1
|
Ozrazgat-Baslanti T, Ren Y, Adiyeke E, Islam R, Hashemighouchani H, Ruppert M, Miao S, Loftus T, Johnson-Mann C, Madushani RWMA, Shenkman EA, Hogan W, Segal MS, Lipori G, Bihorac A, Hobson C. Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients. PLoS One 2024; 19:e0299332. [PMID: 38652731 PMCID: PMC11037544 DOI: 10.1371/journal.pone.0299332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/07/2024] [Indexed: 04/25/2024] Open
Abstract
Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non-race adjusted estimates. We developed two race-agnostic computable phenotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012-8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients. Using clinical adjudication, we validated race-agnostic computable phenotypes developed for preadmission CKD and AKI presence on 300 cases. Race adjustment reclassified 2,113 (8%) to no CKD and 7,901 (29%) to a less severe CKD stage compared to race-agnostic algorithm 1 and reclassified 1,208 (5%) to no CKD and 4,606 (18%) to a less severe CKD stage compared to race-agnostic algorithm 2. Of 12,451 AKI encounters based on race-agnostic algorithm 1, race adjustment reclassified 591 to No AKI and 305 to a less severe AKI stage. Of 12,251 AKI encounters based on race-agnostic algorithm 2, race adjustment reclassified 382 to No AKI and 196 (1.6%) to a less severe AKI stage. The phenotyping algorithm based on refit without race formula performed well in identifying patients with CKD and AKI with a sensitivity of 100% (95% confidence interval [CI] 97%-100%) and 99% (95% CI 97%-100%) and a specificity of 88% (95% CI 82%-93%) and 98% (95% CI 93%-100%), respectively. Race-agnostic algorithms identified substantial proportions of additional patients with CKD and AKI compared to race-adjusted algorithm in African American patients. The phenotyping algorithm is promising in identifying patients with kidney disease and improving clinical decision-making.
Collapse
Affiliation(s)
- Tezcan Ozrazgat-Baslanti
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Yuanfang Ren
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Esra Adiyeke
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Rubab Islam
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Haleh Hashemighouchani
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Matthew Ruppert
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Shunshun Miao
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Tyler Loftus
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Surgery, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Crystal Johnson-Mann
- Department of Surgery, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - R. W. M. A. Madushani
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Elizabeth A. Shenkman
- University of Florida Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, United States of America
| | - William Hogan
- University of Florida Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, United States of America
| | - Mark S. Segal
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Gloria Lipori
- University of Florida Health, Gainesville, Florida, United States of America
| | - Azra Bihorac
- University of Florida Intelligent Clinical Care Center (IC3), Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Charles Hobson
- Department of Health Services Research, Management and Policy, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
| |
Collapse
|
2
|
Fu EL, Levey AS, Coresh J, Grams ME, Faucon AL, Elinder CG, Dekker FW, Delanaye P, Inker LA, Carrero JJ. Accuracy of GFR estimating equations based on creatinine, cystatin C or both in routine care. Nephrol Dial Transplant 2024; 39:694-706. [PMID: 37813817 DOI: 10.1093/ndt/gfad219] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND New equations to estimate glomerular filtration rate based on creatinine (eGFRcr), cystatin C (eGFRcys) or both (eGFRcr-cys) have been developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the European Kidney Function Consortium (EKFC). There is a need to evaluate the performance of these equations in diverse European settings to inform implementation decisions, especially among people with key comorbid conditions. METHODS We performed a cross-sectional study including 6174 adults referred for single-point plasma clearance of iohexol in Stockholm, Sweden, with 9579 concurrent measurements of creatinine and cystatin C. We assessed the performance of the CKD-EPI 2009/2012/2021, EKFC 2021/2023, revised Lund-Malmö (RLM) 2011 and Caucasian, Asian, Pediatric and Adult (CAPA) 2014 equations against measured GFR (mGFR). RESULTS Mean age was 56 years, median mGFR was 62 mL/min/1.73 m2 and 40% were female. Comorbid conditions were common: cardiovascular disease (30%), liver disease (28%), diabetes (26%) and cancer (26%). All eGFRcr-cys equations had small bias and P30 (the percentage of estimated values within 30% of mGFR) close to 90%, and performed better than eGFRcr or eGFRcys equations. Among eGFRcr equations, CKD-EPI 2009 and CKD-EPI 2021 showed larger bias and lower P30 than EKFC 2021 and RLM. There were no meaningful differences in performance across eGFRcys equations. Findings were consistent across comorbid conditions, and eGFRcr-cys equations showed good performance in patients with liver disease, cancer and heart failure. CONCLUSIONS In conclusion, eGFRcr-cys equations performed best, with minimal variation among equations in this Swedish cohort. The lower performance of CKD-EPI eGFRcr equations compared with EKFC and RLM may reflect differences in population characteristics and mGFR methods. Implementing eGFRcr equations will require a trade-off between accuracy and uniformity across regions.
