Evidence map›Paper›PMID 30153851›Full record

ArticleDiagnostic pathology2018

Ki 67 assessment in breast cancer in an Egyptian population: a comparative study between manual assessment on optical microscopy and digital quantitative assessment.

Essam Ayad, Ahmed Soliman, Shady Elia Anis, Amira Ben Salem, Pengchao Hu, Youhong Dong

Abstract readComparative Study
In one paragraph

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 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Essam AyadDepartment of Pathology, Cairo University, Cairo, Egypt. essamayad@yahoo.com.ORCID http://orcid.org/0000-0002-4822-1676
Ahmed SolimanDepartment of Pathology, Cairo University, Cairo, Egypt.
Shady Elia AnisDepartment of Pathology, Cairo University, Cairo, Egypt.
Amira Ben SalemDepartment of Pathology, Cairo University, Cairo, Egypt.
Pengchao HuDepartment of Oncology, XiangYang No.1 People's Hospital Affiliated to Hubei University of Medicine, Xiangyang, Hubei, 441000, People's Republic of China.
Youhong DongDepartment of Oncology, XiangYang No.1 People's Hospital Affiliated to Hubei University of Medicine, Xiangyang, Hubei, 441000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is by far the most frequent cancer among women. The proliferative index, Ki-67, is more and more taken into consideration for treatment decisions. However, the reliability of the established Ki-67 scoring is limited. Digital pathology is currently suggested to be a potential solution to Ki 67 assessment problems.

methodsThis is a retrospective and prospective study including 100 patients diagnosed with invasive breast cancer. Three senior pathologists have been asked to estimate the Ki-67 proliferative index for each of the 100 cases by examining the whole glass slides on optical microscope and providing a continuous score then a categorical score ('high' and 'low' Ki 67 index) using once 14%, once 20% as threshold indicative of high Ki67 status. Finally, a digital quantitative assessment of Ki67 was performed.

resultsA high inter-observer agreement was found when using optical microscopy for Ki 67 assessment, with correlation coefficient (CC) estimated at 0.878 (p value < 0.01). The overall agreement between manual and automated evaluation of Ki 67 was only substantial (CC estimated at 0.745 (p value < 0.01)). When using categorical scores, the inter-observers concordance was substantial using both cutoff points with kappa value estimated at 0.796 ([0.696-0.925] while using 14% as a cut off point and at 0.766 ([0.672-0.938] while using 20% as a cutoff point (p value < 0). The inter-observers agreement was better while using 14% as cutoff point. Agreement between manual and automated assessment of Ki 67 indices using both cutoff points was only substantial (Kappa estimated at 0.623, p value < 0.01). In comparison to automated assessment of Ki 67 index, while using 14% as a cutoff point, the overall tendency of all observers was to overestimate the Ki 67 values but to underestimate the proliferation index while using 20% as a cutoff point.

conclusionAutomated assessment of Ki 67 value would appear to be comparable to visual Ki 67 assessment on optical microscopy. Such study would help define the role of digital pathology as a potential easy-to use tool for a robust and standardized fully automated Ki 67 scoring.

Indexed as

Cell ProliferationImage Interpretation, Computer-AssistedImmunohistochemistryMicroscopyAdultAgedAged, 80 and overAutomation, LaboratoryBreast NeoplasmsEgyptFemaleHumansKi-67 AntigenMiddle AgedObserver VariationPredictive Value of TestsKi-67 AntigenMKI67 protein, humanAssessmentAutomatedBreastCancerKi67Manual

Identifiers

PMID30153851
PMCPMC6114705

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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.