Ph.D., Carnegie Mellon University, Statistics, 1990.
M.S., Carnegie Mellon University, Statistics, 1987.
B.S., University of Cape Town, Statistics, 1985.
Methods for evaluating diagnostic tests
Modeling and outcomes research in prostate cancer
Modeling impact of PSA screening and other interventions on prostate cancer incidence and mortality
Costs and benefits of prostate cancer screening
Trends in prostate cancer screening and related behaviors
Dr. Ruth (Douglas) Etzioni is a Full Member in Biostatistics of the Division of Public Health Sciences at the Fred Hutchinson Cancer Research Center. Her work focuses on the development and implementation of statistical methods for prostate cancer studies. In the past, she has worked on assessing the efficacy of PSA screening from population studies, estimating the frequency of overdiagnosis associated with PSA, evaluating novel prostate cancer biomarkers, and tracking patterns and outcomes of prostate cancer care. Her work in prostate cancer surveillance is conducted as part of the Cancer Intervention and Surveillance Modeling Network (CISNET).
As leader of the biostatistics core for the Northwest Prostate Cancer SPORE, Dr. Etzioni has developed methods for analyzing immunohistochemical studies, and combining results from microarray experiments, while working with SPORE investigators to select the most appropriate design and analysis approaches for a broad array of studies. She is an affiliate investigator on the Data Management Coordination Center for the Early Detection Research Network (EDRN) and continues to work with EDRN statisticians on methods for biomarker development. In addition to these projects, her current interests include modeling the development of resistance to androgen ablation therapy.
American Statistical Association
Institute of Mathematical Statistics
International Biometric Society
Society for Medical Decision Making
Honors and Awards
2016, American Statistical Association Fellow
Active Surveillance for Ductal Carcinoma in Situ: Shining Light Into the Modeling Abyss.. Journal of the National Cancer Institute. 108(5). 2016.
Recognizing the Limitations of Cancer Overdiagnosis Studies: A First Step Towards Overcoming Them.. Journal of the National Cancer Institute. 108(3). 2016.
Comparative Effectiveness of Biomarkers to Target Cancer Treatment: Modeling Implications for Survival and Costs.. Medical decision making : an international journal of the Society for Medical Decision Making. 36(5):594-603.. 2016.
Breast Cancer Screening for Women at Average Risk. Obstetrical & Gynecological Survey. 71(3):153-155.. 2016.
The Effect of Treatment Advances on the Mortality Results of Breast Cancer Screening Trials: A Microsimulation Model. Annals of Internal Medicine. 164(4):236.. 2016.
Predictors of preoperative MRI for breast cancer: differences by data source.. Journal of comparative effectiveness research. :1-12.. 2015.
Measures of survival benefit in cancer drug development and their limitations.. Urologic oncology. 33(3):122-7.. 2015.
Effect of Screening Mammography on Cancer Incidence and Mortality.. JAMA internal medicine.. 2015.
Treatment Trends for Stage I Testicular Seminoma in an Equal-Access Medical System.. Clinical genitourinary cancer.. 2015.
Models in the development of clinical practice guidelines.. Annals of internal medicine. 162(7):530-1.. 2015.
Projecting Benefits and Harms of Novel Cancer Screening Biomarkers: A Study of PCA3 and Prostate Cancer.. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 24(4):677-82.. 2015.
Economic Return From the Women's Health Initiative Estrogen Plus Progestin Clinical Trial: A Modeling Study.. Annals of internal medicine. 160(9):594-602.. 2014.
Oversimplifying Overdiagnosis.. Journal of general internal medicine.. 2014.
RE: A Model Too Far.. Journal of the National Cancer Institute.. 2014.
Comparison of Survival Outcomes Among Cancer Patients Treated In and Out of Clinical Trials.. Journal of the National Cancer Institute.. 2014.
Personalizing age of cancer screening cessation based on comorbid conditions: model estimates of harms and benefits.. Annals of internal medicine. 161(2):104-12.. 2014.