Prognostic assessment of lung adenocarcinoma patients with early-staging diseases: a nomogram based on coagulation-related factors

列线图 医学 阶段(地层学) 比例危险模型 肿瘤科 内科学 危险系数 一致性 置信区间 生物 古生物学
作者
Lei‐Lei Wu,Weikang Lin,Jiayi Qian,Shangshang Ma,Mingjun Li,Kun Li,Zhixin Li,Gang Lan,Dong Xie
出处
期刊:European Journal of Cardio-Thoracic Surgery [Oxford University Press]
卷期号:64 (5) 被引量:4
标识
DOI:10.1093/ejcts/ezad313
摘要

Early-stage lung adenocarcinoma (ADC) has a great heterogeneity in prognosis that is difficult to evaluate effectively. Thus, we developed and validated an effective nomogram prognostic model based on the clinical and laboratory characteristics of stage I-IIA ADC.We included 1585 patients with pathologically diagnosed stage I-IIA ADC who underwent surgery at Shanghai Pulmonary Hospital. The nomogram was constructed based on the peripheral blood test and coagulation test indicators and evaluated using Calibration plots, concordance index, decision curve analysis and the X-tile software. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method and the Cox proportional hazard regression model. The primary end point of this study was RFS.Thrombin time and 4 clinical indicators for RFS were integrated into nomograms. A favourable agreement between the nomogram prediction and validation was observed in the calibration curves for RFS probabilities. The concordance index of the nomogram to predict RFS was 0.736 (95% confidence interval, 0.717-0.755). Moreover, significant differences were shown between the high-risk and low-risk groups in RFS and OS (P < 0.001) after effective cut-off values of risk points were found based on the nomogram.We established and validated a prognostic nomogram including thrombin time to predict RFS and OS of stage I-IIA ADC patients. This nomogram provided an effective prediction ability for the prognosis of stage I-IIA ADC patients.
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
豆dou发布了新的文献求助10
刚刚
丘比特应助SS采纳,获得10
1秒前
1秒前
瑶一瑶完成签到,获得积分10
1秒前
接受所有饼干完成签到,获得积分10
1秒前
富贵儿完成签到,获得积分10
2秒前
MHB应助Khr1stINK采纳,获得10
2秒前
cinderella完成签到,获得积分10
3秒前
4秒前
lin发布了新的文献求助10
5秒前
tmpstlml完成签到,获得积分10
5秒前
LUNWENREQUEST完成签到,获得积分20
5秒前
5秒前
Orange应助科研通管家采纳,获得10
5秒前
科研通AI5应助科研通管家采纳,获得10
5秒前
科研通AI5应助科研通管家采纳,获得10
6秒前
共享精神应助科研通管家采纳,获得10
6秒前
搜集达人应助科研通管家采纳,获得10
6秒前
搜集达人应助科研通管家采纳,获得10
6秒前
CipherSage应助科研通管家采纳,获得10
6秒前
NexusExplorer应助科研通管家采纳,获得10
6秒前
我是老大应助科研通管家采纳,获得10
6秒前
RC_Wang应助科研通管家采纳,获得10
6秒前
酷波er应助科研通管家采纳,获得30
6秒前
111发布了新的文献求助10
7秒前
keyanlv完成签到,获得积分10
7秒前
富贵儿发布了新的文献求助10
9秒前
冯度翩翩完成签到,获得积分10
9秒前
sweetbearm应助健壮的涑采纳,获得10
9秒前
村里傻小子完成签到,获得积分20
9秒前
田様应助Khr1stINK采纳,获得10
10秒前
傲娇的凡旋应助小周采纳,获得10
11秒前
潇潇潇完成签到 ,获得积分10
11秒前
12秒前
英俊的铭应助XShu采纳,获得10
13秒前
Hello应助一只大肥猫采纳,获得10
14秒前
allyceacheng完成签到,获得积分10
14秒前
科研通AI5应助phd采纳,获得10
15秒前
15秒前
WTaMi完成签到 ,获得积分10
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808