PRM259 - THE CHALLENGES OF ESTIMATING MULTI-STATE MODEL TRANSITIONS IN RARE DISEASES: INFORMING AN ECONOMIC DECISION MODEL FOR DUCHENNE MUSCULAR DYSTROPHY

Abstract

Duchenne Muscular Dystrophy (DMD) is a rare disease with no single natural history model available that encompasses the full disease pathway. Transition rates between health states are limited in the literature and this has hindered cost-effectiveness analyses. This study synthesised data from the literature in order to perform a unified analysis and to inform future economic decision models. Estimated patient data was obtained via digitising reported Kaplan-Meier curves; simulating from transition rates described in the literature and/or employing a high level approach to synthesise data indirectly from available transition rates. The generated patient data, in addition to any available individual patient data from other sources, were first mapped onto health states that represented a change in either quality of life and/or resource use/cost. A parametric Markov multi-state model was then fitted to the combined dataset with age as the time-scale. Covariates for each transition were considered on availability, clinical importance and statistical significance and each transition was stratified by extraction source. Transition probabilities and length of stay were calculated and were contrasted for different covariate values, where available. A hypothetical model based on clinical experience informed transitions with sparse data. The average age a patient progressed to each health state was consistent with clinical opinion and recently reported studies. Steroid use significantly delayed the progression to poorer health states, while information on other covariates was minimal. This study models the full natural history of DMD in a single analysis and highlights some of the challenges of working in a rare disease area. The results can be used to inform future economic decision models and where primary data collection is required. We also provide user friendly example code to implement the methods within a general multi-state model framework.