Dietary polyphenol and microbiota interactions in the context of prostate health

2021 ◽  
Author(s):  
Jakub P. Piwowarski ◽  
Iwona Stanisławska ◽  
Sebastian Granica
Keyword(s):  
Prostate Health

scholarly journals PHI density prospectively improves prostate cancer detection

2021 ◽  
Author(s):  
Carsten Stephan ◽  
Klaus Jung ◽  
Michael Lein ◽  
Hannah Rochow ◽  
Frank Friedersdorff ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Specific Antigen ◽  
Roc Curves ◽  
Grey Zone ◽  
Net Benefit ◽  
Threshold Probability ◽  
Free Psa ◽  
Prostate Health Index ◽  
Magnetic Resonance Imaging Mri ◽  
Prostate Health

Abstract Purpose To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort. Methods PHID values were calculated from prostate-specific antigen (PSA), free PSA and [− 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate cancer (PCa) and 505 with no evidence of malignancy (NEM). In detail, 562 patients were biopsied at the Charité Hospital Berlin and 495 patients at the Sana Hospital Offenbach. All patients received systematic or magnetic resonance imaging (MRI)/ultrasound fusion-guided biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing areas under the ROC-curves (AUC). The decision curve analysis (DCA) was performed with the MATLAB Neural Network Toolbox. Results PHID provided a significant larger AUC than PHI (0.835 vs. 0.801; p = 0.0013) in our prospective cohort of 1057 men from 2 centers. The DCA had a maximum net benefit of ~ 5% for PHID vs. PHI between 35 and 65% threshold probability. In those 698 men within the WHO-calibrated PSA grey-zone up to 8 ng/ml, PHID was also significantly better than PHI (AUC 0.819 vs. 0.789; p = 0.0219). But PHID was not different from PHI in the detection of significant PCa. Conclusions Based on ROC analysis and DCA, PHID had an advantage in comparison with PHI alone to detect any PCa but PHI and PHID performed equal in detecting significant PCa.

scholarly journals Performance of prostate health index and PSA density in a diverse biopsy‐naïve cohort with mpMRI for detecting significant prostate cancer

BJUI Compass ◽  
2021 ◽  
Author(s):  
Samuel Carbunaru ◽  
James Stinson ◽  
Rilwan Babajide ◽  
Courtney M. P. Hollowell ◽  
Ximing Yang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Health Index ◽  
Psa Density ◽  
Prostate Health Index ◽  
Prostate Health

Clinical performance of the Prostate Health Index (PHI) for the prediction of prostate cancer in obese men: data from the PROMEtheuS project, a multicentre European prospective study

2015 ◽  
Vol 115 (4) ◽  
pp. 537-545 ◽  
Author(s):  
Alberto Abrate ◽  
Massimo Lazzeri ◽  
Giovanni Lughezzani ◽  
Nicolòmaria Buffi ◽  
Vittorio Bini ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prospective Study ◽  
Clinical Performance ◽  
Health Index ◽  
Prostate Health Index ◽  
Prostate Health

Comparison of PHI and PHI Density for Prostate Cancer Detection in a Large Retrospective Caucasian Cohort

2021 ◽  
pp. 1-6
Author(s):  
Robert Peters ◽  
Carsten Stephan ◽  
Klaus Jung ◽  
Michael Lein ◽  
Frank Friedersdorff ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Volume ◽  
Specific Antigen ◽  
Roc Curves ◽  
Net Benefit ◽  
Threshold Probability ◽  
Free Psa ◽  
Prostate Health Index ◽  
Caucasian Cohort ◽  
Prostate Health

<b><i>Background:</i></b> Beyond prostate-specific antigen (PSA), other biomarkers for prostate cancer (PCa) detection are available and need to be evaluated for clinical routine. <b><i>Objective:</i></b> The aim of the study was to evaluate the Prostate Health Index (PHI) density (PHID) in comparison with PHI in a large Caucasian group &#x3e;1,000 men. <b><i>Methods:</i></b> PHID values were used from available patient data with PSA, free PSA, and [−2]pro­PSA and prostate volume from 3 former surveys from 2002 to 2014. Those 1,446 patients from a single-center cohort included 701 men with PCa and 745 with no PCa. All patients received initial or repeat biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing area under the ROC curves (AUCs), precision-recall approach, and decision curve analysis (DCA). <b><i>Results:</i></b> PHID medians differed almost 2-fold between PCa (1.12) and no PCa (0.62) in comparison to PHI (48.6 vs. 33; <i>p</i> always &#x3c;0.0001). However, PHID and PHI were equal regarding the AUC (0.737 vs. 0.749; <i>p</i> = 0.226), and the curves of the precision-recall analysis also overlapped in the sensitivity range between 70 and 100%. DCA had a maximum net benefit of only ∼5% for PHID versus PHI between 45 and 55% threshold probability. Contrary, in the 689 men with a prostate volume ≤40 cm<sup>3</sup>, PHI (AUC 0.732) showed a significant larger AUC than PHID (AUC 0.69, <i>p</i> = 0.014). <b><i>Conclusions:</i></b> Based on DCA, PHID had only a small advantage in comparison with PHI alone, while ROC analysis and precision-recall analysis showed similar results. In smaller prostates, PHI even outperformed PHID. The increment for PHID in this large Caucasian cohort is too small to justify a routine clinical use.

Use of the Prostate Health Index for the Detection of Aggressive Prostate Cancer at Radical Prostatectomy

2015 ◽  
Vol 95 (4) ◽  
pp. 390-399 ◽  
Author(s):  
Luigi Mearini ◽  
Elisabetta Nunzi ◽  
Carla Ferri ◽  
Guido Bellezza ◽  
Carolina Lolli ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Lymph Node ◽  
High Risk ◽  
Radical Prostatectomy ◽  
Gleason Score ◽  
Health Index ◽  
Final Pathology ◽  
High Risk Disease ◽  
Prostate Health Index ◽  
Prostate Health

Introduction: In current study, we compared the accuracy of the PSA isoform p2PSA and its derivatives, the percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI) in the detection of prostate cancer (PC) characteristics at the final pathology with respect to reference standards. Materials and Methods: This was an observational prospective study evaluating 43 consecutive PC patients treated with laparoscopic/robotic radical prostatectomy (RP). Logistic regression models were fitted to test the predictors of pT3 stage, pathologic Gleason score ≥8 or Gleason score upgrading, margin status, lymph node invasion, and the presence of high-risk disease (pT3 disease and/or Gleason score ≥8 and/or positive lymph node). The comparative base model included tPSA, clinical stage, biopsy Gleason score, and percentage of positive core. Results: Seventeen patients (39.5%) were affected by pT3 disease or had a pathologic Gleason score ≥8; positive margins were detected in 12 patients (27.9%), lymph node invasion was found in 2 patients (4.7%), and 15 patients (34.8%) harbored high-risk disease. In the univariate analysis, p2PSA, %p2PSA, and PHI were significant predictors of pT3 disease, pathologic Gleason score, and the presence of high-risk disease (all p < 0.05), whereas only PHI was an independent predictor of pT3 disease, margin status, and presence of high-risk disease, increasing the accuracy of a base multivariable model by 6.3% (p < 0.05) and 4.2% (p < 0.05) for the prediction of pT3 and high-risk disease, respectively. Conclusions: p2PSA and its derivatives, primarily PHI, were significant predictors of unfavorable PC characteristics as detected at the final pathology, thus improving the clinical performance of standard prognostic factors for aggressive disease.

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