Abstract
BACKGROUND: Emerging evidence has revealed the potential efficacy of Novel Hormonal Agent (NHA) or chemotherapy in high-risk patients with biochemical recurrence (BCR). However, the optimal drug-based treatment strategy remains unknown. METHODS: We conducted a comprehensive search of the PubMed, Cochrane, and Embase databases up to February 18, 2024 to identify relevant studies. Our analysis focused on outcome measures, including prostate-specific antigen progression-free survival (PSA-PFS), overall survival (OS) and the incidence of adverse events (AEs). A Bayesian network meta-analysis was utilized to indirectly compare the efficacy and safety of various treatment modalities. RESULTS: Four randomized controlled trials with 2074 participants were selected for data extraction and analysis. Treatment combining Androgen Deprivation Therapy (ADT) with Enzalutamide (ENZA) significantly enhanced PSA-PFS as compared to ADT monotherapy (Hazard Ratio (HR) = 0.07, 95% Confidence Interval (CI) 0.01-0.97). The surface under the cumulative ranking curve (SUCRA) indicated ADT + ENZA as the most effective strategy for improving PSA-PFS. In terms of OS improvement, the treatments were ranked as follows: ADT + Docetaxel (DOC), ADT + ENZA, ENZA, and ADT. In terms of adverse event incidence, ADT exhibited the lowest incidence of adverse events, followed by ADT + ENZA. In the meta-analysis, ADT + NHA combined therapy achieved superior efficacy in PSA-PFS and OS than ADT. CONCLUSION: This study suggests that ADT + NHA, particularly ADT + ENZA, may provide a significant survival benefit and an acceptable safety profile for prostate cancer patients at high-risk BCR. The findings could potentially inform the selection of medications for these patients, although further confirmation through large-scale clinical trials is imperative.
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CITATION STYLE
Wang, Q., Zhu, Q., Liu, H., Huang, K., Zhang, X., Zhao, J., … Shen, P. (2025). Drug treatment options of high-risk biochemically recurrent prostate cancer based on efficacy and safety: a systematic review and Bayesian network analysis. European Journal of Medical Research, 30(1). https://doi.org/10.1186/s40001-025-02643-y
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