The influence of adjuvant chemotherapy dose intensity on overall survival in resected colon cancer: A multicenter retrospective analysis.
Bibliographic record
Abstract
248 Background: Colorectal cancer remains the second leading cause of cancer death in developed countries. The benefit of using fluorouracil-based chemotherapy with oxaliplatin, such as FOLFOX (fluorouracil (5-FU), leucovorin, oxaliplatin) and CAPOX (capecitabine and oxaliplatin) is well established. The optimal dose intensity (DI) under which overall survival (OS) is inferior is not established. Methods: Patients (pts) treated with adjuvant chemotherapy between 2006 and 2011 for resected stage III colon cancer (CC) from four academic cancer centres in Canada were retrospectively analysed. Patients that received CAPOX and FOLFOX were examined for the relationship between DI and OS. Results: A total of 625 pts with resected high risk stage II or stage III CC that received adjuvant chemotherapy were analysed. The median age was 63. Pts with T4 and N2 disease comprised 35.4% and 29.9% of pts, respectively. Median follow-up was 3.2 years. There was available survival data for 319 pts. The median oxaliplatin DI was 70%. The frequency of pts reaching an oxaliplatin DI of > 80% was 43%, while 76.6% of pts had a dose intensity of > 80% for their FU component. An oxaliplatin DI of > 80% was associated with a significant improvement in survival, HR = 0.42 (95%CI 0.21 – 0.81, p < 0.01). Achieving a DI of > 80% for capecitabine or 5-FU did not improve OS. Other factors associated with inferior OS included T4 (HR = 3.5, p = 0.03) and N2 (HR = 5.27, p = 0.0005) subgroups. The improvement in OS was not significant when restricting the analysis to pts with non-T4 and non-N2 disease (n = 144), HR = 0.16 (0.02 – 1.26; p = 0.08). Conclusions: Oxaliplatin DI of > 80% is associated with improved OS in patients receiving chemotherapy for high risk stage II and stage III CC.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".