[Establishment and validation of a nomogram for predicting prognosis of gastric neuroendocrine neoplasms based on data from 490 cases in a single center]

[基于单中心490例胃神经内分泌肿瘤病例数据,建立并验证预测预后的列线图]

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Abstract

OBJECTIVE: To develop and validate a nomogram for predicting outcomes of patients with gastric neuroendocrine neoplasms (G-NENs). METHODS: We retrospectively collected the clinical data from 490 patients with the diagnosis of G-NEN at our medical center from 2000 to 2021. Log-rank test was used to analyze the overall survival (OS) of the patients. The independent risk factors affecting the prognosis of G-NEN were identified by Cox regression analysis to construct the prognostic nomogram, whose performance was evaluated using the C-index, receiver-operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, DCA, and AUDC. RESULTS: Among the 490 G-NEN patients (mean age of 58.6±10.92 years, including 346 male and 144 female patients), 130 (26.5%) had NET G1, 54 (11.0%) had NET G2, 206 (42.0%) had NEC, and 100 (20.5%) had MiNEN. None of the patients had NET G3. The numbers of patients in stage Ⅰ-Ⅳ were 222 (45.3%), 75 (15.3%), 130 (26.5%), and 63 (12.9%), respectively. Univariate and multivariate analyses identified age, pathological grade, tumor location, depth of invasion, lymph node metastasis, distant metastasis, and F-NLR as independent risk factors affecting the survival of the patients (P < 0.05). The C-index of the prognostic nomogram was 0.829 (95% CI: 0.800-0.858), and its AUC for predicting 1-, 3- and 5-year OS were 0.883, 0.895 and 0.944, respectively. The calibration curve confirmed a good consistency between the model prediction results and the actual observations. For predicting 1-year, 3-year and 5-year OS, the TNM staging system and the nomogram had AUC of 0.033 vs 0.0218, 0.191 vs 0.148, and 0.248 vs 0.197, respectively, suggesting higher net benefit and better clinical utility of the nomogram. CONCLUSION: The prognostic nomogram established in this study has good predictive performance and clinical value to facilitate prognostic evaluation of individual patients with G-NEN.

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