Search Results (205)

Background/Objectives: Prostate cancer is a major public health concern and a leading cause of cancer-related morbidity and mortality among men worldwide, with disproportionately high mortality rates in sub-Saharan Africa. Late diagnosis, limited access to screening services, low health-seeking behaviour, and sociocultural barriers contribute to poor outcomes, particularly in rural settings. However, evidence on effective and context-appropriate strategies for prostate cancer prevention and early detection in African countries remains fragmented. Objective: This scoping review protocol aims to map and synthesize existing evidence on strategies implemented to reduce the burden of prostate cancer in Africa, with a focus on prevention, screening, community engagement approaches, and their acceptability. Methods: This scoping review protocol will be conducted in accordance with established methodological frameworks and reported following the PRISMA-ScR guidelines. A comprehensive search will be undertaken in PubMed (MEDLINE), EBSCOhost, ScienceDirect, CINAHL, and ProQuest. Studies conducted in African countries and published in English, French, or Portuguese will be included. Study selection and data extraction will be managed using Covidence, and findings will be summarized descriptively and thematically. Expected Results: This review is expected to identify and categorize existing prostate cancer prevention and early detection strategies implemented across African settings. Gaps in evidence, differences in implementation, and reported levels of acceptability among men are anticipated to be highlighted. Conclusions: The completed scoping review is expected to provide a comprehensive overview of prostate cancer prevention and early detection strategies implemented in Africa and to identify gaps in evidence. The evidence will inform the development of culturally responsive and context-specific interventions, with particular relevance for rural South African settings. This manuscript presents a protocol for a scoping review; no review findings are reported. Full article

Purpose: A growing body of evidence has emerged on the role of diet for health outcomes in cancer survivors. Patients transitioning to post-treatment care may seek guidance on dietary changes, and summaries of the evidence for dietary patterns recommended by guidelines can support providers in effectively answering questions. Increasing evidence suggests that food choices impact planetary health. Plant-based diets are one eating pattern that may improve patient outcomes and planetary health. Methods: We performed a literature review and used narrative reporting to summarize evidence for plant-based diets and offer specific guidance for breast, colorectal, and prostate cancer patients who are post-diagnosis. Specifically, we reviewed impacts on recurrence, all-cause, and cancer-specific mortality. Results: Increased fibre intake by consuming foods like fruits, vegetables, and whole grains is associated with a decreased risk of breast cancer-specific and all-cause mortality, as well as reduced colon cancer-specific mortality. Replacing refined grains with whole grains is associated with improved disease-free survival for colon cancer survivors. Higher tree nut consumption is associated with improved disease-free survival for breast, colorectal, and prostate cancer survivors. Soy is safe to consume for breast cancer survivors and is associated with a reduced risk of recurrence. Conversely, more Western dietary patterns high in processed meat intake are associated with an increased risk of colon cancer recurrence and prostate cancer mortality. There are also environmental benefits of a shift towards plant-based diets to address the adverse health outcomes associated with climate change and its potential impact on cancer care delivery as previously outlined in a 2024 ASCO policy statement. Conclusions: Based on the best existing evidence, providers can suggest that patients consider plant-based dietary patterns in the post-treatment phase of their cancer care to support health outcomes and planetary health. Full article

Background/Objectives: Prostate cancer is the second most common cause of cancer-related mortality among the male population worldwide. It is among the leading reasons for the increasing number of years of life lost, working years of life lost, and gross domestic product (GDP) loss in Bulgaria. The primary objective of this study is to evaluate the burden of prostate cancer in Bulgaria, including calculating years of life lost (YLL), years of working life lost (YWLL), and the associated indirect costs. Methods: An observational time-series study was conducted using official national data from the National Statistical Institute (NSI), the INFOSTAT database, and the National Social Security Institute. The study covered the period 2008–2023 and included all registered male deaths attributed to malignant neoplasm of the prostate (ICD-10: C61). YLL, YWLL, and indirect costs were calculated using the human capital approach. Due to restricted access to age-specific mortality files, additional mortality records were obtained through formal data requests to NSI. Results: Prostate cancer led to 127,457 YLL and 6345 YWLL, with productivity losses reaching €88.2 million. Mortality showed an overall increasing trend up to 2020, while YWLL declined due to deaths shifting to older age groups. Conclusions: Despite the advancements in prostate cancer diagnosis and treatment, our findings demonstrate a negative trend regarding YLL, YWLL, and indirect costs associated with the disease, in contrast to other European countries. Strengthening early screening, reducing diagnostic delays, and improving national cancer registry capacity are critical to mitigating future health and economic losses. Full article

