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Poster Display session 2

5374 - Establishment of Prognostic Nomogram Based on the Metastatic Lymph Nodes Ratio for Patients with Gastric Neuroendocrine Tumour

Date

29 Sep 2019

Session

Poster Display session 2

Topics

Tumour Site

Neuroendocrine Neoplasms

Presenters

yaobin lin

Citation

Annals of Oncology (2019) 30 (suppl_5): v564-v573. 10.1093/annonc/mdz256

Authors

Y. lin1, Y. Wang1, H. lin1, J. Li2, J. Wu1

Author affiliations

  • 1 Radiation Oncology, Fujian Medical University Cancer Hospital, 350014 - Fuzhou/CN
  • 2 Radiation, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Teaching Hospital of Fujian Medical University, 361003 - Xiamen/CN

Resources

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Abstract 5374

Background

We aimed to validate the prognostic effects of the metastatic lymph nodes ratio (LNR) in patients with gastric neuroendocrine tumour (G-NET), and establish a nomogram to predict the survival of patients.

Methods

A total of 315 patients with G-NET in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 were included. Pearson correlation and Cox regression were performed to identify the association between LNR and survival. Nomograms were adopted to predict overall survival (OS) and cancer-specific survival (CSS).

Results

LNR has a negative correlation with OS and CSS (Pearson correlation coefficients: 0.343, P < 0.001; 0.389, P < 0.001, respectively). The multivariate analyses indicated age, tumour site, differentiation, T staging, M staging, chemotherapy and LNR were independent prognostic factors for both OS and CSS. The concordance index (C-index) of the nomograms for OS and CSS were superior to those of the TNM classification (0.773 vs. 0.731; 0.807 vs. 0.769, respectively). According to the area under the ROC curve (AUC), the predictive ability of the new nomogram for 3- and 5-year OS was better than TNM classification (0.908 vs. 0.846, P = 0.004; 0.899 vs. 0.827, P < 0.001, respectively). And the predictive ability of the new nomogram for 1-, 3- and 5-year CSS was better than TNM classification (0.936 vs. 0.848, P = 0.007; 0.910 vs. 0.855, P = 0.003; 0.894 vs. 0.836, P = 0.001, respectively).

Conclusions

LNR was an independent predictor of OS and CSS in G-NET. The nomograms based on the LNR were superior to the TNM classification in predicting the clinical outcomes for G-NET patients.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Yaobin Lin.

Funding

The Fujian Province Natural Science Foundation (2017J01260), Joint Funds for the Innovation of Science and Technology, Fujian province (2017Y9074), and the Peking University Cancer Hospital & Institute, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education/Beijing (2017 Open Project-9).

Disclosure

All authors have declared no conflicts of interest.

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