Surveillance for asymptomatic recurrence in resected stage III colon cancer: does it result in a more favorable outcome?
Bibliographic record
Abstract
BACKGROUND: Evidence from dated and moderate quality trials supports a modest survival benefit for intensive surveillance in resected colon cancer (CC). This study evaluates surveillance in a modern population-based cohort of stage III CC patients (pts). METHODS: Records of pts who initiated oxaliplatin-based adjuvant chemotherapy (AC) for stage III CC between 2006-2011 at the British Columbia Cancer Agency (BCCA) were reviewed. Kaplan-Meier and log rank test were generated to investigate whether diagnosis of recurrence based on symptoms was associated with worse overall survival (OS). OS1 and OS2 were measured from date of recurrence or date of initial surgery, respectively. RESULTS: Of 635 pts who received AC for stage III CC, 175 pts (27.5%) recurred and 118 (18.6%) died at a median follow-up of 67.7 months. Recurrences were detected by surveillance in 149 pts (41% by CEA elevation and 44% by abnormal imaging), and symptoms in 26 pts (15%). Patients with surveillance-detected recurrences had a shorter median relapse-free survival (RFS) (18.5 vs. 25.3 months, HR 1.82, P<0.001), and longer median OS1 (28.5 vs. 6.5 months, HR 0.37, P<0.001). However, median OS2 was not significantly different (50.9 vs. 39.1 months, HR 0.66, P=0.091). Pts with surveillance-detected recurrence received more potentially curative metastasectomy (39% vs. 7%, P=0.002) and chemotherapy (70% vs. 50%, P=0.03). CONCLUSIONS: In this modern population-based cohort study, the OS impact of detecting asymptomatic recurrences in stage III CC is unclear. However, pts with asymptomatic recurrences were more likely to receive potentially curative metastasectomy and chemotherapy.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".