Very Early Health Technology Assessment for Potential Predictive Biomarkers in the Treatment of Advanced Non-Small Cell Lung Cancer

Various biomarkers are being studied for treatment response to immune-checkpoint inhibitors (ICIs) to save costly and potentially harmful treatment in non-responders. We evaluated the cost-effectiveness of implementing a hypothetical predictive biomarker for ICI-containing treatment response compared with standard of care (e.g., no implemented biomarker) for pembrolizumab-containing treatment in patients with advanced NSCLC in the Netherlands. Standard-of-care-based and predictive-biomarker-based strategies were compared using Markov models for three first-line pembrolizumab-containing treatments depending on a patient’s tumor programmed cell death ligand-1 (PD-L1) expression and histology. A Dutch healthcare system perspective was adopted. Assuming a receiver operating characteristic-area under the curve of 1.0 in identifying responders, alternative treatments were offered for non-responders in the predictive-biomarker-based strategy. Parameters and assumptions were based on real-world data from surveys, literature using a targeted search, expert opinion, and registries. Outcomes included differences in costs, survival (life years (LYs)), and survival corrected for health-related quality of life (QoL) quality-adjusted life-years (QALYs) between the predictive-biomarker- and standard-of-care-based strategy. In this collection, you can find the raw OS and PFS rates over time extracted from literature to calculate transition probabilites, R-scripts for the calculation of transition probabilities and the resulting .RDS files containing parameters of the survival function for the transition probabilities and R-scripts for the Markov models used for each pembrolizumab-containing regimen.