Adjuvant immunotherapy in patients with resected esophageal and gastroesophageal junction cancer: Real-world evidence from Nova Scotia.
Bibliographic record
Abstract
e16047 Background: Post-operative immunotherapy (POI) with nivolumab has become the standard of care for eligible patients with esophageal and gastroesophageal junction cancers (EGEJC) who had pre-operative chemoradiation (POCRT) and definitive surgery. However, not all patients who receive POCRT are eligible for POI. Objective: The primary objective was to determine the proportion of patients who receive POCRT that are eligible for POI in a real-world population. Further, we aimed to identify the specific barriers to POI to determine factors which could be strategically addressed to maximize access to curative intent treatment. Methods: All patients residing in mainland Nova Scotia who received POCRT between July 2016 and April 2019 were analyzed. Disease, patient, and treatment characteristics were collected via chart review. The relative proportion of patients who (1) had definitive surgery, (2) were eligible to receive POI and (3) would have accepted POI were collected. The specific reasons for non-eligibility or refusal of POI were captured. Results: A total of 65 patients received POCRT during the study period. 44 of those went on to have definitive surgery. All 44 of these patients were then screened for eligibility to be enrolled in a trial of POI. 23 were eligible, but 12 declined trial enrolment. 21 were ineligible, with the most common reason being a pathological complete response (n=11). Of the 21 patients who did not undergo surgery, 12 were found to have new metastatic disease on pre-operative restaging and 9 were felt to be too frail. Conclusions: Only 35% of patient receiving POCRT were eligible for POI. This is important real-world data when planning allocation of resources and adapting health care budgets for novel treatments and indications.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".