Prostate cancer is the most common solid tumor in men and the second most common cause of cancer death in the United States. The Cancer Intervention and Surveillance Modeling Network (CISNET) Prostate Working Group (PWG) was formed in the year 2000 to address a wide range of questions about effective prostate cancer control. The PWG studied the rapid increase in prostate cancer diagnoses after PSA screening started in the late 1980s to estimate lead time and overdiagnosis associated with the test. The PWG studied the decline in prostate cancer mortality that began in the early 1990s to quantify the plausible contributions of PSA screening and changes in primary treatments. The PWG also studied how to interpret trends in racial disparities in incidence and survival, how to manage men with low-risk disease on active surveillance, and how to reconcile apparently discordant randomized trials of PSA screening and radical prostatectomy. In recent years, technologies surrounding prostate cancer screening and treatment have evolved rapidly, and opportunities to improve patient care using personalized data abound. Genetic testing can identify men at increased risk for developing aggressive disease, new biomarkers and imaging tools can help men avoid unnecessary biopsies, and new hormonal treatments can lengthen survival for men with advanced disease. The objective of this application is to extend PWG models to evaluate optimal ways to utilize personalized data to improve patient care while limiting harms and costs. We will determine whether we can improve early detection using novel stratification approaches and whether we can safely limit overtreatment and other harms by tailored choices of primary and secondary therapies. These approaches will be applied in the United States and in international cancer control settings with different resources and priorities.
Our specific aims are as follows.
Aim 1 : Precision early detection, including risk-stratified screening and biopsy using genetic tests, novel biomarkers, and imaging technology.
Aim 2 : Precision active surveillance, including adaptive biopsy intervals and imaging technology.
Aim 3 : Precision treatment, including type and timing of initial and salvage therapies.
Aim 4 : Targeting screening, biopsy, and treatment policies to reduce racial disparities.
Aim 5 : Prioritizing screening and treatment interventions in international settings.
These aims are highly responsive to the funding opportunity announcement, addressing 7 of the 9 targeted priority areas to varying degrees. Our cumulative expertise in prostate modeling, our existing models, and our close ties with clinical experts who provide access to large, high-quality datasets for model validation and calibration put us in a strong position to answer critical and impactful questions about how best to control this most common cancer in men.
The most effective ways to personalize the prevention and treatment of prostate cancer using data from an individual patient are unknown. Our team of investigators applies a unique inter-disciplinary approach that combines available data with modern statistical techniques to understand long-term effects of prostate cancer interventions. In this application, we will evaluate personalizing patient care, including screening high-risk men more frequently, using biomarkers and imaging tests to select patients for biopsy, using patient and cancer features to determine when and which kinds of treatment to offer, and practical approaches for reducing racial disparities. This work will advance the evidence necessary to make informed decisions about individualized screening and treatment for this most common cancer in men.
