Evidence map›Paper›PMID 32095144›Full record

ArticleIranian journal of pathology2020

Assessment of Ki67 in Breast Cancer: A Comparison Between the Eye-10 Method, Stepwise Counting Strategy, and International System of Ki67 Evaluation.

Maryam Kadivar, Fatemeh Aram

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Article in Iranian journal of pathology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Maryam KadivarDepartment of Pathology, Rasool Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
Fatemeh AramDepartment of Pathology, Rasool Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
Iran University of Medical Sciences · IRRasool Akram Hospital · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

objectiveKi-67 evaluation is an essential tool to define luminal A and B breast cancers, which is not yet systematized. The International Ki67 in Breast Cancer Working Group suggests the counting of 500 or 1000 cancer cells, which is a time-consuming process. Therefore, novel methods, such as the Eye-10 method and stepwise counting strategy, are proposed to facilitate measurement.

methodsImmunohistochemical staining of Ki67 was performed on 100 hormone-receptor-positive invasive ductal carcinoma specimens. Ki67LI was evaluated for each case, and then results were dichotomized by a cut-off point of 20%. Next, for each sample, an expert pathologist visually assessed percentages of Ki67-positive cells in 10% intervals at a glance (Eye-10 method). Finally, by using a dynamic process with rejection regions, Ki67 was defined so if the estimate belonged to the upper or lower rejection region, the Ki67 status had been determined and if the rejection region could not be reached after counting the maximum number of 400 tumor cells, the specimen was regarded as equivocal (stepwise counting strategy).

resultsThe comparison between Eye-10 and Ki67LI revealed almost perfect agreement (kappa coefficient =0.889), and the concordance between the stepwise counting strategy and Ki67LI was substantial (kappa coefficient =0.639).

conclusionBoth two methods left some results in the gray/intermediate zone, which is unavoidable. Both methods are much faster and simpler than evaluation of Ki67LI and are also reliable. Regarding the gray zone in both methods, further improvements in the methodology, as well as more analytical studies, are needed.

Indexed as

BreastCarcinomaDuctalImmunohistochemistry

Identifiers

PMID32095144
PMCPMC6995680
OpenAlexW3000400733

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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.