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  • Title: The assessment of the optimal number of examined lymph nodes and prognostic models based on lymph nodes for predicting survival outcome in patients with stage N3b gastric cancer.
    Author: Guo S, Shang M, Dong Z, Zhang J, Wang Y, Zhao Y.
    Journal: Asia Pac J Clin Oncol; 2021 Apr; 17(2):e117-e124. PubMed ID: 32762113.
    Abstract:
    BACKGROUND: The optimal number of examined lymph nodes (ELNs) and the prognostic value of different nodal staging systems remain unclear in the context of N3b gastric cancer. AIM: To evaluate the optimal number of ELNs and compare the predictive ability of the ELN number, LN ratio (LNR), and log odds of metastatic LNs (LODDS) for overall survival (OS) in patients with resected stage N3b gastric adenocarcinoma in an international database. METHODS: A total of 868 patients diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database (training cohort) and 144 patients diagnosed between 2011 and 2016 at the Liaoning Cancer Hospital (validation cohort) were identified. Cutoff values were established with X-tile. The 5-year OS rates were compared using Kaplan-Meier curves. Multivariate analysis was conducted with a Cox regression model. The Harrell's concordance index and Akaike's information criterion were used to compare the predictive accuracy of different nodal staging systems. RESULTS: The ELN number, LNR, and LODDS were independent prognostic factors for both the training and validation cohorts in the multivariate analysis. Patient with ≤26 ELNs, LNR of more than 0.9, and LODDS of more than 1.0 were associated with decrease OS. The LNR and LODDS had similar discriminatory ability for OS and performed better than the ELN number in the Eastern and Western populations. CONCLUSION: The optimal number of ELN may be 27 or more because LNs retrieved ≤26 was an independent risk factor for the prognosis. The prognostic prediction efficacy of LNR and LODDS was similar and better than that of ELN. Thus, LNR and LODDS could both serve as valid tools to predict OS for stage N3b patients.
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