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Introduction/objective: The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health., Methods: The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program., Results: A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m 2 , urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group ( P  < .001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from -7.08 ml/min/1.73 m 2 /year to -4.27 ml/min/1.73 m 2 /year in high-risk patients ( P  = .0003), -2.65 to -1.04 in intermediate risk, and -3.26 ml/min/1.73 m 2 /year to +0.45 ml/min/1.73 m 2 /year in patients with low-risk ( P  < .001)., Conclusions: Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: MJD, TM, FF, and RT are employees of Renalytix; SC, GN, MK, and AZ are consultants for Renalytix, All remaining authors have nothing to disclose.

Aims: To develop and validate an updated version of KidneyIntelX (kidneyintelX.dkd) to stratify patients for risk of progression of diabetic kidney disease (DKD) stages 1 to 3, to simplify the test for clinical adoption and support an application to the US Food and Drug Administration regulatory pathway., Methods: We used plasma biomarkers and clinical data from the Penn Medicine Biobank (PMBB) for training, and independent cohorts (BioMe and CANVAS) for validation. The primary outcome was progressive decline in kidney function (PDKF), defined by a ≥40% sustained decline in estimated glomerular filtration rate or end-stage kidney disease within 5 years of follow-up., Results: In 573 PMBB participants with DKD, 15.4% experienced PDKF over a median of 3.7 years. We trained a random forest model using biomarkers and clinical variables. Among 657 BioMe participants and 1197 CANVAS participants, 11.7% and 7.5%, respectively, experienced PDKF. Based on training cut-offs, 57%, 35% and 8% of BioMe participants, and 56%, 38% and 6% of CANVAS participants were classified as having low-, moderate- and high-risk levels, respectively. The cumulative incidence at these risk levels was 5.9%, 21.2% and 66.9% in BioMe and 6.7%, 13.1% and 59.6% in CANVAS. After clinical risk factor adjustment, the adjusted hazard ratios were 7.7 (95% confidence interval [CI] 3.0-19.6) and 3.7 (95% CI 2.0-6.8) in BioMe, and 5.4 (95% CI 2.5-11.9) and 2.3 (95% CI 1.4-3.9) in CANVAS, for high- versus low-risk and moderate- versus low-risk levels, respectively., Conclusions: Using two independent cohorts and a clinical trial population, we validated an updated KidneyIntelX test (named kidneyintelX.dkd), which significantly enhanced risk stratification in patients with DKD for PDKF, independently from known risk factors for progression., (© 2023 John Wiley & Sons Ltd.)

Objectives: Estimated glomerular filtration rate (eGFR) and albuminuria, the current standard-of-care tests that predict risk of kidney function decline in early-stage diabetic kidney disease (DKD), are only modestly useful. We evaluated the decision-making impact of an artificial intelligence-enabled prognostic test, KidneyIntelX, in the management of DKD by primary care physicians (PCPs)., Study Design: This was a prospective web-based survey administered among PCPs in the United States., Methods: We used conjoint analysis with multivariable logit models to estimate PCP preferences. The survey included hypothetical patient profiles with 6 attributes: albuminuria, eGFR, age, blood pressure (BP), hemoglobin A1c (HbA1c), and KidneyIntelX result. Each PCP viewed 8 patient profiles randomly selected from 42 unique profiles having 1 level from each attribute. For each patient, PCPs were asked to indicate whether they would prescribe a sodium-glucose cotransporter-2 (SGLT2) inhibitor, increase angiotensin receptor blocker (ARB) dose, and/or refer to a nephrologist., Results: A total of 401 PCPs completed the survey (response rate, 8.8%). The relative importance of the top 2 attributes for each decision were HbA1c (52%) and KidneyIntelX result (23%) for prescribing SGLT2 inhibitors, BP (62%) and KidneyIntelX result (13%) for increasing ARB dose, and eGFR (42%) and KidneyIntelX result (27%) for nephrologist referral. A high-risk KidneyIntelX result was associated with significantly higher odds of PCPs prescribing SGLT2 inhibitors (odds ratio [OR], 1.64; 95% CI, 1.29-2.08), increasing ARB dose (OR, 1.49; 95% CI, 1.17-1.89), and referring to a nephrologist (OR, 2.47; 95% CI, 1.99-3.08) compared with no test., Conclusions: The KidneyIntelX test had greater relative importance than albuminuria and eGFR to PCPs in making treatment decisions and was second only to eGFR for nephrologist referrals. Because of its significant impact on decision-making, KidneyIntelX has high clinical utility in DKD management.

