Inflammation scores predict survival for hepatitis B virus-related hepatocellular carcinoma patients after transarterial chemoembolization
Bibliographic record
Abstract
AIM: To compare the prognostic ability of inflammation scores for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). METHODS: Data of 224 consecutive patients who underwent TACE for unresectable HBV-related HCC from September 2009 to November 2011 were retrieved from a prospective database. The association of inflammation scores with clinicopathologic variables and overall survival (OS) were analyzed, and receiver operating characteristic curves were generated, and the area under the curve (AUC) was calculated to evaluate the discriminatory ability of each inflammation score and staging system, including tumor-node-metastasis, Barcelona Clinic Liver Cancer, and Cancer of the Liver Italian Program (CLIP) scores. RESULTS: The median follow-up period was 390 d, the one-, two-, and three-year OS were 38.4%, 18.3%, and 11.1%, respectively, and the median OS was 390 d. The Glasgow Prognostic Score (GPS), modifed GPS, neutrophil-lymphocyte ratio, and Prognostic Index were associated with OS. The GPS consistently had a higher AUC value at 6 mo (0.702), 12 mo (0.676), and 24 mo (0.687) in comparison with other inflammation scores. CLIP consistently had a higher AUC value at 6 mo (0.656), 12 mo (0.711), and 24 mo (0.721) in comparison with tumor-node-metastasis and Barcelona Clinic Liver Cancer staging systems. Multivariate analysis revealed that alanine aminotransferase, GPS, and CLIP were independent prognostic factors for OS. The combination of GPS and CLIP (AUC = 0.777) was superior to CLIP or GPS alone in prognostic ability for OS. CONCLUSION: The prognostic ability of GPS is superior to other inflammation scores for HCC patients undergoing TACE. Combining GPS and CLIP improved the prognostic power for OS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".