Evidence map›Paper›PMID 41224966›Full record

ArticleVirchows Archiv : an international journal of pathology2026

Temporality of change in Ki67 labelling following neoadjuvant systemic chemotherapy of breast cancer-the common drop often subsides with time.

Ádám Ferenczi, Tamás Lantos, Gábor Cserni

Abstract read
In one paragraph

Article in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Ádám Ferenczi *Department of Pathology, Albert Szent-Györgyi Medical School, University of Szeged, Állomás U.1, 6725, Szeged, Hungary.ORCID http://orcid.org/0009-0002-3262-8567
Tamás Lantos *Department of Medical Physics and Informatics, Albert Szent-Györgyi Medical School, University of Szeged, Korányi Fasor 9, 6720, Szeged, Hungary.ORCID http://orcid.org/0000-0002-5081-7313
Gábor CserniDepartment of Pathology, Albert Szent-Györgyi Medical School, University of Szeged, Állomás U.1, 6725, Szeged, Hungary. cserni.gabor@med.u-szeged.hu.ORCID http://orcid.org/0000-0003-1344-7744

Funding

Szegedi Tudományegyetem EKÖP-291University of Szeged Open Access Fund 8021
6 · The paper itself

Abstract

Ki67 immunohistochemistry is widely used in clinical settings to assess tumour proliferation in breast cancer, yet the temporal changes in Ki67 labelling index following neoadjuvant chemotherapy (NACT) are underexplored. Matched core biopsy and surgical excision specimens of invasive breast cancers were collected, and the Ki67 immunostained slides were examined. Ki67 labelling index was determined and statistically evaluated based on the time elapsed between the last cycle of NACT and surgery. Subgroup analyses were carried out based on surrogate molecular subtypes, Residual Cancer Burden (RCB), and European Working Group for Breast Screening Pathology tumour regression (TR) categories. The study included 54 paired breast cancer cases post-NACT. Most tumours were RCB-II (n = 39) and TR2b (n = 20). The average time from NACT completion to surgery was 40.3 days. Of three methods (including image-analysis and sample-counting), eye-balling estimation provided the best linear regression fit (p = 0.003, R

Indexed as

Biomarkers, TumorBreast NeoplasmsKi-67 AntigenNeoadjuvant TherapyAdultAgedCell ProliferationChemotherapy, AdjuvantFemaleHumansImmunohistochemistryMiddle AgedTime FactorsBiomarkers, TumorKi-67 AntigenMKI67 protein, humanBreast cancerKi67Neoadjuvant chemotherapyPost-neoadjuvantTemporality

Identifiers

PMID41224966
PMCPMC13477442

What OpenQuestion holds

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Registered trials

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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.