Correlation between RASSF1A Methylation in Cell-Free DNA and the Prognosis of Cancer Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background. Although the effects of methylation of the Ras association domain-containing protein 1 isoform A (RASSF1A) gene in cell-free DNA on the outcomes of patients with different types of cancer have been reported, the results are inconsistent. Objective: To explore the relationships between RASSF1A methylation in cell-free DNA and the outcomes of cancer patients. Methods. The PubMed, Embase, and Web of Science databases were searched for papers related to this topic on December 8, 2021. The retrieved articles were screened by two independent researchers, following which the methodological quality of the selected studies was evaluated using the Newcastle-Ottawa Scale. Additionally, hazard ratios were calculated, and publication bias of the studies was determined using Egger’s test. Results. Nine relevant publications involving a combined total of 1254 patients with different types of cancer were included in this study. The combined results of the random effects models yielded a hazard ratio of 1.73 (95% confidence interval: 1.31, 2.29; P < 0.001 ), which suggested there was a significant association between RASSF1A methylation and overall survival, and patients with an RASSF1A methylation status had a significantly increased risk of total death. Moreover, the Egger test result suggested there was no significant publication bias among the included studies. Conclusions. The methylation of RASSF1A in cell-free DNA in cancer patients was observably associated with an increased risk of poor overall survival.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.007 | 0.011 |
| 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) | 0.002 | 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".