Ten Years Experience With Belatacept-Based Immunosuppression After Kidney Transplantation
Bibliographic record
Abstract
BACKGROUND: Belatacept was approved for prevention of acute rejection in adult kidney transplantation in 2011 based on two randomized, controlled, multicenter phase 3 studies. Long-term experience over 10 years with belatacept-based immunosuppression after kidney transplantation has not been reported before. PATIENTS AND METHODS: Analyzed were 20 patients who had been included into a randomized multicenter phase 2 study by our institution between March 2001 and November 2002. For 10-year follow-up, three different groups could be analyzed: 1) patients with primary calcineurin inhibitor-based (CNI-based) immunosuppression (n = 5), 2) patients with early switch from a belatacept-based to a CNI-based regimen within the first 14 months (n = 8) and 3) patients with completely CNI-free belatacept immunosuppression (n = 7). RESULTS: Fifteen patients received primary belatacept-based immunosuppression and five patients primary cyclosporine A (CyA). Five patients are still on belatacept. Kidney function measured by serum creatinine levels worsened in the CNI group and the belatacept to CNI switch group during long-term follow-up whereas all patients receiving belatacept throughout follow-up showed stable creatinine values. Acute rejections occurred predominantly in the first 12 months after transplantation and were responsible for four of seven switches from belatacept- to CNI-based immunosuppression within the first 14 months. Five of the 20 patients died. CONCLUSIONS: Belatacept is effective and safe in renal transplant patients and was not associated with graft loss due to chronic allograft nephropathy. Belatacept was well tolerated in all patients and caused less nephrotoxic side effects and was well accepted in most patients.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".