Serum HER 2 Extracellular Domain Level Is Correlated with Tissue HER 2 Status in Metastatic Gastric or Gastro-Oesophageal Junction Adenocarcinoma
Bibliographic record
Abstract
BACKGROUND: To explore the association between serum human epidermal growth factor receptor 2 (HER 2) extracellular domain (ECD) levels and tissue HER 2 status in metastatic gastric cancer. PATIENTS AND METHODS: HER 2 status was retrospectively analyzed in 219 advanced gastric or gastroesophageal junction (GEJ) patients. Serum HER 2 ECD was measured by chemiluminescent assay and tissue HER 2 was assessed by fluorescent in situ hybridisation (FISH) and immunohistochemistry (IHC) assay. RESULTS: Significant associations were found between serum HER 2 ECD levels and tissue HER 2 status. Twenty-four patients had HER 2 ECD levels >16.35 ng/mL, which has a sensitivity of 51.4% and a specificity of 97.3% to predict tissue HER 2 status. When the cut-off value was increased to 22 ng/mL, then all 12 patients with serum HER 2 ECD levels>22 ng/mL were tissue HER 2 positive, corresponding to a specificity of 100% and a sensitivity of 32.4%. High serum HER 2 ECD levels were strongly associated with the intestinal histological type (Lauren's classification), liver metastasis, multiple metastasis (>2) and increased LDH levels, but not with overall survival. CONCLUSIONS: The high specificity of the serum HER 2 ECD assay in predicting tissue HER 2 status suggests its potential as a surrogate marker of the HER 2 status in gastric cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".