Northwestern Events Calendar

Feb
25
2019

Biostatistics Seminar Series with a Candidate for the Division of Biostatistics/QDSC Faculty position

When: Monday, February 25, 2019
3:00 PM - 4:00 PM CT

Where: 680 N. Lake Shore Drive, Stamler Conference Room, Ste 1400, Chicago, IL 60611 map it

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Contact: Putri Kusumo   (312) 908-1718

Group: Department of Preventive Medicine

Category: Academic

Description:

 


Hong Zhu, PhD

Assistant Professor
Division of Biostatistics
Department of Population and Data Sciences &
Harold C. Simmons Comprehensive Cancer Center
University of Texas Southwestern Medical Center

Presentation Title
Statistical Challenges and Methods for Clinical Trial Design and Analysis


Brief Abstract
Clinical trials are a necessary tool of bringing experimental intervention to the public. The validity of clinical trials is not judged by the results but by how it is designed, conducted, and analyzed. One of the most important aspects in clinical trial design is the sample size determination. Rigorous sample size estimation ensures that clinical trials have adequate power to detect clinically meaningful effects and avoids the risk of exposing excessive patients to experimental interventions caused by an overpowered study. Dr. Zhu has collaborated with oncologists and health behavioral scientists on design and analysis of both explanatory clinical trials in drug development and real-world pragmatic clinical trials in cancer prevention. Motivated by these collaborations, she has developed novel statistical methods for optimal design of clinical trials, in order to address unique statistical challenges related to historical controls, correlated observations, missing data, varying cluster size, and dose-expansion cohorts. In this talk, Dr. Zhu will present her research work on statistical methods for innovative clinical trial design. Complex survival data, such as semi-competing risks data, often arise from clinical trials and observational studies in clinical and healthcare research. She will also discuss her work on analytical methods for semi-competing risks data with application to health outcome studies, accounting for death as a competing risk for non-terminal endpoints in disease progression.

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