Surveillance for asymptomatic recurrence in resected stage III colon cancer (CC): Does it result in a more favorable outcome?
Bibliographic record
Abstract
3612 Background: Evidence supports a modest survival benefit for intensive post-treatment surveillance following potentially curative resection of CC. However, no studies so far included only patients with stage III CC, who have the highest risk of recurrence. Methods: Medical records of patients who initiated adjuvant chemotherapy (AC) with either 5-FU or capecitabine plus oxaliplatin for stage III CC between 2007 and 2011 at the BC Cancer Agency were reviewed. Kaplan-Meier and log rank test were generated to investigate whether diagnosis of recurrence based on symptoms was associated with worse OS. OS1 was considered from date of recurrence to date of death or last FU. OS2 was considered time from surgery (sg) to date of death or last follow-up (FU). Results: Of635 pts who received oxaliplatin-based AC for stage III colon cancer, 176 patients (27.7%) have recurred and 118 (18.6%) have died at a median FU of 57.9 months. Recurrence was detected based on CEA elevation (G1) in 72 (41.1%) pts, abnormal imaging (G1) in 77 (44%) and symptoms (G2) in 26 (14.9%). Median time from sg to recurrence was shorter in G1 as compared to G2 (18.5 vs 25.7 months, p=0.003, HR 0.501). Median OS1 was significantly prolonged in G1 as compared to G2 (26.7 vs 6.5 months, p<0.001, HR 0.393). However, median OS2 was not statistically different between G1 and G2 (49.8 vs 40.1, p=0.327, HR 0.776). Patients with surveillance detected recurrence underwent significantly more potentially curative metastasectomy than patients with recurrence detected due to symptoms (33% vs 8%, p= 0.014). Conclusions: In our population-based study, patients who were symptomatic at the time of recurrence were diagnosed later than those detected by abnormal CEA or imaging and had shorter OS1. However, OS2 was similar in both groups adjusting for the effect of lead time bias. Surveillance for asymptomatic recurrence may still provide an opportunity for curative metastasectomy but the overall survival impact is unclear.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".