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Updated: Jun 4, 2026

Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients
Published on: September 25, 2018
Clinical Value of the Systemic Immune Inflammation Index and PD-L1 Expression in Advanced NSCLC Treated with
Hyungkeun Cha1, Yong Seok Lee2, Gui Young Kwon3
1Division of Pulmonology, Department of Internal Medicine, Inha University Hospital, Inha University School of Medicine, Incheon, Republic of Korea.
Abstract:
Objective: Studies on the comprehensive utility of complete blood count-derived inflammatory biomarkers (CBC-IBs) as biomarkers in pembrolizumab-treated advanced non-small-cell lung cancer (NSCLC) are scarce. This study aimed to investigate the clinical relevance of a panel of CBC-IBs as potential predictive biomarkers and assess whether integrating the systemic immune-inflammation index (SII) with programmed death-ligand 1 (PD-L1) expression could overcome the limitations of PD-L1 as a standalone predictive biomarker. Methods: Our real-world preliminary study was conducted on a cohort of patients with advanced NSCLC. Patients who had undergone PD-L1 immunohistochemistry testing at the time of diagnosis, and had completed at least three cycles of pembrolizumab were included. The CBC-IBs analyzed in this study were calculated using absolute cell counts of neutrophils, lymphocytes, monocytes, and platelets. Results: A total of 102 patients were included. Low baseline SII was significantly associated with superior progression-free survival (PFS) (p = 0.031) and overall survival (OS) (p = 0.004). In multivariate analysis, SII emerged as the strongest independent predictor for OS among all evaluated CBC-IBs. Furthermore, patients with a combination of low SII and high PD-L1 expression demonstrated the most favorable survival outcomes. Conclusion: Although further prospective and multicenter studies are needed to validate the generalizability of our findings, the clinical implication is that the use of pretreatment SII and/or PD-L1 expression values may predict therapeutic outcomes and assist in optimizing individualized treatment strategies for patients with advanced NSCLC.
