Prostate health index (phi) and prostate cancer antigen 3 (PCA3) significantly improve diagnostic accuracy in patients undergoing prostate biopsy

The Prostate ◽  
2012 ◽  
Vol 73 (3) ◽  
pp. 227-235 ◽  
Author(s):  
Sisto Perdonà ◽  
Dario Bruzzese ◽  
Matteo Ferro ◽  
Riccardo Autorino ◽  
Ada Marino ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Prostate Biopsy ◽  
Health Index ◽  
Cancer Antigen ◽  
Prostate Health Index ◽  
Prostate Cancer Antigen ◽  
Prostate Health

scholarly journals Comparative Assessment of Urinary Prostate Cancer Antigen 3 and TMPRSS2:ERG Gene Fusion with the Serum [−2]Proprostate-Specific Antigen–Based Prostate Health Index for Detection of Prostate Cancer

2013 ◽  
Vol 59 (1) ◽  
pp. 280-288 ◽  
Author(s):  
Carsten Stephan ◽  
Klaus Jung ◽  
Axel Semjonow ◽  
Kai Schulze-Forster ◽  
Henning Cammann ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Biopsy ◽  
Gene Fusion ◽  
Specific Antigen ◽  
Health Index ◽  
Cancer Antigen ◽  
Free Psa ◽  
Prostate Health Index ◽  
Prostate Cancer Antigen ◽  
Prostate Health

BACKGROUND We compared urinary prostate cancer antigen 3 (PCA3), transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) gene fusion (T2:ERG), and the serum [−2]proprostate-specific antigen ([−2]proPSA)-based prostate health index (Phi) for predicting biopsy outcome. METHODS Serum samples and first-catch urine samples were collected after digital rectal examination (DRE) from consented outpatients with PSA 0.5–20 μg/L who were scheduled for prostate biopsy. The PCA3 score (PROGENSA PCA3, Hologic Gen-Probe) and T2:ERG score (Hologic Gen-Probe) were determined. Measurements of serum PSA, free PSA, and [−2]proPSA (Beckman Coulter) were performed, and the percentages of free PSA (%fPSA) and Phi ([−2]proPSA/fPSA × √PSA) were determined. RESULTS Of 246 enrolled men, prostate cancer (PCa) was diagnosed in 110 (45%) and there was no evidence of malignancy (NEM) in 136 (55%). A first set of biopsies was performed in 136 (55%) of all men, and 110 (45%) had ≥1 repeat biopsies. PCA3, Phi, and T2:ERG differed significantly between men with PCa and NEM, and these markers showed the largest areas under the ROC curve (AUCs) (0.74, 0.68, and 0.63, respectively). PCA3 had the largest AUC of all parameters, albeit not statistically different from Phi. Phi showed somewhat lower specificities than PCA3 at 90% sensitivity. Combination of both markers enhanced diagnostic power with modest AUC gains of 0.01–0.04. Although PCA3 had the highest AUC in the repeat-biopsy cohort, the highest AUC for Phi was observed in DRE-negative patients with PSA in the 2–10 μg/L range. CONCLUSIONS PCA3 and Phi were superior to the other evaluated parameters but their combination gave only moderate enhancements in diagnostic accuracy for PCa at first or repeat prostate biopsy.

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers

2012 ◽  
Vol 413 (15-16) ◽  
pp. 1274-1278 ◽  
Author(s):  
Matteo Ferro ◽  
Dario Bruzzese ◽  
Sisto Perdonà ◽  
Claudia Mazzarella ◽  
Ada Marino ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Biopsy ◽  
Health Index ◽  
Cancer Antigen ◽  
Prostate Health Index ◽  
Prostate Cancer Antigen ◽  
Prostate Health

Accuracy of the prostate health index versus the urinary prostate cancer antigen 3 score to predict overall and significant prostate cancer at initial biopsy

The Prostate ◽  
2014 ◽  
Vol 75 (1) ◽  
pp. 103-111 ◽  
Author(s):  
Thomas Seisen ◽  
Morgan Rouprêt ◽  
Didier Brault ◽  
Priscilla Léon ◽  
Géraldine Cancel-Tassin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Health Index ◽  
Cancer Antigen ◽  
Prostate Health Index ◽  
Initial Biopsy ◽  
Prostate Cancer Antigen ◽  
Prostate Health

scholarly journals Prostate Health Index and Prostate Health Index Density as Diagnostic Tools for Improved Prostate Cancer Detection

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Marija Barisiene ◽  
Arnas Bakavicius ◽  
Diana Stanciute ◽  
Jolita Jurkeviciene ◽  
Arunas Zelvys ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Prostate Biopsy ◽  
Diagnostic Tools ◽  
Health Index ◽  
Accurate Predictor ◽  
Prostate Health Index ◽  
Multivariable Models ◽  
Clinically Significant ◽  
Prostate Health

Background. To evaluate the diagnostic potential of [-2] proPSA (p2PSA), %p2PSA, Prostate Health Index (phi), and phi density (PHID) as independent biomarkers and in composition of multivariable models in predicting high-grade prostatic intraepithelial neoplasia (HGPIN) and overall and clinically significant prostate cancer (PCa). Methods. 210 males scheduled for prostate biopsy with total PSA (tPSA) range 2-10 ng/mL and normal digital rectal examination were enrolled in the prospective study. Blood samples to measure tPSA, free PSA (fPSA), and p2PSA were collected immediately before 12-core prostate biopsy. Clinically significant PCa definition was based on Epstein’s criteria or ISUP grade≥2 at biopsy. Results. PCa has been diagnosed in 112 (53.3%) patients. Epstein significant and ISUP grade≥2 PCa have been identified in 81 (72.3%) and 40 (35.7%) patients, respectively. Isolated HGPIN at biopsy have been identified in 24 (11.4%) patients. Higher p2PSA and its derivative mean values were associated with PCa. At 90% sensitivity, PHID with cut-off value of 0.54 have demonstrated the highest sensitivity of 35.7% for overall PCa detection, so PHID and phi with cut-off values of 33.2 and 0.63 have demonstrated the specificity of 34.7% and 34.1% for ISUP grade≥2 PCa detection at biopsy, respectively. In univariate ROC analysis, PHID with AUC of 0.77 and 0.80 was the most accurate predictor of overall and Epstein significant PCa, respectively, so phi with AUC of 0.77 was the most accurate predictor of ISUP grade≥2 PCa at biopsy. In multivariate logistic regression analysis, phi improved diagnostic accuracy of multivariable models by 5% in predicting ISUP grade≥2 PCa. Conclusions. PHID and phi have shown the greatest specificity at 90% sensitivity in predicting overall and clinically significant PCa and would lead to significantly avoid unnecessary biopsies. PHID is the most accurate predictor of overall and Epstein significant PCa, so phi is the most accurate predictor of ISUP grade≥2 PCa. phi significantly improves the diagnostic accuracy of multivariable models in predicting ISUP grade≥2 PCa.

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