PARP Inhibitors in Metastatic Prostate Cancer: Bridging Biomarker Complexity and Clinical Decision-Making Through a Pragmatic Treatment Framework

Background: The therapeutic landscape of metastatic prostate cancer has rapidly evolved with the integration of biomarker-driven strategies, particularly targeting homologous recombination repair (HRR) alterations. Poly(ADP-ribose) polymerase inhibitors (PARPi) have demonstrated clinically meaningful benefit, especially in Breast Cancer genes 1/2-altered tumors, through synthetic lethality. However, the expansion of PARPi across multiple Treatment settings has introduced substantial complexity in patient selection, Treatment sequencing, and biomarker interpretation. This review aims to move beyond a descriptive synthesis of clinical trials and provide a clinically applicable, decision-oriented framework for the use of PARP inhibitors in metastatic prostate cancer. Methods: We conducted a narrative review of pivotal phase II and III trials published between 2020 and 2026 evaluating PARPi as monotherapy or in combination strategies. Evidence was critically analyzed with a focus on biomarker relevance, Treatment positioning, and real-world applicability. Evidence Synthesis: PARPi consistently improve radiographic progression-free survival, with the most robust and clinically meaningful benefit observed in BRCA-altered disease. In contrast, non-BRCA HRR alterations demonstrate heterogeneous and often limited predictive value, highlighting the limitations of a binary biomarker approach. Combination strategies in first-line metastatic castration-resistant prostate cancer (mCRPC) have expanded therapeutic options but raise important concerns regarding toxicity, overTreatment, and unclear benefit in biomarker-unselected populations. In parallel, variability in molecular testing strategies and access continues to limit real-world implementation. Conclusions: PARP inhibitors represent a cornerstone of precision oncology in metastatic prostate cancer, but their optimal use requires a refined, biomarker-informed approach. In this context, we propose a pragmatic 2026 clinical decision framework integrating molecular characteristics, prior Treatment exposure, and clinical factors. This approach aims to bridge the gap between clinical trial evidence, guideline recommendations, and real-world practice.