Presentation and outcomes of KRASG12C mutant non-small cell lung cancer patients with stage IV disease at diagnosis (de novo) versus at recurrence
Bibliographic record
Abstract
Close monitoring after diagnosis of patients with stage I-III non-small cell lung cancer (NSCLC) may result in fitter patients with lower disease burden at the time of metastatic recurrence or progression compared to patients diagnosed initially as stage IV (de novo). We compared the presentation, treatments, and outcomes of patients with KRASG12C-mutated NSCLC with de novo versus recurrent stage IV disease. Of 109 patients, 94% had a smoking history. When compared to patients with KRASG12C-mutated NSCLC who developed stage IV disease at recurrence (n=38), de novo stage IV patients (n=71) had worse ECOG performance status (p=0.007), greater numbers of extra-thoracic metastatic sites (p=0.001), and were less likely to receive 2nd/3rd line systemic therapy (p=0.05, p=0.002) or targeted therapy (p=0.001). De novo metastatic patients had shorter overall survival than metastatic patients at recurrence (9.1 versus 24.2 months; adjusted-hazard-ratio=1.94 (95%CI:1.14-3.28; p=0.01)). There is a critical need for well-tolerated targeted therapies in the first-line setting for metastatic patients with de novo, high-burden, stage IV KRASG12C-mutated NSCLCs.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".