David Hennes

Background/Objectives: On 1 November 2023, the Medicare Benefits Schedule (MBS) introduced major reforms to prostate-specific antigen (PSA) testing in Australia, extending the minimum re-test interval for average-risk men (item 66655) from 12 to 23 months and introducing a new annual high-risk item (66654). These changes were aimed at reducing overscreening, aligning practice with national guidelines, and improving cost efficiency; however, their real-world impact on PSA utilisation, downstream diagnostic activity, and health-system costs has not been evaluated. Methods: We performed a national, population-level analysis of all reimbursed PSA tests (items 66655 and 66654) and prostate magnetic resonance imaging (MRI) scans (item 63541) from November 2021 to October 2025 using MBS claims data. Monthly utilisation trends were examined descriptively and modelled using interrupted time-series segmented regression with Newey–West heteroscedasticity- and autocorrelation-consistent standard errors. Economic impacts were estimated using schedule fees. MRI trends were assessed to explore early signals of downstream diagnostic change. Results: Prior to the reform, average-risk PSA testing (item 66655) averaged 61,704 claims per month (median 62,526). After November 2023, utilisation fell immediately to 49,620 and stabilised at a lower mean of 44,702 claims per month (median 43,495), representing a sustained 27.6 percent reduction. High-risk PSA testing (item 66654) accounted for 130,739 claims post-reform (10.9 percent of monthly post-reform PSA activity), but the increase in high-risk testing did not offset the reduction in average-risk claims; total PSA claims fell from 61,704 to 50,149 per month (−18.7 percent). Interrupted time-series modelling confirmed a large, significant step decrease for item 66655 (−23,191 claims, 95% confidence interval (CI) −31,215 to −15,167; p < 0.001) and for total PSA testing (−16,876 claims, 95% CI −25,899 to −7853; p < 0.001). In contrast, prostate MRI utilisation increased from 3854 to 4454 monthly scans (+15.6 percent) with no significant step-change at the time of the reform (p = 0.74) but a significant acceleration in post-reform growth (+49 scans/month, p = 0.0095). The reform resulted in an estimated net saving of $2.8 million in annual PSA expenditure. Conclusions: The November 2023 MBS reforms led to a large, immediate, and durable reduction in reimbursed PSA screening among average-risk men, while high-risk testing increased modestly but remained proportionally small. Total PSA testing declined meaningfully, producing substantial cost savings for Medicare. Rising MRI utilisation indicates that downstream diagnostic activity did not fall in parallel with reimbursed PSA claims, though this trend may reflect independent drivers of MRI growth rather than preserved screening vigilance. Reductions varied by jurisdiction, with two smaller jurisdictions showing net increases over the study window, underscoring that the national pattern was not uniform.

Background: Artificial intelligence chatbots are increasingly used by patients to obtain health information, including for prostate cancer. While these platforms offer accessible and conversational responses, concerns remain regarding the quality, usability, and clinical relevance of AI-generated content. This study comparatively evaluated patient-directed prostate cancer information generated by commonly used AI chatbots. Methods: Standardised prostate cancer-related prompts were developed using Google Trends and authoritative healthcare resources. Identical queries were submitted to five publicly accessible AI chatbots: ChatGPT 5.2, Google Gemini, Claude AI, Microsoft Copilot, and Perplexity. Responses were independently assessed by two blinded reviewers using the DISCERN instrument for information quality and the Patient Education Materials Assessment Tool for printable materials (PEMAT-P) for understandability and actionability. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). Readability was evaluated using the Flesch–Kincaid Reading Ease score. Descriptive statistics were used for comparative and pooled analyses. Results: Overall information quality was moderate, with a pooled median (interquartile range [IQR]) DISCERN score of 56.5 (53.0–61.0). Higher mean DISCERN scores were observed for ChatGPT 5.2 and Microsoft Copilot, whereas lower scores were observed for Claude and Perplexity. PEMAT-P understandability was consistently high across platforms, with a pooled median (IQR) score of 91.7% (83.3–91.7%). In contrast, PEMAT-P actionability was uniformly poor, with a pooled median (IQR) score of 0% (0–0%). Readability analysis demonstrated moderate complexity, with a pooled median (IQR) Flesch–Kincaid Reading Ease score of 50.4 (49.2–52.5) and a median word count of 666 (657–1022). Inter-rater reliability was good for PEMAT understandability (ICC 0.841) and moderate for DISCERN (ICC 0.712). Conclusions: AI chatbots provide highly understandable but only moderately high-quality patient-directed prostate cancer information, with a consistent lack of actionable guidance. Although variation in content quality was observed across platforms, significant limitations remain in evidence transparency and practical patient support. Future development should prioritise integration of evidence-based resources and actionable decision-support tools to enhance the role of AI chatbots in prostate cancer education.

