Yingye Zheng, PhD
Professor, Biostatistics Program
Public Health Sciences Division, Fred Hutch
Member
Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch
Dr. Yingye Zheng is a biostatistician who develops novel statistical tools for medical decision-making related to disease screening, diagnosis, prognosis and outcome prediction. She is an expert in designing rigorous and efficient biomarker validation study and early detection utility trials. Her work includes evaluating how useful potential biomarkers and disease-risk models will be/are for patients in the clinic and how to use electronic medical records to evaluate cancer screening techniques. She also studies how to use molecular signals that change over time (called longitudinal biomarkers) to dynamically predict risk and monitor patients’ disease status.
Dr. Zheng is the contact principal investigator (PI) for the Fred Hutch-based Data Management and Coordinating Center of the Early Detection Research Network, or EDRN, a national network that develops, evaluates and validates biomarkers for early detection and risk assessment for cancer. She is also the contact PI for the data management unit of Liquid Biopsy Consortium. Dr. Zheng was co-principal investigator of the Fred Hutch-based coordinating center for the Population-based Research to Optimize the Screening Process II, or PROSPR II, a national consortium that aims to reduce false-positive and false-negative test results in cancer screening.
Other Appointments & Affiliations
Affiliate Professor, Biostatistics, University of Washington School of Public Health and Community MedicineAffiliate Professor, Biostatistics
University of Washington School of Public Health and Community Medicine
Education
PhD, Biostatistics, University of Washington, 2002
MS, Biostatistics, University of Washington, 1999
MA, Psychology, Washington University in St. Louis, 1997
BS, Psychology, Peking University, 1992
Research Interests
Evaluation of clinical validities/utilities of novel biomarkers and risk models with censored time-to-event outcome
Dynamic risk prediction and disease surveillance with longitudinal biomarkers
Derivation of clinical decision rules using multimodal data
Evaluation of cancer screening process (recruitment, screening, diagnosis, and referral for treatment) using electronic medical records from health care systems
Study design of biomarker validation studies and early detection utility trials
Prostate cancer early detection and active surveillance
Colorectal cancer screening
Awards & Honors
Senior Student Award, Department of Biostatistics, University of Washington, 2003
Best Paper Published in Biometrics by an IBS Member in 2004 or 2005, 2006
American Statistical Association Elected Fellow, 2020