ArticleHistopathology2023
Measuring cancer burden in prostatic needle core biopsies: simplified assessments outperform complex measurements in assessing outcome: evidence to assist pathologist efficiency and minimize datasets.
Article in Histopathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
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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
5 citing papers in PubMed, 5 citations in OpenAlex.
- Low heterogeneity of tumor grades in multiple MRI-targeted prostate biopsies argues for the aggregate method of grading.Virchows Archiv : an international journal of pathology · 2026Article
- Artificial intelligence in prostate biopsy: diagnostic applications, risk stratification, and precision oncology.Frontiers in oncology · 2026Review
- Clinical and MRI features for predicting maximum cancer involvement of >50% in a single biopsy core among patients diagnosed with prostate cancer at initial systematic biopsy: a machine learning study.American journal of cancer research · 2026Article
- Unexpectedly high variability in determining tumour extent in prostatic biopsies: implications for active surveillance.Histopathology · 2025Article
- Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Parameters Could Predict International Society of Urological Pathology Risk Groups of Prostate Cancers on Radical Prostatectomy.Life (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
aimsThe optimal method of measuring cancer extent in prostate cancer (PCa) biopsies is unknown. METHODS AND
resultsNine hundred eighty-one men with clinically localised PCa managed conservatively were reviewed with follow up. The number of positive cores (NPC), the Maximum Cancer Length in a core (MCL), Total Cancer Length (TCL), and percentage of positive cores (%+cores) was calculated and univariate and multivariate analysis performed using prostate-specific antigen (PSA), T-stage, and Gleason score. The presence of stromal gaps (SG) was recorded. Univariate models were run where SG made a difference to the MCL. All variables showed significant association with PCa death in univariate models. In multivariate models, incorporating PSA, T-stage, and Gleason score, only %+cores was a significant predictor of outcome, with a 10% increase in %+cores resulting in a hazard ratio (HR) of 1.07 (likelihood-ratio test P > Χ
conclusionCancer extent is a strong predictor of PCa death but only %+cores added to the multivariate model. Expressed as a fraction of NPC/total number of cores, this is the simplest method of assessment, which we favour over more complicated methods in nontargeted biopsies.
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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.