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KMID : 1141820170170040319
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Journal of Gastric Cancer
2017 Volume.17 No. 4 p.319 ~ p.330
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Extensive Lymph Node Dissection Improves Survival among American Patients with Gastric Adenocarcinoma Treated Surgically: Analysis of the National Cancer Database
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Naffouje Samer A.
Salti George I.
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Abstract
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Introduction: The extent of lymphadenectomy in the surgical treatment of gastric cancer is a topic of controversy among surgeons. This study was conducted to analyze the American National Cancer Database (NCDB) and conclude the optimal extent of lymphadenectomy for gastric adenocarcinoma.
Methods: The NCDB for gastric cancer was utilized. Patients who received at least a partial gastrectomy were included. Patients with metastatic disease, unknown TNM stages, R1/R2 resection, or treated with a palliative intent were excluded. Joinpoint regression was used to identify the extent of lymphadenectomy that reflects the optimal survival. Cox regression analysis and Bayesian information criterion were used to identify significant survival predictors. Kaplan-Meier was applied to study overall survival and stage migration.
Results: 40,281 patients of 168,377 met the inclusion criteria. Joinpoint analysis showed that dissection of 29 nodes provides the optimal median survival for the overall population. Regression analysis reported the cutoff ≥29 to have a better fit in the prognostic model than that of ≥15. Dissection of ≥29 nodes in the higher stages provides a comparable overall survival to the immediately lower stage. Nonetheless, the retrieval of ≥15 nodes proved to be adequate for staging without a significant stage migration compared to ≥29 nodes.
Conclusion: The extent of lymphadenectomy in gastric adenocarcinoma is a marker of improved resection which reflects in a longer overall survival. Our analysis concludes that the dissection of ≥15 nodes is adequate for staging. However, the dissection of 29 nodes might be needed to provide a significantly improved survival.
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KEYWORD
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Gastric cancer, Lymphadenectomy, Survival, Cancer staging
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