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New method could reduce MS uncertainties


A new study is introducing a method to take some of the unpredictability out of process of MS progression. The method, pioneered by David Engler, of Brigham Young University’s Department of Statistics, and researchers at Massachusetts General Hospital is based heavily on the individual patient’s history.

Every six months, people with MS share certain information with their doctor. First, they answer yes or no whether they experienced a relapse. Second, they estimate the intensity of their symptoms on a 21-point scale (0, 0.5, 1.0 … 9.0, 9.5, 10). A doctor using the model would simply plug in the relapse and intensity information for the past two checkups, along with a few bits of demographic data. The model then returns 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.

To test the model’s usefulness, they applied it to 1,123 MS patients in Boston. As the authors note, their approach is well-suited to identify predictors of a transition from the relapse-remitting phase to the secondary progressive phase of the disease.

“The goal all along has been to develop personalized transition probabilities with regard to where they are in the disease process and where they’re most likely to go in the near future,” Engler said.

The results were published in the journal Statistical Methods in Medical Research.

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