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Prostate Cancer & BPHArchives

Real-World Treatment Patterns in Patients with Metastatic Castration-Sensitive Prostate Cancer in Japan: A Retrospective Health Administrative Data Analysis

 Published on 06/02/2026 |  Original article (Full-text)  | Kawai Taketo et al. | Advances in Therapy 2026; 43(1): 390-406

In Japan, prostate cancer (PC) incidence and mortality rates are increasing [1, 2–3]. In 2022, there were an estimated 96,400 new cases of PC in Japan, and approximately 13,300 deaths were attributable to the disease [2]. The rise in PC cases in Japan is due in part to Japan’s aging population...

Transperineal cognitive fusion MRI-targeted biopsy shows higher detection rates than systematic biopsy in prostate cancer: a prospective cohort study

 Published on 30/01/2026 |  Original article (Full-text)  | Jiang Jifei et al. | BMC Urology 2025; 26(1): 16

Systematic biopsy (SBx) has traditionally been the gold standard for diagnosing prostate cancer, but its clinical application has significant limitations [1, 2]. Although 12-core systematic biopsy has largely replaced the traditional sextant biopsy, its random sampling strategy still cannot overcome...

Deep learning-based diffusion-weighted imaging vs. conventionally obtained diffusion-weighted imaging in prostate cancer extracapsular extension detection: a multicenter retrospective study

 Published on 23/01/2026 |  Original article (Full-text)  | Guo Jianfeng et al. | BMC Medical Imaging 2025; 26(1): 34

Prostate cancer (PCa) is the second most common cancer in men and the third most common cancer of all cancer types [1]. Accurate preoperative staging of PCa is critical for guiding treatment decisions [2]. Extracapsular extension (ECE) is a key determinant in preoperative staging and significantly influences...

Clinically informed intermediate reasoning enables generalizable prostate cancer prognostication through machine learning in limited settings

 Published on 16/01/2026 |  Original article (Full-text)  | Akatsuka Jun et al. | npj Digital Medicine 2026; 9(1): 19

Over the last decade, machine learning (ML) algorithms have been successfully applied to medical image classification, enabling the identification of disease patterns1, 2, 3–4. For instance, algorithms developed as part of the prostate cancer grade assessment (PANDA) challenge have successfully...