Creatinine versus cystatin C for renal function-based mortality prediction in an elderly cohort: The Northern Manhattan Study
Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies...
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| Published in: | PLOS ONE Vol. 15; no. 1; p. e0226509 |
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| Main Authors: | , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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United States
Public Library of Science (PLoS)
01.01.2020
Public Library of Science |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics.
Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population.
The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years.
We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C.
The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr.
Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002).
In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality. |
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| AbstractList | Background Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics. Objective Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population. Design The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years. Participants We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C. Main measures The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr. Results Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002). Conclusions In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality. Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics. Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population. The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years. We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C. The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr. Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002). In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality. Background Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics. Objective Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population. Design The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years. Participants We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C. Main measures The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr. Results Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002). Conclusions In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality. Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics.BACKGROUNDEstimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in clinical practice, the use of cystatin-C to estimate GFR (eGFRcys) has demonstrated superior risk prediction in various populations. Prior studies that derived eGFR formulas have infrequently included high proportions of elderly, African-Americans, and Hispanics.Our objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population.OBJECTIVEOur objective as to compare mortality risk prediction using eGFRcr and eGFRcys in an elderly, race/ethnically diverse population.The Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years.DESIGNThe Northern Manhattan Study (NOMAS) is a multiethnic prospective cohort of elderly stroke-free individuals consisting of a total of 3,298 participants recruited between 1993 and 2001, with a median follow-up of 18 years.We included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C.PARTICIPANTSWe included all Northern Manhattan Study (NOMAS) participants with concurrent measured creatinine and cystatin-C.The eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr.MAIN MEASURESThe eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equations. The performance of each eGFR formula in predicting mortality risk was tested using receiver-operating characteristics, calibration and reclassification. Net reclassification improvement (NRI) was calculated based on the Reynolds 10 year risk score from adjusted Cox models with mortality as an outcome. The primary hypothesis was that eGFRcys would better predict mortality than eGFRcr.Participants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002).RESULTSParticipants (n = 2988) had a mean age of 69±10.2 years and were predominantly Hispanic (53%), overweight (69%), and current or former smokers (53% combined). The mean eGFRcr (74.68±18.8 ml/min/1.73m2) was higher than eGFRcys (51.72±17.2 ml/min/1.73m2). During a mean of 13.0±5.6 years of follow-up, 53% of the cohort had died. The AUC of eGFRcys (0.73) was greater than for eGFRcr (0.67, p for difference<0.0001). The proportions of correct reclassification (NRI) based on 10 year mortality for the model with eGFRcys compared to the model with eGFRcr were 4.2% (p = 0.002).In an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality.CONCLUSIONSIn an elderly, race/ethnically diverse cohort low eGFR is associated with risk of all-cause mortality. Estimated GFR based on serum cystatin-C, in comparison to serum creatinine, was a better predictor of all-cause mortality. |
| Author | S. Ali Husain Ken Cheung Yeseon P. Moon Joshua Z. Willey Ralph L. Sacco Myles Wolf Sumit Mohan Clinton B. Wright Mitchell S.V. Elkind |
| AuthorAffiliation | 4 Departments of Neurology and Public Health Sciences, Leonard M. Miller School of Medicine, the McKnight Brain Institute and the Neuroscience Program, University of Miami, Miami, FL, United States of America 1 Division of Nephrology, Vagelos College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, United States of America 2 Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, United States of America 3 Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America 5 Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States of America 6 Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States of America International University of Health and Welfare, School of Medicine, JAPAN |
| AuthorAffiliation_xml | – name: 5 Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States of America – name: 3 Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America – name: International University of Health and Welfare, School of Medicine, JAPAN – name: 1 Division of Nephrology, Vagelos College of Physicians and Surgeons, Columbia University Medical Center, New York, NY, United States of America – name: 6 Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States of America – name: 2 Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, United States of America – name: 4 Departments of Neurology and Public Health Sciences, Leonard M. Miller School of Medicine, the McKnight Brain Institute and the Neuroscience Program, University of Miami, Miami, FL, United States of America |
| Author_xml | – sequence: 1 givenname: Joshua Z. orcidid: 0000-0001-5180-2044 surname: Willey fullname: Willey, Joshua Z. – sequence: 2 givenname: Yeseon Park surname: Moon fullname: Moon, Yeseon Park – sequence: 3 givenname: S. Ali surname: Husain fullname: Husain, S. Ali – sequence: 4 givenname: Mitchell S. V. surname: Elkind fullname: Elkind, Mitchell S. V. – sequence: 5 givenname: Ralph L. surname: Sacco fullname: Sacco, Ralph L. – sequence: 6 givenname: Myles surname: Wolf fullname: Wolf, Myles – sequence: 7 givenname: Ken surname: Cheung fullname: Cheung, Ken – sequence: 8 givenname: Clinton B. surname: Wright fullname: Wright, Clinton B. – sequence: 9 givenname: Sumit orcidid: 0000-0002-5305-9685 surname: Mohan fullname: Mohan, Sumit |
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| Snippet | Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely used in... Background Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely... BACKGROUND:Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely... Background Estimated glomerular filtration rate (eGFR) is routinely utilized as a measure of renal function. While creatinine-based eGFR (eGFRcr) is widely... |
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| SubjectTerms | Age Aged Area Under Curve Biology and Life Sciences Blood pressure Body weight Calibration Cardiovascular disease Cohort Studies Creatinine Creatinine - blood Cystatin Cystatin C Cystatin C - blood Diabetes Elderly people Epidemiology Epidermal growth factor receptors Ethnicity Female Geriatrics Glomerular Filtration Rate Health risk assessment Health risks Health sciences Humans Hypertension Kidney Kidney - physiology Kidney Function Tests Male Medicine Medicine and Health Sciences Middle Aged Mortality Mortality risk Nephrology Neurology Neurosciences Older people Overweight People and Places Population studies Predictions Public health Q R Race Reclassification Renal function Research and Analysis Methods Research Article Risk Science Stroke Supervision Surgeons |
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| Title | Creatinine versus cystatin C for renal function-based mortality prediction in an elderly cohort: The Northern Manhattan Study |
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