Evidence map›Paper›PMID 19680292›Full record

ReviewOncogene2009

Overview of molecular testing in non-small-cell lung cancer: mutational analysis, gene copy number, protein expression and other biomarkers of EGFR for the prediction of response to tyrosine kinase inhibitors.

T John, G Liu, M-S Tsao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Oncogene, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed
15.3field-weighted citation impact, top 1% 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

99 citing papers in PubMed, 215 citations in OpenAlex.

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  16. Molecular Subtypes of Primary SCLC Tumors and Their Associations With Neuroendocrine and Therapeutic Markers.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2022
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39 more citing papers are in PubMed but not listed here.

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.

T JohnUniversity Health Network, Princess Margaret Hospital Site, Ontario Cancer Institute, University of Toronto, Toronto, Ontario, Canada.
G Liu
M-S Tsao
Princess Margaret Cancer Centre · CAUniversity Health Network · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most patients with non-small-cell lung cancer (NSCLC) present with advanced disease. Current treatment paradigms are shifting from cytotoxic chemotherapies alone to single-agent and combination biological and targeted therapies. As patient responses to these therapies vary, predictive biomarkers will be an important facet of a patient's diagnostic workup in personalized medicine, as there is accumulating evidence that they may enable the prognostication and prediction of therapeutic response. Potential biomarkers for the selection of patients with NSCLC most likely to benefit from epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), such as gefitinib and erlotinib, include mutations, gene copy number increase and single-nucleotide polymorphisms of the EGFR gene, EGFR protein expression and oncogenic mutation on the KRAS gene. Many techniques are available to assay for these biomarkers. In this review, we present the current weight of evidence for using these methods as biomarkers for anti-EGFR therapy in patients with NSCLC.

Indexed as

Antineoplastic AgentsCarcinoma, Non-Small-Cell LungDNA Mutational AnalysisDrug Resistance, NeoplasmErbB ReceptorsGene DosageGenetic MarkersHumansLung NeoplasmsProtein BiosynthesisProtein Kinase InhibitorsTreatment OutcomeAntineoplastic AgentsEGFR protein, humanErbB ReceptorsGenetic MarkersProtein Kinase Inhibitors

Identifiers

PMID19680292
OpenAlexW2089716357

What OpenQuestion holds

Textmetadata
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.