Abstract
Understanding disability progression in multiple sclerosis (MS) patients is essential to estimate the impact of clinical interventions. Detailed assessment of annual changes of patients Expanded Disability Status Scale (EDSS) level is necessary to model EDSS level distribution over time and project the effectiveness and cost of clinical interventions. This data are widely available for relapsing remitting MS, while poor or no data are available for progressive courses. This study aims to fill this gap. MS Primary Progressive (PPMS) and Secondary Progressive (SPMS) patients, with EDSS between 3.0 and 7.0 at first visit, were enrolled in two big MS centers registries in Italy. The registries collected demographic, clinical and treatment data at each visit performed in the centers from 1983 to 2017. Cox proportional hazard models were used to identify clinical characteristic associated to disability progression. Annual EDSS transition probabilities for PPMS and SPMS were estimated using continuous Markov models. Goodness of fit and sensitivity analyses were performed. The study cohort included 758 patients (274 PPMS and 434 SPMS) with a median follow-up of 8.2 years. Relapse rate and EDSS level at first visit were significantly associated to EDSS progression in both progressive courses; while in SPMS disease-modifying treatment in the observational period was also significantly associated. Annual transition probability matrix from EDSS 3.0 to 9.0 were estimated for both MS courses separately, with SPMS reporting a higher annual probability to move within EDSS levels. Goodness of fit was acceptable when comparing predicted and observed EDSS profiles. This study provides for the first time a detailed description of EDSS changes over time for PPMS and SPMS patients. These results could be a useful tool for healthcare decision makers and clinicians to assess the impact of interventions on disability progression in order to select the most valuable ones.
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