Role of Frizzled receptor expression on patients' survival with gastrointestinal cancers: A systematic review with meta-analysis.
Bibliographic record
Abstract
BACKGROUND: Frizzled receptors (FZD) play a pivotal role in the initiation and progression of a wide array of cancers. Dysregulated expression of FZD receptors is correlated with higher metastasis and invasive potential, as well as short survival in many malignancies. In this meta-analysis, we aimed to verify the prognostic value of FZD receptor expression on patients' survival with different types of gastrointestinal (GI) cancers, including gastric, colorectal, and esophageal cancers. METHODS: A systematic search was performed using PubMed, Scopus, and Web of Science from 2000 to November 2020. Fourteen studies, including 2997 patients met our inclusion criteria, in which nine articles were considered FZD7 while the rest were about other FZD members. The fixed-effect model was used to estimate the pooled hazard ratio (HR) and the 5-year overall survival (OS) rate. We used the Newcastle-Ottawa scale of cohort articles to determine the quality of included studies. RESULTS: The results showed that high expression of FZD receptors is associated with the poor survival in patients with GI cancers (HR= 1.83, 95% CI: 1.5-2.17). Moreover, multivariate analysis indicated that FZD receptors could be considered as an independent prognostic factor (HR = 1.76, 95% CI: 1.37-2.16). CONCLUSION: According to our results, overexpression of FZD receptors predicts a poor prognosis in patients with GI cancers and could be used as a useful therapeutic target.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.035 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".