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欧洲儿童癌症数据的质量、可比性及分析方法(1978 - 1997年):自动儿童癌症信息系统项目报告

Quality, comparability and methods of analysis of data on childhood cancer in Europe (1978-1997): report from the Automated Childhood Cancer Information System project.

作者信息

Steliarova-Foucher E, Kaatsch P, Lacour B, Pompe-Kirn V, Eser S, Miranda A, Danzon A, Ratiu A, Parkin D M

机构信息

Descriptive Epidemiology Group, International Agency for Research on Cancer, 150 Cours Albert Thomas, 69372 Lyon Cedex 08, France.

出版信息

Eur J Cancer. 2006 Sep;42(13):1915-51. doi: 10.1016/j.ejca.2006.05.007.

Abstract

In collaboration with 62 population-based cancer registries contributing to the Automated Childhood Cancer Information System (ACCIS), we built a database to study incidence and survival of children and adolescents with cancer in Europe. We describe the methods and evaluate the quality and internal comparability of the database, by geographical region, period of registration, type of registry and other characteristics. Data on 88,465 childhood and 15,369 adolescent tumours registered during 1978-1997 were available. Geographical differences in incidence are caused partly by differences in definition of eligible cases. The observed increase in incidence rates cannot be explained by biases due to the selection of datasets for analyses, and only partially by the registration of non-malignant or multiple primary tumours. Part of the observed differences in survival between the regions may be due to variable completeness of follow-up, but most is probably explained by resource availability and organisation of care. Further standardisation of data and collection of additional variables are required so that this study may continue to yield valuable results with reliable interpretation.

摘要

我们与62个参与儿童癌症自动信息系统(ACCIS)的基于人群的癌症登记处合作,建立了一个数据库,以研究欧洲儿童和青少年癌症的发病率和生存率。我们描述了方法,并按地理区域、登记时间、登记类型和其他特征评估了数据库的质量和内部可比性。可获取1978 - 1997年期间登记的88465例儿童肿瘤和15369例青少年肿瘤的数据。发病率的地理差异部分是由符合条件病例的定义差异造成的。观察到的发病率上升不能用分析数据集选择偏差来解释,非恶性或多原发性肿瘤的登记仅能部分解释这一现象。各地区生存差异的部分原因可能是随访完整性不同,但大部分可能是由资源可用性和医疗组织情况来解释。需要进一步规范数据并收集更多变量,以便本研究能够继续产生具有可靠解释的有价值结果。

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