OBJECTIVES : Multiple sclerosis (MS) is classified as relapsing-remitting (RRMS) or primary progressive (PPMS) in relation to initial course. RRMS is characterized by episodes of neurological dysfunction and it may convert to a secondary-progressive MS (SPMS) course. In the past, cost-effectiveness evaluations model used the same disability progression matrix for different MS types. Our study investigates the impact of specific disability progression matrix for each MS type in disease progression simulation.

METHODS : A previous Markov model developed to simulate the natural history of relapsing MS was used to simulate the three SM types lifetime disability progression. The model used Expanded Disability Status Scale (EDSS) score to define the level of disability and its progression. For PPMS and SPMS we used two specific transition matrix recently developed, while for RRMS we used the one estimated from British Columbia Multiple Sclerosis database. We assumed equal cohort age, gender and EDSS starting distribution. The model estimated the patient average time spent below EDSS 7 (upper limit for accessing diseases modifying treatment) and the patients distribution between EDSS group <7 and 7-9 over time.

RESULTS : The simulation based on the PPMS matrix reported an average time spent with an EDSS<7 of 14.5 years per patients. The SPMS and RRMS matrixes simulations reported an average time that was 5.9% and 8.9% longer, respectively. PPMS matrix simulation reported the highest average time spent in EDSS levels between 7 and 9 (13.7 years per patient). Yearly variation of patients distribution in EDSS<7 and EDSS 7-9, simulated with the three EDSS transition matrixes, ranged from +2.6% to -5.7%.

CONCLUSIONS : This study showed how disability progression changes in relation to the use of specific RRMS, SPMS and PPMS EDSS transition matrixes. These results provided evidence of the importance of using specific transition matrixes for each MS type when assessing the cost-effectiveness of MS intervention.