Colon and rectal cancer survival in seven high-income countries 2010–2014: variation by age and stage at diagnosis (the ICBP SURVMARK-2 project)
Bibliographic record
Abstract
OBJECTIVES: As part of the International Cancer Benchmarking Partnership (ICBP) SURVMARK-2 project, we provide the most recent estimates of colon and rectal cancer survival in seven high-income countries by age and stage at diagnosis. METHODS: Data from 386 870 patients diagnosed during 2010-2014 from 19 cancer registries in seven countries (Australia, Canada, Denmark, Ireland, New Zealand, Norway and the UK) were analysed. 1-year and 5-year net survival from colon and rectal cancer were estimated by stage at diagnosis, age and country, RESULTS: (One1-year) and 5-year net survival varied between (77.1% and 87.5%) 59.1% and 70.9% and (84.8% and 90.0%) 61.6% and 70.9% for colon and rectal cancer, respectively. Survival was consistently higher in Australia, Canada and Norway, with smaller proportions of patients with metastatic disease in Canada and Australia. International differences in (1-year) and 5-year survival were most pronounced for regional and distant colon cancer ranging between (86.0% and 94.1%) 62.5% and 77.5% and (40.7% and 56.4%) 8.0% and 17.3%, respectively. Similar patterns were observed for rectal cancer. Stage distribution of colon and rectal cancers by age varied across countries with marked survival differences for patients with metastatic disease and diagnosed at older ages (irrespective of stage). CONCLUSIONS: Survival disparities for colon and rectal cancer across high-income countries are likely explained by earlier diagnosis in some countries and differences in treatment for regional and distant disease, as well as older age at diagnosis. Differences in cancer registration practice and different staging systems across countries may have impacted the comparisons.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".