KidneyIntelX, a bioprognostic test for assessing risk of CKD progression, risk stratified individuals for kidney, heart failure, and death outcomes in the Canagliflozin Cardiovascular Assessment Study.Individuals scored as high risk seemed to derive more of benefit from treatment with canagliflozin versus placebo.These findings may serve to increase adoption of underutilized therapies for cardiorenal risk reduction in patients with diabetic kidney disease., Competing Interests: S.G. Coca reports consultancy for Axon Therapies, Bayer, Boehringer Ingelheim, Nuwellis, Renalytix, Reprieve Cardiovascular, Takeda, Vifor, and 3ive; ownership interest in pulseData and Renalytix; research funding from ProKidney, Renalytix, Renal Research Institute, and XORTX; patents or royalties from Renalytix; being a scientific co-founder of Renalytix and having equity and royalties and being a consultant and member of the scientific advisory board; an advisory or leadership role with Renalytix and Reprieve Cardiovascular; and being an associate editor for Kidney360 and on the editorial boards of JASN, CJASN, and Kidney International. F. Fleming reports being the chief technology officer and co-founder of Renalytix; being an employee of Renalytix; ownership interest in Renalytix and Verici Dx; and having an advisory or leadership role with Renalytix. M. Hansen reports being an employee of Janssen Research & Development, and ownership interest in Johnson & Johnson. H.L. Heerspink reports being an employee of University Medical Center Groningen; ongoing consultancy agreements with AstraZeneca, Bayer, Boehringer Ingelheim, CSL Behring, Chinook, Dimerix, Eli-Lilly, Gilead, GoldFinch, Janssen, Merck, NovoNordisk, and Travere Pharmaceuticals; research funding from AstraZeneca, Janssen research support (grant funding directed to employer), and NovoNordisk; honoraria from AstraZeneca (lecture fees); and participating in a speakers’ bureau for AstraZeneca. K. Mahaffey reports consultancy for Amgen, Applied Therapeutics, AstraZeneca, Bayer, CSL Behring, Elsevier, Fribrogen, Invo, Johnson & Johnson, Lexicon, Myokardia, Novartis, Novo Nordisk, Otsuka, Phasebio, Portola, Precordior, Quidel, Sanofi, and Theravance; research funding from the American Heart Assocation, Apple, Inc., Bayer, California Institute Regenerative Medicine, Eidos, Ferring, Gilead, Google (Verily), Idorsia, Johnson & Johnson, Luitpold, PAC-12, Precordior, and Sanifit; and honoraria from Amgen, Anthos, Applied Therapeutics, AstraZeneca, Bayer, CSL Behring, Elsevier, Inova, Intermountain Health, Johnson & Johnson, Medscae, Mount Sinai, Mundi Pharma, Myokardia, Novartis, Novo Nordisk, Otsuka, Portola, Sanofi, SmartMedics, and Theravance. G.N. Nadkarni reports consultancy for Daiichi Sankyo, GLG consulting, Qiming Capital, Reata, Renalytix, Siemens Healthineers, and Variant Bio; ownership interest in Data2Wisdom, LLC, Doximity, Nexus iConnect, Pensieve Health, Renalytix, and Verici; research funding from Renalytix; honoraria from Daiichi Sankyo; patents or royalties from Renalytix; an advisory or leadership role with Renalytix; participating in a speakers’ bureau with Daiichi Sankyo; and being a scientific co-founder of Renalytix and having equity and royalties and being a consultant and member of the scientific advisory board. B. Neal reports consultancy for Janssen Research & Development, LLC; research funding from the Australian National Health and Medical Research Council Principal Research Fellowship and Janssen; honoraria from Janssen Research & Development, LLC (paid to the institution); and serving on advisory boards and/or involvement in continuing medical education (CME) programs for Janssen, with any consultancy, honoraria, or travel support paid to his institution. D. Takale reports being an employee of Persistent. Y. Yavin reports being an employer of Janssen, and ownership interest in Bristol-Myers Squibb and Johnson & Johnson., (Copyright © 2022 by the American Society of Nephrology.)

