Tumor markers in non-small cell lung cancer spine metastasis: an assessment of prognosis and overall survival.

Abstract

Purpose: The identification of gene mutations in the modern medical workup of metastatic spine tumors has become more common but has not been highly utilized in surgical planning. Potential utility of these genetic markers as surrogates for cancer behavior in current prognosis scoring systems and overall survival (OS) remains underexplored in existing literature. This study seeks to investigate the association of frequently identified tumor markers, EGFR, ALK, and PD-L1, in metastatic non-small cell lung cancer (NSCLC) to the spine with Tokuhashi prognosis scoring and OS.

Methods: Patients with NSCLC metastasis to spine were identified through chart review. EGFR, ALK, and PD-L1 wild type vs. mutant type were identified from targeted chemotherapy genetic testing. Multiple linear regression was performed to assess gene profile contributions to Tokuhashi score. Cox Proportional Hazards models were generated for each tumor marker to assess the relationship between each marker and OS.

Results: A total of 119 patients with NSCLC spine metastasis were identified. We employed a multiple linear regression analysis to investigate the influence of EGFR, ALK, and PD-L1 genotypes on the Tokuhashi score, revealing statistically significant relationships overall (p = 0.002). Individual genotype contributions include EGFR as a non-significant contributor (p = 0.269) and ALK and PD-L1 as significant contributors (p = 0.037 and p = 0.001 respectively). Overall survival was not significantly associated with tumor marker profiles through Kaplan-Meier analysis (p = 0.46) or by multivariable analysis (p = 0.108).

Conclusion: ALK and PD-L1 were significantly associated with Tokuhashi score while EGFR was not. Tumor markers alone were not predictive of OS. These findings indicate that genetic markers found in NSCLC metastases to the spine may demonstrate prognostic value. Therefore, employing standard tumor markers could enhance the identification of appropriate surgical candidates, although they demonstrate limited effectiveness in predicting overall survival.