Calcineurin Inhibitor Minimization in the Symphony Study: Observational Results 3 Years after Transplantation
Bibliographic record
Abstract
The Symphony study showed that at 1 year posttransplant, a regimen based on daclizumab induction, 2 g mycophenolate mofetil (MMF), low-dose tacrolimus and steroids resulted in better renal function and lower acute rejection and graft loss rates compared with three other regimens: two with low-doses of cyclosporine or sirolimus instead of tacrolimus and one with no induction and standard cyclosporine dosage. This is an observational follow-up for 2 additional years with the same endpoints as the core study. Overall, 958 patients participated in the follow-up. During the study, many patients changed their immunosuppressive regimen (e.g. switched from sirolimus to tacrolimus), but the vast majority (95%) remained on MMF. During the follow-up, renal function remained stable (mean change: -0.6 ml/min), and rates of death, graft loss and acute rejection were low (all about 1% per year). The MMF and low-dose tacrolimus arm continued to have the highest GFR (68.6 +/- 23.8 ml/min vs. 65.9 +/- 26.2 ml/min in the standard-dose cyclosporine, 64.0 +/- 23.1 ml/min in the low-dose cyclosporine and 65.3 +/- 26.2 ml/min in the low-dose sirolimus arm), but the difference with the other arms was not significant (p = 0.17 in an overall test and 0.077, 0.039 and 0.11, respectively, in pair-wise tests). The MMF and low-dose tacrolimus arm also had the highest graft survival rate, but with reduced differences between groups over time, and the least acute rejection rate. In the Symphony study, the largest ever prospective study in de novo kidney transplantation, over 3 years, daclizumab induction, MMF, steroids and low-dose tacrolimus proved highly efficacious, without the negative effects on renal function commonly reported for standard CNI regimens.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".