Development and validation of GFR-estimating equations using diabetes, transplant and weight

Lesley A. Stevens, Christopher H. Schmid, Yaping L. Zhang, Josef Coresh, Jane Manzi, Richard Landis, Omran Bakoush, Gabriel Contreras, Saul Genuth, Goran B. Klintmalm, Emilio Poggio, Peter Rossing, Andrew D. Rule, Matthew R. Weir, John Kusek, Tom Greene, Andrew S. Levey

Research output: Contribution to journalArticle

85 Citations (Scopus)

Abstract

Background. We have reported a new equation (CKD-EPI equation) that reduces bias and improves accuracy for GFR estimation compared to the MDRD study equation while using the same four basic predictor variables: creatinine, age, sex and race. Here, we describe the development and validation of this equation as well as other equations that incorporate diabetes, transplant and weight as additional predictor variables.Methods. Linear regression was used to relate log-measured GFR (mGFR) to sex, race, diabetes, transplant, weight, various transformations of creatinine and age with and without interactions. Equations were developed in a pooled database of 10 studies 23 (N = 5504) for development and 13 (N = 2750) for internal validation, and final model selection occurred in 16 additional studies external validation (N = 3896).Results. The mean mGFR was 68, 67 and 68 mlmin 1.73 m 2 in the development, internal validation and external validation datasets, respectively. In external validation, an equation that included a linear age term and spline terms in creatinine to account for a reduction in the magnitude of the slope at low serum creatinine values exhibited the best performance (bias = 2.5, RMSE = 0.250) among models using the four basic predictor variables. Addition of terms for diabetes and transplant did not improve performance. Equations with weight showed a small improvement in the subgroup with BMI <20 kgm 2.Conclusions. The CKD-EPI equation, based on creatinine, age, sex and race, has been validated and is more accurate than the MDRD study equation. The addition of weight, diabetes and transplant does not significantly improve equation performance.

Original languageEnglish
Pages (from-to)449-457
Number of pages9
JournalNephrology Dialysis Transplantation
Volume25
Issue number2
DOIs
StatePublished - Feb 1 2010

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Creatinine
Transplants
Weights and Measures
Validation Studies
Linear Models
Databases
Serum

Keywords

  • Creatinine
  • Development
  • Estimating equation
  • Glomerular filtration rate
  • Validation

ASJC Scopus subject areas

  • Nephrology
  • Transplantation

Cite this

Stevens, L. A., Schmid, C. H., Zhang, Y. L., Coresh, J., Manzi, J., Landis, R., ... Levey, A. S. (2010). Development and validation of GFR-estimating equations using diabetes, transplant and weight. Nephrology Dialysis Transplantation, 25(2), 449-457. https://doi.org/10.1093/ndt/gfp510

Development and validation of GFR-estimating equations using diabetes, transplant and weight. / Stevens, Lesley A.; Schmid, Christopher H.; Zhang, Yaping L.; Coresh, Josef; Manzi, Jane; Landis, Richard; Bakoush, Omran; Contreras, Gabriel; Genuth, Saul; Klintmalm, Goran B.; Poggio, Emilio; Rossing, Peter; Rule, Andrew D.; Weir, Matthew R.; Kusek, John; Greene, Tom; Levey, Andrew S.

In: Nephrology Dialysis Transplantation, Vol. 25, No. 2, 01.02.2010, p. 449-457.

Research output: Contribution to journalArticle

Stevens, LA, Schmid, CH, Zhang, YL, Coresh, J, Manzi, J, Landis, R, Bakoush, O, Contreras, G, Genuth, S, Klintmalm, GB, Poggio, E, Rossing, P, Rule, AD, Weir, MR, Kusek, J, Greene, T & Levey, AS 2010, 'Development and validation of GFR-estimating equations using diabetes, transplant and weight', Nephrology Dialysis Transplantation, vol. 25, no. 2, pp. 449-457. https://doi.org/10.1093/ndt/gfp510
Stevens, Lesley A. ; Schmid, Christopher H. ; Zhang, Yaping L. ; Coresh, Josef ; Manzi, Jane ; Landis, Richard ; Bakoush, Omran ; Contreras, Gabriel ; Genuth, Saul ; Klintmalm, Goran B. ; Poggio, Emilio ; Rossing, Peter ; Rule, Andrew D. ; Weir, Matthew R. ; Kusek, John ; Greene, Tom ; Levey, Andrew S. / Development and validation of GFR-estimating equations using diabetes, transplant and weight. In: Nephrology Dialysis Transplantation. 2010 ; Vol. 25, No. 2. pp. 449-457.
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AU - Stevens, Lesley A.

AU - Schmid, Christopher H.

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AU - Manzi, Jane

AU - Landis, Richard

AU - Bakoush, Omran

AU - Contreras, Gabriel

AU - Genuth, Saul

AU - Klintmalm, Goran B.

AU - Poggio, Emilio

AU - Rossing, Peter

AU - Rule, Andrew D.

AU - Weir, Matthew R.

AU - Kusek, John

AU - Greene, Tom

AU - Levey, Andrew S.

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N2 - Background. We have reported a new equation (CKD-EPI equation) that reduces bias and improves accuracy for GFR estimation compared to the MDRD study equation while using the same four basic predictor variables: creatinine, age, sex and race. Here, we describe the development and validation of this equation as well as other equations that incorporate diabetes, transplant and weight as additional predictor variables.Methods. Linear regression was used to relate log-measured GFR (mGFR) to sex, race, diabetes, transplant, weight, various transformations of creatinine and age with and without interactions. Equations were developed in a pooled database of 10 studies 23 (N = 5504) for development and 13 (N = 2750) for internal validation, and final model selection occurred in 16 additional studies external validation (N = 3896).Results. The mean mGFR was 68, 67 and 68 mlmin 1.73 m 2 in the development, internal validation and external validation datasets, respectively. In external validation, an equation that included a linear age term and spline terms in creatinine to account for a reduction in the magnitude of the slope at low serum creatinine values exhibited the best performance (bias = 2.5, RMSE = 0.250) among models using the four basic predictor variables. Addition of terms for diabetes and transplant did not improve performance. Equations with weight showed a small improvement in the subgroup with BMI <20 kgm 2.Conclusions. The CKD-EPI equation, based on creatinine, age, sex and race, has been validated and is more accurate than the MDRD study equation. The addition of weight, diabetes and transplant does not significantly improve equation performance.

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KW - Development

KW - Estimating equation

KW - Glomerular filtration rate

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