A real-world, population-based study of the trends for incidence and prognosis in high-grade neuroendocrine tumor of cervix

医学 列线图 入射(几何) 泊松回归 流行病学 宫颈癌 内科学 子宫颈 人口 阶段(地层学) 肿瘤科 人口学 癌症 物理 社会学 古生物学 光学 环境卫生 生物
作者
Xilin Yang,Wenju Guan,Lingna Kou,Mingming Wang,Hua Lai,Da-Jun Wu
出处
期刊:Current Problems in Cancer [Elsevier BV]
卷期号:46 (2): 100800-100800 被引量:2
标识
DOI:10.1016/j.currproblcancer.2021.100800
摘要

To explore the incidence and prognosis trends for high-grade cervical neuroendocrine tumor (HGCNET) and construct a nomogram to predict prognosis for HGCNET. Annual age-adjusted incidence of HGCNET from 1975 to 2015 was retrieved from the Surveillance, Epidemiology, and End Results program, the linear regression, poisson regression and annual percentage changes were used to assess the incidence trend. Also, trends for relative survival (RS) and overall survival (OS) in HGCNET patients from 1975 to 2015 were evaluated. From 1988 to 1975, 514 HGCNET patients were selected and divided into two cohorts with a ratio of 7:3. Nomogram to predict OS for these patients was constructed and validated. The incidence trend for HGCNET was unchanged in the past four decades (P = 0.734), but the proportion of HGCNET in diagnosed cervical cancer slightly increased from 0.9% in 1975 to 1.9% in 2015 (P < 0.001). The 5-year RS and OS for HGCNET in the study periods decreased steadily (RS: P = 0.009; OS: P = 0.008). Nomogram incorporating age, T stage, lymph-node positive, distant metastasis and surgery was constructed. The C-index of the nomogram was 0.716 (0.680-0.752), which was higher than the FIGO staging system. The incidence of HGCNET remained unchanged in the past four decades but the proportion of HGCNET has slightly increased. Besides, a steadily decreasing survival for HGCNET was observed in the study periods. A nomogram was constructed to better predict prognosis for HGCNET.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
wzzznh发布了新的文献求助10
1秒前
852发布了新的文献求助10
1秒前
lvdougao发布了新的文献求助10
2秒前
taku发布了新的文献求助10
3秒前
3秒前
lingling完成签到 ,获得积分10
4秒前
5秒前
华仔应助任性的外套采纳,获得10
6秒前
舒克大王发布了新的文献求助10
6秒前
6秒前
老朱发布了新的文献求助10
7秒前
谦让凌晴完成签到,获得积分10
8秒前
Gray发布了新的文献求助10
9秒前
HHTTY发布了新的文献求助10
9秒前
12秒前
12秒前
12秒前
彭于彦祖应助科研通管家采纳,获得80
12秒前
12秒前
13秒前
13秒前
情怀应助科研通管家采纳,获得10
13秒前
13秒前
英俊的铭应助科研通管家采纳,获得10
13秒前
无极微光应助科研通管家采纳,获得20
13秒前
ee应助Bin_Liu采纳,获得10
13秒前
13秒前
13秒前
13秒前
脑洞疼应助科研通管家采纳,获得10
13秒前
13秒前
13秒前
小二郎应助科研通管家采纳,获得10
13秒前
爆米花应助科研通管家采纳,获得10
14秒前
研友_VZG7GZ应助科研通管家采纳,获得10
14秒前
伯符完成签到 ,获得积分10
14秒前
拼搏的似狮完成签到,获得积分10
16秒前
星期日不上发条完成签到,获得积分10
18秒前
跳跃孤萍发布了新的文献求助10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 生物化学 化学工程 物理 计算机科学 复合材料 内科学 催化作用 物理化学 光电子学 电极 冶金 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6023152
求助须知:如何正确求助?哪些是违规求助? 7647904
关于积分的说明 16171707
捐赠科研通 5171525
什么是DOI,文献DOI怎么找? 2767225
邀请新用户注册赠送积分活动 1750545
关于科研通互助平台的介绍 1637079