Recurrent versus de novo metastatic NSCLC: Impact on outcomes.
Bibliographic record
Abstract
9045 Background: Metastatic non-small-cell lung (NSCLC) cancer has a poor prognosis, with a 5 year survival less than 5%. The majority of patients present with stage IV and many patients treated curatively with stage I-III will develop recurrent metastatic disease. It is unknown if the natural history differs between patients with recurrent versus de novo metastatic NSCLC. We hypothesized that de novo metastatic disease is associated with decreased overall survival compared to recurrent metastatic disease. Methods: A retrospective review was completed of all patients with NSCLC referred to the BC Cancer Agency from 2005-2012. Two cohorts were created; de novo metastatic disease and patients treated with curative intent (surgery or radiotherapy) that developed recurrent, metastatic disease. Information was collected on known prognostic and predictive factors. Overall survival was calculated from the date of diagnosis of metastatic disease. Results: A total of 9656 patients were referred, 5783 (60%) with de novo stage IV disease, and 3873 (40%) with stage I-III disease. Of patients with initial stage I-III, 1801 received curative therapy (751 surgery, 1050 radiotherapy) and 802 developed metastases. Patients in the de novo cohort were more likely to be male (52% vs 47%), have poorer performance status (ECOG≥2 50% vs 43%), and receive no palliative chemotherapy (67% vs 61%). The median overall survival in the de novo cohort was 4.7 m vs 6.9 m in the recurrent cohort (p < 0.001). De novo status was associated with shorter overall survival and this remained significant in a multivariate model that incorporated gender, ECOG and lines of palliative chemotherapy (hazard ratio 1.228[95% confidence interval 1.134-1.330], p-value < 0.001). Conclusions: In a large population based study of NSCLC, de novo metastatic status was independently associated with decreased overall survival from the time of metastatic disease diagnosis. De novo versus recurrent status should be used as a prognostic factor to inform patient decisions and ensure balanced stratification of patients in clinical trials.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".