Adoption of Adjuvant Chemotherapy for Non–Small-Cell Lung Cancer: A Population-Based Outcomes Study
Bibliographic record
Abstract
PURPOSE: Since 2004, several clinical trials have demonstrated that adjuvant chemotherapy (ACT) improves survival in patients with early-stage non-small-cell lung cancer (NSCLC). Here, we evaluate the uptake of ACT and its impact on outcomes in the general population of Ontario, Canada. METHODS: All patients diagnosed with NSCLC in Ontario from 2001 to 2006 who underwent surgical resection (n = 6,304) were identified using the Ontario Cancer Registry. We linked electronic records of treatment to the registry. We described uptake of ACT and compared survival of all patients with surgically resected NSCLC diagnosed from 2001 to 2003 with patients diagnosed from 2004 to 2006. As a proxy measure of ACT-related toxicity, we evaluated hospitalizations within 6 months of surgery. RESULTS: Demographic, disease, and treatment-related characteristics did not differ between the 2001 to 2003 and 2004 to 2006 study cohorts. Over the study period, the proportion of patients receiving ACT increased from 7% (192 of 2,950 patients) to 31% (1,032 of 3,354 patients; P < .001). The proportion of patients admitted to hospital within 6 months of surgery remained stable and (36% in the 2001 to 2003 cohort and 37% in the 2004 to 2006 cohort). However, within 2 years of surgery, there was a 33% reduction in the proportion of patients admitted to hospital with metastatic disease (P < .001). During the study period, there was a substantial improvement in 4-year survival among surgically resected patients, from 52.5% (2001 to 2003) to 56.1% (2004 to 2006; P = .001). CONCLUSION: There has been a rapid uptake of ACT for NSCLC, which was not associated with an increased rate of hospitalization. The adoption of ACT was associated with a substantial improvement in overall survival, suggesting that the benefits seen in clinical trials are generalizable to the general population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".