Lung cancer survival and stage at diagnosis in Australia, Canada, Denmark, Norway, Sweden and the UK: a population-based study, 2004–2007
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The authors consider whether differences in stage at diagnosis could explain the variation in lung cancer survival between six developed countries in 2004-2007. METHODS: Routinely collected population-based data were obtained on all adults (15-99 years) diagnosed with lung cancer in 2004-2007 and registered in regional and national cancer registries in Australia, Canada, Denmark, Norway, Sweden and the UK. Stage data for 57 352 patients were consolidated from various classification systems. Flexible parametric hazard models on the log cumulative scale were used to estimate net survival at 1 year and the excess hazard up to 18 months after diagnosis. RESULTS: Age-standardised 1-year net survival from non-small cell lung cancer ranged from 30% (UK) to 46% (Sweden). Patients in the UK and Denmark had lower survival than elsewhere, partly because of a more adverse stage distribution. However, there were also wide international differences in stage-specific survival. Net survival from TNM stage I non-small cell lung cancer was 16% lower in the UK than in Sweden, and for TNM stage IV disease survival was 10% lower. Similar patterns were found for small cell lung cancer. CONCLUSIONS: There are comparability issues when using population-based data but, even given these constraints, this study shows that, while differences in stage at diagnosis explain some of the international variation in overall lung cancer survival, wide disparities in stage-specific survival exist, suggesting that other factors are also important such as differences in treatment. Stage should be included in international cancer survival studies and the comparability of population-based data should be improved.
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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) | 0.000 | 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) | 0.003 | 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 it