Collapse
Affiliation(s)
- Edouard L Fu
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrew S Levey
- Division of Nephrology, Department of Internal Medicine, Tufts Medical Center, Boston, MA, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Morgan E Grams
- Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Anne-Laure Faucon
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- INSERM UMR 1018, Department of Clinical Epidemiology, Paris-Saclay University, Paris, France
| | - Carl-Gustaf Elinder
- Division of Renal Medicine, Department of Clinical Intervention, and Technology, Karolinska University Hospital and Karolinska Institute, Stockholm, Sweden
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pierre Delanaye
- Department of Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman, Liège, Belgium
- Department of Nephrology-Dialysis-Apheresis, Hôpital Universitaire Carémeau, Nîmes, France
| | - Lesley A Inker
- Division of Nephrology, Department of Internal Medicine, Tufts Medical Center, Boston, MA, USA
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Division of Nephrology, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
3
|
Escribano-Serrano J, Jiménez-Varo E, Escribano-Cobalea M, López-Ceres A, Casto-Jarillo C, Hormigo-Pozo A, Michán-Doña A. Is the use of the new Chronic Kidney Disease Epidemiology Consortium (CKD-EPI 2021) formula appropriate for the Spanish population? Rev Clin Esp 2023; 223:144-153. [PMID: 36796634 DOI: 10.1016/j.rceng.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/17/2022] [Indexed: 02/16/2023]
Abstract
INTRODUCTION United States nephrology societies recommend changing from the CKD-EPI 2009 equation to the new CKD-EPI 2021 equation, which does not include the race coefficient, for calculating estimated glomerular filtration rate (eGFR). It is unknown how this change might affect the distribution of kidney disease in the predominantly Caucasian Spanish population. METHODS Two databases of adults from the province of Cádiz, DB-SIDICA (N=264,217) and DB-PANDEMIA (N=64,217), that had plasma creatinine measurements recorded between 2017 and 2021 were studied. Changes in eGFR and the consequent reclassification into different categories of the KDIGO 2012 classification resulting from substituting the CKD-EPI 2009 equation for the 2021 equation were calculated. RESULTS Compared to the 2009 equation, CKD-EPI 2021 yielded a higher eGFR, with a median of 3.8mL/min/1.73m2 (IQR 2.98-4.48) in DB-SIDICA and 3.89mL/min/1.73m2 (IQR 3.05-4.55) in DB-PANDEMIA. The first consequence was that 15.3% of the total population in DB-SIDICA and 15.1% of the total population in DB-PANDEMIA were reclassified into a higher category of eGFR, as were 28.1% and 27.3%, respectively, of the population with CKD (G3-G5); no subjects were classified into the more severe category. The second consequence was that the prevalence of kidney disease decreased from 9% to 7.5% in both cohorts. CONCLUSIONS Implementing the CKD-EPI 2021 equation in the Spanish population, which is predominantly Caucasian, would increase eGFR by a modest amount (greater in men and those who are older or have a higher GFR). A significant proportion of the population would be classified into a higher eGFR category, with a consequent decrease in the prevalence of kidney disease.
Collapse
Affiliation(s)
- J Escribano-Serrano
- Unidad de Gestión Clínica San Roque, Área de Gestión Sanitaria Campo de Gibraltar Este, Cádiz, Spain; Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain.
| | - E Jiménez-Varo
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Unidad de Gestión Clínica Laboratorio Análisis Clínicos, Hospital La Línea, Área de Gestión Sanitaria Campo de Gibraltar Este, Cádiz, Spain
| | - M Escribano-Cobalea
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Unidad de Gestión Clínica Obstetricia y Ginecología, Hospital Punta Europa de Algeciras, Área de Gestión Clínica Campo de Gibraltar Oeste, Cádiz, Spain
| | - A López-Ceres
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Unidad de Gestión Clínica Laboratorio Análisis Clínicos, Hospital La Línea, Área de Gestión Sanitaria Campo de Gibraltar Este, Cádiz, Spain
| | - C Casto-Jarillo
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Unidad de Gestión Clínica Laboratorio Análisis Clínicos, Hospital La Línea, Área de Gestión Sanitaria Campo de Gibraltar Este, Cádiz, Spain
| | - A Hormigo-Pozo
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Unidad de Gestión Clínica San Andrés-Torcal, Área de Gestión Sanitaria Málaga Guadalhorce, Málaga, Spain
| | - A Michán-Doña
- Instituto de Investigación e Innovación Biomédica de Cádiz (INIBICA), Cádiz, Spain; Departamento de Medicina, Hospital Universitario de Jerez, Área de Gestión Sanitaria Norte de Cádiz, Cádiz, Spain
| | | |
Collapse
|
4
|
Escribano-Serrano J, Jiménez-Varo E, Escribano-Cobalea M, López-Ceres A, Casto-Jarillo C, Hormigo-Pozo A, Michán-Doña A. ¿Es apropiada la aplicación de la nueva ecuación Chronic Kidney Disease Epidemiology Consortium (CKD-EPI 2021) en la población española? Rev Clin Esp 2023. [DOI: 10.1016/j.rce.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
|
5
|
Fu EL, Coresh J, Grams ME, Clase CM, Elinder CG, Paik J, Ramspek CL, Inker LA, Levey AS, Dekker FW, Carrero JJ. Removing race from the CKD-EPI equation and its impact on prognosis in a predominantly White European population. Nephrol Dial Transplant 2022; 38:119-128. [PMID: 35689668 PMCID: PMC9869854 DOI: 10.1093/ndt/gfac197] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND While American nephrology societies recommend using the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimated glomerular filtration rate (eGFR) equation without a Black race coefficient, it is unknown how this would impact disease distribution, prognosis and kidney failure risk prediction in predominantly White non-US populations. METHODS We studied 1.6 million Stockholm adults with serum/plasma creatinine measurements between 2007 and 2019. We calculated changes in eGFR and reclassification across KDIGO GFR categories when changing from the 2009 to 2021 CKD-EPI equation; estimated associations between eGFR and the clinical outcomes kidney failure with replacement therapy (KFRT), (cardiovascular) mortality and major adverse cardiovascular events using Cox regression; and investigated prognostic accuracy (discrimination and calibration) of both equations within the Kidney Failure Risk Equation. RESULTS Compared with the 2009 equation, the 2021 equation yielded a higher eGFR by a median [interquartile range (IQR)] of 3.9 (2.9-4.8) mL/min/1.73 m2, which was larger at older age and for men. Consequently, 9.9% of the total population and 36.2% of the population with CKD G3a-G5 was reclassified to a higher eGFR category. Reclassified individuals exhibited a lower risk of KFRT, but higher risks of all-cause/cardiovascular death and major adverse cardiovascular events, compared with non-reclassified participants of similar eGFR. eGFR by both equations strongly predicted study outcomes, with equal discrimination and calibration for the Kidney Failure Risk Equation. CONCLUSIONS Implementing the 2021 CKD-EPI equation in predominantly White European populations would raise eGFR by a modest amount (larger at older age and in men) and shift a major proportion of CKD patients to a higher eGFR category. eGFR by both equations strongly predicted outcomes.
