|Grant Number:||5R01CA131874-04 Interpret this number|
|Primary Investigator:||Etzioni, Ruth|
|Organization:||Fred Hutchinson Cancer Research Center|
|Project Title:||Outcomes Based Guideline Development for Prostate Cancer Screening and Treatment|
DESCRIPTION (provided by applicant): The broad, long-term objective of this study is to reshape the process by which guidelines for prostate cancer screening are produced. Almost 20 years have passed since PSA was first used for early detection. Yet there is still enormous uncertainty about the right PSA-based criteria for biopsy referral and whether to treat localized tumors detected solely on the basis of a positive test. Many groups have been charged with issuing guidelines for prostate cancer screening, but their recommendations are not consistent. The central premise of this application is that knowledge of the likely benefits and harms associated with candidate policies is critical in the formulation of good practice guidelines. However, in the case of PSA screening, there is no accepted quantitative framework for projection of these outcomes. Most decision models of prostate cancer screening do not explicitly model PSA growth and therefore cannot compare policies that vary the PSA-based criteria for biopsy. There are no published models that jointly evaluate screening and treatment decisions, but liberal screening policies may necessitate adoption of selective treatment policies. The specific objective of the proposed work is to take a recently developed model of PSA growth and prostate cancer progression and detection, and turn it into an outcomes calculator for use in developing guidelines for PSA screening and curative treatment. The calculator will include an interface that will allow users to specify a range of policies of interest and produce a series of outcomes including benefits, harms, and economic costs. Specific Aim 1 is to calibrate and validate the model so that it reproduces age, year-, and stage-specific disease incidence trends in the US and replicates published test-positive and cancer-detection frequencies from two screening trials. This aim will use a simulated maximum-likelihood procedure to produce a validated model of serial PSA levels and risks of disease progression and clinical detection in the absence of treatment. Specific Aim 2 is to use the model to simulate the positive and negative impacts of candidate decision-to- biopsy and decision-to-treat policies. Outcomes will include the number of overdiagnosed cases, the number of clinically significant cases detected early by screening, and the frequencies of overtreatment and appropriate treatment. As part of this aim, we will develop an outcomes calculator interface that allows users to quickly specify policies of interest and compare corresponding outcomes. Specific Aim 3 is to work with the Prostate Cancer Early Detection Panel of the NCCN as well as guidelines panels of the American Urology Association and the American Cancer Society to refine the user interface and evaluate usability of and trust in the outcomes calculator. We will assess the extent to which panel members use the model and hypothesize that trust in the calculator will be positively associated with the extent of its use. Knowing how likely potential users are to take advantage of the model and whether their experience with it is positive are important prerequisites for predicting future adoption of the technology and its potential for impact. PUBLIC HEALTH RELEVANCE: Clinical practice guidelines for prostate cancer screening impact millions of men at risk of a prostate cancer diagnosis. The proposed research aims to improve how these guidelines are produced by providing policy makers with a computerized decision support tool that will quantify the benefit-harm tradeoffs associated with candidate guidelines.
Calibrating Disease Progression Models Using Population Data: A Critical Precursor To Policy Development In Cancer Control
Authors: Gulati R. , Inoue L. , Katcher J. , Hazelton W. , Etzioni R. .
Source: Biostatistics (oxford, England), 2010 Oct; 11(4), p. 707-19.
What If I Don't Treat My Psa-detected Prostate Cancer? Answers From Three Natural History Models
Authors: Gulati R. , Wever E.M. , Tsodikov A. , Penson D.F. , Inoue L.Y. , Katcher J. , Lee S.Y. , Heijnsdijk E.A. , Draisma G. , de Koning H.J. , et al. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2011 May; 20(5), p. 740-50.
Limitations Of Basing Screening Policies On Screening Trials: The Us Preventive Services Task Force And Prostate Cancer Screening
Authors: Etzioni R. , Gulati R. , Cooperberg M.R. , Penson D.M. , Weiss N.S. , Thompson I.M. .
Source: Medical Care, 2013 Apr; 51(4), p. 295-300.
Comparative Effectiveness Of Alternative Prostate-specific Antigen--based Prostate Cancer Screening Strategies: Model Estimates Of Potential Benefits And Harms
Authors: Gulati R. , Gore J.L. , Etzioni R. .
Source: Annals Of Internal Medicine, 2013-02-05 00:00:00.0; 158(3), p. 145-53.
Is Prostate Cancer Screening Cost-effective? A Microsimulation Model Of Prostate-specific Antigen-based Screening For British Columbia, Canada
Authors: Pataky R. , Gulati R. , Etzioni R. , Black P. , Chi K.N. , Coldman A.J. , Pickles T. , Tyldesley S. , Peacock S. .
Source: International Journal Of Cancer, 2014-08-15 00:00:00.0; 135(4), p. 939-47.
Economic Analysis Of Prostate-specific Antigen Screening And Selective Treatment Strategies
Authors: Roth J.A. , Gulati R. , Gore J.L. , Cooperberg M.R. , Etzioni R. .
Source: Jama Oncology, 2016-07-01 00:00:00.0; 2(7), p. 890-8.