Integrated assessment of age, PSA and PI-RADS score in correlation with histopathological outcome in prostate cancer

Authors

DOI:

https://doi.org/10.52556/2587-3873.2025.3(105).04

Keywords:

prostate cancer, PSA, PI-RADS, Gleason score, multiparametric MRI

Abstract

re-biopsy evaluation of prostate cancer relies on the integration of clinical, biological, and imaging parameters; however, the relative contribution of age, total PSA, and the PI-RADS score in correlation with histopathological outcomes requires further clarification. This retrospective study included 218 patients evaluated by multiparametric prostate magnetic resonance imaging and prostate biopsy, for whom complete data on age, total PSA, PI-RADS score, and histopathological results were available. Clinically significant prostate cancer was defined as adenocarcinoma with a Gleason score ≥7. Statistical analysis included univariate and multivariate logistic regression, as well as assessment of discriminatory performance using the area under the receiver operating characteristic curve (AUC). Prostate cancer was identified in 73.9% of patients, with clinically significant forms in 53.7%. Age, analyzed as a continuous variable, showed no significant association with either the presence of malignancy or clinically significant prostate cancer. Total PSA was associated with histopathological outcomes, while the PI-RADS score demonstrated the highest discriminatory ability for prostate cancer and for Gleason score ≥7 (p < 0.001). In multivariate analysis, the inclusion of PSA and PI-RADS improved the model’s discriminatory performance compared with univariate models (AUC = 0.75–0.76). Age was not significantly correlated with histopathological outcomes. The combined use of total PSA and PI-RADS score allows more accurate pre-biopsy oncological risk stratification and supports the use of multiparametric magnetic resonance imaging in the evaluation of patients prior to prostate biopsy.

References

BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. In : CA Cancer J Clin. 2024;74(3):229-263. https://doi.org/10.3322/caac.21834

Cornford P, van den Bergh RCN, Briers E, et al. EAUEANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer-2024 Update. In: Eur Urol. 2024;86(2):148-163. https://doi.org/10.1016/j.eururo.2024.03.027

SIEGEL RL, GIAQUINTO AN, JEMAL A. Cancer statistics, 2024. In : CA Cancer J Clin. 2024;74(1):12-49. https://doi.org/10.3322/caac.21820

O'CONNELL C, POSPIECH J, TANGUAY S. The natural history of prostate cancer. In: Can Urol Assoc J. 2025;19(8):275-281. doi:10.5489/ cuaj.9117.

HAVAS A, PATOCS A. The role of aging in cancer. In: Mol Oncol. 2022;16(15):2843-2861. https://doi.org/10.1002/1878-0261.13302

EPSTEIN JI, EGEVAD L, AMIN MB, et al. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. In: Am J Surg Pathol. 2016;40(2):244-252. https://doi.org/10.1097/PAS.0000000000000530

TURKBEY B, ROSENKRANTZ AB, HAIDER MA, et al. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update. In: Eur Urol. 2019;76(3):340-351. https://doi.org/10.1016/j.eururo.2019.02.033

KASIVISVANATHAN V, RANNIKKO AS, BORGHI M, et al. MRI-targeted or standard biopsy for prostate-cancer diagnosis (PRECISION). In: N Engl J Med. 2018;378(19):1767-1777. https://doi.org/10.1056/NEJMoa1801993

MILONAS D, VENCLOVAS Ž, JIEVALTAS M. Age and aggressiveness of prostate cancer: analysis of clinical and pathological characteristics after radical prostatectomy. In: Cent European J Urol. 2019;72(3):240-246. https://doi.org/10.5173/ceju.2019.1974

KIMURA T. Global trends of latent prostate cancer in autopsy studies. In: Cancers (Basel). 2021;13(14):3590. https://doi.org/10.3390/cancers13143590

LEE DH, KOO KC, LEE SH, et al. Impact of age on prostate cancer aggressiveness after adjusting for clinical variables. In: Prostate Int. 2020;8(3): 112-118. https://doi.org/10.1016/j.prnil.2020.05.002

CATALONA WJ, D'AMICO AV, FITZPATRICK JM, et al. What the clinician should know about PSA: limitations and interpretation. In: Eur Urol. 2018;73(3):337-340. https://doi.org/10.1016/j.eururo.2017.11.007

PATEL HD, FENG Z, LANDIS P, et al. Prostate cancer risk calculators incorporating MRI improve biopsy decision-making. In: Eur Urol. 2022;82(5): 465-472. https://doi.org/10.1016/j.eururo.2022.07.018

OERTHER B, ENGEL H, RADTKE JP, et al. Cancer detection rates of PI-RADS v2.1 categories: systematic review and meta-analysis. In: Prostate Cancer Prostatic Dis. 2022;25:497-506. https://doi.org/10.1038/s41391-021-00417-1

ROSENKRANTZ AB, VERMA S, CHOYKE P, et al. Prostate MRI and PI-RADS: a review of strengths and limitations. In: Radiology. 2021;298(2): 273-285. doi:10.1148/radiol.2020202729.

AHMED HU, EL-SHATER BOSAILY A, BROWN LC, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS). In: Lancet. 2017;389(10071):815-822. https://doi.org/10.1016/S0140-6736(16)32401-1

WOO S, SUH CH, KIM SY, CHO JY, KIM SH. Diagnostic performance of PI-RADS version 2 for detection of clinically significant prostate cancer: meta-analysis.In: Eur Urol. 2017;72(2):177-188. https://doi.org/10.1016/j.eururo.2017.01.042

HAJ-MIRZAIAN A, BURK KS, LACSON R, et al. MRI, clinical, and biopsy parameters for prediction of clinically significant prostate cancer: systematic review and meta-analysis. In: JAMA Netw Open. 2024;7(3):e244258. https://doi.org/10.1001/jamanetworkopen.2024.4258

Published

2026-02-20

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How to Cite

[1]
Arian, I. et al. 2026. Integrated assessment of age, PSA and PI-RADS score in correlation with histopathological outcome in prostate cancer. Public Health Economy and Management in Medicine. 3(105) (Feb. 2026), 27–31. DOI:https://doi.org/10.52556/2587-3873.2025.3(105).04.

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