471. PERIOPERATIVE AVELUMAB WITH DCF IN LOCALLY ADVANCED ESOPHAGO-GASTRIC ADENOCARCINOMA: LONG-TERM, PROPENSITY MATCHED SURVIVAL OUTCOMES
Bibliographic record
Abstract
Abstract Background The efficacy of perioperative immunotherapy in the treatment of esophago-gastric adenocarcinoma remains elusive with many single arm studies supplementing pathological response in lieu of long-term survival outcomes. This study aimed to present propensity matched 5-year overall survival (OS) data for patients with locally advanced esophageal adenocarcinoma treated with perioperative DCF with or without avelumab (aDCF). Methods We performed an ad hoc analysis on data from a recently published phase II, single arm, clinical trial which included patients with clinically staged II to IIIB esophago-gastric adenocarcinoma treated with aDCF followed by en bloc transthoracic resection. Using 1:1 propensity scoring based on pretreatment clinical staging, the trial cohort was matched to historical recipients of perioperative DCF identified from a prospectively maintained database of a regional upper gastrointestinal cancer network in Quebec, Canada. The incidence of pathological complete response (pCR) and long-term OS results were compared between the groups. Results Accrual was completed in 08/2022, with 51 patients enrolled in the aDCF trial of which one subsequently withdrew consent. After propensity score matching, 50/177 historical DCF patients were identified. The trial and control groups were similar in gender, age, tumour location, poorly differentiated lesions and clinical stage (cN+ 31/50 vs 29/50). Whilst pathological nodal positivity and nodal downstaging were similar, a non-significant trend towards increased pCR was noted in the aDCF arm (7/50,14% vs 4/50,8%, p = NS). OS at 3 and 5 years was 35/47(74%) and 17/27(63%) vs 25/37(68%) and 16/26(62%) respectively. Conclusion Whilst the addition of avelumab to DCF improved the incidence of pCR, this did not significantly affect other aspects of pathological response or OS. We suggest these results should prevent using pathological sequalae as a proxy for all important survival outcomes.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".