Literature DB >> 28322234

ProPSA and the Prostate Health Index as predictive markers for aggressiveness in low-risk prostate cancer-results from an international multicenter study.

I Heidegger1, H Klocker1, R Pichler1, A Pircher2, W Prokop3, E Steiner1, C Ladurner4, E Comploj4, A Lunacek5, D Djordjevic6, A Pycha4, E Plas5, W Horninger1, J Bektic1.   

Abstract

BACKGROUND: One of the major challenges in prostate cancer (PCa) treatment is distinguishing insignificant PCa from those forms that need active treatment. We evaluated the impact of PSA isoforms on risk stratification in patients with low-risk PCa as well as in active surveillance (AS) candidates who underwent radical prostatectomy.
METHODS: A total of 112 patients with biopsy confirmed Gleason score (GS) 6 PCa of four different international institutions were prospectively enrolled in the study. Blood withdrawal was performed the day before radical prostatectomy. In addition, patients were classified according to the EAU and NCCN criteria for AS candidates. PSA, free PSA (fPSA) and proPSA were measured using dual monoclonal antibody sandwich immunoassays. In addition, the Prostate Health Index (PHI=proPSA/fPSA × √PSA) was calculated. Final histology of the radical prostatectomy specimens was correlated to PSA, its isoforms and PHI.
RESULTS: Serum proPSA levels were significantly elevated in those patients with an upgrade in final histology (GS⩾7). In addition, higher proPSA levels were predictive for extraprostatic extension (⩾pT3a) as well as for positive surgical margins. Interestingly, PHI had an even higher predictive power when compared with proPSA alone concerning GS upgrading, extraprostatic extension and surgical margins in both the total and the AS patient group.
CONCLUSION: We showed in a multicenter study that proPSA is a valuable biomarker to detect patients with aggressive PCa in a cohort of GS 6 patients, who would benefit from active tumor therapy. Combining proPSA with the standard markers PSA and fPSA using PHI further increases the predictive accuracy significantly. Moreover, our data support the use of PHI for monitoring PCa patients under AS.

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Year:  2017        PMID: 28322234     DOI: 10.1038/pcan.2017.3

Source DB:  PubMed          Journal:  Prostate Cancer Prostatic Dis        ISSN: 1365-7852            Impact factor:   5.554


  7 in total

1.  Prostate Health Index (phi) and its derivatives predict Gleason score upgrading after radical prostatectomy among patients with low-risk prostate cancer.

Authors:  Jia-Qi Yan; Da Huang; Jing-Yi Huang; Xiao-Hao Ruan; Xiao-Ling Lin; Zu-Jun Fang; Yi Gao; Hao-Wen Jiang; Yi-Shuo Wu; Rong Na; Dan-Feng Xu
Journal:  Asian J Androl       Date:  2022 Jul-Aug       Impact factor: 3.054

Review 2.  Epigenetic Signature: A New Player as Predictor of Clinically Significant Prostate Cancer (PCa) in Patients on Active Surveillance (AS).

Authors:  Matteo Ferro; Paola Ungaro; Amelia Cimmino; Giuseppe Lucarelli; Gian Maria Busetto; Francesco Cantiello; Rocco Damiano; Daniela Terracciano
Journal:  Int J Mol Sci       Date:  2017-05-27       Impact factor: 5.923

Review 3.  Indications for and transitioning to secondary treatment while on active surveillance for prostate cancer.

Authors:  Allison S Glass; Marc A Dall'Era
Journal:  Transl Androl Urol       Date:  2018-04

Review 4.  Detection and Prognosis of Prostate Cancer Using Blood-Based Biomarkers.

Authors:  Wei Jin; Xiang Fei; Xia Wang; Yan Song; Fangjie Chen
Journal:  Mediators Inflamm       Date:  2020-05-04       Impact factor: 4.711

5.  Combining prostate health index and multiparametric magnetic resonance imaging in the diagnosis of clinically significant prostate cancer in an Asian population.

Authors:  Po-Fan Hsieh; Wei-Juan Li; Wei-Ching Lin; Han Chang; Chao-Hsiang Chang; Chi-Ping Huang; Chi-Rei Yang; Wen-Chi Chen; Yi-Huei Chang; Hsi-Chin Wu
Journal:  World J Urol       Date:  2019-08-22       Impact factor: 4.226

Review 6.  Blood-Derived Biomarkers of Diagnosis, Prognosis and Therapy Response in Prostate Cancer Patients.

Authors:  Katalin Balázs; Lilla Antal; Géza Sáfrány; Katalin Lumniczky
Journal:  J Pers Med       Date:  2021-04-13

7.  Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance.

Authors:  Sacheth Chandramouli; Patrick Leo; George Lee; Robin Elliott; Christine Davis; Guangjing Zhu; Pingfu Fu; Jonathan I Epstein; Robert Veltri; Anant Madabhushi
Journal:  Cancers (Basel)       Date:  2020-09-21       Impact factor: 6.639

  7 in total

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