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Original Research |

Two Novel Equations to Estimate Kidney Function in Persons Aged 70 Years or Older

Elke S. Schaeffner, MD, MS*; Natalie Ebert, MD, MPH*; Pierre Delanaye, MD, PhD; Ulrich Frei, MD; Jens Gaedeke, MD; Olga Jakob; Martin K. Kuhlmann, MD; Mirjam Schuchardt, PhD; Markus Tölle, MD; Reinhard Ziebig, PhD; Markus van der Giet, MD; and Peter Martus, PhD
[+] Article and Author Information

From Charité University Medicine, Campi Virchow, Mitte, and Benjamin Franklin, Institute of Biostatistics and Clinical Epidemiology, Vivantes Klinikum im Friedrichshain, Labor Berlin, Institute of Laboratory Medicine, Clinical Chemistry and Pathobiochemistry, Berlin, Germany; University of Liège, Centre Hospitalier Universitaire du Sart-Tilman, Liège, Belgium; and Institute of Medical Biostatistics, UKT Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany.

Acknowledgment: The authors thank their colleagues at the 13 study sites in Berlin for providing the necessary infrastructure for the study and Dirk Wiesenthal, MSc (bioinformatics), for statistical programming. They also thank the health insurance fund AOK Nordost-Die Gesundheitskasse for its continuous cooperation and technical support and the participants of the BIS for their participation and commitment.

Grant Support: By the Kuratorium für Dialyse und Nierentransplatation (KfH) Foundation of Preventive Medicine and the Dr. Werner Jackstädt Foundation.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-0477.

Reproducible Research Statement: Study protocol: Available from Dr. Schaeffner (e-mail, elke.schaeffner@charite.de). Statistical code and data set: Not available.

Requests for Single Reprints: Elke S. Schaeffner, MD, MS, Charité Hospital, Campus Virchow Klinikum, Division of Nephrology and Intensive Care Medicine, Augustenburger Platz 1, 13353 Berlin, Germany; e-mail, elke.schaeffner@charite.de.

Current Author Addresses: Drs. Schaeffner, Ebert, and Frei: Division of Nephrology and Intensive Care Medicine, Charité Campus Virchow, Augustenburger Platz 1, 13353 Berlin, Germany.

Dr. Delanaye: Department of Nephrology-Dialysis-Transplantation, University of Liège, Centre Hospitalier Universitaire du Sart-Tilman, 4000 Liège, Belgium.

Dr. Gaedeke: Division of Nephrology, Charité Campus Mitte, Charitéplatz 1, 10117 Berlin, Germany.

Ms. Jakob: Institute for Biostatistics and Clinical Epidemiology, Charité Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany.

Dr. Kuhlmann: Department of Nephrology, Vivantes Klinikum im Friedrichshain, Landsberger Allee 49, 10249 Berlin, Germany.

Drs. Schuchardt, Tölle, and van der Giet: Division of Nephrology and Endocrinology, Charité Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany.

Dr. Ziebig: Campus Virchow, Augustenburger Platz 1, 13353 Berlin, Germany.

Dr. Martus: Institute of Medical Biostatistics, Eberhard Karls University Tübingen, Silcherstrasse 5, 72078 Tübingen.

Author Contributions: Conception and design: E.S. Schaeffner, N. Ebert, M.K. Kuhlmann, M. van der Giet, P. Martus.

Analysis and interpretation of the data: E.S. Schaeffner, N. Ebert, P. Delanaye, U. Frei, J. Gaedeke, O. Jakob, M.K. Kuhlmann, M. Schuchardt, M. Tölle, R. Ziebig, M. van der Giet, P. Martus.

Drafting of the article: E.S. Schaeffner, N. Ebert, P. Martus.

Critical revision of the article for important intellectual content: E.S. Schaeffner, N. Ebert, P. Delanaye, U. Frei, J. Gaedeke, O. Jakob, M.K. Kuhlmann, M. Schuchardt, M. Tölle, R. Ziebig, M. van der Giet, P. Martus.

Final approval of the article: E.S. Schaeffner, N. Ebert, P. Delanaye, U. Frei, J. Gaedeke, O. Jakob, M.K. Kuhlmann, M. Schuchardt, M. Tölle, R. Ziebig, M. van der Giet, P. Martus.

Provision of study materials or patients: E.S. Schaeffner, N. Ebert, J. Gaedeke, M. van der Giet.

Statistical expertise: E.S. Schaeffner, P. Delanaye, O. Jakob, P. Martus.

Obtaining of funding: E.S. Schaeffner, N. Ebert, J. Gaedeke, M.K. Kuhlmann, M. van der Giet, P. Martus.

