UCLA study finds traditional prostate cancer features fail to predict hormone therapy benefit

A study led by investigators at the UCLA Health Jonsson Comprehensive Cancer Center has found that traditional pathological features used to classify aggressive prostate cancer do not accurately predict which patients will benefit from adding hormone therapy to postoperative radiation.

While features such as high-grade disease, cancer extending outside the prostate, or involvement of the seminal vesicles can help identify patients at risk for worse outcomes, they fail to determine the effectiveness of hormone therapy. This is significant because hormone therapy, while potentially improving outcomes, can cause side effects like fatigue, bone loss, and metabolic changes.

Researchers analyzed data from 4,781 patients across five phase 3 randomized clinical trials. They utilized an adverse feature count score based on four high-risk findings: high-grade disease, seminal vesicle involvement, extension outside the prostate, and positive surgical margins. The findings, published in European Urology, suggest a critical need for molecular biomarkers to better personalize treatment based on specific tumor biology.