Objectives: To develop and validate a prostate cancer (PCa) risk calculator (RC) incorporating multiparametric magnetic resonance imaging (mpMRI) and to compare its performance with that of the Prostate Biopsy Collaborative Group (PBCG) RC.
Patients And Methods: Men without a PCa diagnosis receiving mpMRI before biopsy in the Prospective Loyola University mpMRI (PLUM) Prostate Biopsy Cohort (2015-2020) were included. Data from a separate institution were used for external validation. The primary outcome was diagnosis of no cancer, grade group (GG)1 PCa, and clinically significant (cs)PCa (≥GG2). Binary logistic regression was used to explore standard clinical and mpMRI variables (prostate volume, Prostate Imaging-Reporting Data System [PI-RADS] version 2.0 lesions) with the final PLUM RC, based on a multinomial logistic regression model. Receiver-operating characteristic curve, calibration curves, and decision-curve analysis were evaluated in the training and validation cohorts.
Results: A total of 1010 patients were included for development (N = 674 training [47.8% PCa, 30.9% csPCa], N = 336 internal validation) and 371 for external validation. The PLUM RC outperformed the PBCG RC in the training (area under the curve [AUC] 85.9% vs 66.0%; P < 0.001), internal validation (AUC 88.2% vs 67.8%; P < 0.001) and external validation (AUC 83.9% vs 69.4%; P < 0.001) cohorts for csPCa detection. The PBCG RC was prone to overprediction while the PLUM RC was well calibrated. At a threshold probability of 15%, the PLUM RC vs the PBCG RC could avoid 13.8 vs 2.7 biopsies per 100 patients without missing any csPCa. At a cost level of missing 7.5% of csPCa, the PLUM RC could have avoided 41.0% (566/1381) of biopsies compared to 19.1% (264/1381) for the PBCG RC. The PLUM RC compared favourably with the Stanford Prostate Cancer Calculator (SPCC; AUC 84.1% vs 81.1%; P = 0.002) and the MRI-European Randomized Study of Screening for Prostate Cancer (ERSPC) RC (AUC 84.5% vs 82.6%; P = 0.05).
Conclusions: The mpMRI-based PLUM RC significantly outperformed the PBCG RC and compared favourably with other mpMRI-based RCs. A large proportion of biopsies could be avoided using the PLUM RC in shared decision making while maintaining optimal detection of csPCa.
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http://dx.doi.org/10.1111/bju.15835 | DOI Listing |
Here we report results of a phase 1 multi-institutional, open-label, dose-escalation trial (NCT02744287) of BPX-601, an investigational autologous PSCA-directed GoCAR-T® cell product containing an inducible MyD88/CD40 ON-switch responsive to the activating dimerizer rimiducid, in patients with metastatic pancreatic (mPDAC) or castration-resistant prostate cancer (mCRPC). Primary objectives were to evaluate safety and tolerability and determine the recommended phase 2 dose/schedule (RP2D). Secondary objectives included the assessment of efficacy and characterization of the pharmacokinetics of rimiducid.
View Article and Find Full Text PDFBackground: In TALAPRO-2, the poly(ADP-ribose) polymerase inhibitor talazoparib plus the androgen receptor-signaling inhibitor enzalutamide improved radiographic progression-free survival (rPFS) versus placebo plus enzalutamide (hazard ratio [HR] = 0.63; 95% CI, 0.51-0.
View Article and Find Full Text PDFWorld J Surg Oncol
December 2024
Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: To assess the clinical utility of PCA3 in the diagnostic accuracy, the correlation between PCA3 and biopsy or pathological characteristics and the performance of PCA3 to reduce the unnecessary biopsies in Chinese population.
Methods: A prospective study including patients with indication of prostate biopsies from 4 centers was conducted. All patients underwent PCA3 urine tests and prostate biopsies.
BMC Med Imaging
December 2024
Department of MRI, Xinxiang Central Hospital (The Fourth Clinical College of Xinxiang Medical University), 56 Jinsui Road, Xinxiang, Henan, 453000, China.
Background: To develop and validate an interpretable machine learning model based on intratumoral and peritumoral radiomics combined with clinicoradiological features and metabolic information from magnetic resonance spectroscopy (MRS), to predict clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4) and avoid unnecessary biopsies.
Methods: This study retrospectively analyzed 350 patients with suspicious prostate lesions from our institution who underwent 3.0 Tesla multiparametric magnetic resonance imaging (mpMRI) prior to biopsy (training set, n = 191, testing set, n = 83, and a temporal validation set, n = 76).
J West Afr Coll Surg
August 2024
Division of Urology, Department of Surgery, College of Health Sciences, University of Abuja, Abuja, Nigeria.
Background: Prostate cancer (PCa) was the most common noncutaneous cancer among Nigerian men in 2020. Despite this high incidence, documented rates may be an underestimation.
Objectives: This study aimed to determine the hospital incidence rate, trends, and characterise the clinicopathologic features, and treatment outcomes of patients with PCa in our institution.
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