ArticleCancers2021
Significant Inter- and Intralaboratory Variation in Gleason Grading of Prostate Cancer: A Nationwide Study of 35,258 Patients in The Netherlands.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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
19 citing papers in PubMed.
- Validation of diagnostic artificial intelligence models for prostate pathology in a Middle Eastern cohort.Virchows Archiv : an international journal of pathology · 2026Article
- Diagnostic discordance in outside prostate biopsies: Implications for active surveillance patient selection.Investigative and clinical urology · 2026Article
- Article
- The state of the art in artificial intelligence and digital pathology in prostate cancer.Nature reviews. Urology · 2026Review
- ADC-based radiomics for risk stratification in prostate cancer: a clinical decision support study.Frontiers in oncology · 2026Article
- Review
- Deep Learning Classification of Prostate Cancer Using MRI Histopathologic Data.Radiology. Imaging cancer · 2025Article
- A deployment safety case for AI-assisted prostate cancer diagnosis.Computers in biology and medicine · 2025Article
- Implementation of Universal Germline Genetic Testing Into Standard of Care for Patients With Prostate Cancer: The Time Is Now.JCO oncology practice · 2025Article
- Validation and three years of clinical experience in using an artificial intelligence algorithm as a second read system for prostate cancer diagnosis-real-world experience.Journal of pathology informatics · 2024Article
- Predicting Biochemical Recurrence of Prostate Cancer Post-Prostatectomy Using Artificial Intelligence: A Systematic Review.Cancers · 2024Review
- A retrospective external validation study of the Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) for the management of solitary central cartilage tumours of the proximal humerus and around the knee.European radiology · 2024Article
- Robust, credible, and interpretable AI-based histopathological prostate cancer grading.medRxiv : the preprint server for health sciences · 2024Article
- MRI-based prostate cancer classification using 3D efficient capsule network.Medical physics · 2024Article
- Article
- Diagnostic concordance between traditional and digital workflows. A study on 1427 prostate biopsies.Pathologica · 2023Article
- CONFIDENT-trial protocol: a pragmatic template for clinical implementation of artificial intelligence assistance in pathology.BMJ open · 2023Article
- Prostate Cancer: Pathophysiology, Pathology and Therapy.Cancers · 2022Article
- Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
purposeOur aim was to analyze grading variation between pathology laboratories and between pathologists within individual laboratories using nationwide real-life data.
methodsWe retrieved synoptic (
resultsA total of 38,321 reports of 35,258 patients were included. Grade 1 ranged between 19.7% and 44.3% per laboratory (national mean = 34.1%). Out of 40 laboratories, 22 (55%) reported a significantly deviant OR, ranging from 0.48 (95% confidence interval (CI) 0.39-0.59) to 1.54 (CI 1.22-1.93). Case-mix correction was performed for 10,294 reports, altering the status of 3/21 (14%) laboratories, but increasing the observed variation (20.8% vs. 17.7%). Within 15/21 (71%) of laboratories, significant inter-pathologist variation existed.
conclusionSubstantial variation in prostate cancer grading was observed between and within Dutch pathology laboratories. Case-mix correction did not explain the variation. Better standardization of prostate cancer grading is warranted to optimize and harmonize treatment.
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