Dataset Information

Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.

ABSTRACT:

Background

The kidney failure risk equation (KFRE) is a validated risk algorithm for predicting the risk of kidney failure in chronic kidney disease (CKD) patients regardless of etiology. Patients with autosomal dominant polycystic kidney disease (AD-PCKD) experience long disease trajectories and as such identifying individuals at risk of kidney failure would aid in intervention.

Objective

To examine the utility of the KFRE in predicting adverse kidney outcomes compared with existing risk factors in a cohort of patients with AD-PCKD.

Methods

Retrospective cohort study of AD-PCKD patients referred to a tertiary care center with a baseline kidney ultrasound and a KFRE calculation. Cox proportional hazards were used to examine the association of the KFRE and composite of an eGFR decline of >30% or the need for dialysis/transplantation. Discrimination and calibration of a parsimonious fully adjusted model and a model containing only total kidney volume (TKV) with and without the addition of the KFRE was determined.

Results

Of 340 patients with AD-PCKD eligible, 221 (65%) met inclusion criteria. Older age, cardiac disease, cancer, higher systolic blood pressure, albuminuria, lower eGFR and a higher initial TKV were more common in patients with a higher KFRE. A total of 120 events occurred over a median patient follow-up time of 3.2 years. KFRE was independently associated with the composite kidney outcome. Addition of the KFRE significantly improved discrimination and calibration in a TKV only model and a fully adjusted model.

Conclusions

In a diverse, referral population with AD-PCKD, the KFRE was associated with adverse kidney outcomes and improved risk prediction.

SUBMITTER: Akbari A

PROVIDER: S-EPMC7081470 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.

Akbari Ayub A Tangri Navdeep N Brown Pierre A PA Biyani Mohan M Rhodes Emily E Kumar Teerath T Shabana Wael W Sood Manish M MM

Canadian journal of kidney health and disease 20200318

<h4>Background</h4>The kidney failure risk equation (KFRE) is a validated risk algorithm for predicting the risk of kidney failure in chronic kidney disease (CKD) patients regardless of etiology. Patients with autosomal dominant polycystic kidney disease (AD-PCKD) experience long disease trajectories and as such identifying individuals at risk of kidney failure would aid in intervention.<h4>Objective</h4>To examine the utility of the KFRE in predicting adverse kidney outcomes compared with exist ...[more]

PMID: 32215214

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Project description:Background and objectivesProgression of CKD toward ESRD is heterogeneous. The Kidney Failure Risk Equation (KFRE) was developed to identify CKD patients at high risk of ESRD. We aimed to externally validate KFRE and to test whether the addition of predefined Duplex ultrasound markers - renal resistive index (RRI) or difference of resistive indices in spleen and kidney (DI-RISK) - improved ESRD prediction.Design, setting, participants, & measurementsThe prospective Cardiovascular and Renal Outcome in CKD 2-4 Patients-The Fourth Homburg evaluation (CARE FOR HOMe) study recruits CKD stage G2-G4 patients referred to a tertiary referral center for nephrologic care. Four hundred three CARE FOR HOMe participants enrolled between 2008 and 2012 had available RRI measurements at study inclusion; they were subsequently followed for a mean of 4.4±1.6 years. This subcohort was used to validate KFRE and to assess the added value of the ultrasound markers (new models KFRE+RRI and KFRE+DI-RISK). Model performance was assessed by log-likelihood ratio test, c-statistic, integrated discrimination improvement metrics (for study participants without subsequent ESRD [IDI No ESRD] and for patients with ESRD [IDI ESRD]), and calibration plots. If either new model improved on KFRE, we determined to validate it in an independent cohort of 162 CKD patients.ResultsKFRE predicted ESRD in CARE FOR HOMe participants with a c-statistic of 0.91 (95% confidence interval, 0.83 to 0.99). Adding RRI improved the KFRE model (P<0.001), and the KFRE+RRI model was well calibrated; however, the c-statistic (0.91 [0.83-1.00]) was similar, and overall sensitivity (IDI No ESRD=0.05 [0.00-0.10]) or overall specificity (IDI ESRD=0.00 [0.00-0.01]) did not improve. Adding DI-RISK did not improve the KRFE model. In the external validation cohort, we confirmed that the KFRE+RRI model did not outperform KFRE.ConclusionsRoutine Duplex examinations among CKD patients did not improve risk prediction for progression to ESRD beyond a validated equation.