High-risk and locally advanced prostate cancer represents 20–25% of new diagnoses of prostate cancer and is associated with high rates of recurrence, morbidity, and mortality. The neoadjuvant window provides a unique opportunity for systemic control prior to definitive therapy with radical prostatectomy or radiotherapy (RT). Early trials with first-generation androgen deprivation therapy (ADT) achieved pathological downstaging but no survival benefit. In the 2000s, the advent of chemohormonal regimes using docetaxel provided excitement but mixed results tempered expectations and is now not recommended prior to surgery. Second-generation androgen receptor pathway inhibitors (ARPIs) combined with ADT have demonstrated significant survival benefit in metastatic prostate cancer and are currently being evaluated in large phase III trials in the neoadjuvant setting. RT remains an alternative curative modality, and recent data highlights similar issues to surgery in eradicating micrometastatic disease despite excellent local control. This has driven parallel efforts to evaluate intensified systemic therapy in the pre-RT/neoadjuvant settings. In addition to the excitement surrounding ARPIs, radioligand therapy, such as [¹⁷⁷Lu]Lu-PSMA-617 has shown promise in the neoadjuvant setting and continues to be investigated. Future research aims to incorporate genomic and molecular factors to enable personalised neoadjuvant therapies by identifying damage immunologically responsive subtypes that may derive greater benefit from immune-directed therapies in the peri-operative setting. This narrative review synthesises current evidence for neoadjuvant therapies in high-risk prostate cancer and future directions.

Introduction: PI-RADS 3 lesions represent a diagnostic grey zone on multiparametric MRI, with clinically significant prostate cancer (csPCa) detected in only 10–30%. Their equivocal nature leads to both unnecessary biopsies and missed cancers. Artificial intelligence (AI) has emerged as a potential tool to provide objective, reproducible risk prediction. This review summarises current evidence on AI for risk stratification in patients with indeterminate mpMRI findings, including clarification of key multicentre initiatives such as the PI-CAI (Prostate Imaging–Artificial Intelligence) study—a global benchmarking effort comparing AI systems against expert radiologists. Methods: A narrative review of PubMed and Embase (search updated to August 2025) was conducted using terms including “PI-RADS 3”, “radiomics”, “machine learning”, “deep learning”, and “artificial intelligence.” Eligible studies included those evaluating AI-based prediction of csPCa in PI-RADS 3 lesions using biopsy or long-term follow-up as reference standards. Both single-centre and multicentre studies were included, with emphasis on externally validated models. Results: Radiomics studies demonstrate that handcrafted features extracted from T2-weighted and diffusion-weighted imaging can distinguish benign tissue from csPCa, particularly in the transition zone, with area-under-the-ROC curves typically 0.75–0.82. Deep learning approaches—including convolutional neural networks and large-scale representation-learning frameworks—achieve higher performance and can reduce benign biopsy rates by 30–40%. Models that integrate imaging-based AI with clinical predictors such as PSA density further improve discrimination. The PI-CAI study, the largest international benchmark to date (>10,000 MRI exams), shows that state-of-the-art AI systems can match or exceed expert radiologists for csPCa detection across diverse scanners, centres, and populations, though prospective validation remains limited. Conclusions: AI shows strong potential to refine management of PI-RADS 3 lesions by reducing unnecessary biopsies, improving csPCa detection, and mitigating inter-reader variability. Translation into routine practice will require prospective multicentre validation, harmonised imaging protocols, and integration of AI outputs into clinical workflows with clear thresholds, decision support, and safety-net recommendations.

