Member Research and Reports

Member Research and Reports

MS Symptom Change and Effect on Relapse and Disability Studied by UAB Statistician

Dr. Yuliang “William” Liu, statistician in the department of biostatistics at the University of Alabama at Birmingham, recently evaluated the link between changes in multiple sclerosis (MS) symptoms and the risk of relapse activity (RA) and disability progression (DP), with an aim to facilitating decisions regarding appropriate treatment. UAB co-investigators are department colleagues Dr. Charity Morgan, assistant professor; Dr. Amber Salter, statistician; Dr. Stacey Cofield, associate professor; and Dr. Gary R. Cutter, professor.

[Photo: Dr. Yuliang “William” Liu]

Using North American Research Committee on Multiple Sclerosis (NARCOMS) registry data from a five-year period, the investigators assessed symptom changes with scores based on symptom worsening (SW) and Average of Performance Scales (APS). They marked the progression of disability when a point or higher increase in the Patient-Determined Disease Steps (PDDS) score occurred from one update to the next.

“Repeated measures logistic regression was used to investigate the relationship between symptom change and RA and DP. SW and APS were both significant predictors of subsequent RA and DP. Both SW and APS have a significant interaction with levels of disability (Mildly Impaired versus Highly Impaired) for the prediction of the subsequent RA or DP. For Mildly Impaired MS subjects, both SW and APS were significant predictors of both RA and DP. However, for Highly Impaired MS subjects, SW did not significantly predict future RA and neither SW nor APS predicted disability progression,” notes Dr. Liu.

According to study findings “changes in self-reported overall symptomatology may precede and predict clinical relapse and future disability progression. The predictive power of symptom changes may only be present at lower levels of disability.”

“Relationship between Symptom Change, Relapse Activity and Disability Progression in Multiple Sclerosis” was published online in the March edition of Journal of the Neurological Sciences.

Journal article: