NRI and SIRI are the optimal combinations for prognostic risk stratification in patients with non-small cell lung cancer after EGFR-TKI therapy

NRI 和 SIRI 是 EGFR-TKI 治疗后非小细胞肺癌患者预后风险分层的最佳组合。

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Abstract

BACKGROUND: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC) with EGFR mutations. However, NSCLC heterogeneity leads to differences in efficacy; thus, potential biomarkers need to be explored to predict the prognosis of patients. Recently, the prognostic importance of pre-treatment malnutrition and systemic inflammatory response in cancer patients has received increasing attention. METHODS: In this study, clinical information from 363 NSCLC patients receiving EGFR-TKI treatment at our clinical center was used for analysis. RESULTS: High nutritional risk index (NRI) and systemic inflammation response index (SIRI) were significantly associated with poor overall survival (OS) and progression-free survival (PFS) in NSCLC patients (P < 0.05). Importantly, NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients and independent OS and PFS predictors. Moreover, a nomogram model was constructed by combining NRI/SIRI, sex, smoking history, EGFR mutation, TNM stage, and surgery treatment to visually and personally predict the 1-, 2-, 3-, 4-, and 5-year OS of patients with NSCLC. Notably, risk stratification based on the nomogram model was better than that based on the TNM stage. CONCLUSION: NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients receiving EGFR-TKI treatment, which may be a novel biomarker for supplement risk stratification in NSCLC patients.

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