Analysis of Biomarkers Within the Initial 2 Years Posttransplant and 5-Year Kidney Transplant Outcomes
Bibliographic record
Abstract
BACKGROUND: An early posttransplant biomarker/surrogate marker for kidney allograft loss has the potential to guide targeted interventions. Previously published findings, including results from the Clinical Trials in Organ Transplantation (CTOT)-01 study, showed that elevated urinary chemokine CXCL9 levels and elevated frequencies of donor-reactive interferon gamma (IFNγ)-producing T cells by enzyme-linked immunosorbent spot (ELISPOT) assay associated with acute cellular rejection within the first year and with lower 1-year posttransplant estimated glomerular filtration rate (eGFR). How well these biomarkers correlate with late outcomes, including graft loss, is unclear. METHODS: In CTOT-17, we obtained 5-year outcomes in the CTOT-01 cohort and correlated them with (a) biomarker results and (b) changes in eGFR (Chronic Kidney Disease Epidemiology Collaboration formula) over the initial 2 years posttransplant using univariable analysis and multivariable logistic regression. RESULTS: Graft loss occurred in 14 (7.6%) of 184 subjects 2 to 5 years posttransplant. Neither IFNγ ELISPOTs nor urinary CXCL9 were informative. In contrast, a 40% or greater decline in eGFR from 6 months to 2 years posttransplant independently correlated with 13-fold odds of 5-year graft loss (adjusted odds ratio, 13.1; 95% confidence interval, 3.0-56.6), a result that was validated in the independent Genomics of Chronic Allograft Rejection cohort (n = 165; adjusted odds ratio, 11.2). CONCLUSIONS: We conclude that although pretransplant and early posttransplant ELISPOT and chemokine measurements associate with outcomes within 2 years posttransplant, changes in eGFR between 3 or 6 months and 24 months are better surrogates for 5-year outcomes, including graft loss.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".