A comparison between 5-fluorouracil/mitomycin and capecitabine/mitomycin in combination with radiation for anal cancer
Bibliographic record
Abstract
BACKGROUND: There are no randomized phase III trials comparing 5-fluorouracil/mitomycin (FM) versus capecitabine/mitomycin (CM) in combination with radiotherapy (RT) for locally advanced anal cancer. We aim to evaluate the outcomes of patients treated with FM and CM at our institution. METHODS: Patients with stage I-III anal cancer who initiated curative-intent RT (50-54 Gy) with either CM or FM between 1998 and 2013 at the BC Cancer Agency were reviewed. Cox proportional models were used to analyze the impact of regimen on disease-free survival (DFS) and anal cancer-specific survival (ACSS). RESULTS: A total of 300 patients were included. Baseline characteristics were well-distributed between the groups. A total of 194 patients (64.6%) received FM and 106 (35.3%) CM. The 2-year DFS was 79.7% for CM [95% confidence intervals (95% CI), 71.1-88.3%] and 78.8% for FM (95% CI, 73-84.6%); 2-year ACSS was 88.7% for CM (95% CI, 81.8-95.5%) and 87.5% for FM (95% CI, 82.8-92.2%). On multivariate analysis, only HIV status, clinical T size (≤5 vs. >5 cm), and N status (negative vs. positive) remained as significant prognostic factors for both DFS and ACSS. Chemotherapy regimen (CM vs. FM) had no impact on either DFS [P=0.995; hazard ratios (HR) =0.99; 95% CI, 0.57-1.74] or ACSS (P=0.847; HR =0.93; 95% CI, 0.46-1.86). CONCLUSIONS: In our population-based study, CM and FM concomitant with RT achieved similar DFS and ACSS. Substitution of capecitabine for infusional 5-FU may therefore be a reasonable option for patients and physicians who prefer to avoid the inconvenience and potential complications of a central infusional device.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".