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
班莉齐完成签到,获得积分10
刚刚
深情安青应助悲惨服务员采纳,获得10
1秒前
Aiman发布了新的文献求助10
2秒前
小太阳发布了新的文献求助10
3秒前
是问发布了新的文献求助10
4秒前
4秒前
S4ndy完成签到,获得积分10
4秒前
6秒前
凡凡发布了新的文献求助10
6秒前
桐桐应助曾欢采纳,获得10
6秒前
lqiqivv发布了新的文献求助10
7秒前
迷你的怀绿完成签到,获得积分10
8秒前
8秒前
8秒前
11秒前
qjl完成签到,获得积分20
11秒前
12秒前
孟祥合发布了新的文献求助10
12秒前
wjt发布了新的文献求助10
14秒前
14秒前
wanci应助凡凡采纳,获得10
14秒前
Min完成签到,获得积分10
15秒前
Adam发布了新的文献求助10
17秒前
20秒前
隐形君浩发布了新的文献求助100
20秒前
一介书生发布了新的文献求助10
21秒前
22秒前
ricedoctor完成签到,获得积分20
26秒前
26秒前
ghhu发布了新的文献求助10
28秒前
ricedoctor发布了新的文献求助10
29秒前
31秒前
Adam完成签到,获得积分10
32秒前
科研通AI2S应助neurospine采纳,获得10
34秒前
35秒前
裴瑞志完成签到,获得积分10
35秒前
番茄的蛋发布了新的文献求助10
37秒前
大模型应助孟祥合采纳,获得10
37秒前
一介书生完成签到 ,获得积分20
38秒前
39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
Research Handbook on the Law of the Paris Agreement 1000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Superabsorbent Polymers: Synthesis, Properties and Applications 500
Photodetectors: From Ultraviolet to Infrared 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 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 6352031
求助须知:如何正确求助?哪些是违规求助? 8166633
关于积分的说明 17187262
捐赠科研通 5408115
什么是DOI,文献DOI怎么找? 2863145
邀请新用户注册赠送积分活动 1840560
关于科研通互助平台的介绍 1689629