A risk classification system predicting the cancer-specific survival for postoperative stage IB non-small-cell lung cancer patients without lymphovascular and visceral pleural invasion

医学 淋巴血管侵犯 肿瘤科 内科学 肺癌 癌症分期 阶段(地层学) 癌症 转移 生物 古生物学
作者
Zegui Tu,Caili Li,Tian Tian,Qian Chen
出处
期刊:Lung Cancer [Elsevier BV]
卷期号:161: 114-121 被引量:9
标识
DOI:10.1016/j.lungcan.2021.09.014
摘要

Background This study aims to formulate a risk classification system predicting the cancer-specific survival (CSS) for postoperative stage IB NSCLC patients without lymphovascular (LVI) and visceral pleural (VPI) invasion to guide treatment decision making and assist patient counseling. Method A total of 4,238 patients were included in this study. Patients were randomly divided into training and validation cohorts (7:3). The risk factors were identified by Cox regression. Concordance index (C-index), calibration curves, and Decision Curve Analyses (DCAs) were used to evaluate the performance of nomogram. We applied X-tile to calculate the optimal cut-off points and develop a risk classification system. The Kaplan-Meier method was conducted to evaluate CSS in different risk groups, and the significance was evaluated by log-rank test. Result Among the 4,238 patients, 1,014(23.9%) suffered cancer-specific death. In the training cohort, univariable and multivariable Cox regression analyses revealed that age, gender, pathological subtype, grade, tumor size, the number of removed lymph nodes and surgical type were significantly associated with CSS. According to these results, the nomogram was formulated. The C-index of the prediction model was 0.755 in the training cohort (95%CI: 0.733–0.777) and 0.726 (95%CI: 0.695–0.757) in the validation cohort. The calibration curves in training and validation cohort exhibited good agreement between the predictions and actual observations. The Decision Curve Analyses (DCAs) showed net benefit can be achieved for nomogram. A risk classification system was further constructed that could perfectly classify patients into three risk groups. Conclusion In this study, we constructed a nomogram to support individualized evaluation of CSS and a risk classification system to identify patients in the different risk groups in stage IB NSCLC patients without LVI and VPI. These tools could be useful in guiding treatment decision making and assisting patient counseling.

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
王院士完成签到,获得积分10
1秒前
1秒前
桐桐应助会长采纳,获得10
1秒前
1秒前
HDrinnk完成签到,获得积分10
1秒前
1秒前
太叔夜南完成签到,获得积分10
2秒前
2秒前
牧童1997发布了新的文献求助10
2秒前
彭于晏应助摄氏度26采纳,获得10
2秒前
董竹君发布了新的文献求助10
2秒前
俏皮鸡翅完成签到,获得积分10
2秒前
俊逸的芾发布了新的文献求助10
3秒前
情怀应助李悟尔采纳,获得10
3秒前
biancaliu发布了新的文献求助10
3秒前
慕青应助永远之久远采纳,获得10
3秒前
萧萧发布了新的文献求助10
4秒前
感动澜完成签到,获得积分10
4秒前
xyf完成签到,获得积分10
5秒前
donwe发布了新的文献求助10
5秒前
苗条的素发布了新的文献求助30
5秒前
6秒前
Smart发布了新的文献求助10
6秒前
NexusExplorer应助勋出色采纳,获得10
6秒前
彭于晏应助caili采纳,获得10
6秒前
6秒前
7秒前
无极微光应助weiliu采纳,获得20
7秒前
liu发布了新的文献求助10
8秒前
8秒前
yuuuu发布了新的文献求助10
9秒前
桃子发布了新的文献求助10
9秒前
9秒前
10秒前
谨慎鞅完成签到,获得积分10
10秒前
10秒前
汪欣怡完成签到,获得积分10
10秒前
10秒前
小蘑菇应助sjc采纳,获得10
10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
Cronologia da história de Macau 5000
Braunwald’s Heart Disease, 2 Vol Set A Textbook of Cardiovascular Medicine 13th Edition 1000
Petrology and Plate Tectonics 800
Prompt Engineering for Clinicians: Harnessing AI in Everyday Medical Practice 600
Electrode Potentials 550
Handbook Of Synthetic Methodologies And Protocols Of Nanomaterials 500
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 内科学 物理 复合材料 催化作用 细胞生物学 光电子学 物理化学 电极 基因 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 6996012
求助须知:如何正确求助?哪些是违规求助? 8671941
关于积分的说明 18388427
捐赠科研通 6469444
什么是DOI,文献DOI怎么找? 3098825
关于科研通互助平台的介绍 2161428
邀请新用户注册赠送积分活动 2075096