A new model for predicting individualized prognosis in patients with multiple sclerosis (MS) has been developed, according to a new study published in the journal Statistical Methods in Medical Research.

The progression of MS is unpredictable and it is difficult to anticipate how the disease will progress in the future. Statistician David Engler, from Brigham Young University, and fellow researchers at Massachusetts General Hospital created a model that can predict the odds that MS will retreat to a milder stage, advance to a more aggressive stage, or maintain the status quo in the next six months. The model calculates the odds with certain information that each patient shares with their doctor every six months. This data includes whether the patient has experienced a relapse during that period, the intensity of the symptoms on a 21-point scale, and some demographic data.

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The model was tested on 1,123 MS patients in Boston to test its usefulness. Study authors reported that the model was able to identify predictors of patients transitioning from the relapse-remitting phase to the secondary progressive phase of MS. This model can “help identify new treatments which improve overall disability measures,” Tanuja Chitnis, a co-author of the study noted.

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