The Prognostic Value of Cancer Stem Cell Markers in Cervical Cancer: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Prognostic biomarkers in cervical cancer are widely investigated, including cancer stem cell (CSC) markers. However, their significance remains uncertain. This study aimed to determine the role of cervical cancer stem cell (CCSC) markers for survival. MATERIALS AND METHODS: We conducted a systematic review and meta-analysis (PROSPERO CRD42021237072) of studies reporting CCSC markers as the prognostic predictor based on PRISMA guidelines. We included English articles investigating associations of CCSCs expression in tissue tumor with overall survival (OS) or disease-free survival (DFS) from PubMed, EBSCO, and The Cochrane Library databases. The quality of studies was analyzed based on Newcastle-Ottawa Quality Assessment Scale. RESULTS: From 413 publications, after study selection with inclusion and exclusion criteria, 22 studies were included. High expressions of CCSC markers were associated with poor OS and DFS (HR= 1.05, 95% CI: 1.03 - 1.07, P <0.0001; HR= 1.31, 95% CI: 1.09 - 1.17, P <0.00001; respectively). Sub-analysis of individual CCSC markers indicated significant correlations between CD44 (HR= 1.14, 95% CI: 1.07 - 1.22, P 0.0001), SOX2 (HR= 1.58, 95% CI: 1.17 - 2.14, P 0.003), OCT4 (HR= 1.03, 95% CI: 1.01 - 1.06, P 0.008), ALDH1 (HR= 1.36, 95% CI: 1.13 - 1.64, P 0.001), and CD49f (HR= 3.02, 95% CI: 1.37 - 6.64, P 0.006) with worse OS; OCT4 (HR= 1.14, 95% CI 1.06 - 1.22, P 0.0003), SOX2 (HR= 1.11, 95% CI: 1.06 - 1.16, P <0.0001), and ALDH1 (HR= 1.22, 95% CI: 1.10 - 1.35, P 0.0002) with poor DFS. We did not conduct a meta-analysis for MSI-1 and CK17 because only one study investigated those markers. CONCLUSION: Expressions of OCT4, SOX2, and ALDH1 were associated with poor OS and DFS in cervical cancer tissue. These markers might have potential roles as prognostic biomarkers to predict unfavorable survival.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it