Liver transplantation outcomes after transarterial chemotherapy for hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: Transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) awaiting liver transplantation is widespread, although evidence that it improves outcomes is lacking and there exist concerns about morbidity. The impact of TACE on outcomes after transplantation was evaluated in this study. METHODS: Patients with HCC who had liver transplantation in the UK were identified, and stratified according to whether they received TACE between 2006 and 2016. Cox regression methods were used to estimate hazard ratios (HRs) for death and graft failure after transplantation adjusted for donor and recipient characteristics. RESULTS: In total, 385 of 968 patients (39·8 per cent) received TACE. Five-year patient survival after transplantation was similar in those who had or had not received TACE: 75·2 (95 per cent c.i. 68·8 to 80·5) and 75·0 (70·5 to 78·8) per cent respectively. After adjustment for donor and recipient characteristics, there were no differences in mortality (HR 0·96, 95 per cent c.i. 0·67 to 1·38; P = 0·821) or graft failure (HR 1·01, 0·73 to 1·40; P = 0·964). The number of TACE treatments (2 or more versus 1: HR 0·97, 0·61 to 1·55; P = 0·903) or the time of death after transplantation (within or after 90 days; P = 0·291) did not alter the outcome. The incidence of hepatic artery thrombosis was low in those who had or had not received TACE (1·3 and 2·4 per cent respectively; P = 0·235). CONCLUSION: TACE delivered to patients with HCC before liver transplant did not affect complications, patient death or graft failure after transplantation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".