Rostaing, Lionel

Background: Although donor and recipient characteristics are used to estimate graft failure risk, they remain limited in predicting early acute rejection. We developed and validated a next-generation sequencing (NGS) assay targeting the pre-transplant immunologic profile to predict early acute rejection following kidney transplantation. Methods: This prospective, international study enrolled 321 kidney transplant participants across 13 sites, forming discovery and validation cohorts. Peripheral blood was collected prior to transplant and at 1, 3, 6, 12, and 24 months post-transplant, with protocol biopsies performed at 3 and 12 months, as well as any indication biopsies. Biopsies were assessed by a blinded central pathologist according to the 2019 Banff criteria. The pre-transplant risk assessment (PTRA™) test to evaluate RNA expression of a 29-gene signature algorithm designed to predict early acute rejection risk was clinically validated utilizing 122 deceased donor kidney transplant recipients. Results: PTRA classified 31 of 122 participants (25%) as high-risk and 91 (75%) as low-risk. There were 9 early acute rejection events in the first 60 days post-transplant: 6/31 (19%) in the high-risk group and 3/91 (3%) in the low-risk group. PTRA discrimination for early acute rejection at 60 days post-transplant yielded an AUC of 0.78 (95% confidence interval [CI]: 64.4 to 91.5), p<0.001. A cut-off of ≤45 was defined as low-risk and >45 as high-risk for early acute rejection within 60 days post-transplant. Sensitivity 0.67 (95% CI: 0.36 to 0.97), specificity 0.78 (95% CI: 0.70 to 0.86), positive predictive value 0.19 (95% CI: 0.05 to 0.33), and negative predictive value 0.97 (95% CI: 0.93 to 1.00). The odds ratio comparing patients identified as high- vs low-risk by PTRA was 7.04 (95% CI: 1.64 to 30.2), p=0.009. Conclusions: This study validates the ability of PTRA to stratify kidney transplant recipients as high- or low-risk for early acute rejection using a pre-transplant transcriptomic profile, with implications for graft health and personalized treatment management.

ABSTRACT Background Creatinine-based equations are the most used to estimate glomerular filtration rate (eGFR). The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), the re-expressed Lund-Malmö Revised (r-LMR) and the European Kidney Function Consortium (EKFC) equations are the most validated. The EKFC and r-LMR equations have been suggested to have better performances in young adults, but this is debated. Methods We collected data (GFR) measured by clearance of an exogenous marker (reference method), serum creatinine, age and sex from 2366 young adults (aged between 18 and 25 years) both from Europe and the USA. Results In the European cohorts (n = 1892), the bias (in mL/min/1.73 m²) was systematically better for the EKFC and r-LMR equations compared with the CKD-EPI equation [2.28, 95% confidence interval (1.59; 2.91), –2.50 (–3.85; –1.76), 17.41 (16.49; 18.47), respectively]. The percentage of estimated GFR within 30% of measured GFR (P30) was also better for EKFC and r-LMR equations compared with the CKD-EPI equation [84.4% (82.8; 86.0), 87.2% (85.7; 88.7) and 65.4% (63.3; 67.6), respectively]. In the US cohorts (n = 474), the bias for the EKFC and r-LMR equations was better than for the CKD-EPI equation in the non-Black population [0.97 (–1.69; 3.06), –2.62 (–5.14; –1.43) and 7.74 (5.97; 9.63), respectively], whereas the bias was similar in Black US individuals. P30 results were not different between the three equations in US cohorts. Analyses in sub-populations confirmed these results, except in individuals with high GFR levels (GFR ≥120 mL/min/1.73 m²) for whom the CKD-EPI equation might have a lower bias. Conclusions We demonstrated that both the EKFC and r-LMR creatinine-based equations have a better performance than the CKD-EPI equation in a young population. The only exception might be in patients with hyperfiltration.

AimThe Cockcroft‐Gault (CG) creatinine‐based equation is still used to estimate glomerular filtration rate (eGFR) for drug dosage adjustment. Incorrect eGFR may lead to hazardous over‐ or underdosing.MethodsIn a cross‐sectional analysis, CG was validated against measured GFR (mGFR) in 14 804 participants and compared with the Modification‐of‐Diet‐in‐Renal‐Diseases (MDRD), Chronic‐Kidney‐Disease‐Epidemiology (CKD‐EPI), Lund‐Malmö‐Revised (LMR) and European‐Kidney‐Function‐Consortium (EKFC) equations. Validation focused on bias, imprecision and accuracy (percentage of estimates within ±30% of mGFR, P30), overall and stratified for mGFR, age and body mass index at mGFR <60 mL/min, as well as classification in mGFR stages.ResultsThe CG equation performed worse than the other equations, overall and in mGFR, age and BMI subgroups in terms of bias (systematic overestimation), imprecision and accuracy except for patients ≥65 years where bias and P30 were similar to MDRD and CKD‐EPI, but worse than LMR and EKFC. In subjects with mGFR <60 mL/min and at BMI 18.5‐25 kg/m2, all equations performed similarly, and for BMI < 18.5 kg/m2 CG and LMR had the best results though all equations had poor P30‐accuracy. At BMI ≥ 25 kg/m2 the bias of the CG increased with increasing BMI (+17.2 mL/min at BMI ≥ 40 kg/m2). The four more recent equations also classified mGFR stages better than CG.ConclusionsThe CG equation showed poor ability to estimate GFR overall and in analyses stratified for mGFR, age and BMI. CG was inferior to correctly classify the patients in the mGFR staging compared to more recent creatinine‐based equations.

Abstract Background The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation is routinely used to assess renal function but exhibits varying accuracy depending on patient characteristics and clinical presentation. The overall aim of the present study was to assess if and to what extent glomerular filtration rate (GFR) estimation based on creatinine can be improved. Methods In a cross-sectional analysis covering the years 2003–17, CKD-EPI was validated against measured GFR (mGFR; using various tracer methods) in patients with high likelihood of chronic kidney disease (CKD; five CKD cohorts, n = 8365) and in patients with low likelihood of CKD (six community cohorts, n = 6759). Comparisons were made with the Lund–Malmö revised equation (LMR) and the Full Age Spectrum equation. Results 7In patients aged 18–39 years old, CKD-EPI overestimated GFR with 5.0–16 mL/min/1.73 m2 in median in both cohort types at mGFR levels &lt;120 mL/min/1.73 m2. LMR had greater accuracy than CKD-EPI in the CKD cohorts (P30, the percentage of estimated GFR within 30% of mGFR, 83.5% versus 76.6%). CKD-EPI was generally the most accurate equation in the community cohorts, but all three equations reached P30 above the Kidney Disease Outcomes Quality Initiative benchmark of 90%. Conclusions None of the evaluated equations made optimal use of available data. Prospects for improved GFR estimation procedures based on creatinine exist, particularly in young adults and in settings where patients with suspected or manifest CKD are investigated.