Purpose: Up to 47% of patients with localized prostate cancer (PCa) treated with radiotherapy (EBRT) eventually develop local recurrence. To date, no clear consensus exists on optimal management. A growing body of interest supports the use of stereotaxic re-irradiation (rSBRT), with promising oncological outcomes and low toxicity profile. We collected a single-center case series of locally recurrent PCa who underwent re-irradiation after a previous course of postoperative or definitive radiotherapy.
Methods And Materials: Data from 101 patients treated at our institution for locally recurrent PCa from June 2012 to June 2021 were retrospectively collected. Patients underwent rSBRT with CyberKnife system (Accuray Inc., Sunnyvale, CA, USA), delivered to intraprostatic or macroscopic recurrences within the prostate bed, for a total dose of 30 Gy in 5 fractions.
Results: All patients received prior EBRT. The median EQD2 total dose was 75.0 Gy (range, 60-80 Gy). Thirty-two (32%) patients were receiving androgen deprivation therapy (ADT) after prior biochemical recurrence. After a median follow-up of 57.8 months, BR occurred in 55 patients (54.5%), with a median BR-free survival (BRFS) of 40.4 months (95% C.I. 34.3-58.3). Thirty-two patients (31.7%) developed metastatic disease, with a median metastasis-free survival (MFS) not reached. PSA ≥ 2.5 ng/ml and ADT were associated with worst BRFS (26.06 vs. 39.3 months, p = 0.03 and 22.7 vs. 27 months, p = 0.01, respectively). Castration-resistant status and ADT were found to be predictive of worst MFS (34.1 vs. 50.5 months, p = 0.02 and 33.5 vs. 53.1 months, p = 0.002, respectively). Concomitant ADT was confirmed as an independent factor for MFS (HR 4.8, 95% CI 1.5-10.6, p = 0.007). No grade > /2 adverse were recorded.
Conclusions: After almost 5 years of follow-up, with a median BRFS of 40.4 months and no grade ≥ 2 AEs, Cyberknife rSBRT proved effective and safe in a cohort of 101 patients affected by locally recurrent PCa.
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http://dx.doi.org/10.1007/s11547-023-01721-7 | DOI Listing |
Transpl Infect Dis
December 2024
Department of Infectious Diseases, The University of Tokyo Hospital, Tokyo, Japan.
Introduction: The appropriate duration of therapy for uncomplicated gram-negative bloodstream infection (GN-BSI) in liver transplant (LTx) recipients remains unknown. This study aims to explore the effectiveness of a short-course antimicrobial therapy.
Methods: This retrospective study was performed in a single LTx center in Japan.
Int Urol Nephrol
December 2024
Department of Urology, Unidade Local de Saúde de Santo António, Centro Hospitalar Universitário Do Porto, 8th floor, Largo Do Prof. Abel Salazar, 4099-001, Porto, Portugal.
Introduction: The primary aim of stone treatment is to achieve stone-free status. Residual fragments can cause stone growth, recurrence, urinary tract infections, and ureteric obstruction. Our goal was to describe the natural history of stone burden after retrograde intrarenal surgery (RIRS) based on stone-free status (SFS), evaluating stone growth and stone-events.
View Article and Find Full Text PDFHead Neck
December 2024
Head and Neck Unit, The Royal Marsden Hospital, London, UK.
Background: To investigate the management of recurrent head and neck squamous cell carcinoma (rHNSCC) and describe survival outcomes.
Methods: Post hoc subgroup analysis of a retrospective national observational cohort was conducted. All patients with rHNSCC who received a definitive treatment decision between September 1, 2021 and November 30, 2021 were included.
Int J Clin Oncol
December 2024
Japan Society of Clinical Oncology, Editorial Committee, Tokyo, Japan.
Sci Rep
December 2024
School of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar, 161006, China.
A prediction model of the pig house environment based on Bayesian optimization (BO), squeeze and excitation block (SE), convolutional neural network (CNN) and gated recurrent unit (GRU) is proposed to improve the prediction accuracy and animal welfare and take control measures in advance. To ensure the optimal model configuration, the model uses a BO algorithm to fine-tune hyper-parameters, such as the number of GRUs, initial learning rate and L2 normal form regularization factor. The environmental data are fed into the SE-CNN block, which extracts the local features of the data through convolutional operations.
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