Project description:Rationale & objectiveThe Kidney Failure Risk Equation (KFRE) is a simple widely validated prediction model using age, sex, estimated glomerular filtration rate, and urinary albumin-creatinine ratio to predict the risk for end-stage kidney disease. Data are limited for its applicability to kidney transplant recipients.Study designValidation study of the KFRE as a post hoc analysis of the Folic Acid for Vascular Outcomes Reduction in Transplantation (FAVORIT) Trial.Setting & participantsAdult kidney transplant recipients with functioning kidney allografts at least 6 months posttransplantation from 30 centers in the United States, Canada, and Brazil. Participants with estimated glomerular filtration rates < 60 mL/min/1.73 m2 at study entry were included.Predictor2- and 5-year kidney failure risk predicted by the KFRE using variables at study entry.OutcomeGraft loss, defined by initiation of dialysis.Analytical approachDiscrimination of the KFRE was assessed using C statistics; calibration was assessed by plotting predicted risk against observed cumulative incidence of graft loss.Results2,889 participants were included. Within 2 years, 98 participants developed graft loss, 107 participants died with a functioning graft, and 129 participants were lost to follow-up, and by 5 years, 252 had developed graft loss, 265 died with a functioning graft, and 1,543 were lost to follow-up. The KFRE demonstrated accurate calibration and discrimination (C statistic, 0.85 [95% CI, 0.81-0.88] at 2 years and 0.81 [95% CI, 0.78-0.84] at 5 years); performance was similar regardless of donor type (living vs deceased) and graft vintage, with the noted exception of poorer calibration for graft vintage less than 2 years.LimitationsUnavailable cause of graft loss.ConclusionsThe KFRE accurately predicted the risk for graft loss among adult kidney transplant recipients with graft vintage longer than 2 years and may be a useful prognostic tool for nephrologists caring for kidney transplant recipients.

Project description:In some jurisdictions, routine reporting of the estimated glomerular filtration rate (eGFR) has led to an increase in nephrology referrals and wait times.We describe the use of the Kidney Failure Risk Equation (KFRE) as part of a triage process for new nephrology referrals for patients with chronic kidney disease stages 3 to 5 in a Canadian province.A quasi-experimental study design was used.This study took place in Manitoba, Canada.Demographics, laboratory values, referral numbers, and wait times were compared between periods.In 2012, we adopted a risk-based cutoff of 3% over 5 years using the KFRE as a threshold for triage of new referrals. Referrals who did not meet other prespecified criteria (such as pregnancy, suspected glomerulonephritis, etc) and had a kidney failure risk of <3% over 5 years were returned to primary care with recommendations based on diabetes and hypertension guidelines. The average wait time and number of consults seen between the pretriage (January 1, 2011, to December 31, 2011) and posttriage period (January 1, 2013, to December 31, 2013) were compared using a general linear model.In the pretriage period, the median number of referrals was 68/month (range: 44-76); this increased to 94/month (range: 61-147) in the posttriage period. In the posttriage period, 35% of referrals were booked as urgent, 31% as nonurgent, and 34% of referrals were not booked. The median wait times improved from 230 days (range: 126-355) in the pretriage period to 58 days (range: 48-69) in the posttriage period.We do not have long-term follow-up on patients triaged as low risk. Our study may not be applicable to nephrology teams operating under capacity without wait lists. We did not collect detailed information on all referrals in the pretriage period, so any differences in our pretriage and posttriage patient groups may be unaccounted for.Our risk-based triage scheme is an effective health policy tool that led to improved wait times and access to care for patients at highest risk of progression to kidney failure.

