Decision making in medicine has become increasingly complex for patients and practitioners. This has resulted from factors such as the shift away from physician authority toward shared decision making, unfiltered information on the Internet, new technology providing additional data, numerous treatment options with associated risks and benefits, and results from new clinical studies. Within this context medical screening procedures are routinely performed for several diseases. Most prominent examples can be found in cancer research, where, for example, mammographic screening is performed for the detection of breast cancer in asymptomatic patients, and prostate-specific antigen (PSA) levels are used to monitor the progression of prostate cancer in men who had already been diagnosed with the disease. In general, the aim of screening procedures is to optimize the benefits, i.e., early detection of disease or deterioration of the condition of a patient, while also balancing the respective costs.
In this project we aim to develop novel techniques for optimally choosing when to collect biomarker information for patients in a screening phase, and when to plan an invasive procedure (e.g., prostate biopsies) for patient in an active surveillance schedule. The key element of these techniques is their personalized and dynamic nature, i.e., they suitably adapt utilizing the available information on a patient.