Prostate-specific membrane antigen (PSMA) is a type II transmembrane glycoprotein that has become central to prostate cancer (PCa) diagnostics and treatment. Beyond its enzymatic role in folate and glutamate metabolism, PSMA is upregulated in advanced PCa, where it contributes to angiogenesis, tumour progression, and therapeutic resistance. This review integrates current understanding of PSMA biology with an emphasis on the role of PSMA expression and the hallmarks of cancer-proliferative signalling, metabolic adaptation, and evasion of cell death. While PSMA has revolutionised theranostic strategies in PCa, its utility as a sole biomarker is limited in select cases such as neuroendocrine differentiation and discordant disease biology. To address these challenges, we highlight emerging biomarkers and novel imaging markers that complement PSMA, including genomic alterations, circulating tumour markers, and exosomal microRNAs. Advances in radiomics and dual-tracer positron emission tomography (PET) further refine patient selection by capturing aggressive low-PSMA phenotypes. Furthermore, PSMA-PET is showing promise in other malignancies, including renal cell carcinoma (RCC) and glioblastoma multiforme (GBM), where neovasculature expression may extend its theranostic applications beyond PCa. By situating PSMA within this broader biomarker landscape, we outline opportunities for theranostic integration, including predictive models, combination therapies and expansion into non-prostate malignancies. Understanding the biology of PSMA in conjunction with novel biomarkers provides a framework for optimising theranostic applications and advancing personalised cancer care.

Targeted prostate cancer screening using polygenic risk scores: lessons from the BARCODE1 trial

Background: Reliable imaging techniques to assist in the diagnosis of prostate cancer (PCa) were not available until the advent of multiparametric magnetic resonance imaging (mpMRI), which has been shown to improve the detection and characterization of prostate lesions. In 2018, the Australian Medicare Benefits Schedule (MBS) extended its coverage to include mpMRI for PCa diagnosis and surveillance. Methods: This retrospective cohort study evaluated the impact of the MBS item expansion on mpMRI referral patterns, sources, yields and patient demographics at a Victorian center. Referrals for prostate mpMRI were analysed over a 30‐month period before and after a 54‐month period following the MBS update. All indications were considered, without exclusion criteria. Baseline continuous variables (age, PSA, PSA density, prostate volume, PIRADS score) were summarized using medians and interquartile ranges. Categorical variables were expressed as numbers and proportions. Statistical analyses included Mann–Whitney U ‐tests and T ‐tests for continuous variables, preceded by a Shapiro–Wilk normality test. GraphPad Prism 6 (San Diego, California, USA) facilitated data analysis. Results: Following the MBS update, there was a yearly average increase of 13.8% in mpMRI referrals, notably with a 125% surge in urologist referrals. The proportion of diagnostic scans rose from 42% pre‐update to 70% post‐update. These results highlight enhanced referral pathways and specific clinical applications of mpMRI after the MBS expansion. Conclusions: In conclusion, federal funding led to a notable rise in mpMRI utilization. Continued monitoring and analysis of the role of mpMRI in PCa diagnostic algorithms are imperative to optimize its benefits and enhance clinical outcomes.

Introduction and Hypothesis Autologous fascia lata has been increasingly utilised in pelvic floor reconstructive surgeries such as sacrocolpopexy and sacrohysteropexy. This case highlights sacrohysteropexy with autologous fascia lata as a promising option for women with advanced uterovaginal prolapse who wish to preserve their uterus and avoid synthetic mesh. Methods We report the case of a 65-year-old woman with stage 3 pelvic organ prolapse following one forceps and one spontaneous vaginal delivery. She presented with cervical-dominant prolapse (6 cm beyond the hymen) and a widened genital hiatus. She was initially managed with a Gellhorn pessary for 7 months, which was removed before surgery. Preoperative findings included prolapse of the cervix, anterior, and posterior vaginal walls (+ 1 cm distal to the hymen). A robot-assisted laparoscopic sacrohysteropexy with autologous fascia lata was performed. Results The 120-min procedure, conducted by a certified urogynaecologist, began with harvesting a 12 × 4 cm autologous fascia lata graft from the left thigh. The graft site was closed with 2–0 absorbable sutures and supported with a compression bandage for 4 weeks. The graft was secured to the cervix and anterior longitudinal ligament through laparoscopic dissection and robot-assisted suturing. No perioperative complications occurred, and the patient was discharged on postoperative day 2. At 1-year follow-up, there was no recurrence of prolapse. Conclusions Sacrohysteropexy using autologous fascia lata is a feasible and effective alternative to synthetic mesh, providing an additional surgical treatment option for women in settings where synthetic polypropylene meshes are not approved, contraindicated, or an unacceptable option.