Project description:BackgroundPredicting allograft failure in kidney transplant recipients can help plan renal replacement therapy and guide patient-provider communication. The kidney failure risk equation (KFRE) accurately predicts the need for dialysis in patients with chronic kidney disease (CKD), but has not been validated in kidney transplant recipients.ObjectiveWe sought to validate the 4-variable KFRE (age, sex, estimated glomerular filtration rate [eGFR], and urine albumin-to-creatinine ratio [ACR]) for prediction of 2- and 5-year death-censored allograft failure.DesignRetrospective cohort study.SettingFour independent North American Cohorts from Ontario, Canada; Alberta, Canada; Manitoba, Canada; and Wisconsin, United States, between January 1999 and December 2017.PatientsAdult kidney transplant patients at 1-year posttransplantation.MeasurementsKidney failure risk as measured by the KFRE (eGFR, urine ACR, age, and sex).MethodsWe included all adult patients who had at least 1 serum creatinine and at least 1 urine ACR measurement approximately 1 year following kidney transplantation. The performance of the KFRE was evaluated using the area under the receiver operating characteristic curve (C-statistic). C-statistics from the 4 cohorts were meta-analyzed using random-effects models.ResultsA total of 3659 patients were included. Pooled C-statistics were good in the entire population, at 0.81 (95% confidence interval: 0.72-0.91) for the 2-year KFRE and 0.73 (0.67-0.80) for the 5-year KFRE. Discrimination improved among patients with poorer kidney function (eGFR < 45 mL/min/1.73 m2), with a C-statistic of 0.88 (0.78-0.98) for the 2-year KFRE and 0.83 (0.74-0.91) for the 5-year KFRE.LimitationsThe KFRE does not predict episodes of acute rejection and there was heterogeneity between cohorts.ConclusionsThe KFRE accurately predicts kidney failure in kidney transplant recipients at 1-year posttransplantation. Further validation in larger cohorts with longer follow-up times can strengthen the case for clinical implementation.

Project description:BACKGROUND:Patients with chronic kidney disease (CKD) are at high risk of end-stage kidney disease (ESKD). The Kidney Failure Risk Equation (KFRE), which predicts ESKD risk among patients with CKD, has not been validated in primary care clinics in Southeast Asia (SEA). Therefore, we aimed to (1) evaluate the performance of existing KFRE equations, (2) recalibrate KFRE for better predictive precision, and (3) identify optimally feasible KFRE thresholds for nephrologist referral and dialysis planning in SEA. METHODS:All patients with CKD visiting nine primary care clinics from 2010 to 2013 in Singapore were included and applied 4-variable KFRE equations incorporating age, sex, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR). ESKD onset within two and five years were acquired via linkage to the Singapore Renal Registry. A weighted Brier score (the squared difference between observed vs predicted ESKD risks), bias (the median difference between observed vs predicted ESKD risks) and precision (the interquartile range of the bias) were used to select the best-calibrated KFRE equation. RESULTS:The recalibrated KFRE (named Recalibrated Pooled KFRE SEA) performed better than existing and other recalibrated KFRE equations in terms of having a smaller Brier score (square root: 2.8% vs. 4.0-9.3% at 5?years; 2.0% vs. 6.1-9.1% at 2?years), less bias (2.5% vs. 3.3-5.2% at 5?years; 1.8% vs. 3.2-3.6% at 2?years), and improved precision (0.5% vs. 1.7-5.2% at 5?years; 0.5% vs. 3.8-4.2% at 2?years). Area under ROC curve for the Recalibrated Pooled KFRE SEA equations were 0.94 (95% confidence interval [CI]: 0.93 to 0.95) at 5 years and 0.96 (95% CI: 0.95 to 0.97) at 2 years. The optimally feasible KFRE thresholds were?>?10-16% for 5-year nephrologist referral and?>?45% for 2-year dialysis planning. Using the Recalibrated Pooled KFRE SEA, an estimated 82 and 89% ESKD events were included among 10% of subjects at highest estimated risk of ESKD at 5-year and 2-year, respectively. CONCLUSIONS:The Recalibrated Pooled KFRE SEA performs better than existing KFREs and warrants implementation in primary care settings in SEA.

