Modeling long-term health and economic implications of new treatment strategies for Parkinson's disease: an individual patient simulation study.

Abstract

Background: Simulation modeling facilitates the estimation of long-term health and economic outcomes to inform healthcare decision-making. Objective: To develop a framework to simulate progression of Parkinson's disease (PD), capturing motor and non-motor symptoms, clinical outcomes, and associated costs over a lifetime. Methods: A patient-level simulation was implemented accounting for individual variability and interrelated changes in common disease progression scales. Predictive equations were developed to model progression for newly diagnosed patients and were combined with additional sources to inform long-term progression. Analyses compared a hypothetical disease-modifying therapy (DMT) with a standard of care to explore the drivers of cost-effectiveness. Results: The equations captured the dependence between the various measures, leveraging prior values and rates of change to obtain realistic predictions. The simulation was built upon several interrelated equations, validated by comparison with observed values for the Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) and UPDRS subscales over time. In a case study, disease progression rates, patient utilities, and direct non-medical costs were drivers of cost-effectiveness. Conclusions: The developed equations supported the simulation of early PD. This model can support conducting simulations to inform internal decision-making, trial design, and strategic planning early in the development of new DMTs entering clinical trials.