Background and Objectives: Clinical trials in nephrology are enriched for patients with micro- or macroalbuminuria to enroll patients at risk of kidney failure. However, patients with normoalbuminuria can also progress to kidney failure. TNF receptor-1, TNF receptor-2, and kidney injury marker-1 (KIM-1) are known to be associated with kidney disease progression in patients with micro- or macroalbuminuria. We assessed the value of TNF receptor-1, TNF receptor-2, and KIM-1 as prognostic biomarkers for CKD progression in patients with type 2 diabetes and normoalbuminuria., Design, Setting, Participants, & Measurements: TNF receptor-1, TNF receptor-2, and KIM-1 were measured using immunoassays in plasma samples from patients with type 2 diabetes at high cardiovascular risk participating in the Canagliflozin Cardiovascular Assessment Study trial. We used multivariable adjusted Cox proportional hazards analyses to estimate hazard ratios per doubling of each biomarker for the kidney outcome, stratified the population by the fourth quartile of each biomarker distribution, and assessed the number of events and event rates., Results: In patients with normoalbuminuria ( n =2553), 51 kidney outcomes were recorded during a median follow-up of 6.1 (interquartile range, 5.8-6.4) years (event rate, 3.5; 95% confidence interval, 2.6 to 4.6 per 1000 patient-years). Each doubling of baseline TNF receptor-1 (hazard ratio, 4.2; 95% confidence interval, 1.8 to 9.6) and TNF receptor-2 (hazard ratio, 2.3; 95% confidence interval, 1.5 to 3.6) was associated with a higher risk for the kidney outcome. Baseline KIM-1, urinary albumin-creatinine ratio, and eGFR were not associated with kidney outcomes. The event rates in the highest quartile of TNF receptor-1 (≥2992 ng/ml) and TNF receptor-2 (≥11,394 ng/ml) were 5.6 and 7.0 events per 1000 patient-years, respectively, compared with 2.8 and 2.3, respectively, in the lower three quartiles., Conclusions: TNF receptor-1 and TNF receptor-2 are associated with kidney outcomes in patients with type 2 diabetes and normoalbuminuria., Clinical Trial Registry Name and Registration Number: CANagliflozin cardioVascular Assessment Study (CANVAS), NCT01032629., (Copyright © 2022 by the American Society of Nephrology.)

Background: Cell therapies explore unmet clinical needs of patients with chronic kidney disease with the potential to alter the pathway toward end-stage kidney disease. We describe the design and baseline patient characteristics of a phase II multicenter clinical trial utilizing the novel renal autologous cell therapy (REACT), by direct kidney parenchymal injection via the percutaneous approach in adults with type 2 diabetic kidney disease (T2DKD), to delay or potentially avoid renal replacement therapy., Design: The study conducted a prospective, multicenter, randomized control, open-label, phase II clinical trial between an active treatment group (ATG) receiving REACT from the beginning of the trial and a contemporaneous deferred treatment group (DTG) receiving standard of care for 12 months before crossing over to receive REACT., Objectives: The objective of this study was to establish the safety and efficacy of 2 REACT injections with computed tomography guidance, into the renal cortex of patients with T2DKD administered 6 months apart, and to compare the longitudinal change in renal function between the ATG and the DTG., Setting: This was a multicenter study conducted in major US hospitals., Patients: We enrolled eighty-three adult patients with T2DKD, who have estimated glomerular filtration rates (eGFRs) between 20 and 50 mL/min/1.73 m2., Methods: All patients undergo an image-guided percutaneous kidney biopsy to obtain epithelial phenotype selective renal cells isolated from the kidney tissue that is then expanded ex vivo over 4-6 weeks, resulting in the REACT biologic product. Patients are randomized 1:1 into the ATG or the DTG. Primary efficacy endpoints for both study groups include eGFR measurements at baseline and at 3-month intervals, through 24 months after the last REACT injection. Safety analyses include biopsy-related complications, REACT injection, and cellular-related adverse events. The study utilizes Good Clinical and Manufacturing Practices and a Data and Safety Monitoring Board. The sample size confers a statistical power of 80% to detect an eGFR change in the ATG compared to the DTG at 24 months with an α = 0.05., Limitations: Blinding cannot occur due to the intent to treat procedure, biopsy in both groups, and open trial design., Conclusion: This multicenter phase II randomized clinical trial is designed to determine the efficacy and safety of REACT in improving or stabilizing renal function among patients with T2DKD stages 3a-4., (© 2022 The Author(s). Published by S. Karger AG, Basel.)

