Childhood Cancer Cluster Simulation

: Incidence of newly diagnosed childhood cancer (140/1,000,000 children under 15 years) and nephroblastoma (7/1,000,000) was simulated. Clusters of defined size (1 to 50) were randomly assembled on the district level in Germany. Each cluster was simulated with different relative risk levels (1 to 100). For each combination 2000 iterations were done. Simulated data was then analyzed by three local clustering tests: Besag-Newell method, spatial scan statistic and Bayesian Besag-York-Mollié with Integrated Nested Laplace Approximation approach. The operating characteristics (sensitivity, specificity, predictive values, power and correct classification) of all three methods were systematically described.

本研究模拟了新发儿童癌症与肾母细胞瘤（nephroblastoma）的发病情况：15岁以下儿童的新发儿童癌症发病率为140/100万，肾母细胞瘤发病率为7/100万。在德国的区级行政单元层面，随机构建规模为1至50的集群，并为每个集群设置1至100的不同相对风险水平开展模拟。针对每一组参数组合，均执行2000次迭代运算。随后采用三种局部集群检验方法对模拟数据进行分析：贝萨格-纽厄尔法（Besag-Newell method）、空间扫描统计量（spatial scan statistic）以及集成嵌套拉普拉斯近似（Integrated Nested Laplace Approximation）框架下的贝叶斯贝萨格-约克-莫利模型（Bayesian Besag-York-Mollié）。最终系统阐述了三种方法的各项操作特征，包括灵敏度、特异度、预测值、统计功效与正确分类率。