MODELING THE NATURAL HISTORY OF SECONDARY-PROGRESSIVE MULTIPLE SCLEROSIS- A NEW MODELING APPROACH USING DISCRETE EVENT SIMULATION

Author(s)

Hernandez L1, Guo S1, Altincatal A1, Naoshy S2, Watson C2
1Evidera, Lexington, MA, USA, 2Biogen, Cambridge, MA, USA

OBJECTIVES: The ongoing ASCEND trial of natalizumab utilizes a novel composite endpoint, comprised of the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW) and 9-Hole Peg Test (9HPT) to assess disability progression in patients with secondary-progressive multiple sclerosis (SPMS), due to the limited ability of EDSS alone to assess disability progression in this patient population. Given that the ASCEND data are not available, data from the IMPACT study was used to assess the cost-effectiveness of SPMS treatments in an economic model capturing the interrelated changes of these measures for individual patients. This study presents the model concept and assesses its external predictability. METHODS: A discrete event simulation was developed to predict times to disability progressions on EDSS, T25FW, and 9HPTand the occurrence of relapses over time, using four parametric (Weibull) functions, each adjusted by a Cox model to ensure that each event time was estimated based on patients’ baseline and time-varying factors. Each disability scale’s value is updated as events occur. Data from the IMPACT study (n=436, followed for 2 years) was extrapolated for longer term. Published data on EDSS from the University of British Columbia (UBC) MS database were used for long-term external validations. RESULTS: The model closely replicated all four endpoints as observed in the IMPACT study at two years. The predicted times for 25% of patients to reach EDSS 8 were consistent with those from the UBC data, with 13.4 (model) vs. 14.8 (UBC) years from EDSS 3.5–4.5, and 8.7 vs. 8.6 years from EDSS 6.0. The distributions of T25FW and 9HPT by EDSS level predicted at 10 years were consistent with those observed from the IMPACT study. CONCLUSIONS: This SPMS model reliably predicts short- and long-term disability levels, and can serve as the basis for economic evaluations of treatments for SPMS.

Conference/Value in Health Info

2015-11, ISPOR Europe 2015, Milan, Italy

Value in Health, Vol. 18, No. 7 (November 2015)

Code

PRM100

Topic

Methodological & Statistical Research

Topic Subcategory

Modeling and simulation

Disease

Neurological Disorders

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