Introduction and Objective: The lack of precision to identify patients with early-stage diabetic kidney disease (DKD) at near-term risk for progressive decline in kidney function results in poor disease management often leading to kidney failure requiring unplanned dialysis. The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to generate a risk score for progressive decline in kidney function over 5-year in adults with early-stage DKD. Our objective was to assess the impact of KidneyIntelX on management and outcomes in a Health System in the real-world evidence (RWE) study., Methods: KidneyIntelX was introduced into a large metropolitan Health System via a population health-defined approved care pathway for patients with stages 1 to 3 DKD between [November 2020 to March 2022]. Decision impact on visit frequency, medication management, specialist referral, and selected lab values was assessed. We performed an interim analysis in patients through 6-months post-test date to evaluate the impact of risk level with clinical decision-making and outcomes., Results: A total of 1686 patients were enrolled in the RWE study and underwent KidneyIntelX testing and subsequent care pathway management. The median age was 68 years, 52% were female, 26% self-identified as Black, and 94% had hypertension. The median baseline eGFR was 59 ml/minute/1.73 m 2 , urine albumin-creatinine ratio was 69 mg/g, and HbA1c was 7.7%. After testing, a clinical encounter in the first month occurred in 13%, 43%, and 53% of low-risk, intermediate-risk, and high-risk patients, respectively and 46%, 61%, and 71% had at least 1 action taken within the first 6 months. High-risk patients were more likely to be placed on SGLT2 inhibitors (OR = 4.56; 95% CI 3.00-6.91 vs low-risk), and more likely to be referred to a specialist such as a nephrologist, endocrinologist, or dietician (OR = 2.49; 95% CI 1.53-4.01) compared to low-risk patients., Conclusions: The combination of KidneyIntelX, clinical guidelines and educational support resulted in changes in clinical management by clinicians. After testing, there was an increase in visit frequency, referrals for disease management, and introduction to guideline-recommended medications. These differed by risk category, indicating an impact of KidneyIntelX risk stratification on clinical care.

Introduction: KidneyIntelX is a composite risk score, incorporating biomarkers and clinical variables for predicting progression of diabetic kidney disease (DKD). The utility of this score in the context of sodium glucose co-transporter 2 inhibitors and how changes in the risk score associate with future kidney outcomes are unknown., Methods: We measured soluble tumor necrosis factor receptor (TNFR)-1, soluble TNFR-2, and kidney injury molecule 1 on banked samples from CANagliflozin cardioVascular Assessment Study (CANVAS) trial participants with baseline DKD (estimated glomerular filtration rate [eGFR] 30-59 mL/min/1.73 m2 or urine albumin-to-creatinine ratio [UACR] ≥30 mg/g) and generated KidneyIntelX risk scores at baseline and years 1, 3, and 6. We assessed the association of baseline and changes in KidneyIntelX with subsequent DKD progression (composite outcome of an eGFR decline of ≥5 mL/min/year [using the 6-week eGFR as the baseline in the canagliflozin group], ≥40% sustained decline in the eGFR, or kidney failure)., Results: We included 1,325 CANVAS participants with concurrent DKD and available baseline plasma samples (mean eGFR 65 mL/min/1.73 m2 and median UACR 56 mg/g). During a mean follow-up of 5.6 years, 131 participants (9.9%) experienced the composite kidney outcome. Using risk cutoffs from prior validation studies, KidneyIntelX stratified patients to low- (42%), intermediate- (44%), and high-risk (15%) strata with cumulative incidence for the outcome of 3%, 11%, and 26% (risk ratio 8.4; 95% confidence interval [CI]: 5.0, 14.2) for the high-risk versus low-risk groups. The differences in eGFR slopes for canagliflozin versus placebo were 0.66, 1.52, and 2.16 mL/min/1.73 m2 in low, intermediate, and high KidneyIntelX risk strata, respectively. KidneyIntelX risk scores declined by 5.4% (95% CI: -6.9, -3.9) in the canagliflozin arm at year 1 versus an increase of 6.3% (95% CI: 3.8, 8.7) in the placebo arm (p < 0.001). Changes in the KidneyIntelX score at year 1 were associated with future risk of the composite outcome (odds ratio per 10 unit decrease 0.80; 95% CI: 0.77, 0.83; p < 0.001) after accounting for the treatment arm, without evidence of effect modification by the baseline KidneyIntelX risk stratum or by the treatment arm., Conclusions: KidneyIntelX successfully risk-stratified a large multinational external cohort for progression of DKD, and greater numerical differences in the eGFR slope for canagliflozin versus placebo were observed in those with higher baseline KidneyIntelX scores. Canagliflozin treatment reduced KidneyIntelX risk scores over time and changes in the KidneyIntelX score from baseline to 1 year associated with future risk of DKD progression, independent of the baseline risk score and treatment arm., (© 2022 The Author(s). Published by S. Karger AG, Basel.)

