Multicenter Validation of Urinary CXCL9 as a Risk-Stratifying Biomarker for Kidney Transplant Injury
Bibliographic record
Abstract
Noninvasive biomarkers are needed to assess immune risk and ultimately guide therapeutic decision-making following kidney transplantation. A requisite step toward these goals is validation of markers that diagnose and/or predict relevant transplant endpoints. The Clinical Trials in Organ Transplantation-01 protocol is a multicenter observational study of biomarkers in 280 adult and pediatric first kidney transplant recipients. We compared and validated urinary mRNAs and proteins as biomarkers to diagnose biopsy-proven acute rejection (AR) and stratify patients into groups based on risk for developing AR or progressive renal dysfunction. Among markers tested for diagnosing AR, urinary CXCL9 mRNA (odds ratio [OR] 2.77, positive predictive value [PPV] 61.5%, negative predictive value [NPV] 83%) and CXCL9 protein (OR 3.40, PPV 67.6%, NPV 92%) were the most robust. Low urinary CXCL9 protein in 6-month posttransplant urines obtained from stable allograft recipients classified individuals least likely to develop future AR or a decrement in estimated glomerular filtration rate between 6 and 24 months (92.5-99.3% NPV). Our results support using urinary CXCL9 for clinical decision-making following kidney transplantation. In the context of acute dysfunction, low values can rule out infectious/immunological causes of injury. Absent urinary CXCL9 at 6 months posttransplant defines a subgroup at low risk for incipient immune injury.
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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".