Meta-analysis of the prognostic value of pretreatment serum ferritin in hepatobiliary and pancreas (HBP) cancers
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Studies have shown that serum ferritin (SF) has unfavourable prognostic value in hepatobiliary and pancreas (HBP) cancers. This meta-analysis aimed to comprehensively assess the prognostic role of pretreatment SF in patients with HBP cancers. METHODS: Eligible studies published before January 2020 were obtained through a comprehensive search in the PubMed, Web of Science, Cochrane Library and EMBASE databases. Pooled HRs and 95% CIs were then employed as effect sizes. RESULTS: Seven studies comprising 1244 patients were pooled. Elevated pretreatment SF was associated with worse overall survival (OS) (HR 1.60, 95% CI 1.36 to 1.88, p<0.001) and recurrence-free survival/progression-free survival/time to recurrence (HR 1.70, 95% CI 1.15 to 2.52, p=0.008). Significant prognostic value of elevated pretreatment SF on OS was detected in the subgroups regardless of the cancer type, race, SF cut-off value, tumour-node-metastasis stage and Newcastle-Ottawa Scale score. CONCLUSION: Elevated pretreatment SF was associated with worse survival outcome of patients with HBP cancers. As such, it may serve as a novel prognostic biomarker for HBP cancers.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| 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".