Administrative, technical, or logistic support: E.S. Schaeffner, N. Ebert, U. Frei, M. Schuchardt, R. Ziebig, M. van der Giet.

Collection and assembly of data: E.S. Schaeffner, N. Ebert, M. Tölle, M. van der Giet.


Ann Intern Med. 2012;157(7):471-481. doi:10.7326/0003-4819-157-7-201210020-00003
Text Size: A A A

Background: In older adults, current equations to estimate glomerular filtration rate (GFR) are not validated and may misclassify elderly persons in terms of their stage of chronic kidney disease.

Objective: To derive the Berlin Initiative Study (BIS) equation, a novel estimator of GFR in elderly participants.

Design: Cross-sectional. Data were split for analysis into 2 sets for equation development and internal validation.

Setting: Random community-based population of a large insurance company.

Participants: 610 participants aged 70 years or older (mean age, 78.5 years).

Intervention: Iohexol plasma clearance measurement as gold standard.

Measurements: GFR, measured as the plasma clearance of the endogenous marker iohexol, to compare performance of existing equations of estimated GFR with measured GFR of the gold standard; estimation of measured GFR from standardized creatinine and cystatin C levels, sex, and age in the learning sample; and comparison of the BIS equations (BIS1: creatinine-based; BIS2: creatinine- and cystatin C–based) with other estimating equations and determination of bias, precision, and accuracy in the validation sample.

Results: The new BIS2 equation yielded the smallest bias followed by the creatinine-based BIS1 and Cockcroft–Gault equations. All other equations considerably overestimated GFR. The BIS equations confirmed a high prevalence of persons older than 70 years with a GFR less than 60 mL/min per 1.73 m2 (BIS1, 50.4%; BIS2, 47.4%; measured GFR, 47.9%). The total misclassification rate for this criterion was smallest for the BIS2 equation (11.6%), followed by the cystatin C equation 2 (15.1%) proposed by the Chronic Kidney Disease Epidemiology Collaboration. Among the creatinine-based equations, BIS1 had the smallest misclassification rate (17.2%), followed by the Chronic Kidney Disease Epidemiology Collaboration equation (20.4%).

Limitation: There was no validation by an external data set.

Conclusion: The BIS2 equation should be used to estimate GFR in persons aged 70 years or older with normal or mild to moderately reduced kidney function. If cystatin C is not available, the BIS1 equation is an acceptable alternative.

Primary Funding Source: Kuratorium für Dialyse und Nierentransplatation (KfH) Foundation of Preventive Medicine.

Figures

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Appendix Figure.

Models with change of slope for creatinine.

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Figure 1.

Comparison of mGFR with eGFR equations in the validation sample.

Boxes indicate medians (line inside box), quartiles (upper and lower margins of box). Antennae are defined by the rule upper–lower box margin ± 1.5 × interquartile range. Circles indicate outliers. The dotted line represents the GFR cutoff of 60 mL/min per 1.73 m2. For estimating equations, refer to Appendix 2. Standardized cystatin C values were converted by formula (−0.105 + 1.13 × cystatin C) before being used for the equations CysC1, CysC2, and CysC3. BIS = Berlin Initiative Study; BSA = body surface area; CKD-EPI = Chronic Kidney Disease Epidemiology; CysC = cystatin C; eGFR = estimated glomerular filtration rate; GFR = glomerular filtration rate; MDRD = Modification of Diet in Renal Disease; mGFR = measured glomerular filtration rate.

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Figure 2.

Estimated GFR progression with age in persons aged 70 y or older.

Quadratically smoothed estimated GFR, by age, for men and women of the iohexol population of the BIS. For estimating equations, refer to Appendix 2. BIS = Berlin Initiative Study; GFR = glomerular filtration rate.

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Figure 3.

Performance of GFR-estimating equations in the validation sample.

The figure differs from Bland–Altman plots in choosing eGFR instead of mean eGFR and mGFR for the x-axis. This type of display emphasizes the predictive nature of the equation for eGFR. Moreover, the fit of both the bias and the limits of agreement were done by cubic regression. Thus, estimates may be less accurate for extremely low or high values of eGFR. Local estimation was not feasible because of the moderate sample size. For estimating equations, refer to Appendix 2. Standardized cystatin C values were converted by formula (−0.105 + 1.13 × cystatin C) before being used for the equation CysC2. BIS = Berlin Initiative Study; CKD-EPI = Chronic Kidney Disease Epidemiology; CysC = cystatin C; eGFR = estimated glomerular filtration rate; GFR = glomerular filtration rate; MDRD = Modification of Diet in Renal Disease; mGFR = measured glomerular filtration rate.

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