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Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer.

ABSTRACT: OBJECTIVES:The purpose of the present study was to evaluate the prognostic value of a systemic immune-inflammation index (SII) and the relationship between SII and the effectiveness of postoperative treatment in patients with non-small cell lung cancer (NSCLC). METHODS:A total of 538 patients diagnosed with NSCLC who had undergone curative surgery were retrospectively enrolled in the study. Clinicopathologic and laboratory variables were collected. SII was defined as neutrophil × platelet/lymphocyte counts. Both univariate and multivariate analyses were performed to analyze the prognostic value of these factors. RESULTS:The preoperative SII level was associated with sex, smoking history, histological type, lesion type, resection type, pathological stage, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), fibrinogen and bone metastasis (P<0.05). The univariate and multivariate analyses revealed that SII was an independent prognostic factor for disease-free survival (DFS, P=0.033) and overall survival (OS, P=0.020). Furthermore, the prognostic value of SII was also verified regardless of the histological type and pathological stage. The subgroup analysis demonstrated that patients with a high SII may benefit from adjuvant therapy (P=0.024 for DFS and P=0.012 for OS). CONCLUSION:An increased preoperative SII may independently predict the poor DFS and OS in patients with resectable NSCLC. SII may help select NSCLC patients who might benefit from adjuvant chemotherapy.

SUBMITTER: Yan X

PROVIDER: S-EPMC7103585 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer.

Yan Xue X Li Guowei G

Bioscience reports 20200301 3

<h4>Objectives</h4>The purpose of the present study was to evaluate the prognostic value of a systemic immune-inflammation index (SII) and the relationship between SII and the effectiveness of postoperative treatment in patients with non-small cell lung cancer (NSCLC).<h4>Methods</h4>A total of 538 patients diagnosed with NSCLC who had undergone curative surgery were retrospectively enrolled in the study. Clinicopathologic and laboratory variables were collected. SII was defined as neutrophil × ...[more]

PMID: 32175568

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Project description:BackgroundDespite recent progresses in immune checkpoint blockade (ICB) in small-cell lung cancer (SCLC), a lack of understanding regarding the systemic tumor immune environment (STIE) and local tumor immune microenvironment (TIME) makes it difficult to accurately predict clinical outcomes and identify potential beneficiaries from ICB therapy.MethodsWe enrolled 191 patients with stage I-III SCLC and comprehensively evaluated the prognostic role of STIE by several quantitative measurements, and further integrate it with a local immune score system (LISS) established by eXtreme Gradient Boosting (XGBoost) machine learning algorithm. We also test the value of STIE in beneficiary selection in our independent advanced SCLC cohort receiving programmed cell death 1 ligand 1 (PD-L1) blockade therapy.ResultsAmong several systemic immune markers, the STIE as assessed by prognostic nutritional index (PNI) was correlated with disease-free survival (DFS) and overall survival (OS), and remained as an independent prognostic factor for SCLC patients [hazard ratio (HR): 0.473, 95% confidence interval (CI): 0.241-0.929, P=0.030]. Higher PNI score was closely associated with inflamed SCLC molecular subtype and local tumor-infiltrating lymphocytes (TILs). We further constructed a LISS which combined top three important local immune biomarkers (CD8+ T-cell count, PD-L1 expression on CD8+ T-cell and CD4+ T-cell count) and integrated it with the PNI score. The final integrated immune risk system was an independent prognostic factor and achieved better predictive performance than Tumor Node Metastasis (TNM) stages and single immune biomarker. Furthermore, PNI-high extensive-stage SCLC patients achieved better clinical response and longer progression-free survival (PFS) (11.8 vs. 5.9 months, P=0.012) from PD-L1 blockade therapy.ConclusionsThis study provides a method to investigate the prognostic value of overall immune status by combining the PNI with local immune biomarkers in SCLC. The promising clinical application of PNI in efficacy prediction and beneficiary selection for SCLC immunotherapy is also highlighted.

Dataset Information

Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer.

Publications

Preoperative systemic immune-inflammation index predicts prognosis and guides clinical treatment in patients with non-small cell lung cancer.

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