Erschienen in:
27.06.2018 | 2018 SSAT Quick Shot Presentation
Further Classification for Node-Positive Gastric Neuroendocrine Neoplasms
verfasst von:
Linda M. Pak, Tingsong Yang, Jiping Wang
Erschienen in:
Journal of Gastrointestinal Surgery
|
Ausgabe 4/2019
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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).