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Record W4407001040 · doi:10.1016/j.lungcan.2025.108412

EGFR testing practices, treatment choice and clinical outcomes in advanced NSCLC in a real-world setting: A retrospective analysis of a US-based electronic health records database

2025· article· en· W4407001040 on OpenAlexaff
Janakiraman Subramanian, Jeffrey P. Gregg, Mehmet Berktaş, Jingyi Li, Natasha B. Leighl

Bibliographic record

VenueLung Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
FundersAstraZeneca
KeywordsMedicineHealth recordsElectronic databaseRetrospective cohort studyElectronic health recordReal world evidenceMedical recordDatabaseInternal medicineHealth care

Abstract

fetched live from OpenAlex

OBJECTIVES: Guidelines recommend epidermal growth factor receptor (EGFR) mutation testing for patients with advanced non-small cell lung cancer (NSCLC) and initiation of first-line EGFR tyrosine kinase inhibitors (EGFR-TKIs) for EGFR mutation-positive (EGFRm) NSCLC. We analyzed a nationwide electronic health record-derived de-identified database to describe EGFR testing practices, treatment choice, and outcomes in patients from the United States (US) with advanced NSCLC. MATERIALS AND METHODS: Adults diagnosed with stage IIIB-IV NSCLC January 2015-January 2020, who received first-line treatment from a network of ∼280 US cancer clinics were included. Demographics/characteristics, EGFR status, time from advanced diagnosis to EGFR test result, first-line treatment, time from treatment initiation to discontinuation/death (TTD), next treatment/death (TTNTD), and overall survival (OS) were extracted. RESULTS: 12,577/16,309 (77 %) eligible patients had an EGFR test recorded; 1,914/12,577 (15 %) patients had EGFRm NSCLC. Of 1,778 patients with confirmed EGFRm NSCLC before first-line treatment, 75 % received first-line EGFR-TKIs, 11 % chemotherapy, 9 % immunotherapy, and 4 % other treatment. Of 136 patients with an EGFRm result after initiating first-line treatment, 13 % received EGFR-TKIs, 50 % chemotherapy, 19 % immunotherapy, and 18 % other treatment in first-line. Among patients with EGFRm NSCLC, median time from advanced diagnosis to EGFR test result was shorter in patients who received first-line EGFR-TKIs versus first-line chemotherapy/immunotherapy/other treatment. Patients treated with first-line EGFR-TKIs had significantly improved TTD/TTNTD versus those who received first-line chemotherapy/immunotherapy/other treatment (p < 0.001). OS was significantly longer in patients receiving treatment ≥21 versus <21 days after index (p < 0.001). CONCLUSIONS: Nearly one-quarter of patients with advanced NSCLC in a US health network were not tested for EGFR mutations. Of patients who received a EGFRm result after initiating first-line treatment, 13 % received first-line EGFR-TKIs. These real-world data support the need to improve EGFR testing implementation and time to result to optimize first-line treatment for advanced NSCLC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.484
Teacher spread0.449 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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