Prostate cancer remains the most frequently diagnosed malignancy in men and a leading cause of cancer-related mortality. Multiparametric MRI (mpMRI) has become the gold standard for non-invasive diagnosis, staging, and follow-up. Yet, its widespread adoption is hampered by long acquisition times, inter-reader variability, and interpretative complexity. Though most papers focus on specific applications without offering a cohesive therapeutic perspective, artificial intelligence (AI) has recently attracted attention as a potential solution to these shortcomings. For instance, deep learning models can help optimize imaging protocols for biparametric and multiparametric MRI, and AI-based reconstruction techniques have shown promise for reducing acquisition times without sacrificing diagnostic performance. Several systems have produced outcomes in the diagnostic phase that are comparable to those of skilled radiologists, as demonstrated in multicenter settings such as PI-CAI. Radiomics and radiogenomics provide more detailed insights into the biology of the disease by extracting quantitative features associated with tumor aggressiveness, extracapsular expansion, and treatment response, in addition to detection. Despite these developments, methodological variability, a lack of multicenter validation, proprietary algorithms, and unresolved standardization and governance difficulties continue to restrict clinical translation. Our work emphasizes the maturity of existing technologies, ongoing gaps, and the progressive integration necessary for successful clinical adoption by presenting AI applications aligned with the patient pathway. In this context, this review aims to outline how AI can support the entire patient journey—from acquisition and protocol selection to detection, quantitative analysis, treatment assessment, and follow-up—while maintaining a clinically centered perspective that emphasizes practical relevance over theoretical discussion, potentially enabling more reliable, effective, and customized patient care in the field of prostate cancer. Full article

Prostate cancer is one of the most common malignancies in men, and advanced or metastatic disease remains associated with substantial morbidity and mortality. Therapeutic progress in recent years has been driven by the introduction of targeted treatment strategies, notably poly (ADP-ribose) polymerase (PARP) inhibitors, prostate-specific membrane antigen (PSMA)–directed radioligand therapy (RLT), and androgen receptor pathway inhibitors (ARPIs). This review summarizes evidence from phase II and III clinical trials, meta-analyses, and real-world studies evaluating the efficacy, safety, and clinical integration of olaparib, lutetium (¹⁷⁷Lu) vipivotide tetraxetan, and abiraterone in advanced prostate cancer. Emphasis is placed on the practical clinical application of these agents, including patient selection, treatment sequencing, and combination strategies. PARP inhibition with olaparib has demonstrated clear benefits in metastatic castration-resistant prostate cancer (mCRPC) with homologous recombination repair (HRR) mutations, particularly BRCA1/2 alterations. PSMA-directed RLT offers a survival advantage in PSMA-positive mCRPC following AR pathway inhibition, with distinct toxicity considerations that influence patient selection. Abiraterone remains a cornerstone therapy across disease stages and plays an important role both as monotherapy and as a combination partner. Emerging data suggest a potential synergy between PARP inhibitors and AR-targeted agents, while also highlighting the limitations of biomarker-unselected approaches. We conclude that the optimal use of PARP inhibitors, PSMA-targeted RLT, and ARPIs requires a personalized strategy guided by molecular profiling, functional imaging, prior treatment exposure, and safety considerations. This clinically focused overview aims to support evidence-based decision-making in an increasingly complex treatment landscape. Full article

Prostate cancer remains one of the most common malignancies in men worldwide, with incidence and mortality steadily increasing across diverse populations. While early detection and radical prostatectomy can achieve durable control in a subset of patients, approximately 40% of men will ultimately experience biochemical recurrence often in the absence of clinically detectable disease. Conventional imaging approaches—CT, MRI, and bone scintigraphy—have limited sensitivity for early relapses, frequently leading to delayed diagnosis and suboptimal treatment planning. The discovery of prostate-specific membrane antigen (PSMA) in 1987 and its subsequent clinical translation into positron emission tomography (PET) imaging with [⁶⁸Ga]Ga-PSMA-11 in 2012, followed by U.S. FDA approval in 2020, has transformed the landscape of prostate cancer imaging. PSMA PET has demonstrated superior accuracy over conventional imaging, as highlighted in the landmark proPSMA trial and now serves as the foundation for theranostic approaches that integrate diagnostic imaging with targeted radioligand therapy. The clinical approval of [¹⁷⁷Lu]Lu-PSMA-617 (Pluvicto^®: (lutetium Lu 177 vipivotide tetraxetan, Advanced Accelerator Applications USA, Inc., a Novartis company) has established targeted radioligand therapy as a viable option for men with metastatic castration-resistant prostate cancer, extending survival in patients with limited alternatives. Emerging strategies, including next-generation ligands with improved tumor uptake and altered clearance pathways, as well as the integration of artificial intelligence for imaging quantification, are poised to further refine patient selection, dosimetry, and treatment outcomes. This review highlights the evolution of PSMA-based imaging and therapy, discusses current clinical applications and limitations, and outlines future directions for optimizing theranostic strategies in prostate cancer care. Full article

