Analysis of risk factors for recurrence after curative resection of well-differentiated pancreatic neuroendocrine tumors based on the new grading classification.

分级(工程) 回顾性队列研究 胰腺 切除术 胰腺癌 放射科
作者
Kosuke Tsutsumi,Takao Ohtsuka,Minoru Fujino,Hiroshi Nakashima,Shinichi Aishima,Junji Ueda,Shunichi Takahata,Masafumi Nakamura,Yoshinao Oda,Masao Tanaka
出处
期刊:Journal of Hepato-biliary-pancreatic Sciences [Wiley]
卷期号:21 (6): 418-25 被引量:50
标识
DOI:10.1002/jhbp.47
摘要

It is difficult to predict the malignant potential of pancreatic neuroendocrine tumors (PNETs) precisely. This study investigated the validity of a new grading system adopted by the World Health Organization 2010 classification to determine risk factors for recurrence of PNETs.Data of 70 patients with PNETs who underwent curative resection were retrospectively examined by uni- and multivariate analyses. Histopathological findings were re-reviewed by experienced pathologists. NET G1 was defined as mitotic count <2 per 10 high power fields (HPF) and/or ≤2% Ki67 index, and NET G2 as 2-20 mitosis per 10 HPF and/or 3-20% Ki67 index.There were 58 patients with NET G1 and 12 with NET G2. Incidence of recurrence was 11.4%. Univariate analysis demonstrated significant risk factors for recurrence including NET G2 of histological grade (P = 0.0089), male gender (P = 0.0333), tumor size ≥ 20 mm (P = 0.0117), lymph node metastasis (P = 0.0004), liver metastasis (P < 0.0001), lymphatic invasion (P = 0.046), and neural invasion (P = 0.0002). By multivariate analysis, histological grade (hazard ratio; 59.76, P = 0.0022) and neural invasion (hazard ratio; 147.49, P = 0.0016) were significantly associated with recurrence of PNETs.This study confirmed the prognostic relevance of the new grading classification and that evaluation of perineural invasion and histological grade should be considered as prognostic predictors in well-differentiated PNETs (NET G1 and G2).

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
huifang完成签到,获得积分10
刚刚
个性迎彤发布了新的文献求助10
刚刚
脑洞疼应助王金金采纳,获得10
1秒前
HH完成签到,获得积分10
1秒前
小巧风华完成签到 ,获得积分10
1秒前
哆1627_完成签到,获得积分10
2秒前
2秒前
YifanWang应助那就发个呆采纳,获得30
2秒前
hu完成签到,获得积分10
2秒前
yhp完成签到 ,获得积分10
2秒前
~静完成签到,获得积分10
2秒前
图书馆完成签到,获得积分10
3秒前
王三岁完成签到,获得积分10
3秒前
3秒前
3秒前
张春梦紫发布了新的文献求助10
3秒前
小z发布了新的文献求助10
3秒前
交大市长完成签到,获得积分10
3秒前
3秒前
3秒前
雅痞男士完成签到,获得积分10
4秒前
GGBOND完成签到,获得积分20
4秒前
4秒前
Liuhui完成签到,获得积分10
5秒前
gongwei完成签到,获得积分20
5秒前
吴金菊完成签到,获得积分10
5秒前
元七七完成签到 ,获得积分10
5秒前
夏昼苦长发布了新的文献求助10
5秒前
crane完成签到,获得积分10
6秒前
Nature已接受完成签到,获得积分10
6秒前
牛牛发布了新的文献求助10
7秒前
7秒前
酷波er应助Lalny采纳,获得10
7秒前
7秒前
小蘑菇应助郭WL采纳,获得10
7秒前
Viikey完成签到,获得积分0
7秒前
哎呀呀发布了新的文献求助10
7秒前
CipherSage应助小泽采纳,获得10
7秒前
GGBOND发布了新的文献求助10
7秒前
陶醉的鹤轩完成签到,获得积分10
7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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6362494
求助须知:如何正确求助?哪些是违规求助? 8176257
关于积分的说明 17226680
捐赠科研通 5417220
什么是DOI,文献DOI怎么找? 2866743
邀请新用户注册赠送积分活动 1843871
关于科研通互助平台的介绍 1691640