Incidence and survival trends for gastric neuroendocrine neoplasms: An analysis of 3523 patients in the SEER database.

来自 PUBMED

作者:

Cao LLLu JLin JXZheng CHLi PXie JWWang JBChen QYLin MTu RHHuang CM

展开

摘要:

The aim of this study is to investigate trends in the incidence and survival of patients with gastric neuroendocrine neoplasms (g-NENs). and methods: Patients diagnosed with g-NENs (n = 3523) were identified from the Surveillance, Epidemiology and End Results (SEER) database. Patients diagnosed with g-NENs (n = 199) in our department were designated as a validation dataset. Nomograms were adopted to predict disease-specific survival (DSS) and overall survival (OS). The incidence of g-NENs is steadily increasing over time at a rate higher than any other cancer [annual percentage change (APC) = 6.3%, 95% confidence interval (CI) 5.6-7.0]. The 1-, 3-, and 5-year DSS rates were 87%, 78.6% and 70.6%, respectively, and the corresponding OS rates were 84.3%, 71.9%, and 53.7%, respectively. The multivariate analysis identified age, sex, T stage, M stage, and histological type as independent prognostic factors for both DSS and OS (all P < .05). The concordance indexes of the nomograms for DSS and OS in the training dataset were superior to those of the traditional tumor-node-metastasis (TNM) staging system [0.899 and 0.849 versus 0.864 and 0.783]. Calibration plots of the nomograms showed that the probability of DSS and OS closely corresponded to the actual observations in both the SEER-based training dataset and our inpatient validation dataset. The incidence of g-NENs has been steadily increasing at a rapid rate over the past four decades. The nomograms based on the analysis of the SEER database were superior to the TNM staging system in predicting the clinical outcomes for g-NEN patients.

收起

展开

DOI:

10.1016/j.ejso.2018.01.082

被引量:

18

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(380)

参考文献(0)

引证文献(18)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读