Abstract Details

Title Modelling Disability Progression in Patients with Secondary Progressive Multiple Sclerosis Shows Non-linearity of EDSS Changes over Time

Topic Multiple Sclerosis

Presentation(s) MS and CNS Inflammatory Disease Posters (7:00 AM-5:00 PM)

Poster/Presentation
Number 043

Objective To describe and model disability progression over time of patients with secondary progressive multiple sclerosis (SPMS).

Background Disability progression is the main clinical outcome used to assess the disease course in SPMS patients. Better understanding and prediction of disease progression is needed in order to select the best suited clinical practice for individual patients.

Design/Methods We used data from the Swedish MS registry, including patients with clinically assigned SPMS with ages ≥ 18 years at the beginning of the index period (1 January 2001 – 30 November 2019) and known year of SPMS conversion. The index was the date of the nearest clinic visit around the year of SPMS conversion. Disability was assessed using the expanded disability status scale [EDSS] score. Mixed models for repeated measures of EDSS change over time, adjusted for index EDSS, age and gender were used.

Results

There were 1,635 SPMS patients with at least one EDSS measure at index. Out of these 762, 635, 573, 513 and 408 patients had EDSS at one, two, three, four and five years post-index, respectively. The mean (median) changes in EDSS from index to one, two, three, four and five years post-index were 0.4 (0), 0.6 (0.5), 0.9 (0.5), 1.1 (1.0), and 1.3 (1.0) respectively. At least 25% of the patients did not demonstrate worsening of EDSS during the follow-up.

We found a significant negative effect of index EDSS and age on the progression rate and strong non-linearity of EDSS changes over time, independent of other patient characteristics.

Conclusions Understanding and prediction of disability progression is important for personalized treatment decisions in SPMS. The analysis confirmed the complexity of course of disease. Although the model performed well at the cohort level, complex approaches using pattern recognition and machine learning techniques may be required for a more precise prediction at the individual level.

Authors/Disclosures
Vladimir Bezlyak (Novartis Pharma AG) PRESENTER	Vladimir Bezlyak has received personal compensation for serving as an employee of Novartis Pharma AG. Vladimir Bezlyak has received stock or an ownership interest from Novartis Pharma AG.
	No disclosure on file
	No disclosure on file
Nicholas Adlard	Nicholas Adlard has received personal compensation for serving as an employee of Novartis Pharma AG.
Thomas Hach	Thomas Hach has received personal compensation for serving as an employee of Novartis Pharma AG. Thomas Hach has received stock or an ownership interest from Novartis.
	No disclosure on file
	No disclosure on file
Jan A. Hillert, MD (Karolinska Institute, Neurology R54)	Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Biogen. Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Celgene. Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Merck. Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Sandoz. Dr. Hillert has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Sanofi. The institution of Dr. Hillert has received research support from Biogen. The institution of Dr. Hillert has received research support from Celgene. The institution of Dr. Hillert has received research support from Merck. The institution of Dr. Hillert has received research support from Novartis. The institution of Dr. Hillert has received research support from Sanofi. The institution of Dr. Hillert has received research support from Roche.

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