Relationship between human epidermal growth factor receptor 2 (HER2) status and central nervous system metastases in gastroesophageal cancer.
Bibliographic record
Abstract
145 Background: Central nervous system (CNS) metastases (mets) in gastroesophageal (GE) cancers are rare. There have only been limited studies examining the role of HER2 status in CNS mets in GE cancers. Methods: A retrospective analysis was performed for patients (pts) treated for GE cancers at the Princess Margaret Cancer Centre from 2011-2016. Quantitative and qualitative data were collected for all pts with CNS mets. Kaplan-Meier method was used to calculate overall survival (OS) and CNS progression free survival (PFS) for CNS mets pts. Results: Of 34 GE cancer pts diagnosed with CNS mets, 11 were HER2+, 11 HER2- and 12 had unknown HER2 status. Median time from initial cancer diagnosis to CNS mets was 10.3 months (13.4 in HER2+, 5.8 in HER2-, 11.7 in HER2 unknown). Characteristics at CNS mets diagnosis included: median age 63; 85% male; 74% had extracranial systemic mets; performance status ECOG 0-1 (64%), 2 (12%), 3-4 (24%). Treatment for CNS mets is shown in Table 1. Median OS from diagnosis of CNS mets was 6.1 months (95%CI 3.2-16.4) for all pts, 17.1 (95%CI 9.9-NA) in HER2+, 1.8 (95%CI 0.6-NA) in HER2-, 6.0 (95%CI 1.9-NA) in HER2 unknown, p=0.01. Median OS from initial cancer diagnosis was 18.5 months (95%CI 13.6-33.7) for all pts, 28.9 (95%CI 21.32-NA) in HER2+, 10.8 (95%CI 6.37-NA) in HER2-, 18.6 (95%CI 10-NA) in HER2 unknown, p=0.015. The 1 year CNS PFS rate was 35% (95%CI 22.1 – 55.5%) for all pts, 53% (95%CI 29.9 – 94%) in HER2+, 18.2% (95%CI 5.3 – 63.7%) in HER2-, 33% (95%CI 15 – 74.2%) in HER2 unknown, p=0.053. Conclusions: HER2+ pts tended to develop CNS mets later than HER2-. HER2+ pts were more likely to receive CNS-directed interventions, with more HER2+ pts having surgery for CNS mets while more HER2- had supportive care. This analysis is the first to suggest that in pts with CNS mets, HER2+ pts had longer survival than HER2-, both from initial diagnosis and after developing CNS metastases.[Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".