Evidence map›Paper›PMID 36231142›Full record

ReviewCells2022

Patient Selection Approaches in FGFR Inhibitor Trials-Many Paths to the Same End?

Peter Ellinghaus, Daniel Neureiter, Hendrik Nogai, Sebastian Stintzing, Matthias Ocker

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Peter EllinghausGlobal Clinical Development Oncology, Merck Healthcare KGaA, 64293 Darmstadt, Germany.
Daniel NeureiterInstitute of Pathology, University Clinics Salzburg, Paracelsus Medical University, 5020 Salzburg, Austria.ORCID 0000-0001-9155-5762
Hendrik NogaiRyvu Therapeutics, 30-394 Krakow, Poland.
Sebastian StintzingDivision of Hematology, Oncology, and Tumor Immunology (Campus Charité Mitte), Medical Department, Charité University Medicine Berlin, 10117 Berlin, Germany.ORCID 0000-0002-3297-5801
Matthias OckerDivision of Hematology, Oncology, and Tumor Immunology (Campus Charité Mitte), Medical Department, Charité University Medicine Berlin, 10117 Berlin, Germany.ORCID 0000-0001-8263-6288
Charité - Universitätsmedizin Berlin · DEMerck (Germany) · DEParacelsus Medical University · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inhibitors of fibroblast growth factor receptor (FGFR) signaling have been investigated in various human cancer diseases. Recently, the first compounds received FDA approval in biomarker-selected patient populations. Different approaches and technologies have been applied in clinical trials, ranging from protein (immunohistochemistry) to mRNA expression (e.g., RNA in situ hybridization) and to detection of various DNA alterations (e.g., copy number variations, mutations, gene fusions). We review, here, the advantages and limitations of the different technologies and discuss the importance of tissue and disease context in identifying the best predictive biomarker for FGFR targeting therapies.

Indexed as

DNA Copy Number VariationsProtein Kinase InhibitorsDNAHumansPatient SelectionReceptors, Fibroblast Growth FactorRNARNA, MessengerDNAProtein Kinase InhibitorsReceptors, Fibroblast Growth FactorRNARNA, Messengeramplificationclinical trialsFGFR inhibitorfibroblast growth factor receptorfusionmutationpredictive biomarker

Identifiers

PMID36231142
PMCPMC9563413
OpenAlexW4304128322

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.