Background: Prostate cancer remains a leading cause of mortality in men, making early, accurate detection crucial for early intervention. While radiologists utilize the Prostate Imaging Reporting and Data System (PI-RADS) for the interpretation of MRI imaging, variations in expertise and inter-reader differences can affect diagnostic accuracy. Artificial intelligence (AI) has emerged as a promising tool for automated detection, with the potential to achieve diagnostic performance comparable to radiologists in identifying clinically significant prostate cancer (csPCa), streamline workflows, and reduce unnecessary biopsies. However, its real-world performance compared to expert radiologists remains a topic of ongoing debate. Purpose: This meta-analysis aims to evaluate whether AI can achieve diagnostic performance that is comparable to that of radiologists in MRI-based prostate cancer detection by comparing diagnostic accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Methods: Following PRISMA 2020 guidelines, we searched PubMed for studies directly comparing AI and radiologists in MRI-based detection of csPCa. Ten studies (20,423 patients) were included, and quality was assessed using QUADAS-2. Analyses included forest plots for diagnostic sensitivity and specificity, funnel plots of AUROC to assess publication bias, and paired AUROC difference plots to directly compare diagnostic accuracy. Results: Pooled sensitivity was 0.87 (95% CI: 0.81–0.94) for AI and 0.85 (95% CI: 0.77–0.94) for radiologists; pooled specificity was 0.61 (95% CI: 0.51–0.72) for AI and 0.63 (95% CI: 0.54–0.71) for radiologists. Funnel plots of AUROC against standard error showed no strong visual evidence of publication bias. Paired AUROC difference analysis demonstrated no significant performance difference between AI and radiologists, with a pooled difference of 0.018 (p = 0.378). Conclusions: AI systems demonstrated diagnostic performance comparable to radiologists for MRI-based detection of csPCa, with a nonsignificant and slightly higher pooled sensitivity and AUROC. Moreover, AI has the potential to improve workflow speed, uniformity across expertise levels, and hybrid AI-radiologist approaches to reduce unnecessary biopsies. Large-scale, prospective trials with standardized protocols are needed to assess AI’s effectiveness across diverse clinical settings. Full article

Prostate cancer remains a leading cause of cancer-related mortality and castration-resistant prostate cancer (CRPC) is a critical therapeutic challenge. This review establishes a conceptual framework analyzing ferroptosis vulnerability through two principles: “robustness through redundancy” in defense systems and the “evolutionary arms race” between androgen receptor (AR) signaling and oxidative resistance. We traced the evolutionary trajectory of hormone-sensitive diseases, where the AR coordinates ferroptosis defenses via SLC7A11, MBOAT2, and PEX10 regulation through progressive adaptations: AR-V7 splice variants that maintain defense independently of androgens, AR amplification conferring hypersensitivity, and AR-independent JMJD6-ATF4 bypass in SPOP-mutated tumors. This transforms ferroptosis from a static vulnerability to a stage-specific strategy. Novel approaches include menadione-based VPS34 targeting, which induces triaptosis through an oxidative endosomal catastrophe. We categorized the rational combinations mechanistically as vertical inhibition (multi-step targeting of single pathways), horizontal inhibition (synthetic lethality across parallel defenses), and vulnerability induction (creating exploitable dependencies). Ferroptosis-induced immunogenic cell death enables synergy with checkpoint inhibitors, potentially transforming immunologically “cold” prostate tumors. This review establishes ferroptosis targeting as a precision medicine paradigm exploiting the tension between the oxidative requirements of cancer cells and their evolved, yet architecturally vulnerable, defense systems, providing a framework for stage-specific, biomarker-guided interventions. Full article

