Kulldorff Martin, Fang Zixing, Walsh Stephen J
Division of Epidemiology and Biostatistics, School of Medicine, and Department of Statistics, University of Connecticut, USA.
Biometrics. 2003 Jun;59(2):323-31. doi: 10.1111/1541-0420.00039.
Many databases exist with which it is possible to study the relationship between health events and various potential risk factors. Among these databases, some have variables that naturally form a hierarchical tree structure, such as pharmaceutical drugs and occupations. It is of great interest to use such databases for surveillance purposes in order to detect unsuspected relationships to disease risk. We propose a tree-based scan statistic, by which the surveillance can be conducted with a minimum of prior assumptions about the group of occupations/drugs that increase risk, and which adjusts for the multiple testing inherent in the many potential combinations. The method is illustrated using data from the National Center for Health Statistics Multiple Cause of Death Database, looking at the relationship between occupation and death from silicosis.
有许多数据库可用于研究健康事件与各种潜在风险因素之间的关系。在这些数据库中，有些具有自然形成层次树结构的变量，例如药品和职业。利用此类数据库进行监测，以发现与疾病风险的意外关系，这非常有趣。我们提出了一种基于树的扫描统计量，通过该统计量可以在对增加风险的职业/药物组的先验假设最少的情况下进行监测，并且可以针对许多潜在组合中固有的多重检验进行调整。使用美国国家卫生统计中心多死因数据库的数据说明了该方法，该数据着眼于职业与矽肺病死亡之间的关系。
