From Diagnosis to Advanced Disease: a Comprehensive Review of Contemporary Management of Prostate Cancer, Including Surgical Techniques, Systemic Therapies, and Modern Technologies
Year: 2026
Type: article
Abstract: Background: Prostate cancer management has profoundly evolved from generalized protocols to a personalized, technology-driven paradigm. The integration of robotic surgery, artificial intelligence (AI), and novel systemic therapies necessitates a synthesis of the current state of care. Aim: To synthesize evidence on contemporary prostate cancer management, focusing on the comparative effectiveness of surgical techniques, the impact of surgeon experience, and the role of emerging technologies like AI and novel systemic therapies. Material and methods: A structured analysis of 27 provided scientific documents (systematic reviews, trials, guidelines) was performed. Key data on diagnostic, functional, and oncological outcomes were extracted and synthesized. Results: AI-powered analysis of mpMRI achieves high accuracy (AUROC >0.90) in detecting significant disease. Robotic radical prostatectomy (RARP) is superior to laparoscopy (LRP) with fewer complications and better outcomes for continence (RR 0.43), erectile function (RR 1.38), and biochemical recurrence (RR 0.59). Surgeon experience is a key factor (250-case learning curve). For mHSPC, adding ARPIs to ADT improves survival (HR for mortality ~0.63). In mCRPC, PARP inhibitors and 177Lu-PSMA-617 offer survival benefits in selected patients. Conclusions: Contemporary prostate cancer care emphasizes precision. RARP is the surgical standard for localized disease, but outcomes depend heavily on surgeon volume. AI shows promise but requires extensive validation for clinical adoption. Early combination therapies are standard in advanced disease. A multidisciplinary, evidence-based approach is required to integrate these modalities and optimize patient outcomes.
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $100
OpenAlex ID: W7140041951
