Trends and Disparities in the Receipt of Treatment for Colon Cancer in Older Adults in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Adults aged ≥ 70 years represent approximately half of all patients diagnosed with colon cancer, but undertreatment in this population persists. Recent guidelines have aimed to reduce age-related biases in the treatment of colon cancer. We evaluated the age-related disparities in the receipt of curative-intent surgical and medical treatment of colon cancer, and their changes over time. METHODS: This was a population-based cohort study of adult patients diagnosed with colon adenocarcinoma between 2010 and 2018 in Alberta, Canada. Surgery receipt was assessed in patients with stage I-III disease, while systemic therapy receipt was assessed in stage III to IV disease. Patients were stratified by age at diagnosis (< 70 and ≥ 70 years). Cox proportional hazard models were used to evaluate interactions between age and treatment status, and their associations with cancer-specific survival (CSS). Time trends associated with treatment receipt were identified with multivariable logistic regression. RESULTS: Among the 10,838 patients included, 48% were aged ≥ 70 years. For surgery recipients, 5-year CSS was 0.90 (95% CI, 0.88-0.91) and 0.79 (95% CI, 0.77-0.80) for patients < 70 and patients ≥ 70 years of age respectively. Systemic therapy recipients aged < 70 years had a 5-year CSS of 0.57 (95% CI, 0.55-0.60), while individuals aged ≥ 70 years had a 5-year CSS of 0.51 (95% CI, 0.49-0.55). The association between treatment receipt and CSS was independent of age for both treatment modalities (P = .17). Treatment receipt trends remained consistent between 2010 and 2018. CONCLUSION: Despite evolving practice guidelines and non-age-dependent survival benefits, disparities persist in the receipt of treatment for older adults with colon adenocarcinoma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".