Joint Modeling Tumor Burden and Time to Event Data in Clinical Trials

摘要：

The tumor burden process is postulated to be the primary mechanism through which most anti-cancer treatments provide benefit. However, longitudinal tumor burden process suffers from informative missingness due to progression or death. We propose to analyze the treatment effect on tumor growth kinetics using a joint modeling framework accounting for the informative missing mechanism. Our approach is illustrated by multi-setting simulation studies. The proposed analyses can be performed in early phase clinical trials to better characterize treatment effect and thereby inform decision-making.

关键词： Overall survival tumor burden process longitudinal data informative missing joint modeling

作者: Ye Shen Aparna Anderson Ritwik Sinha Yang Li Ye Shen

作者单位: Assistant Professor,Dept.of Epidemiology and BiostatisticsCollege of Public Health,University of Geo Director,Dept.of Global Biometric Sciences,Research & Development,Bristol-Myers Squibb,Wallingford,C Analytics Technical Lead,Customer Intelligence,Hewlett-Packard Company,Bengaluru,India Research Associate,Division of Biostatistics School of Public Health,Yale University Correspondence Dept.of Epidemiology and Biostatistics University of Georgia 120 Coverdell Building Athens,GA 30602

会议类型: 国际会议

会议名称: Second Joint Biostatistics Symposium(第二届生物统计国际研讨会2012)

会议地点: 北京

会议语种:英文

页码: 86-100

在线出版日期: 2012-07-08（万方平台首次上网日期，不代表论文的发表时间）