Efficacy and Safety of Everolimus With Low-Dose Tacrolimus in De Novo Renal Transplant Recipients: 12-Month Randomized Study.
Bibliographic record
Abstract
A multicenter (52 US & Canadian centers), randomized, open-label non-inferiority study assessed efficacy and safety of everolimus (EVR)+low-dose tacrolimus (LTac) vs mycophenolate mofetil (MMF)+standard-dose Tac (STac) regimen in de novo renal transplant recipients (RTxR). RTxR (n=613) started EVR at 0.75 mg bid to maintain trough level of 3-8 ng/mL+LTac (n=309) or MMF (2 g/day)+STac (n=304); with induction therapy, basiliximab (PRA<20%) or rabbit anti-thymocyte globulin (PRA≥20% or high risk) & steroids per local practice. Composite efficacy failure rate at 12M included tBPAR, graft loss, death, or loss to follow-up. Renal function (eGFR) was estimated at 12M using MDRD-4 formula. Of 613 patients (pts), 575 (EVR+LTac 94.8%; MMF+STac 92.8%) completed the study. Donor and recipient characteristics were comparable between treatment arms, except, statistically higher HLA mismatches (HLA≥3; EVR+LTac vs MMF+STac 85.3% vs 78.9% p<0.05), higher baseline diabetes mellitus (36.3% vs 31.3%), deceased donors (55.5% vs 51.4%) & extended criteria donors (ECD; 11.1% vs 8.9%) in EVR arm; and higher current PRA≥20% (13.1% vs 18.1%) in MMF arm. Incidence rates of efficacy endpoints are shown below (Table). At M12, mean eGFR was similar with EVR+LTac & MMF+STac (63.14 vs 63.06 mL/min/1.73m2). Serious adverse event rates through M12 were 50.3% with EVR+LTac vs 46.7% with MMF+STac. Overall infection rates were lower in EVR vs MMF arms (59.2% vs 64.1%). In pts from centers that maintained target EVR levels (excluding pts from centers that have >30% of their EVR levels <3 ng/mL), composite efficacy failure was similar, 22.1% with EVR+LTac and 20.3% with MMF+STac arm [95% CI -5.4, 9.0].Table: No Caption available.In this study, non-inferiority (10% margin) in composite efficacy failure rate for EVR+LTac was not achieved due to higher rate of acute rejection possibly from a higher number of pts with HLA≥3, deceased donors and ECDs in the EVR arm. Despite higher rejection rates, there was significantly lower rate of graft loss in EVR vs MMF arm with similar renal function. It is important to maintain EVR trough levels for a balance between efficacy and safety. DISCLOSURE:Shaffer, D.: Grant/Research Support, Novartis. Peddi, V.: Grant/Research Support, Novartis, Astellas. Shihab, F.: Other, Novartis, Consultant and Speaker, Astellas, Consultant. Yilmaz, S.: Other, Novartis, Service Agreement, Astellas, Service Agreement. McCague, K.: Employee, Novartis Pharmaceuticals Corporation. Patel, D.: Employee, Novartis Pharmaceuticals Corporation. Mulgaonkar, S.: Grant/Research Support, Novartis, Other, Novartis, Advisor.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".