Circulating tumor DNA as part of the routine work-up for patients with suspected advanced lung cancer
Bibliographic record
Abstract
Liquid biopsy (LB) is a useful tool in patients with advanced non-small cell lung cancer (aNSCLC) to detect actionable molecular alterations and thereby allow genotype-matched therapies. Currently, LB is recommended for individuals diagnosed with aNSCLC who have an insufficient tissue sample or difficult-to-reach tumour tissue. Despite the potential advantages of LB, its incorporation into the standard diagnostic work-up for all newly diagnosed patients with aNSCLC is lacking. Our study aimed to evaluate whether addition of plasma circulating tumor DNA (ctDNA) next generation sequencing (NGS) testing early in the diagnostic work-up for patients with aNSCLC can improve the time to molecular results and treatment initiation. This was a single-centre quality improvement initiative with two cohorts of patients. Patients in the 'ctDNA cohort' had plasma ctDNA testing in addition to the standard diagnostic work-up. The 'reference cohort' was a parallel group of patients who had the standard work-up (no LB). Tissue biopsy and reflex tissue NGS testing were done in both cohorts. ctDNA testing shortened the time to molecular results in the ctDNA cohort compared to the reference cohort (median, 14 vs 35 days; p = 0.01), the time from first respirology/thoracic surgery consult to molecular results (median, 22 vs 48 days respectively; p = 0.01), and the time from medical oncology consultation to initiation of first-line treatment (median, 12 vs 22 days; p = 0.01). In conclusion, in a publicly funded and single-payer healthcare system, ctDNA testing as part of the standard work-up for patients with aNSCLC provides molecular results significantly faster than tissue-based testing and shortens the time to treatment initiation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".