Introduction: Enzalutamide, a second-generation androgen receptor inhibitor, is indicated for the treatment of metastatic disease, as well as in the treatment of non-metastatic castration resistant prostate cancer (PCa). This systematic review aims to determine outcomes and toxicity in patients with non-metastatic castration sensitive prostate cancer (nmCSPC) treated with enzalutamide in the primary or salvage settings. Method: We performed a systematic review focusing on the role of Enzalutamide in the treatment of nmCSPC, using the PubMed/Medline database. Articles focusing on androgen receptor inhibitors in nmCSPC were included, while articles discussing exclusively metastatic or castration-resistant PCa were excluded. Results: The initial search retrieved 401 articles, of which 15 underwent a thorough assessment for relevance. Ultimately, 12 studies with pertinent outcomes were meticulously examined. Among these, seven studies were dedicated to the investigation of enzalutamide in the primary setting, while the remaining five publications specifically addressed its use in salvage settings. Regardless of the treatment setting, our data revealed two distinct therapeutic strategies. The first advocates for the substitution of enzalutamide for androgen deprivation therapy (ADT), based on the premise of achieving equivalent, if not superior, oncological outcomes while minimizing treatment-related toxicity. The second, adopting a more conventional approach, entails augmenting the effectiveness of ADT by incorporating enzalutamide. Conclusion: Enzalutamide has considerable potential as a therapeutic strategy for nmCSPC, either used alone or in combination with ADT in the primary or in the salvage settings. The use of enzalutamide instead of ADT is an appealing strategy. However, more trials will be required to further understand the efficacy and side-effect profile of enzalutamide monotherapy.

Background: Large language models (LLMs) hold promise for supporting clinical tasks, particularly in data-driven and technical disciplines such as radiation oncology. While prior evaluation studies have focused on examination-style settings for evaluating LLMs, their performance in real-life clinical scenarios remains unclear. In the future, LLMs might be used as general AI assistants to answer questions arising in clinical practice. It is unclear how well a modern LLM, locally executed within the infrastructure of a hospital, would answer such questions compared with clinical experts. Objective: This study aimed to assess the performance of a locally deployed, state-of-the-art medical LLM in answering real-world clinical questions in radiation oncology compared with clinical experts. The aim was to evaluate the overall quality of answers, as well as the potential harmfulness of the answers if used for clinical decision-making. Methods: Physicians from 10 departments of European hospitals collected questions arising in the clinical practice of radiation oncology. Fifty of these questions were answered by 3 senior radiation oncology experts with at least 10 years of work experience, as well as the LLM Llama3-OpenBioLLM-70B (Ankit Pal and Malaikannan Sankarasubbu). In a blinded review, physicians rated the overall answer quality on a 5-point Likert scale (quality), assessed whether an answer might be potentially harmful if used for clinical decision-making (harmfulness), and determined if responses were from an expert or the LLM (recognizability). Comparisons between clinical experts and LLMs were then made for quality, harmfulness, and recognizability. Results: There were no significant differences between the quality of the answers between LLM and clinical experts (mean scores of 3.38 vs 3.63; median 4.00, IQR 3.00-4.00 vs median 3.67, IQR 3.33-4.00; P=.26; Wilcoxon signed rank test). The answers were deemed potentially harmful in 13% of cases for the clinical experts compared with 16% of cases for the LLM (P=.63; Fisher exact test). Physicians correctly identified whether an answer was given by a clinical expert or an LLM in 78% and 72% of cases, respectively. Conclusions: A state-of-the-art medical LLM can answer real-life questions from the clinical practice of radiation oncology similarly well as clinical experts regarding overall quality and potential harmfulness. Such LLMs can already be deployed within the local hospital environment at an affordable cost. While LLMs may not yet be ready for clinical implementation as general AI assistants, the technology continues to improve at a rapid pace. Evaluation studies based on real-life situations are important to better understand the weaknesses and limitations of LLMs in clinical practice. Such studies are also crucial to define when the technology is ready for clinical implementation. Furthermore, education for health care professionals on generative AI is needed to ensure responsible clinical implementation of this transforming technology.

Objective: To review the efficacy and safety of reduced dose compared to standard dose Enzalutamide treatment for patients with castration-resistant prostate cancer (CRPC). Methods: PubMed, Scopus, Web of Science, and Cochrane databases were searched for randomized controlled trials and cohort studies reporting the use of Enzalutamide in reduced and standard doses in patients with castration-resistant prostate cancer. Searches were limited to articles published in the English language. Outcome assessments included progression-free survival (PFS), overall survival (OS), adverse events, and serum prostate-specific antigen (PSA) response. Results: Ten studies met the inclusion criteria, including 2481 patients treated with Enzalutamide. Seven studies were retrospective cohorts, two were prospective trials, and one was a prospective cohort. No consistent relationship was identified between OS and PFS and the Enzalutamide dosage. Reduced doses of Enzalutamide decreased the incidence of adverse events, particularly among elderly patients. Conclusions: This systematic review suggests that reduced doses of Enzalutamide in CRPC may maintain therapeutic efficacy in selected patients while improving tolerability. However, inconsistent findings and methodological limitations highlight the need for prospective randomized trials to define optimal and individualized dosing strategies.

