Efficacy and Safety of Everolimus With Reduced Tacrolimus Compared to Standard Tacrolimus in Recipients of Living Donor Liver Transplant: Design of a Randomized Study.
Bibliographic record
Abstract
Purpose: Living donor liver transplantation (LDLT) is an attractive approach to address deceased donor shortage and increasing demand. However, data from randomized clinical studies evaluating effect of different immunosuppressive regimens in LDLT recipients is sparse. Here we present the design of H2307 study, the first study to evaluate efficacy and safety of everolimus (EVR) with reduced tacrolimus (rTAC) vs. standard TAC control (TAC-C) in LDLT recipients. Methods: H2307 is a 24-month (M), multicenter, randomized, controlled study planned to enroll at least 470 LDLT recipients (male and female, ≥18 years). To allow for optimal allograft regeneration and wound healing, patients enter a 30-day run-in period with TAC (8-12ng/mL) ± mycophenolate mofetil ± anti-IL2 induction and steroids before stratified randomization (RND) in a 1:1 ratio to receive EVR (C0 3-8ng/mL) + rTAC (C0 3-5ng/mL) or TAC-C (6-10ng/mL) (Figure 1). Stratification is based on hepatocellular carcinoma (HCC) at time of LT. Main inclusion criteria include: 1) HIV negative status and 2) known HCV and HBV status. Exclusion criteria include: 1) HCV negative subjects receiving transplant from HCV positive donor, 2) MELD score >35 within 1M prior to transplantation, and 3) HCC patients with extra-hepatic spread or macrovascular invasion. Study objectives include composite efficacy failure of treated biopsy-proven acute rejection, graft loss or death as well as evolution of renal function from RND to M12 and M24, and incidence of adverse events. Specific objectives include incidence and time to HCC recurrence, evolution of HCV viral load, and allograft regeneration. Results: The study will be run at 41 centers across 11 countries. 12M results are expected in 2016. Conclusion: For the first time, a randomized, multicenter study is performed in a large cohort of LDLT recipients, comparing the efficacy and safety of EVR+rTAC vs. TAC-C.Figure: No Caption available.DISCLOSURES:Levy, G.: Speaker's Bureau, Novartis, Astellas, Abott. Speziale, A.: Employee, Novartis. Rauer, B.: Employee, Novartis. Wang, Z.: Employee, Novartis. Junge, G.: Employee, Novartis. Uemoto, S.: Other, Novartis, Advisory committee.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".