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

Xia Liu; Peipei Wang; Guolong Liu

doi:10.1007/s12094-024-03735-7

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

Clin Transl Oncol. 2024 Sep 20. doi: 10.1007/s12094-024-03735-7. Online ahead of print.

Authors

Xia Liu^{1

2}, Peipei Wang^#^{3

4}, Guolong Liu^#^{5

6}

Affiliations

¹ The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong, China.
² Department of Oncology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, Guangdong, China.
³ Department of Oncology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, Guangdong, China. peipeiwang2016@163.com.
⁴ School of Biomedical Sciences and Engineering, Guangzhou International Campus, South China University of Technology, Guangzhou, Guangdong, China. peipeiwang2016@163.com.
⁵ The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong, China. eyglliu@scut.edu.cn.
⁶ Department of Oncology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, Guangdong, China. eyglliu@scut.edu.cn.

^# Contributed equally.

PMID: 39304598
DOI: 10.1007/s12094-024-03735-7

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.

Keywords: Biomarker; EGFR-TKI; NRI; Non-small cell lung cancer; Risk stratification; SIRI.