The aim of the study was to estimate the minimally important difference (MID) for interpreting group-level change over time, both within a group and between groups, for the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) scores in patients with prostate cancer.
The retinoblastoma tumor suppressor (RB) is a critical regulator of E2F-dependent transcription, controlling a multitude of pro-tumorigenic networks including but not limited to cell cycle control. Here, genome-wide assessment of E2F1 function after RB loss in isogenic models of prostate cancer revealed unexpected repositioning and cooperation with oncogenic transcription factors, including the major driver of […]
Abiraterone and enzalutamide are two oral novel androgen receptor axis-targeted agents approved for the treatment of castration-resistant prostate cancer (mCRPC). Despite the availability of multiple treatments, there is a need to improve the knowledge and management of these drugs in the real-world setting, especially in patient groups under-represented in clinical trials.
To investigate the recent real-world use of first-generation antiandrogens (FGAs) in metastatic castration-resistant prostate cancer (mCRPC) using a retrospective multicentre cohort study. The electronic CRPC Australian Database (ePAD) was interrogated to identify patients with mCRPC.
Background: The European Association of Urology (EAU) Prostate Cancer Guidelines Panel recommends risk groups for biochemically recurrent prostate cancer (BCR) to identify men at high risk of progression or metastatic disease.
To evaluate the relationship between deep inguinal lymph node metastasis (ILNM) and pelvic lymph node metastasis (PLNM) and explore the prognostic value of deep ILNM in penile squamous cell carcinoma (PSCC).
Surveillance regimens for non-muscle invasive bladder cancer (NMIBC) are disparate and controlled trials could inform guidelines. The feasibility of randomizing patients to variable frequency surveillance is unknown.
Characterizing likelihood of response to neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is an important yet unmet challenge. In this study, a machine-learning framework is developed using imaging of biopsy pathology specimens to generate models of likelihood of NAC response.
Controversy regarding cancer-specific mortality (CSM) of elderly and very elderly patients with muscle-invasive, non-metastatic, urothelial carcinoma of the urinary bladder (UCUB) undergoing radical cystectomy (RC) vs radiotherapy (RT) still exists.
The determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer remains a major biological and clinical challenge1,2. Recent advances in interpretability of machine learning models as applied to biomedical problems may enable discovery and prediction in clinical cancer genomics3-5.
