A research team at MedUni Vienna developed a method which utilizes multi-omics and machine learning to identify prostate cancer patients for whom surgical treatment is the best option, potentially avoiding unnecessary surgery in patients with a lower risk of tumor spread.
Investigators at the UCLA Health Jonsson Comprehensive Cancer Center have validated a test that can accurately predict which patients with prostate cancer are at higher risk of developing long-lasting urinary side effects after receiving radiation therapy.
