Impact of cytolysis following transarterial chemoembolization for hepatocellular carcinoma.
Bibliographic record
Abstract
BACKGROUND AIMS: Transarterial chemoembolization (TACE) is increasingly used as a treatment of hepatocellular carcinoma. Cytolysis, which may occur within days following the procedure is due to either necrosis of the tumour or of the non-tumoral parenchyma. Therefore it may influence either tumour response or liver function or both. We evaluated the impact of cytolysis after TACE on tumour response, incidence of hepatobiliary complications and overall survival. METHODS: We conducted a retrospective analysis of 157 patients with liver disease who underwent 271 treatments for hepatocellular carcinoma. Cytolysis was defined as an increase of AST value above 100 IU/L with at least doubling of the baseline value. The associations between cytolysis and radiologic tumor response two months following each treatment and adverse hepatobiliary events were estimated using generalized estimating equations models. Comparison of 18 months survival after a first treatment of chemoembolization between the groups with and without cytolysis was performed using the proportional hazards model. RESULTS: Cytolysis occurred in 198 out of 271 cases and was associated with a favourable radiological response (OR 1.90, 1.03-3.54) at two months compared to non-cytolysis with no difference in the occurrence of adverse hepatobiliary events. The adjusted hazard ratio for overall survival was 1.33 times greater in the group with cytolysis compared to non-cytolysis (0.45-3.90). CONCLUSIONS: The occurrence of cytolysis was associated with a favorable radiological response, but had no impact on short-term adverse events and on survival at 18 months.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".