SYSTEMATIC REVIEW article
Front. Oncol.
Sec. Thoracic Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1601575
Prognostic value of lymph node ratio in patients with non-small cell lung cancer: A Systematic Review and Meta-analysis
Provisionally accepted
- Guangzhou Medical University, Guangzhou, China
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The lymph node ratio (LNR), by indirectly quantifying the dynamic balance between metastatic burden and host immune clearance, may provide more accurate prognostic stratification information. This meta-analysis aims to evaluate the prognostic value of LNR in patients with non-small cell lung cancer (NSCLC). Methods: A systematic literature search was conducted in PubMed, Embase, Cochrane, and Web of Science databases, with the search date up to January 7, 2025. Studies were strictly selected based on pre-specified inclusion and exclusion criteria. Data were merged and analyzed using Stata 16.0. Results: This meta-analysis included 11 studies. High LNR was significantly associated with decreased overall survival (OS) (multivariable HR=1.76, 95% CI=1.36-2.27; univariable HR=2.26, 95% CI=1.95-2.63) and increased risk of shorter disease-free survival (DFS) (multivariable HR=1.66, 95% CI=1.48-1.88). Subgroup analysis showed that regardless of whether the LNR cutoff was set at >0.25 (OS-HR=1.62; DFS-HR=1.82) or ≤0.25 (OS-HR=2.02; DFS-HR=1.58), high LNR indicated poor prognosis. Heterogeneity analysis showed high heterogeneity for OS outcomes (I²=91.8%) and low heterogeneity for DFS outcomes (I²=21.5%). After publication bias was corrected by trim-and-fill method, the combined effect size remained stable. Conclusion: LNR is an independent prognostic factor for survival in NSCLC patients. Future prospective studies are needed to optimize the LNR cutoff values and integrate molecular biomarkers to construct precise prognostic models, which could provide evidence for updating the TNM staging system and personalized treatment.
Keywords: lymph node ratio, lymph node metastasis, lung cancer, non-small cell prognostic predictive efficacy, Meta-analysis
Received: 28 Mar 2025; Accepted: 16 Jun 2025.
Copyright: © 2025 Zheng, Zhong, Quan, Gao and Ying. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zhiyan Gao, Guangzhou Medical University, Guangzhou, China
Songsong Ying, Guangzhou Medical University, Guangzhou, China
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