Evidence map›Paper›PMID 27026269›Full record

ArticleVirchows Archiv : an international journal of pathology2016

Expression of cell cycle markers is predictive of the response to primary systemic therapy of locally advanced breast cancer.

Tímea Tőkés, Anna-Mária Tőkés, Gyöngyvér Szentmártoni, Gergő Kiszner, Lilla Madaras, Janina Kulka, Tibor Krenács, Magdolna Dank

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Article in Virchows Archiv : an international journal of pathology, 2016. 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
0.7field-weighted citation impact, top 31% 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.

  1. Observational
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Spatial Attention-Based Deep Learning System for Breast Cancer Pathological Complete Response Prediction with Serial Histopathology Images in Multiple Stains.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
    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

8 authors at 1 institution in 1 country.

Tímea Tőkés1st Department of Internal Medicine, Oncological Division, Semmelweis University, Tömő utca 25-29, 4th floor, Budapest, 1083, Hungary.
Anna-Mária TőkésMTA-SE Tumor Progression Research Group, 2nd Department of Pahtology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary.
Gyöngyvér Szentmártoni1st Department of Internal Medicine, Oncological Division, Semmelweis University, Tömő utca 25-29, 4th floor, Budapest, 1083, Hungary.
Gergő Kiszner1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, Budapest, 1085, Hungary.
Lilla Madaras2nd Department of Pathology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary.
Janina Kulka2nd Department of Pathology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary.
Tibor KrenácsMTA-SE Tumor Progression Research Group, 2nd Department of Pahtology, Semmelweis University, Üllői út 93, Budapest, 1091, Hungary.
Magdolna Dank1st Department of Internal Medicine, Oncological Division, Semmelweis University, Tömő utca 25-29, 4th floor, Budapest, 1083, Hungary. phd.se.oncology@gmail.com.
Semmelweis University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to analyze to what extent expression of four cell cycle regulation markers-minichromosome maintenance protein (MCM2), Ki-67, cyclin A, and phosphohistone-H3 (PHH3)-predict response to primary systemic therapy in terms of pathological complete remission (pCR). In search of an accurate and reproducible scoring method, we compared computer-assisted (CA) and routine visual assessment (VA) of immunoreactivity. We included 57 patients with breast cancer in the study. The cell cycle markers were detected using immunohistochemistry on pre-therapy core biopsy samples. Parallel CA (validated by manual labeling) and standard VA were performed and compared for diagnostic agreement and predictive value for pCR. CA and VA results were dichotomized based on receiver operating characteristic analysis defined optimal cut-off values. "High" was defined by staining scores above the optimal cut-off, while "low" had staining scores below the optimal cut-off. The CA method resulted in significantly lower values for Ki-67 and MCM2 compared to VA (mean difference, -3.939 and -4.323). Diagnostic agreement was highest for cyclin A and PHH3 (-0.586 and -0.666, respectively). Regardless of the method (CA/VA) used, all tested markers were predictive of pCR. Optimal cut-off-based dichotomization improved diagnostic agreement between the CA and VA methods for every marker, in particular for MCM2 (κ = 1, p < 0.000). Cyclin A displayed excellent agreement (κ = 0.925; p < 0.000), while Ki-67 and PHH3 showed good agreement (κ = 0.789, p < 0.000 and κ = 0.794, p < 0.000, respectively). We found all cell cycle markers (Ki-67, MCM2, cyclin A, and PHH3) predictive of pCR. Diagnostic agreement between CA and VA was better at lower staining scores but improved after optimal cut-off-based dichotomization.

Indexed as

ImmunohistochemistryAdultAgedBiomarkers, TumorBreast NeoplasmsCell CycleCell Cycle ProteinsFemaleHumansKi-67 AntigenMiddle AgedBiomarkers, TumorCell Cycle ProteinsKi-67 AntigenBreast cancerCell cycleDigital pathologyPrimary systemic therapyProliferation

Identifiers

PMID27026269
OpenAlexW2320206053

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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.