Evidence map›Paper›PMID 34196797›Full record

ReviewVirchows Archiv : an international journal of pathology2022

Grading of invasive breast carcinoma: the way forward.

C van Dooijeweert, P J van Diest, I O Ellis

Open access · hybridAbstract readReview
In one paragraph

Review in Virchows Archiv : an international journal of pathology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 2% 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

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

C van DooijeweertDepartment of Pathology, University Medical Center Utrecht, Utrecht, Netherlands.
P J van DiestDepartment of Pathology, University Medical Center Utrecht, Utrecht, Netherlands. p.j.vandiest@umcutrecht.nl.ORCID https://orcid.org/0000-0003-0658-2745
I O EllisDepartment of Histopathology, Nottingham University Hospitals, Nottingham, UK.ORCID https://orcid.org/0000-0001-5292-8474
Nottingham University Hospitals NHS Trust · GBUniversity Medical Center Utrecht · NLUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histologic grading needs to be performed accurately, on properly fixed specimens, and by adequately trained dedicated pathologists that take the time to diligently follow the protocol methodology. In this paper, we review the history of histologic grading, describe the basics of grading, review prognostic value and reproducibility issues, compare performance of grading to gene expression profiles, and discuss how to move forward to improve reproducibility of grading by training, feedback and artificial intelligence algorithms, and special stains to better recognize mitoses. We conclude that histologic grading, when adequately carried out, remains to be of important prognostic value in breast cancer patients.

Indexed as

Artificial IntelligenceBreast NeoplasmsFemaleHumansMitosisNeoplasm GradingPathologistsReproducibility of ResultsBreastCarcinomaGradingHistology

Identifiers

PMID34196797
PMCPMC8983621
OpenAlexW3176465542

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.