Determining Line of Therapy from Real-World Data in Non-Small Cell Lung Cancer

IntroductionDetermining lines of therapy (LOT) using real-world data is crucial to inform clinical decisions and support clinical research. Existing rules for determining LOT in patients with metastatic non-small cell lung cancer (mNSCLC) do not incorporate the growing number of targeted therapies used in treatment today. Therefore, we propose rules for determining LOT from real-world data of patients with mNSCLC treated with targeted therapies. MethodsLOT rules were developed through expert consensus using a real-world cohort of 550 patients with ALK+ or ROS1+ mNSCLC in the multi-institutional, electronic medical record-based Academic Thoracic Oncology Medical Investigators Consortiums (ATOMIC) Driver Mutation Registry. Rules were subsequently modified based on a review of appropriate LOT determination. These resulting rules were then applied to an independent cohort of patients with EGFR+ mNSCLC to illustrate their use. ResultsSix rules for determining LOTs were developed. Among 1133 patients with EGFR mutations and mNSCLC, a total of 3168 regimens were recorded with a median of 2 regimens per patient (IQR, 1-4; range, 1-13). After applying our rules, there were 2834 total LOTs with a median of 2 LOTs per patient (IQR, 1-3; range, 1-11). Rules 1-3 kept 11% of regimen changes from advancing the LOT. When compared to previously published rules, LOT assignments differed 5.7% of the time, mostly in LOTs with targeted therapy. ConclusionThese rules provide an updated framework to evaluate current treatment patterns, accounting for the increased use of targeted therapies in patients with mNSCLC and promote standardization of methods for determining LOT from real-world data. Key PointsO_LIUse of targeted therapy to treat patients with mNSCLC is growing C_LIO_LIDetermining lines of therapy from real-world data is crucial for clinical research C_LIO_LIOur rules aim to advance the line of therapy to reflect changes in clinical status C_LIO_LIUsing these rules can lead to better method harmonization in mNSCLC research C_LI