Impact of adjuvant treatment in elderly patients with locally advanced rectal cancer: A population-based retrospective study.
Bibliographic record
Abstract
3613 Background: Little is known about the benefit and use of adjuvant chemotherapy (ADJ) in the elderly population (age ≥ 65) with locally advanced rectal cancer (LARC). We undertook a provincial review of LARC patients to evaluate the potential benefits, including survival and time to relapse (TTR), of ADJ in elderly patients. Methods: We performed a retrospective analysis of 286 LARC patients (stage 2 and 3) diagnosed between January 2010 and December 2013 from Nova Scotia, Canada, who underwent curative-intent surgery. Baseline patient, tumor and treatment characteristics were collected. Survival and TTR analysis were performed using Kaplan-Meier and Cox-regression statistics. Results: 152 patients were age ≥65, and 92 age ≥70. Median follow-up was 46 months. 178 patients (62%) received neoadjuvant chemo-radiation (NEOADJ). While 109 patients (81%) age < 65 received ADJ, only 68 patients (45%) age ≥ 65 received ADJ. Kaplan-Meier analysis revealed a significant survival and TTR advantage for ADJ irrespective of age (table). In cox-regression multivariate analysis, ECOG status, T stage, and ADJ were significant predictors of survival (p < 0.04), while age was not. Similarly, N stage, NEOADJ, and ADJ were significant predictors of TTR (p < 0.007). Poor ECOG status was the most common cause of ADJ omission. There was a significantly higher amount of grade≥ 1 chemotherapy-related toxicity experienced by patients age ≥ 65 treated with ADJ compared to no ADJ (77% vs 32%, p < 0.0001), which consisted mostly of diarrhea and mucositis. Toxicity was the main reason for non-completion of ADJ in the elderly. Conclusions: Elderly patients with LARC have significantly improved overall survival with ADJ, but the use of ADJ is lower than in patients age < 65. However, elderly patients experience more chemotherapy-related toxicities, leading to higher rates of early treatment discontinuation. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".