Trends and disparities in the treatment of older adults with colon cancer.
Bibliographic record
Abstract
e18776 Background: Adults aged ≥70 years represent approximately half of all patients diagnosed with colon cancer (CC), but undertreatment in this population persists. Recent guidelines have aimed to reduce age-related biases in the treatment of CC and emphasized the importance of personalizing management with comprehensive geriatric assessments (CGAs). Therefore, we hypothesized that age-related disparities in the curative-intent treatment of CC would improve over time. Methods: This was a retrospective, population-based cohort study of adults diagnosed with CC between 2010 and 2018 in Alberta, Canada. The study data included patient demographics and clinical characteristics collected through the Alberta Cancer Registry and electronic medical records. Patients were stratified by age: < 70 and ≥70 years. Cox proportional hazard models (CPHM) were generated to evaluate the associations and interaction between age groups and treatment status on disease-specific survival (DSS), after adjusting for important covariates. Multivariable logistic regression was used to identify time trends and predictors of treatment receipt. Results: A total of 10,838 patients were included, of whom 5,176 (48%) were aged ≥70 years and 2,468 (23%) had stage IV CC at initial diagnosis. Older age was associated with greater comorbidity and less advanced disease ( p < 0.001, standardized mean difference > 0.1 for both). The vast majority (87%) of patients in the overall cohort received surgery while 34% received systemic therapy. In multivariable CPHM, older age was associated with lower DSS (HR 1.42, 95%CI 1.31-1.54, p < 0.001) while surgery and systemic therapy were each associated with higher DSS (HR 0.30, 95%CI 0.27-0.33, p < 0.001; HR 0.40, 95%CI 0.37-0.43, p < 0.001; respectively). However, the interaction between age and treatment status was not statistically significant ( p = 0.78 for surgery; p = 0.17 for systemic therapy). Compared to the younger age group, the odds of receiving surgery and systemic therapy were 3 and 5 times lower, respectively, among older patients (OR 0.27, 95%CI 0.18-0.40, p < 0.001; OR 0.18, 95%CI 0.16-0.20, p < 0.001; respectively). In addition to younger age, predictors of surgery receipt included less comorbidity and stage II/III vs I disease, whereas predictors of systemic therapy receipt included male sex, southern residence, higher neighbourhood income, less comorbidity, and stage III vs IV disease ( p < 0.05 for all). There were no statistically significant correlations between year of diagnosis and treatment receipt ( ptrend = 0.07 for surgery; ptrend = 0.26 for systemic therapy). Conclusions: Surgery and systemic therapy continue to improve CC outcomes regardless of age. However, rates of curative-intent treatment for CC were consistently lower in patients aged ≥70 years, with minimal changes over time. Better integration of CGAs into routine care may be needed to reduce persistent age-related treatment disparities.
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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 | 0.002 |
| 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) | 0.002 | 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".