Ye Wang1, Yiyi Zhang1, Hexin Lin1, Meifang Xu2, Xin Zhou3, Jinfu Zhuang1, Yuanfeng Yang1, Bin Chen1, Xing Liu1,4, Guoxian Guan1,4. 1. Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China. 2. Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China. 3. Departments of Colorectal Cancer Surgery, The First Affiliated Hospital of Xiamen University, Teaching Hospital of Fujian Medical University, Xiamen, China. 4. Department of Colorectal Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Abstract
BACKGROUND: The well-differentiated rectal neuroendocrine tumors (RNETs) can also have lymph node metastasis (LNM). Large multicenter data were reviewed to explore the risk factors for LNM in RNETs. Further, we developed a model to predict the risk of LNM in RNETs. METHODS: In total, 223 patients with RNETs from the Fujian Medical University Union Hospital, the First Affiliated Hospital of Fujian Medical University, and the First Affiliated Hospital of Xiamen University were retrospectively enrolled. Logistic regression analysis was performed to study the factors affecting LNM, and recursive partitioning analysis (RPA) was performed to stratify the risk of LNM. RESULTS: Among the 223 patients diagnosed with RNETs, the incidence of LNM was 10.8%. Univariate and multivariate regression analyses revealed that tumor size, World Health Organization (WHO) grade, and depth of tumor invasion were independent risk factors for LNM (p < 0.05). The area under the curve was 0.948 (95% confidence interval: 0.890-1.000). Furthermore, the incidence of LNM in patients divided into low- and high-risk groups according to RPA was 1.1% and 56.4%, respectively. CONCLUSION: Compared with tumor size, the depth of tumor invasion and WHO grade are more important factors in predicting LNM. Then, we developed a model based on RPA to predict the risk of LNM in RNETs and identify patients who are suitable for local resection.
BACKGROUND: The well-differentiated rectal neuroendocrine tumors (RNETs) can also have lymph node metastasis (LNM). Large multicenter data were reviewed to explore the risk factors for LNM in RNETs. Further, we developed a model to predict the risk of LNM in RNETs. METHODS: In total, 223 patients with RNETs from the Fujian Medical University Union Hospital, the First Affiliated Hospital of Fujian Medical University, and the First Affiliated Hospital of Xiamen University were retrospectively enrolled. Logistic regression analysis was performed to study the factors affecting LNM, and recursive partitioning analysis (RPA) was performed to stratify the risk of LNM. RESULTS: Among the 223 patients diagnosed with RNETs, the incidence of LNM was 10.8%. Univariate and multivariate regression analyses revealed that tumor size, World Health Organization (WHO) grade, and depth of tumor invasion were independent risk factors for LNM (p < 0.05). The area under the curve was 0.948 (95% confidence interval: 0.890-1.000). Furthermore, the incidence of LNM in patients divided into low- and high-risk groups according to RPA was 1.1% and 56.4%, respectively. CONCLUSION: Compared with tumor size, the depth of tumor invasion and WHO grade are more important factors in predicting LNM. Then, we developed a model based on RPA to predict the risk of LNM in RNETs and identify patients who are suitable for local resection.
Authors: Angela Dalia Ricci; Sara Pusceddu; Francesco Panzuto; Fabio Gelsomino; Sara Massironi; Claudio Giovanni De Angelis; Roberta Modica; Gianluca Ricco; Martina Torchio; Maria Rinzivillo; Natalie Prinzi; Felice Rizzi; Giuseppe Lamberti; Davide Campana Journal: J Clin Med Date: 2022-01-28 Impact factor: 4.241