弥合结直肠癌查中的公平差距:高收入国家对高收入国家的比较分析
Yasmin Jahan1, Atiqur Sm-Rahman2
1London School of Hygiene and Tropical Medicine, London, United Kingdom.
Journal of cancer policy
|October 25, 2025
概括
高收入国家的结肠直肠癌 (CRC) 查计划显示存在差异. 实施以公平为重点的政策和文化定制的教育对于改善所有人群的查准入和结果至关重要.
科学领域:
- 公共卫生 公共卫生
- 卫生政策 卫生政策
- 预防癌症 预防癌症
背景情况:
- 高收入国家 (HIC) 存在着结肠直肠癌 (CRC) 查计划,但获得和结果仍然不平等.
- 以公平为重点的政策至关重要,以确保CRC预防有利于所有群体,特别是服务不足和边缘化的人群.
研究的目的:
- 进行10个HIC中CRC查系统的比较政策分析.
- 识别查获取和结果中的差异.
- 评估以公平为重点的政策在CRC预防方面的有效性.
主要方法:
- 在十个HIC中对CRC查系统进行比较政策分析.
- 审查同行评审的文献,国家癌症机构的报告和查数据.
- 开发关于选方式,覆盖范围,间隔和股权政策的汇总表.
主要成果:
- 在HIC之间,CRC查方式和覆盖率存在显著差异.
- 有组织的,以人口为基础的查计划通常显示出更高的吸收率.
- 共同政策的差距包括农村外展有限,少数群体的选不足,以及不充分的股权数据收集.
结论:
- 该研究为癌症预防的跨国政策基准测试提供了一个框架.
- 将公平纳入CRC选计划是减少差异的必要条件.
- 改善不同卫生系统的结果需要在癌症预防策略中关注健康公平.
更多相关视频
11:34Building Up a High-throughput Screening Platform to Assess the Heterogeneity of HER2 Gene Amplification in Breast Cancers
Published on: December 5, 2017
13.0K
10:13A Multiplexed Luciferase-based Screening Platform for Interrogating Cancer-associated Signal Transduction in Cultured Cells
Published on: July 3, 2013
11.6K
相关概念视频
02:59Cancer Prevention
7.6K
Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
Some...
7.6K
01:29Bias in Epidemiological Studies
1.3K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.3K