Purpose: To compare two stereotactic body radiotherapy (SBRT) regimens in patients with intermediate- or high-risk prostate cancer with regards toxicity and efficacy. Methods/Material: We retrospectively collected data from 198 patients treated with SBRT for prostate cancer at two different institutions. Patients received either 35–36.25 Gy in five fractions (group A) using Cyberknife robotic platform or 42.7 Gy in seven fractions (group B) using a C-arm LINAC (image-guided). Propensity score matching was done (2:1 nearest neighbor matching without replacement), resulting in 120 patients (80 patients for group A, 40 patients for group B). Toxicity, PSA nadir, biochemical failure and disease-free survival (DFS) were analyzed. Results: Median follow up of all patients was 13 months (range 1–91 months). Overall, 23.3% of patients had ≥G2 acute GU toxicity (21.1% group A versus 30% group B (p = 0.222)) and 6.6% of patients ≥G2 GI toxicity (2.5% versus 15% (p = 0.010)). There was one acute G3 GU toxicity in arm A and one acute G4 rectal bleeding in group B (anticoagulated patient). Regarding late toxicity, 14.1% of patients had ≥G2 late GU toxicity (17.4% versus 6.6% (p = 0.159)) and 5.0% of patients had ≥G2 late GI toxicity (1.4% versus 13.3% (p = 0.013)). There was one G3 late GU toxicity in arm B and two G3 late GI toxicities, one in each arm. Relative median PSA reduction was 92.4% (−53.9–99.9%) from baseline PSA (93.7% (−53.9–99.9%) in group A versus 87.7% (39.8–99.9%) in group B (p = 0.043). In total, 4.2% of patients had biochemical relapse, 5.0% in group A and 2.5% in group B (p = 0.518). One-year DFS in the overall cohort was 97.3%, 98.8% in group A and 94.3% in group B (p = 0.318). Conclusion: Both SBRT regimens have acceptable acute and late toxicity and good efficacy. There are significantly more GI toxicities in the seven-fraction regimen. Longer follow-up is warranted for better comparison of long-term efficacy.

Riggenbach E, et al. J Gynecol Oncol. 2025 Dec;37:e41. https://doi.org/10.3802/jgo.2026.37.e41

BACKGROUND Salvage radiation therapy (sRT) is often the sole curative option in patients with biochemical recurrence after radical prostatectomy. After sRT, we developed and validated a nomogram to predict freedom from biochemical failure. OBJECTIVE This study aims to evaluate prostate-specific membrane antigen–positron emission tomography (PSMA-PET)–based sRT efficacy for postprostatectomy prostate-specific antigen (PSA) persistence or recurrence. Objectives include developing a random survival forest (RSF) model for predicting biochemical failure, comparing it with a Cox model, and assessing predictive accuracy over time. Multinational cohort data will validate the model’s performance, aiming to improve clinical management of recurrent prostate cancer. METHODS This multicenter retrospective study collected data from 13 medical facilities across 5 countries: Germany, Cyprus, Australia, Italy, and Switzerland. A total of 1029 patients who underwent sRT following PSMA-PET–based assessment for PSA persistence or recurrence were included. Patients were treated between July 2013 and June 2020, with clinical decisions guided by PSMA-PET results and contemporary standards. The primary end point was freedom from biochemical failure, defined as 2 consecutive PSA rises >0.2 ng/mL after treatment. Data were divided into training (708 patients), testing (271 patients), and external validation (50 patients) sets for machine learning algorithm development and validation. RSF models were used, with 1000 trees per model, optimizing predictive performance using the Harrell concordance index and Brier score. Statistical analysis used R Statistical Software (R Foundation for Statistical Computing), and ethical approval was obtained from participating institutions. RESULTS Baseline characteristics of 1029 patients undergoing sRT PSMA-PET–based assessment were analyzed. The median age at sRT was 70 (IQR 64-74) years. PSMA-PET scans revealed local recurrences in 43.9% (430/979) and nodal recurrences in 27.2% (266/979) of patients. Treatment included dose-escalated sRT to pelvic lymphatics in 35.6% (349/979) of cases. The external outlier validation set showed distinct features, including higher rates of positive lymph nodes (47/50, 94% vs 266/979, 27.2% in the learning cohort) and lower delivered sRT doses (<66 Gy in 57/979, 5.8% vs 46/50, 92% of patients; P<.001). The RSF model, validated internally and externally, demonstrated robust predictive performance (Harrell C-index range: 0.54-0.91) across training and validation datasets, outperforming a previously published nomogram. CONCLUSIONS The developed RSF model demonstrates enhanced predictive accuracy, potentially improving patient outcomes and assisting clinicians in making treatment decisions.