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Randomized Controlled Trial
. 2023 Aug 1;34(8):1456-1469.
doi: 10.1681/ASN.0000000000000160. Epub 2023 May 25.

Randomized Trial to Assess the Clinical Utility of Renal Allograft Monitoring by Urine CXCL10 Chemokine

Affiliations
Randomized Controlled Trial

Randomized Trial to Assess the Clinical Utility of Renal Allograft Monitoring by Urine CXCL10 Chemokine

Patricia Hirt-Minkowski et al. J Am Soc Nephrol. .

Abstract

Significance statement: This study is the first randomized controlled trial to investigate the clinical utility of a noninvasive monitoring biomarker in renal transplantation. Although urine CXCL10 monitoring could not demonstrate a beneficial effect on 1-year outcomes, the study is a rich source for future design of trials aiming to explore the clinical utility of noninvasive biomarkers. In addition, the study supports the use of urine CXCL10 to assess the inflammatory status of the renal allograft.

Background: Urine CXCL10 is a promising noninvasive biomarker for detection of renal allograft rejection. The aim of this study was to investigate the clinical utility of renal allograft monitoring by urine CXCL10 in a randomized trial.

Methods: We stratified 241 patients, 120 into an intervention and 121 into a control arm. In both arms, urine CXCL10 levels were monitored at three specific time points (1, 3, and 6 months post-transplant). In the intervention arm, elevated values triggered performance of an allograft biopsy with therapeutic adaptations according to the result. In the control arm, urine CXCL10 was measured, but the results concealed. The primary outcome was a combined end point at 1-year post-transplant (death-censored graft loss, clinical rejection between month 1 and 1-year, acute rejection in 1-year surveillance biopsy, chronic active T-cell-mediated rejection in 1-year surveillance biopsy, development of de novo donor-specific HLA antibodies, or eGFR <25 ml/min).

Results: The incidence of the primary outcome was not different between the intervention and the control arm (51% versus 49%; relative risk (RR), 1.04 [95% confidence interval, 0.81 to 1.34]; P = 0.80). When including 175 of 241 (73%) patients in a per-protocol analysis, the incidence of the primary outcome was also not different (55% versus 49%; RR, 1.11 [95% confidence interval, 0.84 to 1.47]; P = 0.54). The incidence of the individual end points was not different as well.

Conclusions: This study could not demonstrate a beneficial effect of urine CXCL10 monitoring on 1-year outcomes (ClinicalTrials.gov_ NCT03140514 ).

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Conflict of interest statement

All authors have nothing to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
Study design. The target Tac trough levels are given for specific time frames post-transplant. BKPyV, polyomavirus BK; MPA, mycophenolic acid; Tac, tacrolimus; UTI, urinary tract infection. Figure 1 can be viewed in color online at www.jasn.org.
Figure 2
Figure 2
Patient flow. The intention-to-treat analysis included 121 patients in the intervention arm and 120 patients in the control arm. For the modified intention-to-treat analysis, only those patients having an adequate 1-year surveillance biopsy were included (intervention arm [n=102], control arm [n=99]). Finally, the per-protocol analysis included 82 patients in the intervention arm and 93 patients in the control arm.
Figure 3
Figure 3
Details of CXCL10 monitoring results and subsequent diagnostic/therapeutic interventions in the intervention arm. (A) Summary of the diagnostic (i.e., allograft biopsy) and therapeutic interventions in the intervention arm. (B) Urine CXCL10 monitoring results at the three time points, stratified by study arm. For the intervention arm, the interpretation was done prospectively; in the control arm, the interpretation was added retrospectively after study completion applying the same rules as for the intervention arm. Figure 3 can be viewed in color online at www.jasn.org.
Figure 4
Figure 4
Incidence of clinical and clinical/subclinical rejection. (A) Defined by the Banff 2015 classification. (B) Defined by the Banff 2019 classification. Figure 4 can be viewed in color online at www.jasn.org.
Figure 5
Figure 5
Correlation of CXCL10 burden with occurrence of rejection in the 1-year surveillance biopsy. Overall, patients had six urine CXCL10 monitoring checkpoints. Those having 5 or 6 measurements were included to calculate the CXCL10 burden (n=227; mean of 5 or 6 measurement). These 227 patients were then divided into three CXCL10 tertiles (low, intermediate, high). Of these 227 patients, 195 had 1-year surveillance biopsies (low [n=61], intermediate [n=67], high [n=67]). (A) Correlation of tertiles of CXCL10 burden with subsequent rejection in 1-year surveillance biopsies using the Banff 2015 classification including borderline changes (Cochran–Armitage trend test P = 0.13). (B) Correlation of tertiles of CXCL10 burden with subsequent rejection in 1-year surveillance biopsies using the Banff 2019 classification including borderline changes (Cochran–Armitage trend test P = 0.01). Figure 5 can be viewed in color online at www.jasn.org.
Figure 6
Figure 6
Distribution of rejection phenotypes and diagnostic characteristics of urine CXCL10. (A) Rejection phenotypes among diagnostic, CXCL10-triggered, and 1-year surveillance biopsies defined by the Banff 2015 and Banff 2019 classifications. (B) Diagnostic characteristics of urine CXCL10 for detection of rejection according to the Banff 2015 and Banff 2019 classifications. Figure 6 can be viewed in color online at www.jasn.org.

Comment in

References

    1. Sellares J, de Freitas DG, Mengel M, et al. . Understanding the causes of kidney transplant failure: the dominant role of antibody-mediated rejection and nonadherence. Am J Transplant. 2012;12(2):388–399. doi:10.1111/j.1600-6143.2011.03840.x - DOI - PubMed
    1. Mayrdorfer M, Liefeldt L, Wu K, et al. . Exploring the complexity of death-censored kidney allograft failure. J Am Soc Nephrol. 2021;32(6):1513–1526. doi:10.1681/ASN.2020081215 - DOI - PMC - PubMed
    1. Wehmeier C, Amico P, Sidler D, et al. . Pre-transplant donor-specific HLA antibodies and risk for poor first-year renal transplant outcomes: results from the Swiss Transplant Cohort Study. Transplant Int. 2021;34(12):2755–2768. doi:10.1111/tri.14119 - DOI - PubMed
    1. El-Zoghby ZM, Stegall MD, Lager DJ, et al. . Identifying specific causes of kidney allograft loss. Am J Transplant. 2009;9(3):527–535. doi:10.1111/j.1600-6143.2008.02519.x - DOI - PubMed
    1. Rush D. Protocol transplant biopsies: an underutilized tool in kidney transplantation. Clin J Am Soc Nephrol. 2006;1(1):138–143. doi:10.2215/CJN.00390705 - DOI - PubMed

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