Evidence map›Paper›PMID 38015260›Full record

ReviewVirchows Archiv : an international journal of pathology2024

Molecular pathology in breast disease: diagnostic, prognostic, and therapeutic tools.

Zsuzsanna Varga, Umberto Maccio

Open access · hybridAbstract readReview
In one paragraph

Review in Virchows Archiv : an international journal of pathology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Pathologica · 2025
    Article
  2. 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

2 authors at 1 institution in 1 country.

Zsuzsanna VargaDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstrasse 12, CH-8091, Zurich, Switzerland. zsuzsanna.varga@usz.ch.ORCID http://orcid.org/0000-0002-2855-983X
Umberto MaccioDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstrasse 12, CH-8091, Zurich, Switzerland.
University Hospital of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular testing in breast cancer gained increasing attention and importance as specific molecular results can tailor not only oncological decisions on systemic adjuvant or neoadjuvant or in metastatic setting, but increasingly serve in diagnostic routine histopathological services to differentiate between morphologically overlapping or ambiguous histological pictures. Diagnostic tools involve in most cases a broad spectrum of immunohistochemical panels, followed by entity-specific in situ hybridization probes and in given cases NGS-based sequencing. Workflow of which methodology is applied and in which order depends on the specific entity resp. on the given differential diagnosis in question. Regarding prognostic/predictive molecular testing, the choice of assay and the workflow are based on clinical algorithms and on the evidence of targeted therapies following the molecular alterations. In this review paper, we aim to address the use of molecular technics in [1] the histological diagnostic setting (such as subtyping of invasive carcinomas/malignant spindle cell tumors and sarcomas and some B3 lesions) and [2] in the context of adjuvant or neoadjuvant or other clinical settings with special focus of targeted therapies.

Indexed as

Breast NeoplasmsCarcinomaSarcomaFemaleHumansPathology, MolecularPrognosisBreast cancerCarcinomasMolecular testing

Identifiers

PMID38015260
PMCPMC10948467
OpenAlexW4389083490

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.