OBJECTIVES

: Traditional cost-utility analyses for the treatment of BOS stationarize temporal dynamics in time series models. In this study, we demonstrate that dynamic cost-utility analyses of BOS and similar other heart and lung transplant-induced diseases can be more accurately predicted using the emerging technology of multiple agent systems (MAS), calibrated to real-world evidence. Embracing the latest advances in modern computing, we report the results of a calibrated MAS model that can simulate the dynamics of heterogeneous patient responses to extracorporeal photopheresis (ECP) treatment offered to BOS patients at earlier versus later stages of BOS severity.

METHODS

: Using evidence generated by three patient-level experimental studies of BOS treatments, we developed a MAS that simulates a heterogeneous population of BOS patient dynamics. The study reports novel results from more than 100,000 Monte Carlo experimental simulations of alternate BOS patient responses to earlier vs later introduction of ECP, and their associated costs and utilities according to the guidelines established by International Society for Heart and Lung Transplantation (ISHLT).

RESULTS

: By calibrating Monte Carlo experimental simulations to real-world, individualized characteristics across MAS, we report that earlier introduction of ECP for patients with specific age, gender and underlying disease dynamics could increase survival rates as compared with a scenario in which ECP is not introduced. Using changes from baseline in forced expiratory volume (FEV) per second, as per ISHLT guidelines, and their respective proxy life-adjusted quality years for patients in different stages of BOS, our MAS modeling approach can predict an optimal timing of treatment intervention for a specific patient conditional upon her/his disease history, age, gender and hypothesized uncertainties associated with positive responses to ECP.

CONCLUSIONS

: Our models demonstrate that ECP is cost-effective as compared with pharmacological alternatives. Dynamic cost utility analysis, when calibrated to real-world data, can inform the treatment of BOS using ECP.