Further Classification for Node-Positive Gastric Neuroendocrine Neoplasms View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Linda M. Pak, Tingsong Yang, Jiping Wang

ABSTRACT

BACKGROUND: For gastric neuroendocrine neoplasms (GNEN), the current AJCC lymph node (N) stage classifies patients into N0/N1 disease (with/without locoregional nodal metastases); however, this does not account for the number of involved nodes. The objective of this study was to evaluate the prognostic significance of the number of involved locoregional nodes among resected GNEN. METHODS: The National Cancer Database (2004-2014) was queried for GNEN patients who had undergone partial/total gastrectomy with known nodal status. Nearest-neighborhood grouping was used to identify survival clusters by number of metastatic nodes and to use these groupings to construct a new N classification (pN). External validation was performed using the SEER database. Kaplan-Meier analysis and Cox regression models were used to assess the prognostic strength of the pN classification. RESULTS: One thousand two hundred seventy-five patients met study inclusion criteria. Patients with 1-6 positive nodes (pN1) demonstrated a distinct survival pattern from patients with > 6 positive nodes (pN2) as well as those with no positive nodes (N0) {5-year OS N0: 80% (95% CI 77-83%) vs. 65% (95% CI 61-69%) vs. 43% (95% CI 33-53%), p < 0.001}. On external validation, the pN classification demonstrated strong discriminatory ability for survival {5-year OS N0: 70% (95% CI 65-75%) vs. pN1:53% (95% CI 46-59%) vs. pN2:18% (95% CI 9-29%), p < 0.001}. On multivariable analysis, the pN classification remained an independent predictor of OS. CONCLUSIONS: The number of metastatic lymph nodes is an independent prognostic factor in GNEN. Current AJCC N1 disease contains two groups of patients with distinctive prognoses, hence needs to be subclassified into pN1 (1-6 positive lymph nodes) and pN2 (> 6 positive nodes). More... »

PAGES

720-729

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11605-018-3845-3

DOI

http://dx.doi.org/10.1007/s11605-018-3845-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105170547

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29951901


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