Project description:Background and objectivesThe kidney failure risk equation is a clinical tool commonly used for prediction of progression from CKD to kidney failure. The kidney failure risk equation's accuracy in advanced CKD and whether this varies by CKD etiology remains unknown. This study examined the kidney failure risk equation's discrimination and calibration at 2 and 5 years among a large tertiary care population with advanced CKD from heterogeneous etiologies.Design, setting, participants, & measurementsThis retrospective cohort study included 1293 patients with advanced CKD (median eGFR 15 ml/min per 1.73 m2) referred to the Ottawa Hospital Multi-Care Kidney Clinic between 2010 and 2016, with follow-up clinical data available through 2018. Four-variable kidney failure risk equation scores for 2- and 5-year risks of progression to kidney failure (defined as dialysis or kidney transplantation) were calculated upon initial referral and correlated with the subsequent observed kidney failure incidence within these time frames. Receiver operating characteristic curves and calibration plots were used to measure the discrimination and calibration of the kidney failure risk equation both in the overall advanced CKD population and by CKD etiology: diabetic kidney disease, hypertensive nephrosclerosis, GN, polycystic kidney disease, and other. Pairwise comparisons of the receiver operating characteristic curves by CKD etiology were performed to compare kidney failure risk equation discrimination.ResultsThe kidney failure risk equation provided adequate to excellent discrimination in identifying patients with CKD likely to progress to kidney failure at the 2- and 5-year time points both overall (2-year area under the curve, 0.83; 95% confidence interval, 0.81 to 0.85; 5-year area under the curve, 0.81; 95% confidence interval, 0.77 to 0.84) and across CKD etiologies. The kidney failure risk equation displayed adequate calibration at the 2- and 5-year time points both overall and across CKD etiologies (Hosmer-Lemeshow P≥0.05); however, the predicted risks of kidney failure were higher than the observed risks across CKD etiologies with the exception of polycystic kidney disease.ConclusionsThe kidney failure risk equation provides adequate discrimination and calibration in advanced CKD and across CKD etiologies.

Project description:The Kidney Failure Risk Equation (KFRE) predicts the need for dialysis or transplantation using age, sex, estimated glomerular filtration rate (eGFR), and urine albumin to creatinine ratio (ACR). The eGFR and ACR have known biological and analytical variability. We examined the effect of biological and analytical variability of eGFR and ACR on the 2-year KFRE predicted kidney failure probabilities using single measure and the average of repeat measures of simulated eGFR and ACR. Previously reported values for coefficient of variation (CV) for ACR and eGFR were used to calculate day to day variability. Variation was also examined with outpatient laboratory data from patients with an eGFR between 15 and 50 mL/min/1.72 m2. A web application was developed to calculate and model day to day variation in risk. The biological and analytical variability related to ACR and eGFR lead to variation in the predicted probability of kidney failure. A male patient age 50, ACR 30 mg/mmol and eGFR 25, had a day to day variation in risk of 7% (KFRE point estimate: 17%, variability range 14% to 21%). The addition of inter laboratory variation due to different instrumentation increased the variability to 9% (KFRE point estimate 17%, variability range 13% to 22%). Averaging of repeated measures of eGFR and ACR significantly decreased the variability (KFRE point estimate 17%, variability range 15% to 19%). These findings were consistent when using outpatient laboratory data which showed that most patients had a KFRE 2-year risk variability of ? 5% (79% of patients). Approximately 13% of patients had variability from 5-10% and 8% had variability > 10%. The mean age (SD) of this cohort was 64 (15) years, 36% were females, the mean (SD) eGFR was 32 (10) ml/min/1.73m2 and median (IQR) ACR was 22.7 (110). Biological and analytical variation intrinsic to the eGFR and ACR may lead to a substantial degree of variability that decreases with repeat measures. Use of a web application may help physicians and patients understand individual patient's risk variability and communicate risk (https://mccudden.shinyapps.io/kfre_app/). The web application allows the user to alter age, gender, eGFR, ACR, CV (for both eGFR and ACR) as well as units of measurements for ACR (g/mol versus mg/g).

Dataset Information

Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.

Background

Objective

Methods

Results

Conclusions

Publications

Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.

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