Donna P Ankerst1, Martin Goros2, Scott A Tomlins3, Dattatraya Patil4, Ziding Feng4, John T Wei3, Martin G Sanda4, Jonathan Gelfond2, Ian M Thompson5, Robin J Leach6, Michael A Liss7. 1. Department of Urology, University of Texas Health at San Antonio, San Antonio, TX, USA; Department of Epidemiology and Biostatistics, University of Texas Health at San Antonio, San Antonio, TX, USA; Department of Mathematics, Technical University Munich, Garching, Germany. Electronic address: ankerst@tum.de. 2. Department of Epidemiology and Biostatistics, University of Texas Health at San Antonio, San Antonio, TX, USA. 3. Departments of Pathology and Urology, Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, MI, USA. 4. Department of Urology, The Emory University School of Medicine, Atlanta, GA, USA. 5. CHRISTUS Medical Center Hospital, San Antonio, TX, USA. 6. Department of Urology, University of Texas Health at San Antonio, San Antonio, TX, USA; Department of Cell Systems and Anatomy, University of Texas Health at San Antonio, San Antonio, TX, USA. 7. Department of Urology, University of Texas Health at San Antonio, San Antonio, TX, USA. Electronic address: liss@uthscsa.edu.
Abstract
BACKGROUND: The Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) is a commonly used risk tool for predicting the outcome on biopsy based on the established risk factors. OBJECTIVE: To determine whether incorporation of the novel urinary markers prostate cancer antigen 3 (PCA3) and TMPRSS2:ERG (T2:ERG) into the PCPTRC improves its discrimination, accuracy, and clinical net benefit. DESIGN, SETTING, AND PARTICIPANTS: Since PCA3 and T2:ERG were not measured as part of the PCPTRC, a Bayesian modeling approach was used to combine data where the markers were measured in a Michigan cohort with the PCPTRC as prior probabilities to form an updated PCPTRC. This update was compared to the existing PCPTRC on an independent Early Detection Research Network cohort in terms of discrimination, calibration, and decision curve analysis. RESULTS AND LIMITATIONS: Among the 1225 Michigan biopsies, 57.7%, 24.0%, and 18.3% were negative, with low- and high-grade (Gleason grade≥7) prostate cancer, respectively. Evaluated on the Early Detection Research Network validation set comprising 854 biopsies, areas under the curve (95% confidence interval) for predicting high-grade cancer in the 854 biopsies comprising the validation set were 70.0% (66.0-74.0%), 76.4% (72.8-80.0%), and 77.1% (73.6-80.6%) for the PCPTRC alone, with PCA3 added, and PCA3 and T2:ERG added, respectively. Net benefit was improved for the updated PCPTRC, while calibration was not. Limitations are that the updated PCPTRC is based on two different cohorts, the PCPT and Michigan, and that 20% of the validation set came from the Michigan center. More validation is required; hence, the updated risk tool is posted online. CONCLUSIONS: Incorporation of PCA3 into the PCPTRC improved validation on an independent cohort, whereas T2:ERG offered negligible utility in addition to PCA3. PATIENT SUMMARY: After passing external validation, prostate cancer antigen 3 has been added to the online Prostate Cancer Prevention Trial Risk Calculator for use by patients in deciding whether to proceed to biopsy. TMPRSS2:ERG did not improve prediction on the external validation set, but is included for further validation. Published by Elsevier B.V.
BACKGROUND: The Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) is a commonly used risk tool for predicting the outcome on biopsy based on the established risk factors. OBJECTIVE: To determine whether incorporation of the novel urinary markers prostate cancer antigen 3 (PCA3) and TMPRSS2:ERG (T2:ERG) into the PCPTRC improves its discrimination, accuracy, and clinical net benefit. DESIGN, SETTING, AND PARTICIPANTS: Since PCA3 and T2:ERG were not measured as part of the PCPTRC, a Bayesian modeling approach was used to combine data where the markers were measured in a Michigan cohort with the PCPTRC as prior probabilities to form an updated PCPTRC. This update was compared to the existing PCPTRC on an independent Early Detection Research Network cohort in terms of discrimination, calibration, and decision curve analysis. RESULTS AND LIMITATIONS: Among the 1225 Michigan biopsies, 57.7%, 24.0%, and 18.3% were negative, with low- and high-grade (Gleason grade≥7) prostate cancer, respectively. Evaluated on the Early Detection Research Network validation set comprising 854 biopsies, areas under the curve (95% confidence interval) for predicting high-grade cancer in the 854 biopsies comprising the validation set were 70.0% (66.0-74.0%), 76.4% (72.8-80.0%), and 77.1% (73.6-80.6%) for the PCPTRC alone, with PCA3 added, and PCA3 and T2:ERG added, respectively. Net benefit was improved for the updated PCPTRC, while calibration was not. Limitations are that the updated PCPTRC is based on two different cohorts, the PCPT and Michigan, and that 20% of the validation set came from the Michigan center. More validation is required; hence, the updated risk tool is posted online. CONCLUSIONS: Incorporation of PCA3 into the PCPTRC improved validation on an independent cohort, whereas T2:ERG offered negligible utility in addition to PCA3. PATIENT SUMMARY: After passing external validation, prostate cancer antigen 3 has been added to the online Prostate Cancer Prevention Trial Risk Calculator for use by patients in deciding whether to proceed to biopsy. TMPRSS2:ERG did not improve prediction on the external validation set, but is included for further validation. Published by Elsevier B.V.
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