Longitudinal Disease Detection Rates for the Evaluation of Disease Detection Technologies with Application in High-Risk Breast Cancer Screening 2932-2935
Dr. Jacob Levman,
(a) Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
(b) Imaging Research, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.
Context: This study presents a longitudinal simulation of disease screening at a variety of different test sensitivities.
Aims: It is demonstrated that the difference between the performance of high quality tests and poor quality tests are relatively small in terms of the commonly used longitudinally measured disease detection rate.
Statistical Analysis: This simulation study is focused on the screening of patients at high-risk for breast cancer and thus used plausible rates of new cases of disease and initial disease prevalence for this population.
Results and Conclusions: The effects of varying the rate at which the disease enters the population and the initial disease prevalence is also discussed and was determined to not affect this study’s conclusions regarding the inappropriateness of the use of the longitudinally measured disease detection rate for the evaluation of screening technologies.