Clinicopathological and Prognostic Significance of Preoperative Prognostic Nutritional Index in Patients with Upper Urinary Tract Urothelial Carcinoma

医学 尿路上皮癌 比例危险模型 内科学 阶段(地层学) 肿瘤科 多元分析 上尿路 子群分析 生物标志物 泌尿系统 T级 总体生存率 泌尿科 癌症 膀胱癌 置信区间 化学 古生物学 生物 生物化学
作者
Jianyong Liu,Pengjie Wu,Shicong Lai,Xinda Song,Miao Wang,Xuan Wang,Shengjie Liu,Huimin Hou,Yaoguang Zhang,Jianye Wang
出处
期刊:Nutrition and Cancer [Routledge]
卷期号:74 (8): 2964-2974 被引量:6
标识
DOI:10.1080/01635581.2022.2049829
摘要

Purpose: To investigate the prognostic value of preoperative prognostic nutritional index (PNI) to predict oncological outcome and intravesical recurrence (IVR) in upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU). Method: This study involved the clinical data of 255 patients with UTUC who had undergone RNU from 2004 to 2019 at our institution. Patients were grouped according to an optimal value of preoperative PNI. Kaplan–Meier analyses and Cox proportional hazards models were used to analyze the associations of preoperative PNI with progression-free survival (PFS), cancer-specific survival (CSS), overall survival (OS), and IVR. Result: Patients with low PNI were more likely to be older, have higher tumor stage, higher eGFR, and multifocal lesions. No significant association was found between PNI and CSS, IVR. In subgroup analysis according to the risk stratification, low PNI was associated with worse PFS, CSS, and OS for patients with higher risk. Multivariate analyses showed that elevated PNI was an independent prognostic indicator for PFS (P = 0.014) and OS (P = 0.048). Conclusion: A low PNI is an independent predictor of PFS and OS in patients with UTUC after RNU. By subgroup analysis, the prognostic value of PNI was limited to patients with higher risk. PNI may become a useful biomarker to predict oncological outcomes in patients with UTUC after RNU.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Dr.L完成签到,获得积分10
1秒前
拉拉完成签到,获得积分20
1秒前
1秒前
1秒前
2秒前
CarolineSH完成签到 ,获得积分10
2秒前
SciGPT应助王翔采纳,获得10
2秒前
hd完成签到,获得积分10
2秒前
wansida完成签到,获得积分10
4秒前
浮游应助kukuku采纳,获得10
5秒前
xumengsuo发布了新的文献求助10
5秒前
乐乐发布了新的文献求助10
5秒前
天天快乐应助3100采纳,获得10
6秒前
czq发布了新的文献求助10
6秒前
6秒前
7秒前
陈玉发布了新的文献求助10
8秒前
8秒前
程雯慧发布了新的文献求助10
9秒前
xh发布了新的文献求助10
9秒前
10秒前
12秒前
云望发布了新的文献求助10
12秒前
12秒前
WN发布了新的文献求助10
15秒前
15秒前
llll完成签到 ,获得积分0
16秒前
17秒前
17秒前
拉拉关注了科研通微信公众号
19秒前
王翔发布了新的文献求助10
19秒前
充电宝应助可靠冥幽采纳,获得10
20秒前
李健应助云望采纳,获得10
20秒前
情怀应助xumengsuo采纳,获得10
20秒前
Jasper应助Dr.L采纳,获得10
20秒前
杀出个黎明举报求助违规成功
21秒前
YWang举报求助违规成功
21秒前
哆啦的空间站举报求助违规成功
21秒前
21秒前
21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
Acute Mountain Sickness 2000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5061232
求助须知:如何正确求助?哪些是违规求助? 4285332
关于积分的说明 13354142
捐赠科研通 4103141
什么是DOI,文献DOI怎么找? 2246531
邀请新用户注册赠送积分活动 1252193
关于科研通互助平台的介绍 1183040