Serological Response Patterns to Assess Treatment Outcomes in Advanced Non-Small Cell Lung Cancer: A Real-World Exploratory Multi-Center Observational Cohort Study

Abstract

Background: Previous studies mainly investigated singular serum tumor marker (STM) measurements for the management of advanced cancer patients, resulting in differences between recommended cut-off points and associated accuracies in evaluating treatment outcomes. We aimed to determine which STM dynamics recur during treatment in advanced non-small cell lung cancer (NSCLC) patients with disease control three months after starting with immune checkpoint inhibitor (ICI)-containing treatment and explore whether these dynamics retain information on treatment outcomes. Methods: This real-world exploratory multi-center observational cohort study included advanced NSCLC patients with clinical and radiological disease control three months after starting with ICI-containing treatment and at least three STM measurements for at least one STM during treatment. STM dynamics visualized for all patients were subclassified into three serological response patterns by two investigators who were blinded for treatment outcomes. Results: Between March 2013 and January 2023, 256 patients were included at two thoracic oncology outpatient clinics in The Netherlands. Kaplan–Meier survival analyses showed a significant association between the serological response patterns and both progression-free survival (PFS) and overall survival (OS). Additionally, the serological response patterns could be used to distinguish a durable response versus secondary treatment resistance, and oligoprogression versus systemic progression. Conclusions: Our findings underscore the value of monitoring STM dynamics in advanced NSCLC patients during ICI-containing treatment to improve response classification and decision-making in clinical practice. Future studies should explore the value of the identified dynamics in other tumor- and systemic treatment-types and tumor cell analytes for assessing treatment outcomes across multiple indications.