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Evaluation of the proliferation marker Ki-67 in gliomas: Interobserver variability and digital quantification.
Diagnostic Pathology 2018 June 10
BACKGROUND: The 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.
METHODS: In 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.
RESULTS: The 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).
CONCLUSIONS: Interobserver 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.
METHODS: In 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.
RESULTS: The 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).
CONCLUSIONS: Interobserver 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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