Clinical implementation of circulating tumour DNA testing for <i>EGFR</i> T790M for detection of treatment resistance in non-small cell lung cancer
Bibliographic record
Abstract
Aims Epidermal growth factor receptor ( EGFR ) T790M mutations can be detected in the circulating tumour DNA from plasma of patients with non-small cell lung cancer (NSCLC) to triage patients for osimertinib eligibility and monitor patients longitudinally for development of T790M-mediated resistance. Methods Using droplet digital PCR (ddPCR), we examined the EGFR T790M status of 343 sequential patients with NSCLC and correlated mutational status with demographic and clinical features. Where available, serial T790M blood test results were assessed to identify clinical triggers and timing of repeat testing. Results Of the 343 patients with liquid biopsy test results, 24% were T790M positive. No clear clinical correlation with a T790M positive test result was identified in this study, although the number of metastatic sites did correlate significantly with the presence of EGFR sensitising mutations (L858R or exon 19 deletion) in patient plasma, as a measure of tumour DNA shedding. Of the 59 serial blood tests from patients that initially tested negative, 14% were positive on sequential testing, at a time interval up to 6 months after an initially negative blood test. Conclusions The ddPCR test for EGFR T790M mutations effectively triaged 24% of patients for treatment with osimertinib, avoiding the need for invasive tissue biopsy in these patients. Our findings suggest that initial and repeat ctDNA testing can be used to monitor for acquired EGFR T790M resistance for NSCLC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".