Aim: Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, prognostic risk score (KidneyIntelX™) combining electronic health records (EHR) and biomarkers., Methods: This is an observational cohort study of patients with prevalent DKD/banked plasma from two EHR-linked biobanks. A random forest model was trained, and performance (AUC, positive and negative predictive values [PPV/NPV], and net reclassification index [NRI]) was compared with that of a clinical model and Kidney Disease: Improving Global Outcomes (KDIGO) categories for predicting a composite outcome of eGFR decline of ≥5 ml/min per year, ≥40% sustained decline, or kidney failure within 5 years., Results: In 1146 patients, the median age was 63 years, 51% were female, the baseline eGFR was 54 ml min -1 [1.73 m] -2 , the urine albumin to creatinine ratio (uACR) was 6.9 mg/mmol, follow-up was 4.3 years and 21% had the composite endpoint. On cross-validation in derivation (n = 686), KidneyIntelX had an AUC of 0.77 (95% CI 0.74, 0.79). In validation (n = 460), the AUC was 0.77 (95% CI 0.76, 0.79). By comparison, the AUC for the clinical model was 0.62 (95% CI 0.61, 0.63) in derivation and 0.61 (95% CI 0.60, 0.63) in validation. Using derivation cut-offs, KidneyIntelX stratified 46%, 37% and 17% of the validation cohort into low-, intermediate- and high-risk groups for the composite kidney endpoint, respectively. The PPV for progressive decline in kidney function in the high-risk group was 61% for KidneyIntelX vs 40% for the highest risk strata by KDIGO categorisation (p < 0.001). Only 10% of those scored as low risk by KidneyIntelX experienced progression (i.e., NPV of 90%). The NRI event for the high-risk group was 41% (p < 0.05)., Conclusions: KidneyIntelX improved prediction of kidney outcomes over KDIGO and clinical models in individuals with early stages of DKD.

Background: A majority of diabetic kidney disease (DKD) patients receive medical care in the primary care setting, making it an important opportunity to improve patient management. There is limited evidence evaluating whether primary care physicians (PCPs) are equipped to effectively manage these patients in routine clinical practice. The present study was undertaken to identify gaps in primary care and unmet needs in the diagnosis and monitoring of DKD in type 2 diabetes (T2D) patients among PCPs., Methods: This was a qualitative analysis based on 30-45-min interviews with PCPs treating T2D patients. PCPs were recruited via email and were board-certified, in practice for more than 3 years, spent most of their time in direct clinical care, and provided care for more than three T2D patients in a week. Descriptive data analysis was conducted to identify and examine themes that were generated by interviews. Two reviewers evaluated interview data to identify themes and developed consensus on the priority themes identified., Results: A total of 16 PCPs satisfying the inclusion criteria were recruited for qualitative interviews. Although the PCPs recognized kidney disease as an important comorbidity in T2D patients, testing for kidney disease was not consistently top of mind, with 56% reportedly performing kidney function testing in their T2D patients. PCPs most frequently reported using estimated glomerular filtration rate (eGFR) alone to monitor and stage DKD; only 25% PCPs reported testing for albuminuria. Most PCPs incorrectly believed that a majority of DKD patients are diagnosed in early stages. Also, early stages of DKD emerged as ambiguous areas of decision-making, wherein treatments prescribed greatly varied among PCPs. Lastly, early and accurate risk stratification of DKD patients emerged as the most important unmet need; which, if it could be overcome, was consistently identified by PCPs as a key to monitoring, appropriate nephrologist referrals, and intervening to improve outcomes in patients with DKD., Conclusions: Our study highlights important unmet needs in T2D DKD testing, staging, and stratification in the PCP setting that limit effective patient care. Health systems and insurers in the U.S. should prioritize the review and approval of new strategies that can improve DKD staging and risk stratification.

