takes advantage of extant clinical trials data and allows one to model the near term future course of this chronic disease for an individual patient.ResultsFor 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.ConclusionThis 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.
Highlights
Multiple sclerosis is a chronic disease of uncertain aetiology
The matching algorithm automatically selects the most similar subgroup of patients that are included in the banked database, with similarity defined by the covariates on a disease course specific outcome
The resulting display shows the disease course of all patients in the database that are similar to the patient of interest, and this information can be used to project a hypothesized outcome for the patient of interest, based on the behaviour of similar patients in the database
Summary
Multiple sclerosis is a chronic disease of uncertain aetiology. Variations in its disease course make it difficult to impossible to accurately determine the prognosis of individual patients. The Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) developed an "online analytical processing (OLAP)" tool that takes advantage of extant clinical trials data and allows one to model the near term future course of this chronic disease for an individual patient. It remains impossible to accurately predict the prognosis of individual patients, which could be important for patient counselling and in weighing therapeutic options. 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.
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