Modeling Challenges in Cost-Effectiveness Analysis of First-Line Immuno-Oncology Therapies in Non-small Cell Lung Cancer

March 2022

Lung cancer is the leading cause of global cancer-related mortality, accounting for 1.80 million deaths annually; non-small cell lung cancer (NSCLC) accounts for 85-90% of lung cancers.

One of the most promising treatment modalities for NSCLC that has emerged in recent years is that of immune-oncology therapy (IO). A systematic literature review was conducted to review models of IO for previously untreated advanced or metastatic NSCLC to identify methodological challenges associated with cost-effectiveness analyses (CEAs) from published literature and technological appraisal (TAs).

The dominant approaches of IO in NSCLC are Markov and partitioned survival models and none of the identified TAs utilized patient level simulations. All models compared one or more IO monotherapies or combination therapies with chemotherapy. The lack of long-term trial results led to the use of real-world data for survival extrapolation and a treatment effect lasting for three or five years after the initiation of the therapy was commonly assumed in various models.

Most models used similar approaches, yet heterogeneity in handling methodological aspects was significant. Challenges such as variation in PD-L1 testing and survival extrapolation and validation using real-world data should be further examined for future models in advanced or metastatic NSCLC. It is encouraged to construct a scientifically sound and transparent model that could be used as a benchmark for future CEAs of IO for previously untreated advanced or metastatic NSCLC.

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