Aim: To evaluate the U.S. payer budget-impact of KidneyIntelX, an artificial intelligence-enabled in vitro diagnostic to predict kidney function decline in Type 2 Diabetic Kidney Disease (T2DKD) patients, stages 1-3b., Materials and Methods: We developed an Excel-based model according to International Society of Pharmacoeconomics and Outcomes Research (ISPOR) good practices to assess U.S. payer budget impact associated with the use of the KidneyIntelX test to optimize therapy T2DKD patients compared to standard of care (SOC) (without KidneyIntelX). A hypothetical cohort of 100,000 stages 1-3b T2DKD patients was followed for 5 years. Peer-reviewed publications were used to identify model parameter estimates. KidneyIntelX costs incremental to SOC (without KidneyIntelX) included test cost, additional prescription medication use, specialist referrals and PCP office visits. Patients managed with KidneyIntelX experienced a 20% slowed progression rate compared to SOC (without KidneyIntelX) attributed to slowed DKD progression, delayed or prevented dialysis and transplants, and reduced dialysis crashes. Associated costs were compared to SOC (without KidneyIntelX). Sensitivity analyses were conducted by varying the definition of progression and the DKD progression rate associated with KidneyIntelX testing and related interventions., Results: Projected undiscounted base case 5-year savings for 100,000 patients tested with KidneyIntelX were $1.052 billion, attributed mostly to slowed progression through DKD stages. The breakeven point for the health plan adopting KidneyIntelX is expected to occur prior to year 2 after adoption. Sensitivity analysis based on the assessment of the most conservative definition of progression and a 5% reduction in progression rate attributed to KidneyIntelX, resulted in a projected 5-year savings of $145 million associated with KidneyIntelX., Limitations and Conclusions: Limitations included reliance on literature-based parameter estimates, including effect size of delayed progression supported by the literature. Incorporating KidneyIntelX in contemporary care of early-stage T2DKD patients is projected to result in substantial savings to payers.

Background: Glomerular endothelial dysfunction and neoangiogenesis have long been implicated in the pathogenesis of diabetic kidney disease (DKD). However, the specific molecular pathways contributing to these processes in the early stages of DKD are not well understood. Our recent transcriptomic profiling of glomerular endothelial cells identified a number of proangiogenic genes that were upregulated in diabetic mice, including leucine-rich α -2-glycoprotein 1 (LRG1). LRG1 was previously shown to promote neovascularization in mouse models of ocular disease by potentiating endothelial TGF- β /activin receptor-like kinase 1 (ALK1) signaling. However, LRG1's role in the kidney, particularly in the setting of DKD, has been unclear., Methods: We analyzed expression of LRG1 mRNA in glomeruli of diabetic kidneys and assessed its localization by RNA in situ hybridization. We examined the effects of genetic ablation of Lrg1 on DKD progression in unilaterally nephrectomized, streptozotocin-induced diabetic mice at 12 and 20 weeks after diabetes induction. We also assessed whether plasma LRG1 was associated with renal outcome in patients with type 2 diabetes., Results: LRG1 localized predominantly to glomerular endothelial cells, and its expression was elevated in the diabetic kidneys. LRG1 ablation markedly attenuated diabetes-induced glomerular angiogenesis, podocyte loss, and the development of diabetic glomerulopathy. These improvements were associated with reduced ALK1-Smad1/5/8 activation in glomeruli of diabetic mice. Moreover, increased plasma LRG1 was associated with worse renal outcome in patients with type 2 diabetes., Conclusions: These findings identify LRG1 as a potential novel pathogenic mediator of diabetic glomerular neoangiogenesis and a risk factor in DKD progression., (Copyright © 2019 by the American Society of Nephrology.)

