Development, Validation, and Dissemination of an Integrated Risk Prediction Model and Decision Aid to Discern Aggressive Versus Indolent Prostate Cancer
Abstract
Prostate cancer screening remains the subject of much controversy, largely because there are unacceptable levels of over-treatment of low-risk, indolent prostate cancer, which incurs significant morbidity and costs with minimal impacton life expectancy. Over-treatment leads not only to avoidable morbidity and cost, but also to decisional regret, low satisfaction, and much avoidable suffering associated with prostate cancer diagnosis. We will address both incomplete information and poor understanding among men diagnosed with low-risk prostate cancer. We propose that an integrated risk prediction model, and implementation of a decision support intervention to help patients understand their disease risk and management options, we will reduce anxiety and uncertainty, improve decision quality and satisfaction, and increase acceptance of initial active surveillance for low-risk prostate cancer. We will evaluate this hypothesis through the following specific aims: Aim 1: We will develop and validate a novel integrated risk prediction model, incorporating clinical, lifestyle, tumor genomic, and germline genetic variables, to provide better information to men about their risk of having more aggressive disease. Aim 2: We will implement and evaluate (in a randomized controlled trial) a decision support intervention, based on the risk model from Aim 1, to improve understanding of ones disease risks, and the pros and cons of different management options.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2019
- Accession Number
- AD1097115
Entities
People
- June Chan
- Matthew R Cooperberg
- Peter R. Carroll
Organizations
- University of California, San Francisco