Risk of Venous Thromboembolism by Cancer Type: A Network Meta-Analysis

医学 癌症 荟萃分析 内科学 相对风险 肺癌 肿瘤科 置信区间
作者
Marissa Betts,Xuejun Liu,Daniela R. Junqueira,Kyle Fahrbach,Binod Neupane,Sarah M. Ronnebaum,Amol Dhamane
出处
期刊:Seminars in Thrombosis and Hemostasis [Georg Thieme Verlag KG]
卷期号:50 (03): 328-341 被引量:3
标识
DOI:10.1055/s-0044-1779672
摘要

Abstract Patients with cancer have an increased risk of venous thromboembolism (VTE). Comparing tumor-specific VTE risk is complicated by factors such as surgery, disease stage, and chemotherapy. Network meta-analysis (NMA) using cancer types as network nodes enabled us to estimate VTE rates by leveraging comparisons across cancer types while adjusting for baseline VTE risk in individual studies. This study was conducted to estimate the risk of VTE by cancer type and factors influencing VTE risk. The Embase, MEDLINE, and Cochrane Library repositories were systematically searched to identify clinical trials and observational studies published from 2005 to 2022 that assessed the risk of primary cancer-related VTE among two or more distinct cancer types. Studies with similar cancer populations and study methods reporting VTE occurring within 1 year of diagnosis were included in the NMA. Relative VTE rates across cancer types were estimated with random-effects Bayesian NMAs. Absolute VTE rates were calculated from these estimates using the average VTE incidence in lung cancer (the most frequently reported type) as the “anchor.” From 2,603 records reviewed, 30 studies were included in this NMA. The general network described 3,948,752 patients and 18 cancer types: 3.1% experienced VTE within 1 year of diagnosis, with cancer-specific rates ranging from 0.7 to 7.4%. Consistent with existing VTE risk prediction tools, pancreatic cancer was associated with higher-than-average VTE risk. Other cancer types with high VTE risk were brain and ovarian cancers. The relative rankings of VTE risk for certain cancers changed based on disease stage and/or receipt of chemotherapy or surgery.
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
光亮面包完成签到 ,获得积分10
刚刚
小猪啵比完成签到 ,获得积分10
刚刚
小智发布了新的文献求助10
刚刚
毛慢慢发布了新的文献求助10
刚刚
lilac应助1234567890采纳,获得10
1秒前
OYE发布了新的文献求助10
1秒前
木木发布了新的文献求助10
2秒前
zhy完成签到,获得积分10
3秒前
3秒前
自由的刺猬完成签到,获得积分20
3秒前
潇洒甜瓜发布了新的文献求助10
4秒前
jessie完成签到,获得积分10
4秒前
化学胖子完成签到,获得积分10
4秒前
5秒前
CTL关闭了CTL文献求助
5秒前
詹严青完成签到,获得积分10
5秒前
5秒前
5秒前
5秒前
顾矜应助Long采纳,获得10
5秒前
6秒前
木木完成签到,获得积分20
6秒前
爆米花应助1ssd采纳,获得10
7秒前
Lucas应助reck采纳,获得10
7秒前
西瓜完成签到,获得积分10
7秒前
KDC发布了新的文献求助10
7秒前
潇湘完成签到 ,获得积分10
7秒前
打打应助sss采纳,获得20
7秒前
nicemice完成签到,获得积分10
7秒前
8秒前
GOODYUE发布了新的文献求助10
8秒前
热情的阿猫桑完成签到,获得积分10
9秒前
Gaojin锦完成签到,获得积分10
9秒前
9秒前
小二郎应助愉快的鞯采纳,获得10
10秒前
协和_子鱼发布了新的文献求助10
10秒前
10秒前
10秒前
Danboard发布了新的文献求助10
10秒前
HC完成签到 ,获得积分10
11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 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759