Novel biomarkers are needed to predict kidney function decline in patients with type 2 diabetes, especially those with preserved glomerular filtration rate (GFR). There are limited data on the association of markers of endothelial dysfunction with longitudinal GFR decline. We used banked specimens from a nested case-control study in the Action to Control Cardiovascular Disease (ACCORD) trial (n=187 cases: 187 controls) and from a diverse contemporary cohort of type 2 diabetic patients from the Mount Sinai BioMe Biobank (n=871) to assess the association of plasma endostatin and kidney outcomes. We measured plasma endostatin at enrollment and examined its association with a composite kidney outcome of sustained 40% decline in estimated GFR or end-stage renal disease. Baseline plasma endostatin levels were higher in participants with the composite outcome. Each log 2 increment in plasma endostatin was associated with approximately 2.5-fold higher risk of the kidney outcome (adjusted odds ratio [OR] 2.5; 95% confidence interval [CI] 1.5-4.3 in ACCORD and adjusted hazard ratio [HR] 2.6; 95% CI 1.8-3.8 in BioMe). Participants in the highest vs. lowest quartile of plasma endostatin had approximately four-fold higher risk for the kidney outcome (adjusted OR 3.6; 95% CI 1.8-7.3 in ACCORD and adjusted HR 4.4; 95% CI 2.3-8.5 in BioMe). The AUC for the kidney outcome improved from 0.74 to 0.77 in BioMe with the addition of endostatin to a base clinical model. Plasma endostatin was strongly associated with kidney outcomes in type 2 diabetics with preserved eGFR and improved risk discrimination over traditional predictors., (Copyright © 2018 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Biomarkers of diverse pathophysiologic mechanisms may improve risk stratification for incident or progressive diabetic kidney disease (DKD) in persons with type 2 diabetes. To evaluate such biomarkers, we performed a nested case-control study ( n =190 cases of incident DKD and 190 matched controls) and a prospective cohort study ( n =1156) using banked baseline plasma samples from participants of randomized, controlled trials of early (ACCORD) and advanced (VA NEPHRON-D) DKD. We assessed the association and discrimination obtained with baseline levels of plasma TNF receptor-1 (TNFR-1), TNFR-2, and kidney injury molecule-1 (KIM-1) for the outcomes of incident DKD (ACCORD) and progressive DKD (VA-NEPHRON-D). At baseline, median concentrations of TNFR-1, TNFR-2, and KIM-1 were roughly two-fold higher in the advanced DKD population (NEPHRON-D) than in the early DKD population (ACCORD). In both cohorts, patients who reached the renal outcome had higher baseline levels than those who did not reach the outcome. Associations between doubling in TNFR-1, TNFR-2, and KIM-1 levels and risk of the renal outcomes were significant for both cohorts. Inclusion of these biomarkers in clinical models increased the area under the curve (SEM) for predicting the renal outcome from 0.68 (0.02) to 0.75 (0.02) in NEPHRON-D. Systematic review of the literature illustrated high consistency in the association between these biomarkers of inflammation and renal outcomes in DKD. In conclusion, TNFR-1, TNFR-2, and KIM-1 independently associated with higher risk of eGFR decline in persons with early or advanced DKD. Moreover, addition of these biomarkers to clinical prognostic models significantly improved discrimination for the renal outcome., (Copyright © 2017 by the American Society of Nephrology.)

Background and Objectives: Current measures for predicting renal functional decline in patients with type 2 diabetes with preserved renal function are unsatisfactory, and multiple markers assessing various biologic axes may improve prediction. We examined the association of four biomarker-to-creatinine ratio levels (monocyte chemotactic protein-1, IL-18, kidney injury molecule-1, and YKL-40) with renal outcome., Design, Setting, Participants, & Measurements: We used a nested case-control design in the Action to Control Cardiovascular Disease Trial by matching 190 participants with ≥40% sustained eGFR decline over the 5-year follow-up period to 190 participants with ≤10% eGFR decline in a 1:1 fashion on key characteristics (age within 5 years, sex, race, baseline albumin-to-creatinine ratio within 20 μg/mg, and baseline eGFR within 10 ml/min per 1.73 m(2)), with ≤10% decline. We used a Mesoscale Multiplex Platform and measured biomarkers in baseline and 24-month specimens, and we examined biomarker associations with outcome using conditional logistic regression., Results: Baseline and 24-month levels of monocyte chemotactic protein-1-to-creatinine ratio levels were higher for cases versus controls. The highest quartile of baseline monocyte chemotactic protein-1-to-creatinine ratio had fivefold greater odds, and each log increment had 2.27-fold higher odds for outcome (odds ratio, 5.27; 95% confidence interval, 2.19 to 12.71 and odds ratio, 2.27; 95% confidence interval, 1.44 to 3.58, respectively). IL-18-to-creatinine ratio, kidney injury molecule-1-to-creatinine ratio, and YKL-40-to-creatinine ratio were not consistently associated with outcome. C statistic for traditional predictors of eGFR decline was 0.70, which improved significantly to 0.74 with monocyte chemotactic protein-1-to-creatinine ratio., Conclusions: Urinary monocyte chemotactic protein-1-to-creatinine ratio concentrations were strongly associated with sustained renal decline in patients with type 2 diabetes with preserved renal function., (Copyright © 2016 by the American Society of Nephrology.)

Diabetic kidney disease (DKD) is a common, complex condition that has become a significant public health problem. The beneficial effects of intensive glycemic control in type 1 diabetes mellitus on development of DKD are proven; however, the evidence for nephroprotection in patients with type 2 diabetes is conflicting. Moreover, a strategy of intensive glycemic control increases the risk for adverse effects (hypoglycemic episodes) with no obvious impact on macrovascular events or mortality in recent large randomized controlled trials. The risk for hypoglycemia with intensive therapy is heightened in patients with significant renal dysfunction, due to decreased renal clearance of insulin. Establishing an ideal level of glycemic control in patients requires an individualized approach taking into account duration of diabetes and presence of coexisting comorbidities and pre-existing DKD. In this article, we review the available evidence from both observational studies and randomized controlled trials and provide suggestions about evaluating the potential benefits and harm from intensive glycemic control in patients. We also discuss how in the future, a personalized approach using biomarkers might help identify patients most likely to respond as well as those most susceptible to harm. We believe that using the optimal level of glycemic control in diabetic patients using a multi-pronged strategy will improve individual patient outcomes and decrease the overall burden of morbidity and mortality.

