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结合淋巴结比率为术后胃神经内分泌肿瘤患者建立预后模型。

Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients.

作者信息

Liu Wen, Wu Hong-Yu, Lin Jia-Xi, Qu Shu-Ting, Gu Yi-Jie, Zhu Jin-Zhou, Xu Chun-Fang

机构信息

Department of Gastroenterology, Changzhou Hospital of Traditional Chinese Medicine, Changzhou 213000, Jiangsu Province, China.

Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China.

出版信息

World J Gastrointest Oncol. 2024 Aug 15;16(8):3507-3520. doi: 10.4251/wjgo.v16.i8.3507.

Abstract

BACKGROUND

Lymph node ratio (LNR) was demonstrated to play a crucial role in the prognosis of many tumors. However, research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm (NEN) patients was limited.

AIM

To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.

METHODS

A total of 286 patients from the Surveillance, Epidemiology, and End Results database were divided into the training set and validation set at a ratio of 8:2. 92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set. Cox regression analysis was used to explore the relationship between LNR and disease-specific survival (DSS) of gastric NEN patients. Random survival forest (RSF) algorithm and Cox proportional hazards (CoxPH) analysis were applied to develop models to predict DSS respectively, and compared with the 8 edition American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging.

RESULTS

Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death. The RSF model exhibited the best performance in predicting DSS, with the C-index in the test set being 0.769 [95% confidence interval (CI): 0.691-0.846] outperforming the CoxPH model (0.744, 95%CI: 0.665-0.822) and the 8 edition AJCC TNM staging (0.723, 95%CI: 0.613-0.833). The calibration curves and decision curve analysis (DCA) demonstrated the RSF model had good calibration and clinical benefits. Furthermore, the RSF model could perform risk stratification and individual prognosis prediction effectively.

CONCLUSION

A higher LNR indicated a lower DSS in postoperative gastric NEN patients. The RSF model outperformed the CoxPH model and the 8 edition AJCC TNM staging in the test set, showing potential in clinical practice.

摘要

背景

淋巴结比率(LNR)已被证明在许多肿瘤的预后中起关键作用。然而,关于LNR在胃神经内分泌肿瘤(NEN)患者术后预后价值的研究有限。

目的

探讨LNR在胃NEN患者术后的预后价值,并结合LNR建立预后模型。

方法

将来自监测、流行病学和最终结果数据库的286例患者按8:2的比例分为训练集和验证集。将来自中国苏州大学附属第一医院的92例患者指定为测试集。采用Cox回归分析探讨LNR与胃NEN患者疾病特异性生存(DSS)之间的关系。分别应用随机生存森林(RSF)算法和Cox比例风险(CoxPH)分析建立预测DSS的模型,并与美国癌症联合委员会(AJCC)第8版肿瘤-淋巴结-转移(TNM)分期进行比较。

结果

多因素分析表明,LNR是胃NEN患者术后的独立预后因素,LNR越高,死亡风险越高。RSF模型在预测DSS方面表现最佳,测试集中的C指数为0.769 [95%置信区间(CI):0.691-0.846],优于CoxPH模型(0.744,95%CI:0.665-0.822)和AJCC第8版TNM分期(0.723,95%CI:0.613-0.833)。校准曲线和决策曲线分析(DCA)表明RSF模型具有良好的校准和临床效益。此外,RSF模型可以有效地进行风险分层和个体预后预测。

结论

较高的LNR表明胃NEN患者术后DSS较低。在测试集中,RSF模型优于CoxPH模型和AJCC第8版TNM分期,在临床实践中显示出潜力。

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