Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator.

To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related discomfort and risks. Data from 655 patients who underwent transperineal prostate biopsy at the First Affiliated Hospital of Wannan Medical College from July 2021 to January 2023 were collected and analyzed. After applying the Synthetic Minority Over-sampling TEchnique class balancing on the training set, multiple machine learning models were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection to identify the significant variables.

Role and correlation of exosomes and integrins in bone metastasis of prostate cancer.

Prostate cancer (PCa) is one of the most prevalent tumours of the male genitourinary system in the world. In recent years, the morbidity of PCa is steadily rising annually in China. Prostate cancer is prone to distant metastasis, and the most significant complication among patients with advanced PCa is bone metastases.