Abstract

In this clinical validation study, we developed and validated a urinary Q-Score generated from the quantitative test QSant, formerly known as QiSant, for the detection of biopsy-confirmed acute rejection in kidney transplants. Using a cohort of 223 distinct urine samples collected from three independent sites and from both adult and pediatric renal transplant patients, we examined the diagnostic utility of the urinary Q-Score for detection of acute rejection in renal allografts. Statistical models based upon the measurements of the six QSant biomarkers (cell-free DNA, methylated-cell-free DNA, clusterin, CXCL10, creatinine, and total protein) generated a renal transplant Q-Score that reliably differentiated stable allografts from acute rejections in both adult and pediatric renal transplant patients. The composite Q-Score was able to detect both T cell-mediated rejection and antibody-mediated rejection patients and differentiate them from stable non-rejecting patients with a receiver–operator characteristic curve area under the curve of 99.8% and an accuracy of 98.2%. Q-Scores < 32 indicated the absence of active rejection and Q-Scores ≥ 32 indicated an increased risk of active rejection. At the Q-Score cutoff of 32, the overall sensitivity was 95.8% and specificity was 99.3%. At a prevalence of 25%, positive and negative predictive values for active rejection were 98.0% and 98.6%, respectively. The Q-Score also detected subclinical rejection in patients without an elevated serum creatinine level but identified by a protocol biopsy. This study confirms that QSant is an accurate and quantitative measurement suitable for routine monitoring of renal allograft status.

Highlights

  • The total number of living kidney transplant recipients with a functioning graft is expected to pass 250,000 in the 1–2 years [1]

  • Scientific Registry of Transplant Recipients (SRTR) data showed that 97% of kidney transplants are working at the end of a month, 93% are working at the end of a year, and 83% are working at the end of 3 years [1]

  • acute rejection (AR) was defined, at minimum, by the following criteria: (1) T-cell-mediated rejection (TCMR) consisting of either a tubulitis (t) score > 2 accompanied by an interstitial inflammation (i) score > 2 or vascular changes (v) score > 0; (2) C4d-positive antibody-mediated rejection (ABMR) consisting of positive donor-specific antibodies (DSAs) (MFI > 1500) with a glomerulitis (g) score > 0 or peritubular capillaritis score > 0 or v > 0 with unexplained acute tubular necrosis/thrombotic microangiopathy (ATN/TMA) with C4d = 2; or (3) C4d-negative ABMR consisting of positive DSA with unexplained ATN/TMA with g + ptc ≥ 2 and C4d = 0 or 1

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Summary

Introduction

The total number of living kidney transplant recipients with a functioning graft is expected to pass 250,000 in the 1–2 years [1]. There is a critical clinical need for a sensitive, quantitative, non-invasive diagnostic test that can detect changes in graft status to guide clinically indicated biopsy decisions and monitor rejection risk longitudinally to improve allografts lifespan and long-term outcomes. The Q-Score scaled from 0–100 was generated as discussed in the foundational clinical paper by Yang et al [11], with the same fixed Q-Score cut-off of greater than or equal to 32 for diagnosis of acute rejection, and applied to two separate datasets, generated in the CLIA Lab, to re-evaluate the sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy of assessment of allograft rejection status, as assessed by a renal allograft biopsy, paired with the urine sample processed for QSant. Increasing use and applications of the Q-Score in prospective clinical trials may further support the Q-Score as a surrogate endpoint for acute rejection therapy effectiveness and kidney transplant rejection outcome measurements without the need of repeated invasive transplant biopsies

Study Population and Sample Collection
Kidney Biopsy
QSant Assay
Statistical Analysis and Algorithm Development
Study Design and Cohort Description
Differentiation of AR Patients from STA Patients
Conclusions
Full Text
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