Ten-year follow-up of a province-wide cohort of surgical lung cancer patients in Nova Scotia.
Bibliographic record
Abstract
BACKGROUND: After a diagnosis of lung carcinoma, survival is poor for all patients. We sought to assess 10-year survival and predictors of outcome after surgery for lung cancer in Nova Scotia. METHODS: We identified all patients n = 130) undergoing resection for lung cancer in Nova Scotia in 1994 from the Nova Scotia Cancer Registry and hospital charts and followed them prospectively for 10 years. We used Cox proportional hazards modelling to identify predictors of survival. RESULTS: The patients' mean age at operation was 67.7 (standard deviation [SD] 8.2) years, and 70% of the patients were men. Most of the operations n = 80, 61.5%) were performed in Halifax, and adenocarcinoma n = 55, 42.3%) was the most common histologic type. At the time of surgery, 66.9% of the cases were stage 1, 20.0% were stage 2 and 13.1% were stage 3. Survival at 5 and 10 years was 34% and 13%, respectively. Age of 70 years or older (hazard ratio [HR] 1.79, 95% confidence interval [CI] 1.20-2.68), large cell carcinoma (HR 2.27, 95% CI 1.31-3.94) and stage 3 cancer (HR 2.21, 95% CI 1.25-3.90) were significant independent predictors of survival. Hospital site was not associated with any difference in survival (p = 0.66), although there was a trend toward differential rates of lymph node sampling across sites (p = 0.06). The presence of node sampling was associated with improved survival in a separate multivariate model (HR 0.51, 95% CI 0.29-0.89). CONCLUSION: Actuarial survival after resection of lung carcinoma in Nova Scotia in 1994 was 34% at 5 years and 13% after 10 years. Age, stage and histology are independent predictors of survival; lymph node sampling was associated with greater survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".