提高肺癌查率的干预措施的有效性:随机临床试验的系统审查和元分析
Wenjuan Tao1, Xiumei Tang2, Xuefeng Jiao3
1Institute of Hospital Management/General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Preventive medicine
|December 25, 2025
概括
干预措施适度增加了肺癌查 (LCS) 的吸收率. 多元组件策略和患者导航在提高高风险成年人查率方面表现最有前途.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 预防癌症 预防癌症
背景情况:
- 尽管有证据支持其对高风险个体的好处,但肺癌查 (LCS) 的吸收仍然不够理想.
- 确定有效的干预措施对于改善LCS参与和降低肺癌死亡率至关重要.
研究的目的:
- 系统地审查和元分析旨在增加肺癌查吸收率的干预措施的有效性.
- 确定影响这些干预措施成功实施的因素.
主要方法:
- 从2010年1月到2025年11月,对多个数据库 (MEDLINE,CINAHL,EMBASE,Cochrane图书馆,Web of Science) 进行了全面的搜索.
- 包括的研究是随机对照试验,评估干预措施,以改善高风险的成年人中LCS吸收,符合低剂量计算机断层扫描查的条件.
主要成果:
- 包括11项试验,主要来自美国.
- 总体而言,干预措施显示LCS吸收的适度但显著增加 (RR=1.34).
- 多组件干预 (RR=2.11) 和患者导航显示,对查吸收产生最显著的积极影响.
结论:
- 干预措施可以适度提高肺癌查的采用率,多组件方法和患者导航特别有效.
- 未来的研究应该集中在多元组件策略,以股权为重点的设计和多样化的国际环境上,以优化LCS交付.
更多相关视频
04:04Endobronchial Ultrasound-guided Intratumoral Injection of Cisplatin for the Treatment of Isolated Mediastinal Recurrence of Lung Cancer
Published on: February 12, 2017
10.9K
05:22Author Spotlight: Demonstrating Systematic Endobronchial Ultrasound to New Endoscopists
Published on: August 11, 2023
2.7K
相关概念视频
Statistical Methods for Analyzing Epidemiological Data
864
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
864
Cancer Survival Analysis
626
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
626
