ArticleFrontiers in surgery2022
Construction of a new clinical staging system for colorectal cancer based on the lymph node ratio: A validation study.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- T1 colorectal cancer: determinants of lymph node metastasis, survival patterns, and risk-adapted management.Updates in surgery · 2026Review
- Proportional Nodal Burden as a Marker of Recurrence Risk in Non-Metastatic Colorectal Adenocarcinoma: The Prognostic Role of Lymph Node Ratio.Journal of clinical medicine · 2026Article
- Lymph node ratio and overall survival in patients with colon cancer: a prospective multicentre cohort study.Scientific reports · 2026Article
- Clinicopathologic Determinants of Lymph Node Count and Prognostic Significance of Metastatic Lymph Node Ratio in Colorectal Cancer.Diagnostics (Basel, Switzerland) · 2025Article
- Prognostic prediction models for postoperative patients with stage I to III colorectal cancer based on machine learning.World journal of gastrointestinal oncology · 2024Article
- Development and Validation of Machine Learning Model Platelet Index-based Predictor for Colorectal Cancer Stage.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- The predictive role of soluble programmed death ligand 1 in digestive system cancers.Frontiers in oncology · 2023Review
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Abstract
Aim: This study aims to construct a new staging system for colorectal cancer (CRC) based on the lymph node ratio (LNR) as a supplement to the American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system for predicting the prognosis of CRC patients with <12 lymph nodes. Methods: The data of 26,695 CRC patients with <12 lymph nodes were extracted from the Surveillance, Epidemiology, and End Results (SEER) database as a training set. A total of 635 CRC patients were also enrolled from Northern Jiangsu People's Hospital affiliated with Yangzhou University as an independent validation set. Classification and regression tree analysis was used to obtain the LNR cutoff value. Survival curves were estimated using the Kaplan-Meier method, and the log-rank test was used for comparisons of differences among the survival curves. The monotonic decreasing trend of the overall survival curve in the staging system was expressed by the linear correlation degree R. Results: The 5-year survival rates of patients in the training set based on the AJCC staging system from stage I to stage IV were 75.6% (95%CI: 74.4-76.8), 59.8% (95%CI: 58.6-61.0), 42.1% (95%CI: 34.5-49.7), 33.2% (95%CI: 24.6-41.8), 72.0% (95%CI: 69.1-74.9), 48.8% (95%CI: 47.4-50.2), 26.5% (95%CI: 23.0-30.0), and 11.3% (95%CI: 10.3-12.3). The 5-year survival rates of patients in the training set from stage I to stage IIIC were 80.4%, 72.9%, 59.8%, 48.4%, 32.5%, and 15.0%, according to the TNM + LNR (TNRM) staging system. According to the AJCC staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 91.3%, 90.8%, 72.6%, 61.3%, 72.4%, 58.1%, and 32.8%. Based on the TNRM staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 99.2%, 90.5%, 81.4%, 78.6%, 60.2%, and 35.8%. Conclusion: The TNRM staging system successfully eliminated "survival paradox" in the AJCC staging system, which might be superior to the AJCC staging system.
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