Serological Response Patterns to Assess Treatment Outcomes in Advanced Non-Small Cell Lung Cancer: A Real-World...

Area of Science:

• Oncology
• Immunotherapy
• Biomarkers

Background:

• Previous research on serum tumor markers (STMs) for advanced cancer management focused on singular measurements, leading to inconsistencies in evaluating treatment outcomes.
• Immune checkpoint inhibitor (ICI) treatments have advanced cancer care, but optimal monitoring strategies require further investigation.

Purpose of the Study:

• To identify recurring serum tumor marker (STM) dynamics in advanced non-small cell lung cancer (NSCLC) patients achieving disease control on ICI-containing treatment.
• To explore the predictive value of these STM dynamics for treatment outcomes, including progression-free survival (PFS) and overall survival (OS).

Main Methods:

• A real-world, multi-center observational cohort study involving advanced NSCLC patients with disease control at three months post-ICI initiation.
• Inclusion required at least three STM measurements during treatment, with dynamics classified into distinct serological response patterns by blinded investigators.

Main Results:

• Analysis of 256 patients revealed significant associations between classified serological response patterns and both PFS and OS.
• The identified STM dynamics effectively differentiated durable responses from secondary resistance and oligoprogression from systemic progression.

Conclusions:

• Monitoring STM dynamics during ICI therapy in advanced NSCLC is valuable for refining response classification and clinical decision-making.
• Further research should investigate these dynamics across different cancer types, treatments, and analytes to broaden their applicability.