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Using a Chemical Biopsy for Graft Quality Assessment
Published on: June 17, 2020
Diagnostic Performance and Resource Utilization of Combining Blood Gene Expression, Cell-Free DNA, and Urine
Akhil Singla1, Sook Park2, Havisha Pedamallu3
1Department of Industrial Engineering and Management Sciences, McCormick School of Engineering, Northwestern University, Evanston, Illinois.
Key Points:
Two-stage urine chemokine screening improved discrimination and positive predictive value versus blood-only testing while preserving high negative predictive value. In validation, urine chemokine C-X-C motif ligand 9/creatinine screening referred only 79% of samples for donor-derived cell-free DNA testing, reducing blood test use. Standalone blood biomarkers were more consistent for antibody-mediated rejection than cellular rejection; urine chemokine screening improved diagnostic yield.
Background:
After kidney transplantation, subclinical acute rejection occurs in 20%-25% of clinically stable recipients; surveillance biopsies are invasive and often indicate no rejection. Moreover, the widespread use of noninvasive biomarkers is limited by cost.
Methods:
We developed and sought to validate two-stage diagnostic models integrating urine chemokine assays (chemokine C-X-C motif ligand 9 [CXCL9] and C-X-C motif ligand 10) with confirmatory blood-based gene expression profiling (GEP) and donor-derived cell-free DNA (dd-cfDNA). Data from two studies, 476 biopsy-paired samples from 226 recipients (discovery) and 144 samples from 134 recipients (validation), were analyzed retrospectively. Rapid, low-cost urine chemokine assays were used for stage 1 screening; recipients with elevated urine chemokines underwent additional stage 2 testing with GEP and/or dd-cfDNA.
Results:
In the validation cohort, dd-cfDNA outperformed GEP for overall rejection and antibody-mediated rejection, whereas neither test validated significant discrimination for cellular rejection. CXCL9-based two-stage testing improved the area under the receiver operating characteristic curve and positive predictive value versus standalone stage-2 testing, while maintaining similar negative predictive value and reducing stage 2 test use. At a probability screening threshold of 0.10, the CXCL9/creatinine-based logistic regression, adjusted for BK virus, urinary tract infection, sex, age, time post-transplant, and donor type, followed by dd-cfDNA validated a higher positive predictive value (0.39 versus 0.34), lower sensitivity (0.56 versus 0.62), and similar negative predictive value around 0.94, compared with dd-cfDNA alone, while recommending dd-cfDNA testing in only 0.79 (95% confidence interval, 0.72 to 0.85) of validation cases. Combined GEP and dd-cfDNA testing validated higher area under the receiver operating characteristic curves than dd-cfDNA as a second-stage test for overall (0.85 [0.79 to 0.94] versus 0.82 [0.74 to 0.92]), antibody-mediated (0.96 [0.93 to 1.00] versus 0.90 [0.79 to 1.00]), and cellular rejections (0.69 [0.61 to 0.89] versus 0.63 [0.53 to 0.81]).
Conclusions:
This staged approach reduces unnecessary biopsies and guides the efficient use of costly blood-based biomarkers while maintaining good clinical performance, particularly for subclinical antibody-mediated rejections.
Clinical Trial Registry Name And Registration Number:
ClinicalTrials.gov, NCT01289717 .
