Joint Seminar with Harvard TH Chan School of Public Health

Thursday April 11, 2024 @ 4pm ET
FXB Building Room 301

Yu Shen PhD
Conversation with a Living Legend Professor & Chair ad interim
Department of Biostatistics
The University of Texas MD Anderson Cancer Center

In comparative effectiveness research and risk prediction for rare types of cancer, it is desirable to combine multiple sources of data, e.g., the primary cohort data together with aggregate information derived from cancer registry databases. Such integration of data may improve statistical efficiency and accuracy of risk prediction, but also pose statistical challenges for incomparability between different sources of data. We develop the adaptive estimation procedures, which used the combined information to determine the degree of information borrowing from the aggregate data of the external resource. We apply the proposed methods to evaluate the long-term effect of several commonly used treatments for inflammatory breast cancer by tumor subtypes, while combining the inflammatory breast cancer patient cohort at MD Anderson and external data.