Evidence map›Paper›PMID 37559526›Full record

ArticleTechnology in cancer research & treatment

Comparison Between Manual and Automated Assessment of Ki-67 in Breast Carcinoma: Test of a Simple Method in Daily Practice.

Xavier Catteau, Egor Zindy, Sarah Bouri, Jean-Christophe Noël, Isabelle Salmon, Christine Decaestecker

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Article in Technology in cancer research & treatment. 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
2.2field-weighted citation impact, top 12% 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

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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, 9 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

6 authors at 1 institution in 1 country.

Xavier CatteauDepartment of Pathology, Erasme's Hospital, Université Libre de Bruxelles, Brussels, Belgium.ORCID 0000-0003-3031-5719
Egor ZindyLaboratory of Image Synthesis and Analysis (LISA), Université Libre de Bruxelles, Bruxelles, Belgium.
Sarah BouriDepartment of Pathology, Erasme's Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Jean-Christophe NoëlDepartment of Pathology, Erasme's Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Isabelle SalmonDepartment of Pathology, Erasme's Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Christine DecaesteckerLaboratory of Image Synthesis and Analysis (LISA), Université Libre de Bruxelles, Bruxelles, Belgium.
Université Libre de Bruxelles · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice. PATIENTS AND

methodsA total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA).

resultsFor Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58).

conclusionsThe DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.

Indexed as

Breast NeoplasmsImage Processing, Computer-AssistedBiomarkers, TumorDiagnostic ImagingFemaleHumansKi-67 AntigenObserver VariationBiomarkers, TumorKi-67 Antigenbreast cancerdigital imaging analysisevaluationKi-67proliferationscore

Identifiers

PMID37559526
PMCPMC10416654
OpenAlexW4385716315

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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.