Age disparities in stage-specific colon cancer survival across seven countries: An International Cancer Benchmarking Partnership SURVMARK-2 population-based study
Bibliographic record
Abstract
We sought to understand the role of stage at diagnosis in observed age disparities in colon cancer survival among people aged 50 to 99 years using population-based cancer registry data from seven high-income countries: Australia, Canada, Denmark, Ireland, New Zealand, Norway and the United Kingdom. We used colon cancer incidence data for the period 2010 to 2014. We estimated the 3-year net survival, as well as the 3-year net survival conditional on surviving at least 6 months and 1 year after diagnosis, by country and stage at diagnosis (categorised as localised, regional or distant) using flexible parametric excess hazard regression models. In all countries, increasing age was associated with lower net survival. For example, 3-year net survival (95% confidence interval) was 81% (80-82) for 50 to 64 year olds and 58% (56-60) for 85 to 99 year olds in Australia, and 74% (73-74) and 39% (39-40) in the United Kingdom, respectively. Those with distant stage colon cancer had the largest difference in colon cancer survival between the youngest and the oldest patients. Excess mortality for the oldest patients with localised or regional cancers was observed during the first 6 months after diagnosis. Older patients diagnosed with localised (and in some countries regional) stage colon cancer who survived 6 months after diagnosis experienced the same survival as their younger counterparts. Further studies examining other prognostic clinical factors such as comorbidities and treatment, and socioeconomic factors are warranted to gain further understanding of the age disparities in colon cancer survival.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".