Scott A Tomlins1, John R Day2, Robert J Lonigro3, Daniel H Hovelson4, Javed Siddiqui5, L Priya Kunju5, Rodney L Dunn6, Sarah Meyer2, Petrea Hodge2, Jack Groskopf2, John T Wei6, Arul M Chinnaiyan7. 1. Michigan Center for Translational Pathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Urology, University of Michigan Medical School, Ann Arbor, MI, USA; Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, USA. Electronic address: tomlinss@umich.edu. 2. Hologic/Gen-Probe Inc., San Diego, CA, USA. 3. Michigan Center for Translational Pathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA; Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, USA. 4. Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA. 5. Michigan Center for Translational Pathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA. 6. Department of Urology, University of Michigan Medical School, Ann Arbor, MI, USA. 7. Michigan Center for Translational Pathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Urology, University of Michigan Medical School, Ann Arbor, MI, USA; Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA; Howard Hughes Medical Institute, University of Michigan Medical School, Ann Arbor, MI, USA. Electronic address: arul@umich.edu.
Abstract
BACKGROUND: TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers. OBJECTIVE: Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy. DESIGN, SETTING, AND PARTICIPANTS: T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit. RESULTS AND LIMITATIONS: Among informative validation cohort samples (n=1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p<0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p<0.001; PCPTrc: 0.754 vs 0.707, p=0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p<0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities. CONCLUSIONS: Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy. PATIENT SUMMARY: Incorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.
BACKGROUND:TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers. OBJECTIVE: Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy. DESIGN, SETTING, AND PARTICIPANTS: T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit. RESULTS AND LIMITATIONS: Among informative validation cohort samples (n=1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p<0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p<0.001; PCPTrc: 0.754 vs 0.707, p=0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p<0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities. CONCLUSIONS: Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy. PATIENT SUMMARY: Incorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.
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