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利用癌症登记数据进行生存研究:以安大略癌症登记处为例。

Using cancer registry data for survival studies: the example of the Ontario Cancer Registry.

作者信息

Hall Stephen, Schulze Karleen, Groome Patti, Mackillop William, Holowaty Eric

机构信息

Division of Cancer Care and Epidemiology, Queen's Cancer Research Institute, 10 Stuart St, Kingston Ontario K7L 3N6, Canada.

出版信息

J Clin Epidemiol. 2006 Jan;59(1):67-76. doi: 10.1016/j.jclinepi.2005.05.001. Epub 2005 Oct 3.

Abstract

BACKGROUND AND OBJECTIVES

The Ontario Cancer Registry (OCR) is a population-based tumor registry created to provide data for epidemiologic research and for cancer surveillance. Recently it has been used for health services research. The objective of this project was to assess the quality of the OCR data that is used in survival analysis.

METHODS AND DESIGN

Clinical information for 898 patients with squamous carcinoma of the head and neck including index tumor site, date of diagnosis, vital status, date of death, and cause of death from a prospective database at the Kingston Regional Cancer Center is compared to the same data elements in the OCR for the same patients.

RESULTS

There is no statistically significant difference in disease-specific survival between the information from the two databases (log rank P = .89). The OCR captured and correctly assigned index tumor site for 81.4% (detection rate). The site assignment was accurate 90.9% of the time (confirmation rate), there was agreement on vital status (dead vs. alive) for all but one patient, and there was excellent agreement on date of death. However, cause of death (cancer vs. noncancer) based on death certificates had a 31% error rate.

CONCLUSION

Researchers can be confident in the survival analysis generated from data in this registry, but need to be aware of potential sources of error.

摘要

背景与目的

安大略癌症登记处(OCR)是一个基于人群的肿瘤登记处,旨在为流行病学研究和癌症监测提供数据。最近,它已被用于卫生服务研究。本项目的目的是评估用于生存分析的OCR数据的质量。

方法与设计

将金斯顿地区癌症中心前瞻性数据库中898例头颈部鳞状细胞癌患者的临床信息(包括索引肿瘤部位、诊断日期、生命状态、死亡日期和死亡原因)与OCR中相同患者的相同数据元素进行比较。

结果

两个数据库的信息在疾病特异性生存方面无统计学显著差异(对数秩检验P = 0.89)。OCR捕获并正确分配索引肿瘤部位的比例为81.4%(检出率)。部位分配在90.9%的情况下是准确的(确认率),除一名患者外,所有患者的生命状态(死亡与存活)一致,死亡日期的一致性非常好。然而,基于死亡证明的死亡原因(癌症与非癌症)错误率为31%。

结论

研究人员可以对该登记处数据生成的生存分析充满信心,但需要意识到潜在的误差来源。

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