Delivery of Adjuvant Oxaliplatin for Colon Cancer: Insights From Routine Clinical Practice
Bibliographic record
Abstract
BACKGROUND: Adjuvant oxaliplatin is now a standard treatment option for patients with early-stage colon cancer. However, treatment delivery and outcomes achieved in routine practice are not well described. METHODS: All cases of colon cancer diagnosed in Ontario from 2002 to 2008 were identified using the Ontario Cancer Registry. Pathology reports were obtained for a 25% random sample to identify stage II and III cases; patients treated with adjuvant oxaliplatin were included in this analysis. Treatment records were reviewed to identify oxaliplatin dose reductions or omissions. Modified Poisson regression was used to evaluate factors associated with dose reduction/omission. Cox proportional hazards model was used to explore factors associated with cancer-specific survival (CSS) and overall survival (OS). RESULTS: The study population included 532 patients; 88% (469/532) had stage III disease. The mean/median number of oxaliplatin cycles delivered was 10/12. A dose reduction/omission of oxaliplatin occurred in 54% of cases (288/532), and the dose was subsequently escalated in 34% of these (97/288). Women were more likely than men to have dose reduction/omission (relative risk, 1.29; 95% CI, 1.10-1.51). Dose reduction/omission was not associated with inferior CSS (hazard ratio [HR], 0.76; 95% CI, 0.51-1.14) or OS (HR, 0.81; 95% CI, 0.59-1.13). Five-year CSS and OS of all cases were 77% (95% CI, 72-81) and 72% (95% CI, 68-76), respectively. On-treatment mortality rates were 1% and 3% within 30 and 90 days of oxaliplatin, respectively. CONCLUSIONS: Dose reductions of adjuvant oxaliplatin are common in routine practice but are not associated with inferior survival. Long-term survival achieved in the general population is comparable to the results of clinical trials.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".