Evidence map›Paper›PMID 35969265›Full record

ArticlePathologie (Heidelberg, Germany)2022

[Predictive molecular diagnostics in breast cancer : What are the requirements for pathology today and in the future?]

Peter J Wild, Carsten Denkert, C Jackisch

Open access · hybridAbstract read
In one paragraph

Article in Pathologie (Heidelberg, Germany), 2022. 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
0.6field-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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

3 authors at 3 institutions in 1 country.

Peter J WildDr. Senckenbergisches Institut für Pathologie, Universitätsklinikum Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Deutschland. peter.wild@kgu.de.
Carsten DenkertInstitut für Pathologie, Universitätsklinikum Gießen-Marburg, Standort Marburg, Baldingerstraße, 35033, Marburg, Deutschland.
C JackischKlinik für Gynäkologie und Geburtshilfe, Sana Klinikum Offenbach, Starkenburgring 66, 63069, Offenbach, Deutschland.
Goethe University Frankfurt · DESana Klinikum Offenbach · DEUniversitätsklinikum Gießen und Marburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With an increasing number of targeted therapy options for the treatment of solid tumors, the demands on predictive molecular diagnostics for pathology are growing. In breast cancer the need to determine genomic predictive markers for available targeted therapies has so far been manageable (detection of PIK3CA mutations in endocrine pretreated luminal tumors and the search for NTRK fusions indicated only in secretory breast cancer). At the latest in cases of nonresponse to first-line or second-line standard treatment, more comprehensive diagnostics using next generation sequencing (NGS) panel diagnostics makes sense. This should be suitable for clarifying resistance mechanisms, e.g. against endocrine therapy or cyclin-dependent kinase 4/cyclin-dependent kinase 6 (CDK4/6) inhibitors and to identify indications for therapies currently in development. The interpretation should be carried out in a quality assured manner in accordance with international standards and the interdisciplinary tumor board should make a transparent and standardized report available in a timely manner.

Indexed as

Breast NeoplasmsBiomarkers, TumorFemaleHigh-Throughput Nucleotide SequencingHumansPathology, MolecularBiomarkers, TumorLiquid biopsyNext generation sequencingPathology, molecularPredictive biomarkersVariant interpretation

Identifiers

PMID35969265
PMCPMC9402728
OpenAlexW4291901803

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.