Evidence map›Paper›PMID 28490348›Full record

Trial reportBreast cancer research : BCR2017

An international reproducibility study validating quantitative determination of ERBB2, ESR1, PGR, and MKI67 mRNA in breast cancer using MammaTyper®.

Zsuzsanna Varga, Annette Lebeau, Hong Bu, Arndt Hartmann, Frederique Penault-Llorca, Elena Guerini-Rocco, Peter Schraml, Fraser Symmans, Robert Stoehr, Xiaodong Teng and 11 more

Open access · goldAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Breast cancer research : BCR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.5field-weighted citation impact, top 20% 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

23 citing papers in PubMed, 39 citations in OpenAlex.

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  17. Polymorphism of XRCC3 in Egyptian Breast Cancer Patients.Pharmacogenomics and personalized medicine · 2020
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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

21 authors at 13 institutions in 8 countries.

Zsuzsanna VargaInstitute of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland. zsuzsanna.varga@usz.ch.
Annette LebeauPrivate Group Practice for Pathology and PathoPlan GbR, Lübeck, Germany.
Hong BuDepartment of Pathology and Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu, China.
Arndt HartmannInstitute of Pathology, University Erlangen-Nürnberg, Erlangen, Germany.
Frederique Penault-LlorcaCentre Jean Perrin, Centre regional de Lutte contre le cancer d'Auvergne, Clermont-Ferrand, France.
Elena Guerini-RoccoEuropean Institute of Oncology, University of Milan, Milan, Italy.
Peter SchramlInstitute of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Fraser SymmansUniversity of Texas MD Anderson Cancer Center, Houston, TX, USA.
Robert StoehrInstitute of Pathology, University Erlangen-Nürnberg, Erlangen, Germany.
Xiaodong TengDepartment of Pathology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Andreas TurzynskiPrivate Group Practice for Pathology and PathoPlan GbR, Lübeck, Germany.
Reinhard von WasielewskiInstitute of Pathology, Klinikum Region Hannover, Hannover, Germany.
Claudia GürtlerBioNTech Diagnostics GmbH, Mainz, Germany.
Mark LaibleBioNTech Diagnostics GmbH, Mainz, Germany.
Kornelia SchlombsBioNTech Diagnostics GmbH, Mainz, Germany.
Heikki JoensuuDepartment of Oncology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
Thomas KellerACOMED Statistik, Leipzig, Germany.
Peter SinnDepartment of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
Ugur SahinBioNTech Diagnostics GmbH, Mainz, Germany.
John BartlettTransformative Pathology, Ontario Institute for Cancer Research (OICR), Toronto, ON, Canada.
Giuseppe VialeEuropean Institute of Oncology, University of Milan, Milan, Italy.
BioNTech (Germany) · DEFriedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversity Hospital of Zurich · CHUniversity of Milan · ITCentre Jean Perrin · FRHeidelberg University · DEKlinikum Region Hannover · DEOntario Institute for Cancer Research · CASichuan University · CNStatistisches Bundesamt · DEThe University of Texas MD Anderson Cancer Center · USUniversity of Helsinki · FIZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate determination of the predictive markers human epidermal growth factor receptor 2 (HER2/ERBB2), estrogen receptor (ER/ESR1), progesterone receptor (PgR/PGR), and marker of proliferation Ki67 (MKI67) is indispensable for therapeutic decision making in early breast cancer. In this multicenter prospective study, we addressed the issue of inter- and intrasite reproducibility using the recently developed reverse transcription-quantitative real-time polymerase chain reaction-based MammaTyper® test.

methodsTen international pathology institutions participated in this study and determined messenger RNA expression levels of ERBB2, ESR1, PGR, and MKI67 in both centrally and locally extracted RNA from formalin-fixed, paraffin-embedded breast cancer specimens with the MammaTyper® test. Samples were measured repeatedly on different days within the local laboratories, and reproducibility was assessed by means of variance component analysis, Fleiss' kappa statistics, and interclass correlation coefficients (ICCs).

resultsTotal variations in measurements of centrally and locally prepared RNA extracts were comparable; therefore, statistical analyses were performed on the complete dataset. Intersite reproducibility showed total SDs between 0.21 and 0.44 for the quantitative single-marker assessments, resulting in ICC values of 0.980-0.998, demonstrating excellent agreement of quantitative measurements. Also, the reproducibility of binary single-marker results (positive/negative), as well as the molecular subtype agreement, was almost perfect with kappa values ranging from 0.90 to 1.00.

conclusionsOn the basis of these data, the MammaTyper® has the potential to substantially improve the current standards of breast cancer diagnostics by providing a highly precise and reproducible quantitative assessment of the established breast cancer biomarkers and molecular subtypes in a decentralized workup.

Indexed as

Biomarkers, TumorBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesEstrogen Receptor alphaFemaleFormaldehydeGene Expression Regulation, NeoplasticHumansIntracellular Signaling Peptides and ProteinsKi-67 AntigenNuclear ProteinsPrognosisProspective StudiesRNA, MessengerBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesESR1 protein, humanEstrogen Receptor alphaFormaldehydeIntracellular Signaling Peptides and ProteinsKi-67 AntigenMRFAP1 protein, humanNuclear ProteinsRNA, MessengerBreast cancerERBB2ESR1FFPEMammaTyperMKI67PGRReproducibilityRT-qPCR

Identifiers

PMID28490348
PMCPMC5426065
OpenAlexW2612897155

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.