Real-world treatment patterns and outcomes for patients with non-metastatic non-small cell lung cancer: retrospective analyses in Canada, England, and Germany
Bibliographic record
Abstract
BACKGROUND: Recent therapeutic advancements for non-metastatic non-small cell lung cancer (NSCLC) have increased the need for real-world baselines against which future changes in patient management and clinical outcomes can be compared. METHODS: Data on patient characteristics, initial treatment, and overall survival (OS) were derived from adult patients diagnosed with stage I-IIIC NSCLC (2010-2020) in a regional Canadian database (Oncology Outcomes [O2]), an English national registry (Cancer Analysis System [CAS]), and four regional German registries (VONKOdb) and retrospectively analyzed separately using analogous methodology. RESULTS: Data from 85,433 patients were analyzed. Stage at diagnosis varied, with proportions with stage I NSCLC ranging from 30.9% (VONKOdb) to 44.2% (O2) and with stage III disease from 36.9% (O2) to 48.5% (VONKOdb). Across the data sources, proportions receiving surgery ± other treatments were similar for stages I and II, but decreased through stages IIIA, IIIB, and IIIC (range, 24.7-42.7%, 4.6-21.8%, and 0.9-7.5%, respectively). Overall, 70.3-85.2% of patients received active treatment for NSCLC, with a trend toward lower proportions among those with stage III disease. Reached median OS tended to be longest in patients with resected stage I/II NSCLC (range, 28.8-128.0 months) and shortest in patients with stage IIIB/IIIC disease treated with systemic anticancer therapy (SACT) alone, radiotherapy alone, or SACT + palliative radiotherapy (range, 4.8-21.2 months). CONCLUSIONS: These data provide insights into treatment pathways and survival outcomes before the widespread use of immunotherapy-based and targeted therapies and will serve as an important baseline for future evaluations of emerging treatments for patients with non-metastatic NSCLC.
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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) | 0.001 | 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".