Bio
Dr. Hsing is a professor of medicine at Stanford University. A senior fellow for the Center for Innovation in Global Health at Stanford University, Dr. Hsing has conducted population-based epidemiological studies on four continents, including North and South America, Asia, Africa, and Europe. She is a leading expert in the epidemiology and etiology of prostate, hepatobiliary, and thyroid cancers as well as in hormonal carcinogenesis and circadian rhythm. Throughout her 22-year tenure at National Cancer Institute, Dr. Hsing developed extensive expertise in molecular epidemiology, global oncology, cancer prevention, and population-based studies in international settings. She has served on numerous committees and advisory boards, most recently as a member of the Editorial Board of Cancer Epidemiology, Biomarkers & Prevention and as an academic editor of PLOS ONE. Dr. Hsing has authored more than 340 peer-reviewed articles, written seven book chapters, and mentored over 65 post-doctoral fellows and scholars.
Dr. Hsing currently serves as PI on the following funded projects:
• Stanford WELL for Life Study - a longitudinal study of 32,000 individuals in 5 countries (US, China, Taiwan, Singapore, and Thailand) to advance the science of well-being
• A study to assess patterns and trends of liver cancer in the Greater Bay area and in California and to project liver cancer burden in 20 years;
• A pilot study in the Bay area to investigate non-viral factors of liver cancer;
• A pilot study to investigate the clinical utility of ctNDA in post-treatment surveillance of liver cancer in Mongolia
• A study to investigate the role of Traditional Chinese Medicine (TCM) body constitution type in relation to well-being, metabolic syndrome, and mental health;
She also serves as the Stanford PI of a consortium study of a genome-wide association study (GWAS) of prostate cancer in the African countries of Ghana, Senegal, Nigeria, and South Africa. More recently, her her work involves big data studies using such resources as the National Health Insurance Research Database, SEER-Medicare, and other large administrative claims and medical record databases to identify clinically relevant questions to help inform clinical practice.
