Evidence map›Paper›PMID 33346146›Full record

ArticleThe Journal of molecular diagnostics : JMD2021

Rapid EGFR Mutation Detection Using the Idylla Platform: Single-Institution Experience of 1200 Cases Analyzed by an In-House Developed Pipeline and Comparison with Concurrent Next-Generation Sequencing Results.

Amir Momeni-Boroujeni, Paulo Salazar, Tao Zheng, Nana Mensah, Ivelise Rijo, Snjezana Dogan, JinYuan Yao, Christine Moung, Chad Vanderbilt, Jamal Benhamida and 6 more

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.3field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
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  13. Contribution of the IdyllaCurrent oncology (Toronto, Ont.) · 2021
    Article
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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

16 authors at 1 institution in 1 country.

Amir Momeni-BoroujeniDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Paulo SalazarDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Tao ZhengDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Nana MensahDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Ivelise RijoDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Snjezana DoganDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
JinYuan YaoDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Christine MoungDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Chad VanderbiltDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Jamal BenhamidaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Jason ChangDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
William TravisDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Natasha RekhtmanDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Marc LadanyiDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Khedoudja NafaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York.
Maria E ArcilaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York. Electronic address: arcilam@mskcc.org.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Mutations in the epidermal growth factor receptor (EGFR) are the most common targetable alterations in lung adenocarcinoma. To facilitate rapid testing, the Idylla EGFR assay was incorporated as a screening method before next-generation sequencing (NGS). Validation and experience using an in-house developed analysis pipeline, enhanced with a manual review algorithm is described. Results are compared with corresponding NGS results. In all, 1249 samples were studied. Validation demonstrated 98.57% (69/70) concordance with the reference methods. The limit of detection varied from 2% to 5% variant allele frequency for total EGFR quantitation cycle between 20 and 23. Of the 1179 clinical cases, 23.41% were EGFR-positive by Idylla. Concurrent NGS was successfully performed on 94.9% (799/842) requests. Concordance of Idylla with NGS was 98.62% (788/799) and 98.50% (787/799) using our in-house and Idylla analysis pipelines, respectively. Discordances involved missed mutations by both assays associated with low tumor/low input. Incorporating a manual review algorithm to supplement automated calls improved accuracy from 98.62% to 99.37% and sensitivity from 94.68% to 97.58%. Overall reporting time, from receipt of material to official clinical report, ranged from 1 to 3 days. Therefore, Idylla EGFR testing enables rapid and sensitive screening without compromising subsequent comprehensive NGS, when required. Automated calling, enhanced with a manual review algorithm, reduces false-negative calls associated with low tumor/low input samples.

Indexed as

MutationBiomarkers, TumorData AnalysisDNA Mutational AnalysisErbB ReceptorsHigh-Throughput Nucleotide SequencingHumansLung NeoplasmsNucleic Acid Amplification TechniquesReproducibility of ResultsSensitivity and SpecificityWorkflowBiomarkers, TumorEGFR protein, humanErbB Receptors

Identifiers

PMID33346146
PMCPMC7919857
OpenAlexW3111956708

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.