Circulating Tumour DNA in EGFR-Mutant Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
The advent of targeted therapy in non-small-cell lung cancer (NSCLC) has made the routine molecular diagnosis of EGFR mutations crucial for optimal patient management. Obtaining tumour tissue for biomarker testing, especially in the setting of re-biopsy, can present many challenges. A potential alternative source of tumour dna is circulating cell-free tumour-derived DNA (CTDNA). Although CTDNA is present in low quantities in plasma, the convenience of sample acquisition and the increasing reliability of detection methods make this approach a promising one. The various performance characteristics of both digital and nondigital platforms are still variable, and a standardized approach is needed that will make those platforms reliable clinical tools for the detection of EGFR sensitizing mutations and resistance mutations, including the T790M resistance mutation. Information derived from ctdna can be used to assess tumour burden, to identify genomic-based resistance mechanisms, and to track dynamic changes during therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".