Donna P Ankerst1, Jing Xia2, Ian M Thompson3, Josef Hoefler4, Lisa F Newcomb4, James D Brooks5, Peter R Carroll6, William J Ellis4, Martin E Gleave7, Raymond S Lance8, Peter S Nelson9, Andrew A Wagner10, John T Wei11, Ruth Etzioni2, Daniel W Lin4. 1. Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Life Sciences Mathematics Unit, Technische Universitaet Muenchen, Munich, Germany. Electronic address: ankerst@tum.de. 2. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 3. Department of Urology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA. 4. Department of Urology, University of Washington, Seattle, WA, USA. 5. Department of Urology, Stanford University School of Medicine, Stanford, CA, USA. 6. Department of Urology, Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, CA, USA. 7. Department of Urologic Sciences, The Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, Canada. 8. Departments of Microbiology and Molecular Cell Biology and Urology, Eastern Virginia Medical School, Norfolk, VA, USA. 9. Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 10. Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. 11. Department of Urology, University of Michigan, Ann Arbor, MI, USA.
Abstract
BACKGROUND: Men on active surveillance (AS) face repeated biopsies. Most biopsy specimens will not show disease progression or change management. Such biopsies do not contribute to patient management and are potentially morbid and costly. OBJECTIVE: To use a contemporary AS prospective trial to develop a tool to predict AS biopsy outcomes. DESIGN, SETTING, AND PARTICIPANTS: Biopsy samples (median: 2; range: 2-9 per patient) from 859 men participating in the Canary Prostate Active Surveillance Study and with Gleason 6 prostate cancer (median follow-up: 35.8 mo; range: 3.0-148.7 mo) were analyzed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression was used to predict progression, defined as an increase in Gleason score from ≤6 to ≥7 or increase in percentage of cores positive for cancer from <34% to ≥34%. Fivefold internal cross-validation was performed to evaluate the area under the receiver operating characteristic curve (AUC). RESULTS AND LIMITATIONS: Statistically significant risk factors for progression on biopsy were prostate-specific antigen (odds ratio [OR]: 1.045; 95% confidence interval [CI], 1.028-1.063), percentage of cores positive for cancer on most recent biopsy (OR: 1.401; 95% CI, 1.301-1.508), and history of at least one prior negative biopsy (OR: 0.524; 95% CI, 0.417-0.659). A multivariable predictive model incorporating these factors plus age and number of months since last biopsy achieved an AUC of 72.4%. CONCLUSIONS: A combination of readily available clinical measures can stratify patients considering AS prostate biopsy. Risk of progression or upgrade can be estimated and incorporated into clinical practice. PATIENT SUMMARY: The Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator, an online tool, can be used to guide patient decision making regarding follow-up prostate biopsy.
BACKGROUND: Men on active surveillance (AS) face repeated biopsies. Most biopsy specimens will not show disease progression or change management. Such biopsies do not contribute to patient management and are potentially morbid and costly. OBJECTIVE: To use a contemporary AS prospective trial to develop a tool to predict AS biopsy outcomes. DESIGN, SETTING, AND PARTICIPANTS: Biopsy samples (median: 2; range: 2-9 per patient) from 859 men participating in the Canary Prostate Active Surveillance Study and with Gleason 6 prostate cancer (median follow-up: 35.8 mo; range: 3.0-148.7 mo) were analyzed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression was used to predict progression, defined as an increase in Gleason score from ≤6 to ≥7 or increase in percentage of cores positive for cancer from <34% to ≥34%. Fivefold internal cross-validation was performed to evaluate the area under the receiver operating characteristic curve (AUC). RESULTS AND LIMITATIONS: Statistically significant risk factors for progression on biopsy were prostate-specific antigen (odds ratio [OR]: 1.045; 95% confidence interval [CI], 1.028-1.063), percentage of cores positive for cancer on most recent biopsy (OR: 1.401; 95% CI, 1.301-1.508), and history of at least one prior negative biopsy (OR: 0.524; 95% CI, 0.417-0.659). A multivariable predictive model incorporating these factors plus age and number of months since last biopsy achieved an AUC of 72.4%. CONCLUSIONS: A combination of readily available clinical measures can stratify patients considering AS prostate biopsy. Risk of progression or upgrade can be estimated and incorporated into clinical practice. PATIENT SUMMARY: The Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator, an online tool, can be used to guide patient decision making regarding follow-up prostate biopsy.
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