Quantification of circulating free and circulating tumor DNA in pretreated EGFR mutant NSCLC to inform patient outcomes.
Bibliographic record
Abstract
9080 Background: EGFR T790M testing is standard of care for EGFR mutant (EGFRm) NSCLC progressing on 1st/2nd generation TKIs to select patients for osimertinib. Circulating free DNA (cfDNA) levels are measured prior to circulating tumour DNA (ctDNA) testing using droplet digital PCR (ddPCR) to measure activating/resistant EGFR mutations. We reviewed cfDNA levels and ctDNA mutational status to determine the influence on patient outcome. Methods: Following extraction of cfDNA from plasma using the QIAamp Circulating Nucleic Acid Kit, cfDNA levels are measured with a Qubit 2.0 Fluorometer. Custom ddPCR assays were used to test for the appropriate EGFR activating mutation and the EGFR T790M resistance mutation using the Bio-Rad QX200 system. The custom designed ddPCR assays have a limit of detection of < 0.1% variant allele fraction. All patients undergoing ctDNA testing from February-December 2018 were identified. Baseline characteristics and follow up data were collected retrospectively. OS was calculated from date of metastatic diagnosis to death/last follow-up. Results: 142 patients with EGFR mutant adenocarcinoma had EGFR ctDNA testing: results 52% indeterminant, 32% T790M, 16% activating EGFRm only. At the time of testing: median age 66, 64% female, 57% never smokers 53% Asian; systemic treatment (tx) 62% first line only, 25% two lines and 13% ≥ three lines. First TKI therapy: 32% afatanib, 66% gefitinib, 2% erlotinib. Median cfDNA concentration was 5.65 ng/ml (range 0.50-217.72). The 5 yr OS was 72% below cfDNA median and 25% above the median. Tx after ctDNA testing for below and above cfDNA median: 52 vs 33% original TKI, 34 vs 55% osimertinib, 14 vs 12% other systemic tx. Multivariate analysis shows that even accounting for age, sex and ctDNA mutation result, cfDNA concentration remains an independent predictor of outcome (HR 2.36, 95% CI 1.08-5.18, p = 0.032). Conclusions: cfDNA concentration can predict patient outcome in patients with EGFR mutant NSCLC progressing on TKI regardless of ctDNA testing results. Clinicians may consider switching to chemotherapy for patients with high cfDNA and without detectable EGFR T790M ctDNA to avoid missing the window for therapy instead of awaiting repeat EGFR T790M testing
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".