Modelling of Lung Cancer Therapy; Modelled And Real-World Impact of Targeted Therapy And Immunotherapy In The Netherlands

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Abstract Recent discoveries in molecular diagnostics and lung cancer drugs have improved the treatment of patients with advanced (inoperable) non-squamous NSCLC from solely platinum based chemotherapy to more personalized treatment including targeted therapies and immunotherapies. However, these improvements come at considerable costs, highlighting the need to assess cost-effectiveness for optimization of lung cancer care. Traditionally, cost-effectiveness models built to evaluate new lung cancer treatments were based on randomized control trial (RCT) findings. The strict RCT inclusion criteria make RCT patients not representative of real-world patients: Patients in RCT have better prognosis compared to real-world patients. Therefore, in this study we have developed and validated a diagnosis-treatment decision model for patients with advanced (inoperable) non-squamous NSCLC based on real-world data in the Netherlands. The model is a patient-level microsimulation model implemented as discrete event simulation with five health events. Patients are simulated from diagnosis to death, including at most three treatment lines. The base-model (non-personalized strategy) was populated using real-world data of patients treated with platinum-based chemotherapy between 2008 – 2014 in one of six Dutch’s teaching hospitals. To allow simulation of personalized care, molecular tumor characteristics were incorporated in the model based on the literature. The impact of novel targeted treatments and immunotherapies was included based on published RCTs. To validate the model, we compared survival under a personalized treatment strategy against observed real-world survival. This model can be used for health-care evaluation of personalized treatment for patients with advanced (inoperable) NSCLC in the Netherlands.

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