Director, Biostatistics Laboratory
Eric Polley, PhD is an Associate Professor in the Department of Public Health Sciences at The University of Chicago where he is the faculty director for the Data Science concentration in the Master of Public Health program. Dr. Polley was previously an Assistant Professor of Biostatistics in the Department of Quantitative Health Sciences at Mayo Clinic (2015-2021) and a mathematical statistician in the Biometric Research Branch at the U.S. National Cancer Institute (2012-2015). Dr. Polley received his PhD in biostatistics from the University of California, Berkeley in 2010. With Mark van der Laan, they developed the Super Learner ensemble prediction methodology. His research area involves the development and evaluation of prediction methods, innovative methods for diagnostic and prognostic prediction, and precision medicine clinical trial design.
National Cancer Institute
MD
Fellow - Computational Biology
2012
University of California, Berkeley
CA
PhD - Biostatistics
2010
Columbia University
NY
MS - Biostatistics
2005
Saint John's University
MN
BA - Mathematics
2003
Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification.
Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification. Nat Commun. 2025 May 25; 16(1):4852.
PMID: 40413188
Breast Cancer Risk Modification in Women with Pathogenic Variants in BRCA1, BRCA2, ATM, CHEK2, and PALB2.
Breast Cancer Risk Modification in Women with Pathogenic Variants in BRCA1, BRCA2, ATM, CHEK2, and PALB2. Cancer Res Commun. 2025 May 01; 5(5):783-791.
PMID: 40298171
Association of gene variant type and location with breast cancer risk in the general population.
Association of gene variant type and location with breast cancer risk in the general population. Ann Oncol. 2025 Apr 25.
PMID: 40288678
GLP-1RA Use and Thyroid Cancer Risk.
GLP-1RA Use and Thyroid Cancer Risk. JAMA Otolaryngol Head Neck Surg. 2025 Mar 01; 151(3):243-252.
PMID: 39847346
Pathogenic Variants in Cancer Susceptibility Genes Predispose to Ductal Carcinoma In Situ of the Breast.
Pathogenic Variants in Cancer Susceptibility Genes Predispose to Ductal Carcinoma In Situ of the Breast. Clin Cancer Res. 2025 Jan 06; 31(1):130-138.
PMID: 39513960
Pathogenic variants in cancer susceptibility genes predispose to Ductal Carcinoma In situ of the breast.
Pathogenic variants in cancer susceptibility genes predispose to Ductal Carcinoma In situ of the breast. Clin Cancer Res. 2024 Nov 08.
PMID: 39513960
Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach.
Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach. Breast Cancer Res. 2024 Oct 29; 26(1):148.
PMID: 39472970
Retrospective evaluation of adjuvant capecitabine dosing patterns in triple negative breast cancer.
Retrospective evaluation of adjuvant capecitabine dosing patterns in triple negative breast cancer. J Oncol Pharm Pract. 2024 Oct 13; 10781552241289581.
PMID: 39397422
Association of Gene Variant Type and Location with Breast Cancer Risk in the General Population.
Association of Gene Variant Type and Location with Breast Cancer Risk in the General Population. medRxiv. 2024 Oct 12.
PMID: 39417132
Kidney Outcomes with Glucagon-Like Peptide-1 Receptor Agonists, Sodium-Glucose Cotransporter 2 Inhibitors, Dipeptidyl Peptidase-4 Inhibitors, and Sulfonylureas in Type 2 Diabetes and Moderate Cardiovascular Risk.
Kidney Outcomes with Glucagon-Like Peptide-1 Receptor Agonists, Sodium-Glucose Cotransporter 2 Inhibitors, Dipeptidyl Peptidase-4 Inhibitors, and Sulfonylureas in Type 2 Diabetes and Moderate Cardiovascular Risk. Clin J Am Soc Nephrol. 2024 Oct 08.
PMID: 39729347
NCI Director's award for the development of the NCI-MATCH clinical trial
National Cancer Institute
2015