通过实施癌症分期分层框架来收集常规和及时的诊断癌症分期：西澳大利亚癌症登记处的经验。
Collecting routine and timely cancer stage at diagnosis by implementing a cancer staging tiered framework: the Western Australian Cancer Registry experience.
机构信息
School of Population Health, Curtin University, Perth, WA, Australia.
Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia.
出版信息
BMC Health Serv Res. 2024 Jun 28;24(1):770. doi: 10.1186/s12913-024-11224-4.
BACKGROUND
Current processes collecting cancer stage data in population-based cancer registries (PBCRs) lack standardisation, resulting in difficulty utilising diverse data sources and incomplete, low-quality data. Implementing a cancer staging tiered framework aims to improve stage collection and facilitate inter-PBCR benchmarking.
OBJECTIVE
Demonstrate the application of a cancer staging tiered framework in the Western Australian Cancer Staging Project to establish a standardised method for collecting cancer stage at diagnosis data in PBCRs.
METHODS
The tiered framework, developed in collaboration with a Project Advisory Group and applied to breast, colorectal, and melanoma cancers, provides business rules - procedures for stage collection. Tier 1 represents the highest staging level, involving complete American Joint Committee on Cancer (AJCC) tumour-node-metastasis (TNM) data collection and other critical staging information. Tier 2 (registry-derived stage) relies on supplementary data, including hospital admission data, to make assumptions based on data availability. Tier 3 (pathology stage) solely uses pathology reports.
FINDINGS
The tiered framework promotes flexible utilisation of staging data, recognising various levels of data completeness. Tier 1 is suitable for all purposes, including clinical and epidemiological applications. Tiers 2 and 3 are recommended for epidemiological analysis alone. Lower tiers provide valuable insights into disease patterns, risk factors, and overall disease burden for public health planning and policy decisions. Capture of staging at each tier depends on data availability, with potential shifts to higher tiers as new data sources are acquired.
CONCLUSIONS
The tiered framework offers a dynamic approach for PBCRs to record stage at diagnosis, promoting consistency in population-level staging data and enabling practical use for benchmarking across jurisdictions, public health planning, policy development, epidemiological analyses, and assessing cancer outcomes. Evolution with staging classifications and data variable changes will futureproof the tiered framework. Its adaptability fosters continuous refinement of data collection processes and encourages improvements in data quality.
背景
当前，基于人群的癌症登记处（PBCR）在收集癌症分期数据方面缺乏标准化，这导致难以利用多样化的数据来源和获取不完整、低质量的数据。实施癌症分期分层框架旨在改善分期数据的收集，并促进各 PBCR 之间的基准比较。
目的
展示癌症分期分层框架在西澳大利亚癌症分期项目中的应用，以建立一种在 PBCR 中收集癌症诊断时分期数据的标准化方法。
方法
该分层框架由项目咨询小组合作开发，并应用于乳腺癌、结直肠癌和黑色素瘤，提供了业务规则——分期收集的程序。第 1 层代表最高的分期水平，涉及完整的美国癌症联合委员会（AJCC）肿瘤-淋巴结-转移（TNM）数据收集和其他关键分期信息。第 2 层（登记处衍生的分期）依赖于补充数据，包括住院数据，根据数据可用性进行假设。第 3 层（病理学分期）仅使用病理学报告。
发现
分层框架促进了分期数据的灵活利用，认识到数据完整性的不同程度。第 1 层适用于所有目的，包括临床和流行病学应用。第 2 层和第 3 层仅推荐用于流行病学分析。较低的层次为公共卫生规划和政策决策提供了有关疾病模式、风险因素和总体疾病负担的有价值的见解。每个层次的分期数据的采集取决于数据的可用性，随着新数据源的获取，可能会向更高的层次转移。
结论
分层框架为 PBCR 提供了一种记录诊断时分期的动态方法，促进了人群水平分期数据的一致性，并为司法管辖区之间的基准比较、公共卫生规划、政策制定、流行病学分析以及评估癌症结果提供了实用的基础。随着分期分类和数据变量变化的发展，分层框架将具有未来保障。其适应性促进了数据收集流程的不断完善，并鼓励提高数据质量。
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