Incidence, survival, and prognostic factors for patients with gastrointestinal mixed neuroendocrine non-neuroendocrine neoplasms: a SEER population-based study

Author:

Xu Boqi1,Zhang Fan1,Wu Runda1,Peng Yao1,Mao Zhongqi1,Tong Shan1

Affiliation:

1. The First Affiliated Hospital of Soochow University

Abstract

Abstract Background Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs) are a group of rare and significantly heterogeneous tumors with limited research currently available. This study aimed to analyze the incidence, survival, and prognostic factors of gastrointestinal MiNENs.Methods We selected data from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2019 and evaluated the incidence trend of gastrointestinal MiNENs during this period. We utilized univariate and multivariate Cox analysis to assess independent factors of prognosis and established a nomogram to predict 1-, 2-, and 3-year cancer-specific survival (CSS). Calibration and receiver operating characteristic (ROC) curves were drawn to validate the accuracy and reliability of the model. Decision curve analysis (DCA) was used to assess the clinical utility of the model.Results The overall incidence of gastrointestinal MiNENs has been increasing annually. Multivariate Cox regression analysis revealed that tumor grade, size, lymph node metastasis, distant metastasis, and surgery were independent risk factors for CSS in MiNENs patients. Based on these risk factors, the 1-, 2-, and 3-year CSS nomogram model for MiNENs patients was established. Calibration curves, ROC curves, and DCA of the training and validation sets demonstrated that this model had good accuracy and clinical utility.Conclusion Gastrointestinal MiNENs are rare tumors with an increasing incidence rate. The nomogram model is expected to be an effective tool for personalized prognosis prediction in MiNENs patients, which may benefit clinical decision-making.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3