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Overview
The availability of high throughput -omic technologies, novel devices for exposure assessment, and electronic medical records have the potential to facilitate a more comprehensive study of risk factors contributing to development of and outcomes from cancer.
Despite individual successes at identifying genetic, biological, and environmental risk factors for cancer, much of the etiology remains unexplained. This may be due in part to the limited focus of many studies on a single or small set of risk factors or data types (i.e. measures such as DNA sequence, methylation data, variables from questionnaires). Moreover, many studies fail to consider the complexities and interrelations among multiple risk factors and associated outcomes. For example, each individual risk factor, such as a single dietary component or genetic polymorphism, occurs in a broader biological (e.g. pathways) or societal (e.g. individual in social network) context which could modulate the effect of individual risk factors on disease. Further, many risk factors for disease can be highly correlated with possible interactive, synergistic, or attenuating effects. Importantly, risk factors can change over time.
A more comprehensive, systems modeling based type of approach, which accounts for multiple dimensions, integration of diverse data types, and changes over time, is needed to better understand contributors to disease and treatment outcomes and provide clues for improved intervention.
Purpose
The objective of this workshop was to facilitate interdisciplinary discussion about the application of systems modeling approaches for population-based cancer epidemiology research. By bringing together scientists from various fields that use systems modeling the workshop aimed to:
- Identify ideas and strategies to improve understanding of systems modeling among population scientists and epidemiology amongst modelers;
- Share lessons learned in the application of systems approaches from other fields (e.g. cancer biology)
- Identify of potential high-impact use cases for systems modeling in population science;
- Increase understanding of potential barriers and facilitators to taking a system modeling approach in population science (including dataset availabilities, data and methods needs)
- Establish new collaborative interdisciplinary relationships between statisticians, mathematicians, computer scientists, bioinformaticians, epidemiologists, and clinicians.
Agenda
View agenda for February 28, 2019
Thursday, February 28 | Topic |
---|---|
9:00 a.m. | Welcome |
9:15 a.m. | Introduction to the Meeting |
9:35 a.m. |
State of the Science Systems Epidemiology: Definitions, Applications, and Common Misconceptions Group Discussion Elizabeth M. Gillanders, PhD |
10:40 a.m. | Break |
11:00 a.m. |
Successes and Challenges in Systems Modeling (Session I) What Can We Learn from the NIH Obesity Modeling Network – Envision? Systems Approach to Distinguish Aggressive Cancer vs. Benign Breast Lesions: Opportunities and Challenges Successes and Challenges to Population Modeling of Breast Cancer in the Cancer Intervention and Surveillance Modeling Network (CISNET) Panel and Group Discussion Marissa Shams-White, PhD, LAc, MPH |
12:30 p.m. | Lunch |
1:30 p.m. |
Successes and Challenges in Systems Modeling (Session II) Using SEER Data to Develop Synthetic Cancer Trajectories that Enable Cancer Research Challenges and Considerations for Synthetic Data: A Study based on SEER Population Nucleotides to Neighborhoods – Integrating Complex Spatial, Behavioral, and Multi-omits Data Panel and Group Discussion Brionna Hair, PhD, MPH |
3:00 p.m. | Break |
3:20 p.m. |
Successes and Challenges in Systems Modeling (Session III) Collaborative Science through Collaborative Software Systems Approach to Risk Score Prediction in Epidemiology Learning to Impute Methylome Signatures and Environmental Measures into Biobanks Panel and Group Discussion Rolando Barajas, MPH |
4:50 p.m. |
Dissemination and Implementation of Systems Modeling: How can these methods be applied? How can methods be interpreted and translated? Stacy Lindau, MD, MA Nico Pronk, PhD, MA Amy Trentham-Dietz, PhD Panel and Group Discussion Marissa Shams-White, PhD, LAc, MPH |
5:40 p.m. | Adjourn |
View agenda for March 1, 2019
Friday, March 1 | Topic |
---|---|
8:30 a.m. |
Introduction and Charge for Day 2 |
8:40 a.m. |
Perspectives: What is the Ideal Future for Modeling in Epidemiological Studies (Panel Discussion) Bruce Y. Lee, MD Chirag Patel, PhD Sylvia Plevritis, PhD Marylyn D. Ritchie, PhD Panel and Group Discussion Leah E. Mechanic, PhD, MPH |
9:25 a.m. | Break/Travel to Discussion Groups |
9:40 a.m. | Discussion Sessions Group 1: Facilitators and Barriers to Success Group 2: Opportunities for Systems Epidemiology Group 3: Approaches and Methods Group 4: Data Availability Discussion Groups Summarize and Identify Priorities for Reporting |
11:10 a.m. | Break |
11:30 a.m. | Report Back and Group Discussion for Each Topic |
12:50 p.m. |
Next Steps and Action Items Elizabeth M. Gillanders, PhD DCCPS, NCI |
1:00 p.m. | Adjourn |
Workshop Summary
Barajas R, Hair B, Lai G, et al. Facilitating Cancer Systems Epidemiology Research. PLoS One. 2021 Dec 31;16(12):e0255328.
Planning Committee
NCI Staff
- Elizabeth M. Gillanders, PhD, Genomic Epidemiology Branch, Epidemiology and Genomics Research Program (EGRP), Division of Cancer Control and Population Sciences (DCCPS)
- Brionna Hair, PhD, MPH, Office of the Director, DCCPS
- Gabriel Lai, PhD, Environmental Epidemiology Branch, EGRP, DCCPS
- Leah Mechanic, PhD, MPH, Genomic Epidemiology Branch, EGRP, DCCPS
- Jill Reedy, PhD, MPH, RD, Risk Factor Assessment Branch, EGRP, DCCPS
- Melissa Rotunno, PhD, Genomic Epidemiology Branch, EGRP, DCCPS
- Marissa Shams-White, PhD, LAc, MPH, Risk Factor Assessment Branch, EGRP, DCCPS
External Members
- Bruce Y. Lee, MD, Bloomberg School of Public Health and Carey Business School, Johns Hopkins University
- Chirag Patel, PhD, Harvard Medical School
- Marylyn D. Ritchie, PhD, Center for Translational Bioinformatics and Penn Center for Precision Medicine, University of Pennsylvania
- Sylvia K. Plevritis, PhD, Stanford School of Medicine
Contact
Questions about this Workshop can be directed to Leah Mechanic, PhD, MPH, Genomic Epidemiology Branch, EGRP.