Predictors of adjuvant chemotherapy (AT) decision-making in referred patients (pts) with stage II and III colon cancer (CC)
Bibliographic record
Abstract
e15070 Background: Randomized clinical trials have demonstrated a robust survival benefit of AT for node positive (stage III) CC patients; similar evidence for node-negative (stage II) patients is lacking. While guidelines recommend AT for stage III colon cancer but AT is not a routine recommendation for stage II. Actual practice of the evidence varies and suggests the interplay of additional variables. We sought to identify factors associated with practice patterns which vary from conventional AT guidelines, ie no AT in stage III CC and receipt of AT in.stage II CC. Methods: Data pertaining to pt demographics, tumor characteristics, and treatment for pts with resected stage II (n=176) and III CC (n=235) referred to the British Columbia Cancer Agency in 2004 was collected by retrospective chart review. One-sided Fisher's exact test was used to assess statistical significance (p<0.05) by univariate analysis. Results: 28% (n=49) of stage II pts received AT. Compared to untreated pts, stage II pts who received AT were significantly more often younger than 66 years (57% vs 21%), lived in a city with a regional cancer center (71% vs 51%), had T4 disease (33% vs 9%), vascular invasion (22% vs 5%), perineural invasion (10% vs 2%) and high grade (26% vs 2%). Marital status, ethnicity, lymphatic invasion and high CEA were not associated with AT in stage II. 29% (n=69) of stage III pts did not receive AT. Compared to treated pts, stage III pts who did not receive AT were significantly more often older than 65 years (91% vs 51%), had low grade disease (96% vs 84%) and presented for oncology consultation greater than 42 days from surgery (29% vs 11%). Marital status, ethnicity, residence, T4 status or N2 status were not associated with no AT in stage III. Conclusions: For pts with stage II CC, subgroups associated with high risk for relapse were more likely to receive AT although the majority of stage II pts in this cohort remained untreated. For stage III disease, almost one-third of referred pts did not receive AT. Older age and delayed presentation were strongly associated with failure to receive AT. Within the limitations of a retrospective review, these data highlight the significant and commonly observed implications of factors other than stage in AT decision-making for high risk resected CC. No significant financial relationships to disclose.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".