470. INTENSIVE EARLY SURVEILLANCE FOLLOWING ESOPHAGECTOMY IDENTIFIES DISTINCT PATTERNS OF RECURRENCE
Bibliographic record
Abstract
Abstract Background There remains a lack of consensus about the protocol for follow-up following esophagectomy. Some centers will utilize a purely radiological approach to follow-up, while others will include routine endoscopy and blood markers. Furthermore, the frequency of follow-up is debated, though many centers will follow-up every 3 months due to the high recurrence rate in the first year. We follow patients every 3 months for the first year, every 6 months for the next year, then yearly to 5 years, solely with CT scans unless symptoms indicate endoscopy. We sought to examine our recurrence rate and survival using this follow-up protocol. Methods We reviewed our prospectively collected database for recurrence following esophagectomy in patients operated from March 2018 to May 2022. Consenting patients >18 years of age who underwent esophagectomy were included. Demographics including age, sex, and BMI, tumor factors including pathologic stage, tumor regression grade, and neoadjuvant therapy and post-recurrence treatment data were collected. Results We identified 190 patients who underwent esophagectomy and 69 patients had a recurrence. Patients with recurrence were younger (61.3 +/- 10.2 vs 66.4 +/- 10.1, p=0.001), were more likely pT3 (59.4% vs 36.4%, p=0.013) and have a tumor regression grade of 3 (27.5% vs 7.4%, p=0.002). There was no difference between patients with R1 resections vs R0 (5.8% vs 6.6%, p=0.824). Most recurrences were identified on CT scan (95.8%). For patients who recurred within 3 months, the mean time from operation to death was 9.11 months. Patients who recurred between 3-6mo, 6-9mo, and 9-12mo died at 17.1mo, 15.7mo, and 17.5mo following surgery, respectively. Patients who recurred in the next year died around 40 months from surgery. Conclusion As with other reports in the literature, recurrence is highest in the first year after esophagectomy. Patients recurring in the first 3 months had a short survival following esophagectomy and may represent missed micrometastatic disease at staging. Interestingly, patients who recurred between 3-12 months all had a similar time to death from the date of operation, suggesting lead-time bias for those detected at 3-6months. Early and later recurrence appear to have distinct biological behaviours. With improved and tailored adjuvant therapies, earlier detection may yet be beneficial and will require further study.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".