Comparison of long-term outcomes for neoadjuvant chemoradiation (NA-CRT) followed by surgery versus (V) definitive chemoradiation (D-CRT) in localized gastroesophageal cancer (GEC): A single-center analysis.
Bibliographic record
Abstract
371 Background: The therapeutic approach in locally advanced GEC is evolving. NA-CRT followed by surgery has been recommended based on the CROSS trial. The SANO trial reports active surveillance may be an alternative in clinically complete response after D-CRT in both squamous cell carcinoma (SCC) and adenocarcinoma (AC). SCC and AC in GEC are different diseases with differences in tumor location, etiology, and biology. Despite the evolving landscape, there still may be a role for both CROSS and SANO approaches. In our large observational cohort study, we sought to compare the long-term outcomes in localized GEC across all histological subtypes treated with NA-CRT+Surgery V D-CR+Surveillance. Methods: A retrospective analysis comparing NA-CRT + surgery V D-CRT in localized GEC between 2007-2023 treated at the Princess Margaret Cancer Centre was completed. Baseline characteristics including age, gender, race, performance status and Charlson Comorbidity index (CCI) were reviewed. The primary and secondary endpoints were overall survival (OS) and disease-free survival (DFS), respectively and to compare these outcomes in both histologies. Cox proportional hazards analysis and Kaplan-Meier methods were employed. Outcomes were adjusted for baseline characteristics. Results: There were 529 patients (pts) included, 321 (61%) received NA-CRT+Surgery and 208 (39%) D-CR+Surveillance. Median age was 64yrs, 75% were male and 66% had N1+ disease. The proportion of pts with SCC treated with NA-CRT+Surgery and D-CR+Surveillance was 25% and 63%, respectively. There was a statistically significant difference in median OS and DFS between pts who received NA-CRT+surgery and D-CRT+surveillance (Table). Multivariate regression analysis shows a significant association between OS and age (adjusted HR 1.02, p=0.005), male sex (HR 1.55, p=0.003) but no significant association between OS and CCI (HR 1.1 p=0.36). In our subgroup analyses, there was no statistically significant difference in OS (p=0.33) and DFS (p=0.18) between SCC and AC. However, this was significant in D-CRT (OS p<0.0001, DFS p<0.001) favoring SCC. Conclusions: In contrast to the SANO trial, we found that NA-CRT+surgery was associated with a significantly better OS and DFS compared to D-CRT when subtypes were combined. However, in the D-CRT subgroup, SCC was associated with improved OS and DFS compared to AC. Thus, we continue to recommend current approaches in SCC. Awaited updates from SANO will inform whether active surveillance may also be appropriate in pts with AC subtype. Median (95% CI)NA-CRT Surgery Median (95% CI)D-CRT Log-rank test p-value OS (mo) 28.2 (15.1, 57.6) 15.6 (7.7, 33.7) P=<0.0001 DFS (mo) 17.9 (9.6, 40.8) 9.4 (5.0, 20.7) P=<0.0001 pathCR (%) 14 - R0 resection (%) 89 -
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".