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A large real-world cohort study of examined lymph node standards for adequate nodal staging in early non-small cell lung cancer

written on behalf of AME Lung Cancer Collaborative Group, Zhihua Zhu, Zhengbo Song, Wenjie Jiao, Wei-Jian Mei, C. Xu, Qinghua Huang, Chaolun An, Jianguang Shi, Wenxian Wang, Guiping Yu, Pingli Sun, Yinbin Zhang, Jianfei Shen, Yong Song, Jun Qian, Wang Yao, Han Yang

2021Translational Lung Cancer Research31 citationsDOIOpen Access PDF

Abstract

Background: The current National Comprehensive Cancer Network (NCCN) guidelines for non-small cell lung cancer (NSCLC) recommend that surgeons sample is not clear. We aimed to define a minimal number of examined lymph nodes for removal or sampling for optimized nodal staging recommendation, with a focus on T1–3N0M0 patients. Methods: A total of 55,101 consecutive patients were selected, including 52,099 patients with US Surveillance, Epidemiology, and End Results (SEER) data and 3,002 patients in a Chinese multicenter database from 11 thoracic referral centers, who underwent complete resection plus lymph node dissection or sampling for stage T1–3N0M0 NSCLC. Propensity score-matching analysis was performed with R software, and a cut-off value was calculated using X-tile software. Survival was evaluated using the Kaplan-Meier method and Cox proportional hazard models. Results: Five-year survival rates with respect to total examined lymph nodes numbers (examined lymph nodes <10 vs. examined lymph nodes ≥10) were 69% and 64% (group A), 66% and 63% (group B), 62% and 58% (group C), 81% and 75% (group D). There were significant differences between examined lymph nodes <10 and examined lymph nodes >10 in each group (P<0.001). Conclusions: A minimum of 10 examined lymph nodes would significantly improve T1–3N0M0 NSCLC prognosis and patients’ survival rates if implemented as a minimum standard for lymphadenectomy. Therefore, we recommended a minimum of 10 examined lymph nodes for T1–3N0M0 patients.

Topics & Concepts

MedicineNODALLymph nodeCohortLung cancerCancerLungNodal analysisOncologyPathologyInternal medicineElectrical engineeringEngineeringLung Cancer Diagnosis and TreatmentLung Cancer Treatments and MutationsRadiomics and Machine Learning in Medical Imaging