Background: Aggressive glycemic control has been hypothesized to prevent renal disease in patients with type 2 diabetes mellitus. A systematic review was conducted to summarize the benefits of intensive vs conventional glucose control on kidney-related outcomes for adults with type 2 diabetes., Methods: Three databases were systematically searched (January 1, 1950, to December 31, 2010) with no language restrictions to identify randomized trials that compared surrogate renal end points (microalbuminuria and macroalbuminuria) and clinical renal end points (doubling of the serum creatinine level, end-stage renal disease [ESRD], and death from renal disease) in patients with type 2 diabetes receiving intensive glucose control vs those receiving conventional glucose control., Results: We evaluated 7 trials involving 28 065 adults who were monitored for 2 to 15 years. Compared with conventional control, intensive glucose control reduced the risk for microalbuminuria (risk ratio, 0.86 [95% CI, 0.76-0.96]) and macroalbuminuria (0.74 [0.65-0.85]), but not doubling of the serum creatinine level (1.06 [0.92-1.22]), ESRD (0.69 [0.46-1.05]), or death from renal disease (0.99 [0.55-1.79]). Meta-regression revealed that larger differences in hemoglobin A1c between intensive and conventional therapy at the study level were associated with greater benefit for both microalbuminuria and macroalbuminuria. The pooled cumulative incidence of doubling of the serum creatinine level, ESRD, and death from renal disease was low (<4%, <1.5%, and <0.5%, respectively) compared with the surrogate renal end points of microalbuminuria (23%) and macroalbuminuria (5%)., Conclusions: Intensive glucose control reduces the risk for microalbuminuria and macroalbuminuria, but evidence is lacking that intensive glycemic control reduces the risk for significant clinical renal outcomes, such as doubling of the serum creatinine level, ESRD, or death from renal disease during the years of follow-up of the trials.

Introduction: Diabetes is a leading cause of end-stage kidney disease (ESKD). Biomarkers of tubular health may prognosticate chronic kidney disease (CKD) progression beyond estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). Methods: We examined associations of five urinary biomarkers of tubular injury and repair (NGAL, KIM-1, IL-18, MCP-1, YKL-40) with kidney function decline (first occurrence of a decrease in eGFR ≥30 mL/min/1.73 m2 if randomization eGFR ≥60 or ≥50% if randomization eGFR <60; ESKD) and all-cause mortality among 1,135 VA NEPHRON-D trial participants with baseline UACR ≥300 mg/g and available urine samples. Covariates included age, sex, race, BMI, systolic BP, HbA1c, treatment arm, eGFR, and UACR. In a subset of participants with 12-month samples (n = 712), we evaluated associations of KIM-1, MCP-1, and YKL-40 change (from baseline to 12 months) with eGFR decline (from 12 months onward). Results: At baseline, mean age was 65 years, mean eGFR was 56 mL/min/1.73 m2, and median UACR was 840 mg/g. Over a median of 2.2 years, 13% experienced kidney function decline and 9% died. In fully adjusted models, the highest versus lowest quartiles of MCP-1 and YKL-40 were associated with 2.18- and 1.76-fold higher risks of kidney function decline, respectively. One-year changes in KIM-1, MCP-1, and YKL-40 were not associated with subsequent eGFR decline. Higher baseline levels of NGAL, IL-18, MCP-1, and YKL-40 levels (per 2-fold higher) were independently associated with 10–40% higher risk of mortality. Conclusion: Among Veterans with diabetes and CKD, urinary biomarkers of tubular health were associated with kidney function decline and mortality. [ABSTRACT FROM AUTHOR]

The search for relevant kidney injury biomarkers has been a fervent one and well-documented over the past 15 years. Counterintuitively, patients with acute decompensated heart failure who have elevated injury biomarkers and clinical AKI actually have better post-discharge outcomes and better post-discharge kidney function [[10]]. These groups can be potentially broken down into patients with early and/or late diabetic kidney disease, non-diabetic or APOL1-associated kidney disease, various types of glomerulonephritides, patients with chronic heart failure, chronic liver disease and HIV-positive individuals. [Extracted from the article]