Collapse
Affiliation(s)
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA,Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Catherine M Clase
- Departments of Medicine and Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Carl-Gustaf Elinder
- Division of Renal Medicine, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden
| | - Julie Paik
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Chava L Ramspek
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Lesley A Inker
- Division of Nephrology, Tufts Medical Center, Boston, MA, USA
| | - Andrew S Levey
- Division of Nephrology, Tufts Medical Center, Boston, MA, USA
| | - Friedo W Dekker
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Juan J Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
6
|
Casal MA, Ivy SP, Beumer JH, Nolin TD. Effect of removing race from glomerular filtration rate-estimating equations on anticancer drug dosing and eligibility: a retrospective analysis of National Cancer Institute phase 1 clinical trial participants. Lancet Oncol 2021; 22:1333-1340. [PMID: 34399096 PMCID: PMC8425175 DOI: 10.1016/s1470-2045(21)00377-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND Kidney function assessment by estimated glomerular filtration rate (eGFR) equations, such as the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation, is important to determine dosing and eligibility for anticancer drugs. Inclusion of race in eGFR equations calculates a higher eGFR at a given serum creatinine concentration for Black patients versus non-Black patients. We aimed to characterise the effect of removing race from the CKD-EPI equation on dosing and eligibility of anticancer drugs with kidney function cutoffs. METHODS We did a retrospective analysis of patients enrolled in phase 1 studies sponsored by the Cancer Therapy Evaluation Program between January, 1995, and October, 2010. eGFR based on creatinine (eGFRCr) was calculated by the CKD-EPI equation and a version of the CKD-EPI equation without the race term (CKD-EPIwithout race). Estimated creatinine clearance (eClCr) was calculated by the Cockcroft-Gault equation. Dosing simulations based on each assessment of kidney function were done for ten anticancer drugs with kidney function cutoffs for dosing (oxaliplatin, capecitabine, etoposide, topotecan, fludarabine, and bleomycin) or eligibility (cisplatin, pemetrexed, bendamustine, and mitomycin) based on labelling approved by the US Food and Drug Administration or consensus guidelines. The absolute proportion of patients eligible or in each renal dosing range was calculated for each drug. Eligibility and dosing discordance rates were also calculated. FINDINGS Demographics and laboratory values from 340 Black patients (172 men and 168 women) were used. Median age was 57 years (IQR 47-64), median bodyweight was 78·1 kg (67·0-89·8), median body surface area was 1·91 m2 (1·77-2·09), and median serum creatinine concentration was 0·9 mg/dL (0·8-1·1). Median eGFRCr or eClCr was 103 mL/min (85-122) calculated by CKD-EPI, 89 mL/min (73-105) by CKD-EPIwithout race, and 90 mL/min (72-120) by Cockcroft-Gault. Black patients were recommended to receive dose reductions or were rendered ineligible to receive drug more frequently when using CKD-EPIwithout race than when using CKD-EPI, but at a similar rate as when using Cockcroft-Gault. The number of patients ineligible for therapy or recommended to receive any renal dose adjustment when CKD-EPIwithout race versus CKD-EPI was used increased by 72% (from 25 of 340 to 43 of 340 patients) for cisplatin, by 120% (from five to 11) for pemetrexed, by 67% (from three to five) for bendamustine, by 150% (from ten to 25) for capecitabine, by 150% (from ten to 25) for etoposide, by 67% (from three to five) for topotecan, by 61% (from 74 to 119) for fludarabine, and by 163% (from eight to 21) for bleomycin. Up to 18% of patients had discordant recommendations using CKD-EPIwithout race versus CKD-EPI. INTERPRETATION Removing race from the CKD-EPI equation will calculate a lower eGFR for Black patients and exclude more patients from receiving anticancer therapy, which could lead to undertreatment of Black patients with cancer and adversely affect their outcomes. FUNDING National Institutes of Health.
Collapse
Affiliation(s)
- Morgan A Casal
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - S Percy Ivy
- Investigational Drug Branch, Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Jan H Beumer
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA; Hematology/Oncology Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Cancer Therapeutics Program, UPMC Hillman Cancer Center, Pittsburgh, PA, USA
| | - Thomas D Nolin
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA; Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| |
Collapse
|