Impact of adjuvant therapy in patients with a microscopically positive margin after resection for gastroesophageal cancer.
Bibliographic record
Abstract
4069 Background: A microscopically positive (R1) resection margin following resection for gastroesophageal (GE) cancer has been documented to be a poor prognostic factor. The optimal strategy and impact of different modalities of adjuvant treatment for an R1 resection margin remain unclear. Methods: A retrospective analysis was performed for patients (pts) with GE cancer treated at the Princess Margaret Cancer Centre from 2006-2016. Electronic medical records of all pts with an R1 resection margin were reviewed. Kaplan-Meier and Cox proportional hazards methods were used to analyze recurrence free survival (RFS) and overall survival (OS) with stage and neoadjuvant treatment as covariates in the multivariate analysis. Results: We identified 78 GE cancer pts with an R1 resection. 11% had neoadjuvant chemotherapy, 14% chemoradiation (CRT), 75% surgery alone. 28% had involvement of the proximal margin, 13% distal, 56% radial, 3% had multiple positive margins. By the American Joint Committee on Cancer 7th edition classification, 88% had a pT3-4 tumour, 66% pN2-3 nodal involvement, 64% grade 3, 68% with lymphovascular invasion. 3% were pathological stage I, 21% stage II and 74% stage III. Adjuvant therapy was given in 46% of R1 pts (24% CRT, 18% chemotherapy alone, 3% radiation alone, 1% reoperation). Median RFS for all pts was 12.6 months (95% CI 10.3-17.2). Site of first recurrence was 71% distant, 16% locoregional, 13% mixed. Median OS was 29.3 months (95% CI 22.9-50) for all pts. The 5 year survival rate was 23% (95% CI 12%-43%). There was no significant difference in RFS (log-rank test p = 0.63, adjusted p = 0.14) or OS (log-rank test p = 0.68, adjusted p = 0.65) regardless of adjuvant therapy. Conclusions: Most pts with positive margins after resection for GE cancer had advanced pathologic stage and prognosis was poor. Our study did not find improved RFS or OS with adjuvant treatment and only one pt had reresection. The main failure pattern was distant recurrence, suggesting that pts being considered for adjuvant RT should be carefully selected. Further studies are required to determine factors to select pts with good prognosis despite a positive margin, or those who may benefit from adjuvant treatment.
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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 | 0.001 |
| 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".