SynthesisBMC cancer2025
The research progress on diagnostic indicators related to prostate-specific antigen gray-zone prostate cancer.
Synthesis in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Dual-center development and external validation of machine learning models integrating PSA-derived and peripheral inflammatory markers for prostate cancer diagnosis.Translational andrology and urology · 2026Article
- Zone-Specific PSA Density from AI-Assisted mp-MRI as a Predictor of Prostate Cancer in the PSA 4-20 ng/mL Range.Journal of clinical medicine · 2026Article
- The regulatory mechanism and clinical significance of RNA editing in prostate cancer.Current urology · 2026Review
- Diagnosis of Prostate Cancer: A Comparative Evaluation of Biological Techniques.Diseases (Basel, Switzerland) · 2026Review
- Explainable Machine Learning-Based Overall Survival Classification in Prostate Adenocarcinoma Using Integrated Clinical and Transcriptomic Features.Diagnostics (Basel, Switzerland) · 2026Article
- From feasibility to translational pathways: a bibliometric and knowledge-mapping analysis of urine-based liquid biopsy in urologic cancers (2015-2025).Journal of translational medicine · 2026Review
- Focusing on Prostate-Specific Membrane Antigen in Precision Diagnosis and Treatment of Prostate Cancer.Biomedicines · 2026Review
- Non-Coding RNA Biomarkers in Prostate Cancer: Evidence Mapping and In Silico Characterization.Life (Basel, Switzerland) · 2026Article
- Development and validation of an online predictive model for biochemical recurrence after radical prostatectomy in elderly patients.Frontiers in oncology · 2026Article
- Development and validation of a clinical nomogram based on lasso-logistic regression for predicting prostate cancer with PSA 4-20.0 ng/mL: a retrospective study.Frontiers in endocrinology · 2026Article
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis review offers a distinctive perspective by integrating and critically evaluating the latest advancements in non-invasive biomarkers for Prostate-Specific Antigen (PSA) gray-zone prostate cancer. By synthesizing data on Prostate Health Index (PHI), Prostate Cancer Antigen 3 (PCA3), Transmembrane Protease Serine 2-ETS-related Gene fusion (TMPRSS2-ERG fusion gene), proteomics, and microRNA (miRNAs), this work highlights their potential to enhance diagnostic precision while minimizing unnecessary biopsies. Furthermore, this review explores the clinical applicability of these biomarkers, bridging the gap between research innovations and real-world diagnostic strategies.The primary objective of this review is to analyze emerging biomarkers and clinical indicators that address the inherent diagnostic uncertainties within the PSA gray zone (4-10 ng/mL).Given the overlap between benign and malignant conditions in this range, traditional PSA-based screening lacks specificity, often leading to overdiagnosis and overtreatment.This review critically examines the diagnostic performance of the free PSA/total PSA (fPSA/tPSA) ratio, the Prostate Health Index (PHI), and molecular markers such as PCA3 and TMPRSS2-ERG fusion genes.Additionally, we discuss the integration of proteomic and miRNA-based approaches, emphasizing their potential role in refining risk stratification and advancing non-invasive prostate cancer diagnostics.
methodsA systematic review was conducted focusing on peer-reviewed research from databases such as PubMed, MEDLINE, and others.The studies included reported diagnostic accuracy, sensitivity, specificity, and clinical outcomes for biomarkers associated with PSA gray-zone prostate cancer.The inclusion criteria emphasized studies that evaluated human subjects and presented measurable diagnostic outcomes related to fPSA/tPSA ratio, PHI, PCA3, TMPRSS2-ERG, and additional protein-based biomarkers.
resultsThe findings reveal that the fPSA/tPSA ratio enhances diagnostic sensitivity and specificity, making it a valuable tool within the PSA gray zone.PHI demonstrates superior diagnostic accuracy compared to traditional markers like tPSA.Molecular markers, such as PCA3 and TMPRSS2-ERG fusion genes, show considerable potential for distinguishing between benign and malignant conditions, effectively reducing the need for unnecessary biopsies.Additionally, proteomics and glycoprotein biomarkers offer non-invasive diagnostic possibilities, although further validation is necessary to confirm their efficacy.
conclusionIncorporating multiple biomarkers, including the fPSA/tPSA ratio, PHI, PCA3, and TMPRSS2-ERG, presents a more accurate and patient-friendly approach to diagnosing PSA gray-zone prostate cancer.This multi-marker strategy enhances diagnostic precision, reduces biopsy rates, and supports the early detection of aggressive disease forms, representing a significant step forward in prostate cancer management and prognosis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.