Application of Statistical Methods in Epidemiology Studies

今年的工作包括两个主要项目。首先，我们使用患者的甲基化和基因表达数据来开发可预测前列腺癌复发风险的生物标志物面板。与常用的临床生物标志物（如PSA和Gleason评分）相比，建议的面板具有更好的性能。第二，我们正与Kelly Ferguson博士密切合作，确定最适合分析化学混合物对各种健康结果影响的统计方法。

The work this year involves two main projects. First, we used patients' methylation and gene expression data to develop panels of biomarkers that are predictive of prostate cancer recurrence risk. The proposed panel has better performance than the commonly used clinical biomarkers, such as PSA and Gleason score. Second, we are in close collaboration with Dr. Kelly Ferguson to identify statistical methods that are most suitable for the analysis of chemical mixture effects on various health outcomes.