ArticleDiagnostic pathology2018
Evaluation of the proliferation marker Ki-67 in gliomas: Interobserver variability and digital quantification.
Article in Diagnostic pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 9 citations in OpenAlex.
- The Ki-67 proliferation index and recurrence risk of intracranial meningioma: a multicenter, retrospective cohort study of 5,050 patients.Acta neurochirurgica · 2026Article
- ADAR2 induces the differentiation of osteosarcoma cells by editing activity on IGFBP7: new implications for therapy.Bone research · 2026Article
- AOSNP-ADAPTR resource level-based recommendations on practical diagnostic strategies for WHO CNS5 adult-type diffuse gliomas.Brain pathology (Zurich, Switzerland) · 2026Review
- Two-decade clinicopathological spectrum of gliomas at a tertiary center in LMIC: histological profile and the molecular diagnostic gap.Frontiers in oncology · 2026Article
- Histogram analysis of IVIM MRI for differentiating glioma IDH-1 status, grade, and Ki-67 expression: a comparison of bi-exponential models at multiple B-value.BMC medical imaging · 2025Article
- Circulating tumor cells as a recurrence risk marker in glioma: a retrospective study.Translational cancer research · 2025Article
- Added prognostic value of histogram features from preoperative multi-modal diffusion MRI in predicting Ki-67 proliferation for adult-type diffuse gliomas.Quantitative imaging in medicine and surgery · 2025Article
- The role of the Ki-67 labelling index as an independent prognostic factor in indonesian glioma patients.Histology and histopathology · 2025Article
- Brain Tumor-Induced Changes in Routine Parameters of the Lipid Spectrum of Blood Plasma and Its Short-Chain Fatty Acids.Current issues in molecular biology · 2025Article
- CRP/albumin ratio and WBC values correlate with Ki-67 and survival in glioblastoma multiforme.Frontiers in oncology · 2025Article
- Article
- Utilizing the amide proton transfer technique to characterize diffuse gliomas based on the WHO 2021 classification of CNS tumors.The neuroradiology journal · 2024Article
- Integrin receptor-targeted, doxorubicin-loaded cerium oxide nanoparticles delivery to combat glioblastoma.Nanomedicine (London, England) · 2024Article
- Expression and prognostic significance of microsomal triglyceride transfer protein in brain tumors: a retrospective cohort study.Translational cancer research · 2024Article
- Long-read sequencing for brain tumors.Frontiers in oncology · 2024Review
- Association ofCancers · 2023Article
- General Clinico-Pathological Characteristics in Glioblastomas in Correlation with p53 and Ki67.Medicina (Kaunas, Lithuania) · 2023Article
- Low expression of Ki-67/MIB-1 labeling index in IDH wild type glioblastoma predicts prolonged survival independently by MGMT methylation status.Journal of neuro-oncology · 2023Observational
- Predictive Value of KJournal of neurological surgery. Part B, Skull base · 2023Article
- Mass spectrometry imaging discriminates glioblastoma tumor cell subpopulations and different microvascular formations based on their lipid profiles.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Ki-67 Labelling Index (LI) is used as an ancillary tool in glioma diagnostics. Interobserver variability has been reported and no precise guidelines are available. Nor is it known whether novel digital approaches would be an advantage. Our aim was to evaluate the inter- and intraobserver variability of the Ki-67 LI between two pathologists and between pathologists and digital quantification both in whole tumour slides and in hot spots using narrow but diagnostically relevant intervals.
methodsIn samples of 235 low and high grade gliomas, two pathologists (A and B) estimated the Ki-67 LI (5-10% intervals) for whole tumour slides and for hot spots. In 20 of the cases intraobserver variability was evaluated. For digital quantification (C) slides were scanned with subsequent systematic random sampling of viable tumour areas. A software classifier trained to identify positive and negative nuclei calculated the Ki-67 LI. The interobserver agreements were evaluated using kappa (κ) statistics.
resultsThe observed proportions of agreement and κ values for Ki-67 LI for whole tumour slides were: A/B: 46% (κ = 0.32); A/C: 37% (κ = 0.26); B/C: 37% (κ = 0.26). For hot spots equivalent values were: A/B: 14% (κ = 0.04); A/C: 18% (κ = 0.09); B/C: 31% (κ = 0.21).
conclusionsInterobserver variability was pronounced between pathologists and for pathologists versus digital quantification when attempting to estimate a precise value of the Ki-67 LI. Ki-67 LI should therefore be used with caution and should not be over interpreted in the grading of gliomas. Digital quantification of Ki-67 LI in gliomas was feasible, but intra- and interlaboratory robustness need to be determined.
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