Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients

Dominik Steubl; Li Fan; Wieneke M. Michels; Lesley A. Inker; Hocine Tighiouart; Friedo W. Dekker; Raymond T. Krediet; Andrew L. Simon; Meredith C. Foster; Amy B. Karger; John H. Eckfeldt; Hongyan Li; Jiamin Tang; Yongcheng He; Minyan Xie; Fei Xiong; Hongbo Li; Hao Zhang; Jing Hu; Yunhua Liao; Xudong Ye; Tariq Shafi; Wei Chen; Xueqing Yu; Andrew S. Levey

doi:10.1016/j.xkme.2019.04.002

Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients

Dominik Steubl, Li Fan, Wieneke M. Michels, Lesley A. Inker, Hocine Tighiouart, Friedo W. Dekker, Raymond T. Krediet, Andrew L. Simon, Meredith C. Foster, Amy B. Karger, John H. Eckfeldt, Hongyan Li, Jiamin Tang, Yongcheng He, Minyan Xie, Fei Xiong, Hongbo Li, Hao Zhang, Jing Hu, Yunhua LiaoXudong Ye, Tariq Shafi, Wei Chen, Xueqing Yu, Andrew S. Levey

Laboratory Medicine and Pathology

Research output: Contribution to journal › Article › peer-review

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Abstract

Rationale & Objective: Measurement of residual kidney function is recommended for the adjustment of the dialysis prescription, but timed urine collections are difficult and prone to errors. Equations to calculate residual kidney function from serum concentrations of endogenous filtration markers and demographic parameters would simplify monitoring of residual kidney function. However, few equations to estimate residual kidney function using serum concentrations of small solutes and low-molecular-weight proteins have been developed and externally validated. Study Design: Study of diagnostic test accuracy. Setting & Participants: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort). Tests Compared: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β₂-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations. Outcomes: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mCl_UN) and average of creatinine and urea nitrogen clearance (mCl_UN-cr). Results: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eCl_BTP, eCl_B2M, and eCl_BTP-B2M than eCl_UN-cr for both mCl_UN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mCl_UN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mCl_UN > 2.0 mL/min was highest for eCl_B2M (0.853) and eCl_BTP-B2M (0.848). Results were similar for other validated equations. Limitations: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement. Conclusions: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.

Original language	English (US)
Pages (from-to)	104-114
Number of pages	11
Journal	Kidney Medicine
Volume	1
Issue number	3
DOIs	https://doi.org/10.1016/j.xkme.2019.04.002
State	Published - May 1 2019

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Publisher Copyright:
© 2019 The Authors

Keywords

Residual kidney function
creatinine
hemodialysis
low-molecular-weight proteins
peritoneal dialysis

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Steubl, D., Fan, L., Michels, W. M., Inker, L. A., Tighiouart, H., Dekker, F. W., Krediet, R. T., Simon, A. L., Foster, M. C., Karger, A. B., Eckfeldt, J. H., Li, H., Tang, J., He, Y., Xie, M., Xiong, F., Li, H., Zhang, H., Hu, J., ... Levey, A. S. (2019). Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients. Kidney Medicine, 1(3), 104-114. https://doi.org/10.1016/j.xkme.2019.04.002

Steubl, D, Fan, L, Michels, WM, Inker, LA, Tighiouart, H, Dekker, FW, Krediet, RT, Simon, AL, Foster, MC, Karger, AB, Eckfeldt, JH, Li, H, Tang, J, He, Y, Xie, M, Xiong, F, Li, H, Zhang, H, Hu, J, Liao, Y, Ye, X, Shafi, T, Chen, W, Yu, X & Levey, AS 2019, 'Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients', Kidney Medicine, vol. 1, no. 3, pp. 104-114. https://doi.org/10.1016/j.xkme.2019.04.002

