[Prognostic role of human epidermal growth factor receptor 2 in resectable gastric cancer: a meta-analysis].
Bibliographic record
Abstract
OBJECTIVE: To investigate the prognostic association of human epidermal growth factor receptor 2 (HER-2) with resectable gastric cancer. METHODS: The literature databases, such as PubMed, EMBASE, Cochrane Library, Web of Science, CBM,CNKI, and Wanfang database, were extensively searched to retrieve the clinical studies of HER-2 expression in resectable gastric cancer published before July, 2013. The association of HER-2 expression with overall survival(OS) was examined. The state 12.0 version software was used for meta-analysis. The quality of these studies were assessed using the Newcasthe-Ottawa scale. RESULTS: There were nine studies meeting the inclusion criteria for meta-analysis including 4787 cases and the scores of all studies are more than 6 points. Meta-analysis showed no significant heterogeneity (I(2)=10.6%, P=0.347) among these studies. There was no significant difference in overall survival between positive HER-2 and negative HER-2 patients (HR=1.16, 95% CI:0.97-1.38, P=0.114). CONCLUSION: HER-2 overexpression in the tumor is not identified as a significant prognostic factor in patients with resectable gastric cancer.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.049 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".