Adjuvant Treatment in Older Patients with Rectal Cancer: A Population-Based Review
Bibliographic record
Abstract
Background Little is known about the benefits of adjuvant chemotherapy (adj) in the older population with locally advanced rectal cancer (larc). We evaluated use of adj, survival outcomes, and adj-related toxicity in older patients with larc. Methods Our retrospective review included 286 patients with larc (stages ii and iii) diagnosed between January 2010 and December 2013 in Nova Scotia who underwent curative-intent surgery. Baseline patient, tumour, and treatment characteristics were collected. The survival analysis used the Kaplan–Meier method and Cox regression statistics. Results Of 286 identified patients, 152 were 65 years of age or older, and 92 were 70 years of age or older. Median follow-up was 46 months, and 163 patients (57%) received neoadjuvant chemoradiation. Although adj was given to 81% of patients (n = 109) less than 65 years of age, only 29% patients (n = 27) 70 years of age and older received adj. Kaplan–Meier analysis suggested a potential survival advantage for adj regardless of age. In multivariate Cox regression analysis, Eastern Cooperative Oncology Group performance status, T stage, and adj were significant predictors of overall survival (p < 0.04); age was not. Similarly, N stage, neoadjuvant chemoradiation, and adj were significant predictors of disease-free survival (p < 0.01). Poor Eastern Cooperative Oncology Group performance status was the most common cause of adj omission. In patients 70 years of age and older, grade 1 or greater chemotherapy-related toxicities were experienced significantly more often by those treated with adj (85% vs. 68% for those not treated with adj, p < 0.05). Conclusions Regardless of age, patients with larc seem to experience a survival benefit with adj. However, older patients are less likely to receive adj, and when they do, they experience more chemotherapy-related toxicities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".