Soleimani Mohsen, GhaziSaeedi Marjan, Ayyoubzadeh Seyed Mohammad, Jalilvand Ahmad
Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
Arch Public Health. 2025 Apr 10;83(1):99. doi: 10.1186/s13690-025-01584-6.
The increasing global burden of cancer necessitates robust cancer surveillance systems to generate accurate and comprehensive data for effective public health interventions. Despite advancements, significant gaps remain in data standardization, interoperability, and adaptability to diverse healthcare settings. This study aims to develop and validate a comprehensive framework for cancer surveillance systems that addresses these gaps, ensuring enhanced global applicability and regional relevance.
A systematic review was conducted following PRISMA guidelines, analyzing 13 studies selected from an initial pool of 1,085 articles retrieved from five major databases: PubMed, Embase, Scopus, Web of Science, and IEEE. Additionally, a comparative evaluation of 13 international cancer surveillance systems was performed to identify critical data elements and practices. Key indicators were extracted. A researcher-designed checklist consolidating these elements was validated through expert consultation with a response rate of 82% (n = 14), achieving high reliability (Cronbach's alpha = 0.849).
The proposed framework addresses critical gaps in existing cancer surveillance systems by integrating a comprehensive set of epidemiological indicators, including incidence, prevalence, mortality, survival rates, years lived with disability, and years of life lost, calculated using multiple standard populations for age-standardized rates. Furthermore, the framework incorporates key demographic filters such as age, sex, and geographic location to enable stratified analyses. It also includes advanced data elements, such as cancer type classification based on ICD-O standards, ensuring precision, consistency, and enhanced comparability across diverse cancer datasets.
The validated framework provides a structured and adaptable approach to cancer data collection and analysis, enhancing public health decision-making and resource allocation. By addressing current limitations, this study offers a significant advancement in cancer surveillance methodologies, with potential applications in diverse healthcare contexts globally.
Clinical trial number: Not applicable.
全球癌症负担日益加重,需要强大的癌症监测系统来生成准确且全面的数据,以实施有效的公共卫生干预措施。尽管取得了进展,但在数据标准化、互操作性以及对不同医疗环境的适应性方面仍存在重大差距。本研究旨在开发并验证一个针对癌症监测系统的综合框架,以弥补这些差距,确保提高全球适用性和区域相关性。
按照PRISMA指南进行了系统综述,分析了从五个主要数据库(PubMed、Embase、Scopus、Web of Science和IEEE)检索到的1085篇文章的初始库中选出的13项研究。此外,对13个国际癌症监测系统进行了比较评估,以确定关键数据元素和做法。提取了关键指标。通过与专家协商,对整合这些元素的研究人员设计的清单进行了验证,回复率为82%(n = 14),具有较高的可靠性(Cronbach's α = 0.849)。
拟议的框架通过整合一套全面的流行病学指标来弥补现有癌症监测系统中的关键差距,这些指标包括发病率、患病率、死亡率、生存率、残疾生存年数和寿命损失年数,使用多个标准人群计算年龄标准化率。此外,该框架纳入了年龄、性别和地理位置等关键人口统计学筛选因素,以进行分层分析。它还包括先进的数据元素,如基于ICD - O标准的癌症类型分类,确保了不同癌症数据集之间的精确性、一致性和更强的可比性。
经过验证的框架为癌症数据收集和分析提供了一种结构化且可适应的方法,增强了公共卫生决策和资源分配。通过解决当前的局限性,本研究在癌症监测方法上取得了重大进展,在全球不同医疗环境中具有潜在应用价值。
临床试验编号:不适用。