Grant Number:	5U01CA253915-06 Interpret this number
Primary Investigator:	Etzioni, Ruth
Organization:	Fred Hutchinson Cancer Center
Project Title:	Modeling Precision Interventions for Prostate Cancer Control
Fiscal Year:	2024

PROJECT SUMMARY/ABSTRACT 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.




Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis.
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Time-varying associations of patient and tumor characteristics with cancer survival: an analysis of SEER data across 14 cancer sites, 2004-2017.
Authors: Roberts E.K. , Luo L. , Mondul A.M. , Banerjee M. , Veenstra C.M. , Mariotto A.B. , Schipper M.J. , He K. , Taylor J.M.G. , Brouwer A.F. .
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Genetic risk and likelihood of prostate cancer detection on first biopsy by ancestry.
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Using joint models for longitudinal and time-to-event data to investigate the causal effect of salvage therapy after prostatectomy.
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Authors: McLaughlin P.W. , Cousins M.M. , Tsodikov A. , Soni P.D. , Crook J.M. .
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Survival in Patients With De Novo Metastatic Prostate Cancer.
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Isolating the Drivers of Racial Inequities in Prostate Cancer Treatment.
Authors: Hammarlund N. , Holt S.K. , Basu A. , Etzioni R. , Morehead D. , Lee J.R. , Wolff E.M. , Gore J.L. , Nyame Y.A. .
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Efficiency of the Breslow estimator in semiparametric transformation models.
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National Long-term Survival Estimates After Radical Prostatectomy for Prostate Cancer.
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Racial disparities in prostate cancer mortality: a model-based decomposition of contributing factors.
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Benefits and harms of prostate specific antigen testing according to Australian guidelines.
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Prostate Cancer Screening in African American Men: A Review of the Evidence.
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Early Detection of Prostate Cancer: AUA/SUO Guideline Part II: Considerations for a Prostate Biopsy.
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