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Modeling Precision Interventions for Prostate Cancer Control

前列腺癌控制的精准干预建模

基本信息

批准号：
10260543
负责人：
RUTH D ETZIONI
金额：
$ 69.83万
依托单位：
FRED HUTCHINSON CANCER RESEARCH CENTER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-10 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10260543
关键词：
Address Adherence Area Bahamas Behavior Biological Markers Biopsy British Columbia Calibration Cancer Control Cancer Etiology Cancer Intervention Cancer Intervention and Surveillance Modeling Network Cessation of life Clinical Clinical Sciences Clinical Trials Country Data Data Set Data Sources Decision Making Development Diagnosis Diagnostic Disease Disease model Early Diagnosis Event Fred Hutchinson Cancer Research Center Funding Opportunities Hormonal Image Imaging Device Imaging technology Incidence Individual International Intervention Lead Leadership Learning London Long-Term Effects Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of prostate Methodology Michigan Modeling Modernization Natural History Neoplasm Metastasis Outcome PSA screening Patient Care Patients Police Policies Population Population Sciences Positioning Attribute Precision therapeutics Process Prostate Prostate Cancer therapy Radical Prostatectomy Recording of previous events Recurrence Research Personnel Resources Risk Risk Estimate Route Salvage Therapy Saudi Arabia Screening for Prostate Cancer Solid Solid Neoplasm Source Statistical Methods Stratification Techniques Technology Testing Therapeutic Time United Kingdom United States Universities Urologic Oncology Validation Work advanced disease base black men cancer diagnosis college cost curative treatments disease natural history disorder risk early screening evidence base genetic testing health disparity high risk men high risk population improved individual patient individualized prevention innovation interdisciplinary approach men models and simulation mortality novel novel marker overtreatment personalized care personalized intervention personalized medicine personalized screening process optimization prostate biopsy prostate cancer model racial disparity randomized trial risk stratification screening screening policy treatment strategy trend working group

项目摘要

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.

项目总结/文摘