Meta-analysis of FTO expression on the clinicopathologic characteristics and prognosis of gastric cancer
Bibliographic record
Abstract
BACKGROUND: Fat mass and obesity-related gene (FTO) is aberrantly expressed in various cancers including highly expressed in gastric cancer tissues. The aim of this meta-analysis was to explore the effect of FTO expression on clinicopathological and prognostic outcome of gastric cancer. METHODS: China National Knowledge Infrastructure (CNK), Wanfang database, VIP database, Chinese biomedical literature database (CBM), PubMed, Web of Science, the Cochrane library and EMBASE database were searched to screen the literatures according to the inclusion criteria. The search time was the database establishment until May 2023. The two researchers independently searched and screened the literature, extracted pathological data, and conducted The Newcastle-Ottawa scale (NOS) quality evaluation. Analyze the correlation between FTO and pathological indicators of gastric cancer patients and the impact on prognosis, use and Stata 12.0, software for Meta-analysis. RESULTS: A total of 1619 patients were studied in this study. The results of the Meta-analysis showed that higher expression levels of FTO were associated with TMN stage (OR = 1.83, 95% CI: 1.11-3.03, P = .019), liver metastases (OR = 3.73, 95% CI: 1.49-9.31, P = .005), vascular invasion (OR = 2.22, 95% CI: 1.36-3.61, P = .001), poorer overall survival (OS) (HR = 0.46, 95% CI: 0.34-0.58, P < .001) and recurrence-free survival (HR = 0.56, 95% CI: 0.40-0.73, P < .001) in gastric cancer patients. There was no significant relationship with the degree of differentiation (OR = 1.08, 95% CI: 0.49-2.35, P = .852), age (OR = 0.89, 95% CI: 0.71-1.11, P = .306), and gender (OR = 0.92, 95% CI: 0.74-1.14, P = .432). CONCLUSION: High expression of FTO was associated with risk of distant metastases and poor prognosis for patients with gastric cancer. FTO may be a potential prognostic biomarker for gastric cancer, but due to the limited number of literature, the above results need further research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 teacher head, 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".