The Department of Epidemiology has an integrative, multi-disciplinary modern epidemiology research focus that spans the entire spectrum of cancer – from healthy individuals, to pre-malignancy, to diagnosis, to treatment, to clinical outcomes and finally to survivorship.
Our faculty have expertise in traditional epidemiology, biomarker discovery and application, genetics, genomics, bioinformatics, nutritional epidemiology, energy balance, NextGen sequencing analysis, statistical genetics, population genetics, and much more. Our dynamic research programs are highly collaborative, with strong interactions across the institution, nationally, and world-wide. These programs fall into four broad categories:
Integrative Risk Assessment (Cancer Etiology):
We take an integrative approach to investigate factors contributing to cancer risk that includes both epidemiology variables and biomarkers. The goal is to assess individual risk of developing cancer to inform various risk-reduction measures, such as increased screening, diet/physical activity changes, smoking cessation, prophylactic screening or others.
Prediction of Cancer Outcome (Post Cancer Diagnosis):
With a growing number of treatment options for cancer patients, there is a gap in knowledge regarding the mediators of cancer outcomes. We apply the same integrative, comprehensive approach to the spectrum of clinically-relevant endpoints, such as prognosis, treatment response, toxicity, complications, efficacy, symptoms, quality of life, secondary primary tumors, survival, and progression.
Genetic Epidemiology & Risk Model Development ("-omics" and Computational Epidemiology):
We have expertise in large scale population genomics, imputation, and analysis of rare variants from Next-Gen sequencing. We also have statistical capability for analysis of gene-gene and gene-environment interactions to further refine risk. The integration of genotypic, phenotypic, and other “-omic” data allows for the development of prediction models that accurately assess risk of not only developing cancer, but also clinical outcomes across the cancer continuum.
Special Populations and Health Disparities:
We have developed and expanded valuable cohorts that allow for prospective analysis of cancer development and exploration of racial differences in cancer risk and outcomes. This includes the Mano a Mano Cohort which focuses on Mexican-Americans, a quickly growing population undergoing dramatic social change. The MJ Cohort has extensive health screening data on all participants that enables investigation into energy balance, physical activity, screening, early detection, and interventions.
Cancer of the Lung Evaluation and Assessment of Risk
The CLEAR lung cancer risk prediction tool can quantify a smoker’s risk of developing lung cancer in the next five, 10 or 15 years based on the person’s age, sex, smoking history, medical history, family history of cancer and past exposures to asbestos or wood dust. Information obtained from this risk tool can enable physicians and patients in making decisions about lung cancer screening options.
Learn more about the Cancer of the Lung Evaluation and Assessment of Risk (CLEAR).