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title = "Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients",

abstract = "Rationale & Objective: Measurement of residual kidney function is recommended for the adjustment of the dialysis prescription, but timed urine collections are difficult and prone to errors. Equations to calculate residual kidney function from serum concentrations of endogenous filtration markers and demographic parameters would simplify monitoring of residual kidney function. However, few equations to estimate residual kidney function using serum concentrations of small solutes and low-molecular-weight proteins have been developed and externally validated. Study Design: Study of diagnostic test accuracy. Setting & Participants: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort). Tests Compared: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β2-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations. Outcomes: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mClUN) and average of creatinine and urea nitrogen clearance (mClUN-cr). Results: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eClBTP, eClB2M, and eClBTP-B2M than eClUN-cr for both mClUN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mClUN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mClUN > 2.0 mL/min was highest for eClB2M (0.853) and eClBTP-B2M (0.848). Results were similar for other validated equations. Limitations: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement. Conclusions: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.",

keywords = "Residual kidney function, creatinine, hemodialysis, low-molecular-weight proteins, peritoneal dialysis",

author = "Dominik Steubl and Li Fan and Michels, {Wieneke M.} and Inker, {Lesley A.} and Hocine Tighiouart and Dekker, {Friedo W.} and Krediet, {Raymond T.} and Simon, {Andrew L.} and Foster, {Meredith C.} and Karger, {Amy B.} and Eckfeldt, {John H.} and Hongyan Li and Jiamin Tang and Yongcheng He and Minyan Xie and Fei Xiong and Hongbo Li and Hao Zhang and Jing Hu and Yunhua Liao and Xudong Ye and Tariq Shafi and Wei Chen and Xueqing Yu and Levey, {Andrew S.}",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors",

year = "2019",

month = may,

day = "1",

doi = "10.1016/j.xkme.2019.04.002",

language = "English (US)",

volume = "1",

pages = "104--114",

journal = "Kidney Medicine",

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TY - JOUR

T1 - Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients

AU - Steubl, Dominik

AU - Fan, Li

AU - Michels, Wieneke M.

AU - Inker, Lesley A.

AU - Tighiouart, Hocine

AU - Dekker, Friedo W.

AU - Krediet, Raymond T.

AU - Simon, Andrew L.

AU - Foster, Meredith C.

AU - Karger, Amy B.

AU - Eckfeldt, John H.

AU - Li, Hongyan

AU - Tang, Jiamin

AU - He, Yongcheng

AU - Xie, Minyan

AU - Xiong, Fei

AU - Li, Hongbo

AU - Zhang, Hao

AU - Hu, Jing

AU - Liao, Yunhua

AU - Ye, Xudong

AU - Shafi, Tariq

AU - Chen, Wei

AU - Yu, Xueqing

AU - Levey, Andrew S.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Rationale & Objective: Measurement of residual kidney function is recommended for the adjustment of the dialysis prescription, but timed urine collections are difficult and prone to errors. Equations to calculate residual kidney function from serum concentrations of endogenous filtration markers and demographic parameters would simplify monitoring of residual kidney function. However, few equations to estimate residual kidney function using serum concentrations of small solutes and low-molecular-weight proteins have been developed and externally validated. Study Design: Study of diagnostic test accuracy. Setting & Participants: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort). Tests Compared: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β2-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations. Outcomes: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mClUN) and average of creatinine and urea nitrogen clearance (mClUN-cr). Results: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eClBTP, eClB2M, and eClBTP-B2M than eClUN-cr for both mClUN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mClUN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mClUN > 2.0 mL/min was highest for eClB2M (0.853) and eClBTP-B2M (0.848). Results were similar for other validated equations. Limitations: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement. Conclusions: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.

AB - Rationale & Objective: Measurement of residual kidney function is recommended for the adjustment of the dialysis prescription, but timed urine collections are difficult and prone to errors. Equations to calculate residual kidney function from serum concentrations of endogenous filtration markers and demographic parameters would simplify monitoring of residual kidney function. However, few equations to estimate residual kidney function using serum concentrations of small solutes and low-molecular-weight proteins have been developed and externally validated. Study Design: Study of diagnostic test accuracy. Setting & Participants: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort). Tests Compared: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β2-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations. Outcomes: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mClUN) and average of creatinine and urea nitrogen clearance (mClUN-cr). Results: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eClBTP, eClB2M, and eClBTP-B2M than eClUN-cr for both mClUN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mClUN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mClUN > 2.0 mL/min was highest for eClB2M (0.853) and eClBTP-B2M (0.848). Results were similar for other validated equations. Limitations: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement. Conclusions: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.

KW - Residual kidney function

KW - creatinine

KW - hemodialysis

KW - low-molecular-weight proteins

KW - peritoneal dialysis

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Development and Validation of Residual Kidney Function Estimating Equations in Dialysis Patients

Abstract

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Keywords

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