亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Aspirin and Reducing Risk of Gastric Cancer: Systematic Review and Meta-Analysis of the Observational Studies

作者
Thin Thin Win,Saint Nway Aye,Joyce Lau Chui Fern,Cheng Ong Fei
出处
期刊:Journal of Gastrointestinal and Liver Diseases [Editura Medicală Universitară Iuliu Hatieganu]
卷期号:29 (2): 191-198 被引量:19
标识
DOI:10.15403/jgld-818
摘要

BACKGROUND AND AIMS: The latest meta-analysis on the role of aspirin on various cancers was published in early 2018. By including the latest and updated primary observational studies, we aimed to conduct this systematic review and meta-analysis to synthesize stronger evidence on the role of aspirin in reducing gastric cancer (GC) risk. METHODS: The PubMed, Scopus, and MEDLINE databases were systematically searched up to December 2019 to identify relevant studies. Random-effects model was used to calculate summary ORs and 95%CI for I 2 >50%. If the heterogeneity is not significant, the fixed-effects model was used. Overall analysis of the studies, inverse variance weighting after transforming the estimates of each study into log OR and its standard error were used. RESULTS: 21 studies were included in this meta-analysis. Results showed that aspirin significantly reduced the GC risk (OR=0.64, 95%CI=0.54-0.76) with substantial heterogeneity (I 2 =96%). Effect of GC risk reduction in low dose (OR=0.80, 95%CI=0.59-1.09) is slightly greater than high dose aspirin (OR=1.08, 95%CI=0.77-1.52). Protective effect of aspirin uses >5 years (OR=0.67, 95%CI=0.34-1.31) was greater than <5 years (OR=1.01, 95%CI=0.72-1.43) Conclusion: In conclusion, this meta-analysis showed that low dose aspirin with longer duration of more than 5 years were associated with a statistically significant reduction in GC risk. However, due to possible confounding variables and bias, these results should be cautiously treated.

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
1秒前
科研通AI6.4应助景景采纳,获得10
2秒前
aaaaaa发布了新的文献求助10
6秒前
17秒前
dtt应助闭家锁采纳,获得10
18秒前
小蘑菇应助学术混子采纳,获得10
18秒前
nk完成签到 ,获得积分10
20秒前
共享精神应助汪鸡毛采纳,获得10
24秒前
迷人啤酒完成签到,获得积分10
33秒前
科研启动完成签到,获得积分10
34秒前
宣灵薇发布了新的文献求助10
35秒前
48秒前
学术混子发布了新的文献求助10
52秒前
这学真难读下去完成签到,获得积分10
53秒前
59秒前
所所应助热情初瑶采纳,获得30
1分钟前
Leung完成签到,获得积分10
1分钟前
1分钟前
热情初瑶完成签到,获得积分10
1分钟前
热情初瑶发布了新的文献求助30
1分钟前
着急的宝马完成签到 ,获得积分10
1分钟前
cdercder应助科研通管家采纳,获得10
1分钟前
冷傲的傲霜完成签到,获得积分10
1分钟前
1分钟前
景景发布了新的文献求助10
1分钟前
哈哈哈完成签到,获得积分10
1分钟前
1分钟前
布鲁爱思发布了新的文献求助10
1分钟前
1分钟前
布鲁爱思完成签到,获得积分10
1分钟前
1分钟前
choichoi发布了新的文献求助10
1分钟前
头顶花盆降碳给头顶花盆降碳的求助进行了留言
1分钟前
1分钟前
NexusExplorer应助景景采纳,获得10
1分钟前
Nori完成签到 ,获得积分10
1分钟前
赫连山菡发布了新的文献求助10
1分钟前
1分钟前
choichoi完成签到,获得积分10
2分钟前
2分钟前
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
Art Therapy and Career Counseling 600
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 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 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 7619160
求助须知:如何正确求助?哪些是违规求助? 9194632
关于积分的说明 19706160
捐赠科研通 7191201
什么是DOI,文献DOI怎么找? 3272388
关于科研通互助平台的介绍 2435003
邀请新用户注册赠送积分活动 2267604