Liverpool Lung Project lung cancer risk stratification model: calibration and prospective validation

医学 肺癌 十分位 接收机工作特性 入射(几何) 绝对风险降低 人口 全国肺筛查试验 肺癌筛查 内科学 外科 置信区间 统计 数学 环境卫生 几何学
作者
John K. Field,Daniel Vulkan,Michael P.A. Davies,Stephen W. Duffy,Rhian Gabe
出处
期刊:Thorax [BMJ]
卷期号:76 (2): 161-168 被引量:74
标识
DOI:10.1136/thoraxjnl-2020-215158
摘要

BACKGROUND: Early detection of lung cancer saves lives, as demonstrated by the two largest published low-dose CT screening trials. Optimal implementation depends on our ability to identify those most at risk. METHODS: Version 2 of the Liverpool Lung Project risk score (LLPv2) was developed from case-control data in Liverpool and further adapted when applied for selection of subjects for the UK Lung Screening Trial. The objective was to produce version 3 (LLPv3) of the model, by calibration to national figures for 2017. We validated both LLPv2 and LLPv3 using questionnaire data from 75 958 individuals, followed up for lung cancer over 5 years. We validated both discrimination, using receiver operating characteristic (ROC) analysis, and absolute incidence, by comparing deciles of predicted incidence with observed incidence. We calculated proportionate difference as the percentage excess or deficit of observed cancers compared with those predicted. We also carried out Hosmer-Lemeshow tests. RESULTS: There were 599 lung cancers diagnosed over 5 years. The discrimination of both LLPv2 and LLPv3 was significant with an area under the ROC curve of 0.81 (95% CI 0.79 to 0.82). However, LLPv2 overestimated absolute risk in the population. The proportionate difference was -58.3% (95% CI -61.6% to -54.8%), that is, the actual number of cancers was only 42% of the number predicted.In LLPv3, calibrated to national 2017 figures, the proportionate difference was -22.0% (95% CI -28.1% to -15.5%). CONCLUSIONS: While LLPv2 and LLPv3 have the same discriminatory power, LLPv3 improves the absolute lung cancer risk prediction and should be considered for use in further UK implementation studies.
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
尹冰露发布了新的文献求助10
2秒前
迅速雨琴发布了新的文献求助10
2秒前
luhuiluhui完成签到,获得积分10
4秒前
火星上山槐完成签到,获得积分10
5秒前
zzz完成签到,获得积分10
5秒前
6秒前
胡明月发布了新的文献求助10
7秒前
superyu完成签到,获得积分20
9秒前
10秒前
迅速雨琴完成签到,获得积分10
10秒前
怡然冷安完成签到,获得积分10
12秒前
anian发布了新的文献求助10
13秒前
13秒前
GOD伟完成签到,获得积分0
14秒前
牙膏完成签到,获得积分10
14秒前
今后应助迅速雨琴采纳,获得10
14秒前
14秒前
num5thWindMaster完成签到,获得积分10
14秒前
忐忑的书桃完成签到 ,获得积分10
14秒前
Epiphany完成签到 ,获得积分10
15秒前
Reid完成签到 ,获得积分10
15秒前
任罗川完成签到,获得积分10
15秒前
斐乐完成签到,获得积分10
15秒前
laojian完成签到 ,获得积分10
15秒前
biozy完成签到,获得积分10
17秒前
17秒前
曾经安萱完成签到,获得积分10
17秒前
我不到啊完成签到 ,获得积分10
17秒前
如花不如画完成签到 ,获得积分10
18秒前
19秒前
v0id应助芭乐王子采纳,获得10
19秒前
刘丽梅完成签到 ,获得积分0
20秒前
Royzeng完成签到 ,获得积分10
20秒前
希望天下0贩的0应助小猪采纳,获得10
20秒前
QIAOQIAO发布了新的文献求助10
20秒前
xiao完成签到 ,获得积分10
21秒前
哈哈完成签到,获得积分10
21秒前
qi完成签到 ,获得积分10
21秒前
嘲鸫完成签到,获得积分10
22秒前
直率一手完成签到 ,获得积分10
22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
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Les chinois de jakarta: temples et vie collective 500
The fast track to determining transfer functions of linear circuits: The student guide 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
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 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7627452
求助须知:如何正确求助?哪些是违规求助? 9202004
关于积分的说明 19728646
捐赠科研通 7197338
什么是DOI,文献DOI怎么找? 3273849
关于科研通互助平台的介绍 2436168
邀请新用户注册赠送积分活动 2269948