Clinical and pathological characteristics of and predictive model for colorectal neuroendocrine tumors

Jiuyue Ma; Xiaoqian Ma; Jie Xing; Ruyun Song; Yang Zhang; Mo Liu; Shuilong Guo; Qian Zhang; Jing Wu

Heliyon (Aug 2024)

Clinical and pathological characteristics of and predictive model for colorectal neuroendocrine tumors

Jiuyue Ma,
Xiaoqian Ma,
Jie Xing,
Ruyun Song,
Yang Zhang,
Mo Liu,
Shuilong Guo,
Qian Zhang,
Jing Wu

Affiliations

Jiuyue Ma: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Xiaoqian Ma: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Jie Xing: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Ruyun Song: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Yang Zhang: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Mo Liu: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Shuilong Guo: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Qian Zhang: Corresponding author. Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China.; Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China
Jing Wu: Corresponding author. Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China.; Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesions of Digestive Disease, Beijing, 100050, China

Journal volume & issue: Vol. 10, no. 15
p. e35720

Abstract

Read online

Background: The incidence of colorectal neuroendocrine tumors (NETs) is increasing, causing a social burden. At present, there is no specific prognostic model for colorectal NETs. Thus, an accurate model is needed to predict the prognosis of patients with colorectal NETs. Aim: We aimed to create a new nomogram to predict the prognosis of patients with colorectal NETs. Furthermore, we compared nomogram we established and the 8th edition of the AJCC TNM staging system in terms of prediction ability and accuracy. Methods: A total of 3353 patients with colorectal NETs were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier analyses were used to assess overall survival (OS) and cancer-specific survival (CSS). Additionally, LASSO regression was used to select variables for constructing the nomogram. Furthermore, the C-index and time-dependent receiver operating characteristic (tdROC) curve were used to evaluate the nomogram. Decision curve analysis (DCA) was performed to compare the clinical utility of the nomogram with that of the TNM system. An external validation cohort (N = 61) was established to evaluate the nomogram's prediction accuracy. Results: A total of 9 factors (age, sex, marital status, tumor size, T stage, M stage, N stage, grade, and surgery) were selected based on the results of LASSO analysis. The C-indexes of the nomogram in the training and validation sets were 0.807 and 0.775, respectively, which indicated that the nomogram had better prediction accuracy than TNM staging (C-index = 0.700 in the training set and 0.652 in the validation set). The C-index of the nomogram in the external validation cohort was 0.954, indicating that the nomogram had satisfactory prediction accuracy. The results of DCA revealed that the survival nomogram possessed greater utility in clinical practice. Conclusion: We determined the OS and CSS of patients with colorectal NETs and developed a robust and clinically useful survival nomogram.

Published in Heliyon

ISSN: 2405-8440 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Science (General); Social Sciences: Social sciences (General)
Website: https://www.cell.com/heliyon/home

About the journal

Abstract

Keywords