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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 PDFClinical assessment of urinary prostate cancer antigen 3 in Chinese population: a large-scale, prospective and multicenter study.
World 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.
Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features.
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).
The Trends, Clinicopathological Features, and Treatment Outcomes of Patients with Prostate Cancer in Lokoja, Nigeria.
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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