Background: Prostate cancer remains a major contributor to cancer-related morbidity and mortality worldwide, emphasizing the need for safer and more effective therapeutic options. Andrographolide, a diterpenoid lactone derived from Andrographis paniculata, has shown promising anticancer activity, yet its effects on microRNA (miRNA) regulation in prostate cancer remain insufficiently explored. Methods: In this study, we evaluated the cytotoxic and molecular effects of andrographolide on two human prostate cancer cell lines, PC3 and LNCaP, along with HEK-293 cells as a noncancerous model. Results: Cell viability assessment using the MTT assay revealed dose-dependent cytotoxicity, with 24 h IC₅₀ values of 82.31 µM for PC3, 68.79 µM for LNCaP, and 133.9 µM for HEK-293 cells. Subsequent expression analysis of key oncogenic and tumor suppressor miRNAs demonstrated that andrographolide induced the upregulation of miR-16-5p, miR-34a-5p, and miR-200a-5p miRNAs implicated in apoptosis, proliferation control, and androgen receptor signaling. In contrast, the expression of oncomiRs miR-21-5p and miR-221-5p showed minimal or nonsignificant changes, reflecting the complex and context-specific roles of miRNAs in prostate cancer. Gene expression profiling further indicated differential transcriptional responses between the two prostate cancer cell lines, consistent with their distinct molecular backgrounds. Conclusions: Although HEK-293 cytotoxicity and previously reported nephrotoxic effects warrant caution, these results support the potential of andrographolide as an adjuvant phytochemical capable of modulating clinically relevant miRNAs in prostate cancer. Future studies investigating optimized delivery systems and validating direct miRNA targets may help advance andrographolide toward safer and more targeted therapeutic applications. Full article

Prostate cancer is the most diagnosed cancer among Canadian men, except non-melanoma skin cancers. Prostate-specific antigen (PSA) screening can enable early detection, but it is not formally recommended in Canada. Nonetheless, opportunistic screening persists, influenced by US practices and some Canadian guidelines that support screening. This study provides a detailed analysis of trends in prostate cancer incidence, mortality, stage distribution, and net survival in the context of evolving PSA screening guidelines. Prostate cancer case (1984–2022) and death (1984–2023) data were primarily from the Canadian Cancer Registry and the Canadian Vital Statistics Death database, respectively. Joinpoint regression identified incidence and mortality trends. Net survival was determined using the Pohar Perme estimator. Following the introduction of PSA screening, the prostate cancer age-standardized incidence rate among men aged 50–74 increased 1.8% annually until 2007 (p = 0.006) before declining at an annualized rate of −5.9% (p = 0.005) until 2014. Among men aged ≥75, incidence declined at −3.2% annually from 1992 to 2015 (p < 0.001). The prostate cancer age-standardized mortality rate (ASMR) among men aged 50–74 fell at an annualized rate of −4.3% between 1994 and 2010 (p = 0.022), but the decline slowed thereafter. The ASMR among men aged ≥75 continuously declined after a peak in 1995, with the greatest change noted before 2012. From 2010 to 2017, stage IV prostate cancer incidence increased across all 10-year age groups, peaking among men aged 60–69 at 4.1% annually (p < 0.001). Among men aged 50–74, the corresponding annualized increase was 3.7% (p = 0.010), while among men aged ≥75, it was 3.1% (p < 0.001). Although stage IV net survival among men aged 50–74 increased from 49.4% in 2010–2011 to 56.6% in 2016–2017, all-stage net survival declined slightly after 2011, concurrent with a shift towards a greater proportion of stage IV cases. Prostate cancer outcomes in Canada reflect US PSA screening recommendations. Organized and thoughtful screening may represent an opportunity to decrease the rising late-stage incidence. Full article

Prostate cancer remains one of the most prevalent malignancies among men worldwide, with late-stage diagnosis contributing significantly to mortality rates. In this study, we report the development of a graphene oxide (GO)-based QCM biosensor for the early and sensitive detection of Prostate Cancer Antigen 3 (PCA3), a biomarker with higher specificity than conventional PSA tests. The sensor interface was fabricated via a layer-by-layer approach of L-cysteine, GO, and a capture probe onto a gold electrode, resulting in enhanced surface area and biomolecular recognition capacity. Structural and morphological characterizations using XRD, FE-SEM, AFM, and FT-IR confirmed the successful and uniform integration of GO and functional layers. Optimization of fabrication parameters, including EDC-NHS activation time, capture probe concentration, and target incubation time, was performed to achieve maximum sensitivity and binding efficiency. The biosensor demonstrated a distinct, concentration-dependent frequency shift upon hybridization with PCA3 targets over a range of 1.00 fM to 1.00 μM, with a calculated limit of detection (LOD) of 0.268 nM and a rapid response time of 20 min. These results underscore the potential of GO-modified QCM platforms for highly sensitive, rapid, and portable diagnostics, not only for prostate cancer screening but also for broader clinical applications involving biomarkers. Full article

