Population based assessment of HER-2 and PD-L1 positivity in gastric and gastroesophageal junction adenocarcinomas in a Canadian population.
Bibliographic record
Abstract
e16038 Background: Current standard of care for advanced gastric and gastroesophageal cancers combines systemic chemotherapy with either human epidermal growth factor receptor 2 (HER-2) or programmed death ligand 1 (PD-L1) targeting therapy. New data is emerging that for patients whose tumours are positive for both HER-2 overexpression and have a PD-L1 combined positive score (CPS) >1%, combining all three treatment modalities results in superior outcomes. There is limited international data, and no Canadian data, exploring the frequency of patients who have tumours that are both HER-2 and PD-L1 positive who will be eligible for this novel treatment approach. Objective: To determine the proportion of patients in Nova Scotia with HER-2 positive gastric and GEJ adenocarcinomas who have a PD-L1 CPS score above established clinical thresholds. Methods: A retrospective review of PD-L1 and HER-2 status for all patients diagnosed with gastric and GEJ adenocarcinomas in Nova Scotia between June 3, 2022 and August 13, 2023 was completed. PD-L1 CPS was evaluated using the 28-8 assay and was considered positive if >1%. HER-2 overexpression was evaluated by immunohistochemistry and in cases with equivocal expression, status was based on fluorescence in situ hybridization. Results: Over the study period, 56 cases of gastric and 42 cases of GEJ adenocarcinoma were identified for a total of 98 cases. The median age of the study population was 73 years (range 38 - 91). 73 patients (74%) were male and 25 patients (26%) were female. HER-2 expression was evaluated in 92 cases, and PD-L1 CPS was evaluated in 95 cases. 19 cases (21%) were HER-2 positive and 86 cases (91%) were PD-L1 positive. 17 HER-2 positive cases were also PD-L1 positive (89%). Conclusions: This study provides population level data in a Canadian context on patients with gastric and GEJ adenocarcinoma with respect to HER-2 overexpression and PD-L1 status. This data will be helpful in planning allocation of clinical and financial resources as a new standard of care for these patients is established.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".