Construction of a nomogram to predict overall survival for patients with M1 stage of colorectal cancer: A retrospective cohort study

医学 列线图 结直肠癌 内科学 比例危险模型 回顾性队列研究 队列 流行病学 多元统计 肿瘤科 多元分析 生存分析 阶段(地层学) 癌症 统计 生物 古生物学 数学
作者
Hua Ge,Yan Yan,Ming Xie,Lingfei Guo,Dai Tang
出处
期刊:International Journal of Surgery [Elsevier]
卷期号:72: 96-101 被引量:23
标识
DOI:10.1016/j.ijsu.2019.10.021
摘要

The M1 stage of colorectal cancer (CRC) has a poor prognosis. The aim of this study is to develop a reliable tool for the prediction for CRC patients with M1 stage, thus assisting the strategy of clinical diagnosis and treatment.CRC patient information collected in the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 was extracted and evaluated. Multivariate analysis with Cox proportional hazards regression identified risk factors that predicted overall survival (OS) and the results were used to construct a nomogram to predict 3-, and 5-year OS in CRC patients with M1 stage. The Kaplan-Meier curve was plotted to evaluate OS differences.A total of 19,796 patients from the SEER database were included for analysis. All patients were randomly allocated to 2 cohorts, the training cohort (n = 13,860) and the validation cohort (n = 5936). Patients' age at diagnosis; gender; race; tumor site; tumor grade; T and N stage; brain, lung, bone, and liver metastasis status; marital status; and therapy were associated with survival in the multivariate models. All these factors were incorporated to construct a nomogram. Additionally, we divide all 19,796 patients into high-risk group and low-risk group according to our nomogram, and plotted Kaplan-Meier curve. The result indicated that patients with higher risk had worse survival outcomes.Our predictive model has the potential to provide an individualized risk estimate of survival in CRC patients with M1 stage.

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
陌上苏凉完成签到,获得积分10
刚刚
Ava应助嘻嘻哈哈采纳,获得10
刚刚
刚刚
1秒前
积极凌兰完成签到 ,获得积分10
2秒前
今后应助秀丽的小懒虫采纳,获得10
2秒前
hqlran完成签到,获得积分10
3秒前
量子星尘发布了新的文献求助10
4秒前
WX完成签到,获得积分10
4秒前
5秒前
未来完成签到,获得积分20
5秒前
沉静傻姑发布了新的文献求助10
6秒前
6秒前
7秒前
hoongyan完成签到 ,获得积分10
7秒前
超级的幻然完成签到,获得积分10
7秒前
mmol完成签到,获得积分10
8秒前
gdh发布了新的文献求助10
8秒前
哈哈完成签到,获得积分10
8秒前
Jasper应助未来采纳,获得10
8秒前
9秒前
蓝色雪狐完成签到,获得积分20
9秒前
9秒前
淑儿哥哥发布了新的文献求助10
10秒前
cch发布了新的文献求助30
10秒前
11秒前
孙元应助脆啵啵马克宝采纳,获得10
11秒前
11秒前
甜橙完成签到,获得积分10
12秒前
13秒前
13秒前
13秒前
考博圣体发布了新的文献求助10
13秒前
14秒前
14秒前
Cindy发布了新的文献求助10
14秒前
16秒前
16秒前
hanatae发布了新的文献求助10
16秒前
18秒前
高分求助中
2025-2031全球及中国金刚石触媒粉行业研究及十五五规划分析报告 12000
(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
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5695131
求助须知:如何正确求助?哪些是违规求助? 5100385
关于积分的说明 15215391
捐赠科研通 4851561
什么是DOI,文献DOI怎么找? 2602454
邀请新用户注册赠送积分活动 1554227
关于科研通互助平台的介绍 1512186