Long-Term Effects of Everolimus-Facilitated Tacrolimus Reduction in Living-Donor Liver Transplant Recipients with Hepatocellular Carcinoma
Bibliographic record
Abstract
BACKGROUND The study objective was to evaluate the effect of everolimus (EVR) in combination with reduced tacrolimus (rTAC) compared with a standard TAC (sTAC) regimen on hepatocellular carcinoma (HCC) recurrence in de novo living-donor liver transplantation recipients (LDLTRs) with primary HCC at liver transplantation through 5 years after transplantation. MATERIAL AND METHODS In this multicenter, non-interventional study, LDLTRs with primary HCC, who were previously randomized to either everolimus plus reduced tacrolimus (EVR+rTAC) or standard tacrolimus (sTAC), and who completed the 2-year core H2307 study, were followed up. Data were collected retrospectively (end of core to the start of follow-up study), and prospectively (during the 3-year follow-up study). RESULTS Of 117 LDLTRs with HCC at LT in the core H2307 study (EVR+rTAC, N=56; sTAC, N=61), 86 patients (EVR+rTAC, N=41; sTAC, N=45) entered the follow-up study. Overall HCC recurrence was lower but statistically non-significant in the EVR+rTAC group (3.6% vs 11.5% in sTAC; P=0.136) at 5 years after LT. There was no graft loss or chronic rejection. Acute rejection and death were comparable between treatment groups. Higher mean estimated glomerular filtration rate in the EVR+rTAC group (76.8 vs 65.8 mL/min/1.73 m² in sTAC) was maintained up to 5 years. Reported adverse events were numerically lower in the EVR+rTAC group (41.0% vs 53.5% sTAC) but not statistically significant. CONCLUSIONS Although statistically not significant, early EVR initiation reduced HCC recurrence, with comparable efficacy and safety, and better long-term renal function, than that of sTAC treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".