Multicenter Validation of a Urine CXCL10 Assay for Noninvasive Monitoring of Renal Transplants
Bibliographic record
Abstract
BACKGROUND: Urine CXCL10 (C-X-C motif chemokine ligand 10, interferon gamma-induced protein 10 [IP10]) outperforms standard-of-care monitoring for detecting subclinical and early clinical T-cell-mediated rejection (TCMR) and may advance TCMR therapy development through biomarker-enriched trials. The goal was to perform an international multicenter validation of a CXCL10 bead-based immunoassay (Luminex) for transplant surveillance and compare with an electrochemiluminescence-based (Meso Scale Discovery [MSD]) assay used in transplant trials. METHODS: Four laboratories participated in the Luminex assay development and evaluation. Urine CXCL10 was measured by Luminex and MSD in 2 independent adult kidney transplant trial cohorts (Basel and TMCT04). In an independent test and validation set, a linear mixed-effects model to predict (log 10 -transformed) MSD CXCL10 from Luminex CXCL10 was developed to determine the conversion between assays. Net reclassification was determined after mathematical conversion. RESULTS: The Luminex assay was precise, with an intra- and interassay coefficient of variation 8.1% and 9.3%; showed modest agreement between 4 laboratories (R 0.96 to 0.99, P < 0.001); and correlated with known CXCL10 in a single- (n = 100 urines, R 0.94 to 0.98, P < 0.001) and multicenter cohort (n = 468 urines, R 0.92, P < 0.001) but the 2 assays were not equivalent by Passing-Bablok regression. Linear mixed-effects modeling demonstrated an intercept of -0.490 and coefficient of 1.028, showing Luminex CXCL10 are slightly higher than MSD CXCL10, but the agreement is close to 1.0. After conversion of the biopsy thresholds, the decision to biopsy would be changed for only 6% (5/85) patients showing acceptable reclassification. CONCLUSIONS: These data demonstrate this urine CXCL10 Luminex immunoassay is robust, reproducible, and accurate, indicating it can be readily translated into clinical HLA laboratories for serial posttransplant surveillance.
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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".