Five-year follow-up of a phase I trial of donor-derived modified immune cell infusion in kidney transplantation
Bibliographic record
Abstract
Background The administration of modified immune cells (MIC) before kidney transplantation led to specific immunosuppression against the allogeneic donor and a significant increase in regulatory B lymphocytes. We wondered how this approach affected the continued clinical course of these patients. Methods Ten patients from a phase I clinical trial who had received MIC infusions prior to kidney transplantation were retrospectively compared to 15 matched standard-risk recipients. Follow-up was until year five after surgery. Results The 10 MIC patients had an excellent clinical course with stable kidney graft function, no donor-specific human leukocyte antigen antibodies (DSA) or acute rejections, and no opportunistic infections. In comparison, a retrospectively matched control group receiving standard immunosuppressive therapy had a higher frequency of DSA (log rank P = 0.046) and more opportunistic infections (log rank P = 0.033). Importantly, MIC patients, and in particular the four patients who had received the highest cell number 7 days before surgery and received low immunosuppression during follow-up, continued to show a lack of anti-donor T lymphocyte reactivity in vitro and high CD19+CD24hiCD38hi transitional and CD19+CD24hiCD27+ memory B lymphocytes until year five after surgery. Conclusions MIC infusions together with reduced conventional immunosuppression were associated with good graft function during five years of follow-up, no de novo DSA development and no opportunistic infections. In the future, MIC infusions might contribute to graft protection while reducing the side effects of immunosuppressive therapy. However, this approach needs further validation in direct comparison with prospective controls. Trial registration https://clinicaltrials.gov/ , identifier NCT02560220 (for the TOL-1 Study). EudraCT Number: 2014-002086-30.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".