Background/Objectives: Prostate cancer is a leading cause of cancer-related morbidity and mortality. While prostate-specific antigen (PSA) is crucial for monitoring, its static levels are limited in predicting outcomes precisely. The Kinetics of Elimination of PSA (KELIM PSA) has recently emerged as a dynamic biomarker of treatment response. This research sought to determine the predictive power of KELIM PSA in castration-resistant prostate cancer (CRPC) on androgen receptor pathway inhibitors (ARPI). Methods: This study retrospectively analyzed 98 CRPC patients treated with enzalutamide or abiraterone. The patients were categorized as either unfavorable (KELIM < 1) or favorable (KELIM ≥ 1). Demographic and clinical characteristics were compared, and survival outcomes were evaluated using Kaplan–Meier curves and Cox regression. Results: Of the cohort, 42 (42.9%) patients had favorable and 56 (57.1%) unfavorable KELIM values. The unfavorable group had a higher mortality rate (62.5% vs. 38.1%, p = 0.029). Univariate analysis showed that poor KELIM results increased mortality risk twofold (hazard ratio [HR]: 2.30, 95% confidence interval [CI]: 1.26–4.19, p = 0.006). In multivariable analysis, unfavorable KELIM remained independently associated with worse overall survival (HR: 2.09, 95% CI: 1.12–3.89, p = 0.020), together with second-line ARPI (HR: 3.19, 95% CI: 1.71–5.93, p < 0.001) and ADT + docetaxel during CSPC (HR: 2.14, 95% CI: 1.11–4.12, p = 0.022). Kaplan–Meier curves revealed that the unfavorable group had notably reduced overall survival and progression-free survival (log-rank p = 0.018). Conclusions: KELIM PSA is an independent predictor in ARPI-treated CRPC. By integrating PSA kinetics into prognostic models, risk stratification may be improved, and this may guide individualized treatment. Prospective multicenter validation is warranted. Full article

Introduction/Background: Treatment of localized prostate cancer includes radical prostatectomy (RP) with or without pelvic lymph node dissection (PLND). While multiple guidelines recommend PLND for staging purposes, recent data has shown questionable therapeutic benefit. Thus, understanding the morbidity associated with PLND is important for counseling patients. We used the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) targeted prostatectomy database to quantify real-world 30-day postoperative outcomes of patients undergoing contemporary robot-assisted PLND at the time of RP for prostate cancer to quantify the incremental morbidity. Methods: We conducted a retrospective cohort study using the NSQIP database of adult patients undergoing radical prostatectomy from 2019 to 2022. The primary outcomes were procedure-specific outcomes such as lymphocele and rectal injury. Secondary outcomes included a composite of any of the following 30-day major postoperative outcomes: mortality, reoperation, cardiac or neurologic event, as well as the individual components of this outcome, as well as infectious and other complications. We also analyzed yearly trends associated with PLND. Groups were balanced using propensity score matching (PSM) with a 1:1 ratio using demographic characteristics, prior medical history, and cancer staging data. Likelihood of complications was assessed by conditional logistic regression. Results: We identified 13,413 patients between 2019 and 2022 who underwent robotic prostatectomy: 11,341 (85%) had PLND while 2072 (15%) did not. After PSM, our cohort included 2071 matched pairs of patients with and without PLND. Patients who underwent PLND were more likely to be diagnosed with lymphocele (2.14% vs. 0.68%, OR 4.17; 95% CI 2.00, 8.68), have unplanned readmission (4.22% vs. 3.27%, OR 1.31; 95% CI 1.03, 1.65), and develop organ-site/space SSI (1.18% vs. 0.60%) (OR 1.97, 95% CI 1.20, 3.23). There was no significant association between the receipt of PLND and the likelihood of urinary leak or fistula, or ureteral obstruction. There were no significant differences between the two groups with respect to secondary outcomes of interest. Conclusion: Contemporary robotic PLND is associated with a 3-fold increased likelihood of lymphocele, as well as increased likelihood of unplanned readmission and organ-site SSI, though no significant differences in major postoperative complications were identified. We found that the odds of lymphoceles, readmission, and SSI in our study are lower than previously reported. These data provide real-world data to guide patient counseling and optimize patient selection for PLND at the time of RALP. Full article

