Reasons for and outcomes of adjuvant chemotherapy choices in elderly patients with resected stage III colon cancer.
Bibliographic record
Abstract
571 Background: Research suggests that elderly cancer patients are commonly undertreated, but the precise reasons for this are unclear. Robust clinical data on the optimal adjuvant chemotherapy regimen for elderly colon cancer patients are also lacking. Our aims were to: 1) evaluate the impact of advanced age on choice of adjuvant chemotherapy (none vs. capecitabine vs. FOLFOX) for curatively resected colon cancer; b) determine the reasons for selecting a particular regimen; and 3) examine whether treatment effect on outcomes is modified by age. Methods: All patients diagnosed with stage III colon cancer between 2006 and 2008, and referred to any 1 of 5 regional cancer centers in British Columbia, Canada were identified. Descriptive statistics were used to summarize treatment patterns among young patients (YPs) aged <70 years vs. elderly patients (EPs) aged >/=70 years. Multivariate logistic regression models were constructed to evaluate the association between adjuvant chemotherapy and cancer-specific survival (CSS) in YPs and EPs. Results: In total, 810 patients were identified: 51% were male, 52% YPs and 48% EPs, and 74% received adjuvant chemotherapy. When compared to YPs, EPs had worse ECOG and more comorbidities (both p<0.001). EPs were less likely than YPs to receive adjuvant chemotherapy (57% vs. 91%, p<0.001). Frequent reasons for no treatment included age, comorbidities, and small perceived benefit from adjuvant therapy. Among treated pts, EPs were less likely to receive FOLFOX (32% vs. 74%, p<0.0001) in favor of capecitabine due to patient preference, age, and comorbidities. In multivariate analyses, receipt of either FOLFOX or capecitabine was correlated with improved CSS compared to surgery alone. The effect of adjuvant chemotherapy on CSS was not modified by age (interaction p for capecitabine and age = 0.26; interaction p for FOLFOX and age = 0.40). Conclusions: EPs with stage III colon cancer frequently received either no adjuvant treatment or capecitabine monotherapy due to advanced age and co-morbidities. The treatment effect of adjuvant therapy on CSS is similar among EPs and YPs. Adjuvant chemotherapy should not be withheld from colon cancer patients based on advanced age alone.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".