MiR-193b as an effective biomarker in human cancer prognosis for Asian patients: a meta-analysis
Bibliographic record
Abstract
Background: MiR-193b has been widely investigated in the last few years and an aberrant association has been observed between its expression levels and the prognosis of several human malignancies. We performed a meta-analysis to evaluate the prognostic effect of miR-193b on human cancers. Methods: PMC, PubMed, Web of Science (WOS), Embase in English and VIP, Wanfang, SinoMed and the China National Knowledge Infrastructure (CNKI) in Chinese were searched up to May 16, 2020. The pooled hazard ratio (HR) with a 95% confidence interval (CI) was calculated to evaluate its prognosis in human cancers. Also, the pooled odd ratios and the relevant 95% CIs were computed to assess the association of miR-193b levels and clinicopathological characteristics of cancer patients. Results: In overall analysis, a significant association was identified between miR-193b levels and overall survival (HR =0.77, 95% CI: 0.64-0.92), but this association was not significant in the random pooling model. Then, two outliers were identified through sensitivity analysis. After removing outliers, the significant association was identified with random pooling model (HR =0.45, 95% CI: 0.30-0.69). In addition, the significance exited among Asian (HR =0.45, 95% CI: 0.28-0.74), studies with the sample size (≥100) (HR =0.39, 95% CI: 0.27-0.56) and sample size (<100) (HR =0.51, 95% CI: 0.28-0.92), Newcastle-Ottawa scale (NOS) scores (≥8) (HR =0.44, 95% CI: 0.30-0.67) and NOS scores (<8) (HR =0.45, 95% CI: 0.25-0.80) and patients of non-digestive carcinoma (HR =0.35, 95% CI: 0.24-0.52), digestive carcinoma (HR =0.54, 95% CI: 0.31-0.92), non-urogenital carcinoma (HR =0.52, 95% CI: 0.33-0.82) or urogenital carcinoma (HR =0.28, 95% CI: 0.16-0.50). Lower expression of miR-193b was found to be related to larger tumor size and the potential of lymph node metastasis and distance metastasis. Discussion: We have demonstrated that miR-193b serves as an ideal biomarker in the cancer prognosis for Asian patients, and the low expression levels of miR-193b is significantly associated with poor overall survival rates in various human malignancies. Moreover, the patients with lower miR-193b tend to develop the cancers with higher potential of metastasis.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.045 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".