Projects
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An Appraisal of the Comparative Clinical Effectiveness and Value of Management Options for Atrial Fibrillation
Atrial fibrillation (AF) is the most common cardiac arrhythmia seen in clinical practice, affecting approximately 2.5 million persons in the U.S. AF is not only common but also carries significant risks of mortality and morbidity, raising the risk of stroke more than five-fold and contributing to an estimated 15-20% of strokes annually in the U.S. Even patients with AF who do not suffer a stroke often experience diminished quality of life and require frequent hospitalization.
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Applications of Multi-Criteria Optimization (AMCO) for Cancer Simulation Modeling
With the exponential growth of computer power, cancer screening modelers are constructing increasingly complex models that mimic real life clinical trials. In a cancer screening model, parameters that govern critical but unobservable events (e.g., metastasis) are often estimated by calibrating the model to relevant data (e.g., from tumor registries and clinical trials). As simulation models become more complex, calibrating them becomes both more important and more difficult. In the field of engineering, many techniques have been cultivated to improve the speed and the quality of calibration. However, cancer screening modelers utilize few of these techniques. The goal of this project is to transfer and extend engineering simulation techniques to the field of cancer screening simulation modeling.
This project will apply engineering optimization techniques to calibrate numerous cancer screening models at the ITA. We will integrate and automate these techniques to search the natural history parameter space and simultaneously calibrate to multiple endpoints. We will measure, analyze, and compare the performance of these techniques.
This research will advance our understanding and methodologies of constructing and calibrating cancer screening models and will create streamlined procedures for model development. -
Breast Cancer Prevention Model
Includes the development of a model capable of evaluating the medical and economic consequences of several breast cancer prevention options. Through Monte Carlo simulations, the model will provide population-level estimates of the consequences for women with different levels of risk to breast cancer and different levels of susceptibility to the side effects of each option.
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Chemical analysis of coronary atherosclerosis inpatients
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Chemoprevention for the Prevention and Management of Gastrointestinal (GI) Cancers
We have performed analyses using our disease model to determine the effectiveness and cost-effectiveness of aspirin for chemoprevention again EAC in patients with BE. Additional analyses studied patient preferences for aspirin as chemoprevention in both patients with BE and for the prevention of colorectal cancer.