Background/Objectives: Metformin is one of the most frequently used concomitant medications among prostate cancer (PCa) patients. However, the effects of metformin on all-cause and PCa-specific mortality among men diagnosed with advanced/metastatic PCa treated with androgen-deprivation therapy (ADT) remain poorly understood, but they may be specifically explained by emulating a target trial. Methods: We emulated a target trial of metformin therapy and survival using observational data on 7361 patients diagnosed with advanced PCa, who were treated with ADT, from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database (2008–2019), with completed follow-up until 2020. We included patients with diabetes, and participants were assigned as either “initiator of metformin within 6 months after advanced PCa diagnosis” or “non-initiator of metformin.” We estimated mortality risks using Cox proportional hazards models with adjustment for risk factors via inverse probability weighting using both intention-to-treat and per-protocol analyses. Results: Over 13 years of follow-up, with a maximum 3 years of follow-up after PCa diagnosis, all-cause mortality occurred in 52 metformin initiators (47.7%) versus 3052 non-initiators (42.1%), while PCa-specific mortality occurred in 36 initiators (33.0%) versus 1919 non-initiators (26.5%). In the intention-to-treat analysis, metformin initiation was not associated with all-cause mortality (Hazard Ratio [HR] = 1.38, 95% CI: 0.98–1.95) or PCa-specific mortality (HR = 0.99, 95% CI: 0.63–1.55). Similarly, in per-protocol analysis, there was no evidence of risk reduction with all-cause (HR = 1.20, 95% CI = 0.80–1.81) or PCa-specific mortality (HR = 1.45, 95% CI = 0.88–2.38) after adjusting for time-varying covariates and allowing a 30-day gap for metformin discontinuation, adjusted for via inverse probability weighting. Conclusions: Our findings align with prior randomized trials showing no survival benefit of metformin in advanced PCa patients receiving ADT. Timing of metformin discontinuation also showed no significant effect. However, the small size of the metformin initiator group precluded subgroup analyses for hormone-sensitive (HSPC) and castrate-resistant prostate cancer (CRPC), limiting our ability to explore potential differential effects. Full article

Background: Prostate cancer is one of the most common malignancies in men and a leading cause of cancer-related mortality. Early detection is essential to ensure curative treatment and favorable outcomes, but traditional diagnostic approaches—such as serum prostate-specific antigen (PSA) testing, digital rectal examination (DRE), and histopathological confirmation following biopsy—are limited by suboptimal accuracy and variability. Multiparametric magnetic resonance imaging (mpMRI) has improved diagnostic performance but remains highly dependent on reader expertise. Artificial intelligence (AI) offers promising opportunities to enhance diagnostic accuracy, reproducibility, and efficiency in prostate cancer detection. Objective: To evaluate the diagnostic accuracy and reporting timeliness of AI-based technologies compared with conventional diagnostic methods in the early detection of prostate cancer. Methods: Following PRISMA 2020 guidelines, PubMed, Scopus, Web of Science, and Cochrane Library were searched for studies published between January 2015 and April 2025. Eligible designs included randomized controlled trials, cohort, case–control, and pilot studies applying AI-based technologies to early prostate cancer diagnosis. Data on AUC-ROC, sensitivity, specificity, predictive values, diagnostic odds ratio (DOR), and time-to-reporting were narratively synthesized due to heterogeneity. Risk of bias was assessed using the QUADAS-AI tool. Results: Twenty-three studies involving 23,270 patients were included. AI-based technologies achieved a median AUC-ROC of 0.88 (range 0.70–0.93), with median sensitivity and specificity of 0.86 and 0.83, respectively. Compared with radiologists, AI or AI-assisted readings improved or matched diagnostic accuracy, reduced inter-reader variability, and decreased reporting time by up to 56%. Conclusions: AI-based technologies show strong diagnostic performance in early prostate cancer detection. However, methodological heterogeneity and limited standardization restrict generalizability. Large-scale prospective trials are required to validate clinical integration. Full article