Background: Prostate cancer screening has reduced its mortality in 21%. However, this has also led to an increased number of biopsies in order to establish the diagnosis, many of them unnecessary. Current screening guidelines prioritize use of prostatic magnetic resonance and new biomarkers to reduce unnecessary biopsies, however, their implementation in developing countries screening programs is mainly limited by its costs.
Objective: We aimed to evaluate Prostate Biopsy Risk Collaborative Group (PBCG) and Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) 2.0 predictions accuracy in Mexican patients in order to guide prostate biopsy decision making and reduce unnecessary biopsies.
Materials And Methods: We retrospectively analyzed patients between 55 and 90 years old who underwent prostate biopsy in a high-volume center in Mexico between January 2017 and June 2020. Clinical utility of PBCG and PCPTRC 2.0 to predict high-grade prostate cancer (HGPCa) biopsy outcomes was evaluated using decision curve analysis and compared to actual biopsy decision making. Receiver operating characteristics area under the curve (AUC) was used to measure discrimination and external validation.
Results: From 687 patients eligible for prostate biopsy, 433 met selections criteria. One hundred and thirty-five (31.17%) patients were diagnosed with HGPCa, 63 (14.54%) with low-grade disease and 235 (54.27%) had a negative biopsy. PCPTRC 2.0 ≥15% threshold got a standardized net benefit (sNB) of 0.70, while PBCG ≥30% and ≥35% had a sNB of 0.27 and 0.15, respectively. Use of both models for guiding prostate biopsy decision resulted in no statistical difference for HGCPa detection rates, while achieved a significant difference in reducing total and unnecessary biopsies. However, this difference was lower (better) for PCPTRC 2.0, being statistically significative when compared against PBCG thresholds. Both models were well calibrated (AUC 0.79) and achieved external validation compared with international cohorts.
Conclusions: Our study is the first to effectively validate both PCPTRC 2.0 and PBCG predictions for the Mexican population, proving that their use in daily practice improves biopsy decision making by accurately predicting HGPCa and limit unnecessary biopsies without representing additional costs to screening programs.
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http://dx.doi.org/10.1016/j.urolonc.2021.05.022 | DOI Listing |
Eur J Nucl Med Mol Imaging
January 2025
The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Purpose: The study explores the role of multimodal imaging techniques, such as [F]F-PSMA-1007 PET/CT and multiparametric MRI (mpMRI), in predicting the ISUP (International Society of Urological Pathology) grading of prostate cancer. The goal is to enhance diagnostic accuracy and improve clinical decision-making by integrating these advanced imaging modalities with clinical variables. In particular, the study investigates the application of few-shot learning to address the challenge of limited data in prostate cancer imaging, which is often a common issue in medical research.
View Article and Find Full Text PDFJ Gen Intern Med
January 2025
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Background: Active surveillance (AS) is the guideline-recommended treatment for low-risk prostate cancer and involves routine provider visits, lab tests, imaging, and prostate biopsies. Despite good uptake, adherence to AS, in terms of receiving recommended follow-up testing and remaining on AS in the absence of evidence of cancer progression, remains challenging.
Objective: We sought to better understand urologist, primary care providers (PCPs), and patient experiences with AS care delivery to identify opportunities to improve adherence.
Sci Rep
January 2025
Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Moorenstr. 5, 40225, Dusseldorf, Germany.
Aim of this study was to proof the concept of optimizing the contrast between prostate cancer (PC) and healthy tissue by DWI post-processing using a quadrature method. DWI post-processing was performed on 30 patients (median age 67 years, prostate specific antigen 8.0 ng/ml) with PC and clear MRI findings (PI-RADS 4 and 5).
View Article and Find Full Text PDFProstate Cancer Prostatic Dis
January 2025
Department of Urology, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China.
J Urol
January 2025
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO.
Purpose: Conventional prostate magnetic resonance imaging has limited accuracy for clinically significant prostate cancer (csPCa). We performed diffusion basis spectrum imaging (DBSI) prior to biopsy and applied artificial intelligence models to these DBSI metrics to predict csPCa.
Materials And Methods: Between February 2020 and March 2024, 241 patients underwent prostate MRI that included conventional and DBSI-specific sequences prior to prostate biopsy.
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