Clinicopathological and Prognostic Roles of the Expression Levels of the Programmed Cell Death-1 Gene in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Multiple studies have explored the prognostic role and clinical significance of the expression of the programmed cell death-1 ( PD-1 ) gene in hepatocellular carcinoma (HCC). However, the results have been inconsistent. This study evaluated PD-1 expression and its clinical significance in patients with HCC, as well as the correlation between HCC pathological features and prognoses. Methods: All related research in PubMed, Embase, and Web of Science prior to October 31, 2019, was retrieved. The Newcastle-Ottawa Scale was used to evaluate the quality of the literature. Stata 14.0 statistical software was used to analyze the data, and the correlations between PD-1 expression and the clinicopathological characteristics of patients were analyzed using the odds ratio (OR) and its 95% confidence interval (CI). The hazard ratio (HR) and its 95% CI were used to analyze the correlation between PD-1 high expression and patient prognosis. Begg's test was used to evaluate publication bias. Results: A total of 581 patients were analyzed in the six studies included in the meta-analysis. Pooled analysis revealed that high levels of PD-1 expression did not correlate with overall survival (HR = 0.79; 95% CI: [0.41-1.54]; p = 0.493). PD-1 positivity was associated with better disease-free survival (HR = 0.52; 95% CI: [0.38-0.72]; p < 0.0001). Furthermore, elevated PD-1 expression corrected for age (OR = 0.62, 95% CI: [0.41-0.96]; p = 0.030) and alpha-fetoprotein levels (OR = 2.27, 95% CI: [1.46-3.55]; p < 0.0001), were not correlated with patient sex, tumor size, tumor multiplicity, hepatitis B virus history, tumor node metastasis stage or Barcelona Clinic Liver Cancer stage. Conclusions: This meta-analysis revealed that PD-1 expression may be a useful prognostic marker in HCC patients. Prospective clinical studies are needed to support these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".