Interrelations between Patients’ Clinicopathological Characteristics and Their Association with Response to Immunotherapy in a Real-World Cohort of NSCLC Patients

Abstract

Biomarcadores; Eventos adversos relacionados con el sistema inmunitario; Inmunoterapia

Biomarcadors; Esdeveniments adversos relacionats amb el sistema immunitari; Immunoteràpia

Biomarkers; Immune related adverse events; Immunotherapy

Immune checkpoint inhibitors (ICIs) have transformed non-small cell lung cancer (NSCLC) treatment. Unfortunately, only some patients benefit from these therapies. Thus, certain clinicopathological characteristics of the patients have been proposed as biomarkers of ICIs response. We assembled a retrospective cohort of 262 NSCLC patients treated with ICIs, compiled relevant clinicopathological characteristics, and studied their associations with treatment outcome using Cox proportional-hazards survival models. Additionally, we investigated the interrelations between clinicopathological features and devised a method to create a compendium associated with ICIs response by selecting those that provide non-redundant information. In multivariate analyses, ECOG performance status (hazard ratio (HR) 1.37 (95% CI 1.11 to 1.68), p < 0.005), LDH (HR 1.24 (95% CI 1.03 to 1.48), p = 0.02)) and PD-L1 negativity were associated with decreased progression-free survival (PFS) (HR 1.92 (95% CI 1.03 to 3.58), p = 0.04), whereas presentation of immune-related adverse events (irAEs) (HR 0.35 (95% CI 0.22 to 0.55, p < 0.005) or females (HR 0.52 (95% CI 0.33 to 0.80, p < 0.005) had longer PFS. Additionally, numerous clinicopathological indicators were found to be interrelated. Thus, we searched for features that provide non-redundant information, and found the combination of LDH levels, irAEs, and gender to have a better association with ICIs treatment response (cross-validated c-index = 0.66). We concluded that several clinicopathological features showed prognostic value in our real-world cohort. However, some are interrelated, and compendiums of features should therefore consider these interactions. Joint assessment of LDH, irAEs, and gender may be a good prognostic compendium.

None associated with this project.