Estimation of glomerular filtration rate by the MDRD study equation modified for Japanese patients with chronic kidney disease

Clinical and Experimental Nephrology volume 11, pages41–50(2007)Cite this article

Abstract

Background

Accurate estimation of the glomerular filtration rate (GFR) is crucial for the detection of chronic kidney disease (CKD). In clinical practice, GFR is estimated from serum creatinine using the Modification of Diet in Renal Disease (MDRD) study equation or the Cockcroft-Gault (CG) equation instead of the time-consuming method of measured clearance for exogenous markers such as inulin. In the present study, the equations originally developed for a Caucasian population were tested in Japanese CKD patients, and modified with the Japanese coefficient determined by the data.

Methods

The abbreviated MDRD study and CG equations were tested in 248 Japanese CKD patients and compared with measured inulin clearance (Cin) and estimated GFR (eGFR). The Japanese coefficient was determined by minimizing the sum of squared errors between eGFR and Cin. Serum creatinine values of the enzyme method in the present study were calibrated to values of the noncompensated Jaffé method by adding 0.207 mg/dl, because the original MDRD study equation was determined by the data for serum creatinine values measured by the noncompensated Jaffé method. The abbreviated MDRD study equation modified with the Japanese coefficient was validated in another set of 269 CKD patients.

Results

There was a significant discrepancy between measured Cin and eGFR by the 1.0 × MDRD or CG equations. The MDRD study equation modified with the Japanese coefficient (0.881 × MDRD) determined for Japanese CKD patients yielded lower mean difference and higher accuracy for GFR estimation. In particular, in Cin 30–59 ml/min per 1.73 m2, the mean difference was significantly smaller with the 0.881 × MDRD equation than that with the 1.0 × MDRD study equation (1.9 vs 7.9 ml/min per 1.73 m2; P <?0.01), and the accuracy was significantly higher, with 60% vs 39% of the points deviating within 15%, and 97% vs 87% of points within 50%, respectively (both P <?0.01). Validation with the different data set showed the correlation between eGFR and Cin was better with the 0.881 × MDRD equation than with the 1.0 × MDRD study equation. In Cin less than 60 ml/min per 1.73 m2, the accuracy was significantly higher, with 85% vs 69% of the points deviating within 50% (P <?0.01), respectively. The mean difference was also significantly smaller (P <?0.01). However, GFR values calculated by the 0.881 × MDRD equation were still underestimated in the range of Cin over 60 ml/min per 1.73 m2.

Conclusions

Although the Japanese coefficient improves the accuracy of GFR estimation of the original MDRD study equation, a new equation is needed for more accurate estimation of GFR in Japanese patients with CKD stages 3 and 4.

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References

  1. 1

    InstitutionalAuthorNameNational-Kidney-Foundation (2002) ArticleTitleK/DOQI Clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification Am J Kidney Dis 39 S1–S266 Occurrence Handle10.1053/ajkd.2002.32799

    Article  Google Scholar 

  2. 2

    A Levey K Eckardt Y Tsukamoto A Levin J Coresh J Rossert et al. (2005) ArticleTitleDefinition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO) Kidney Int 67 2089–100 Occurrence Handle15882252 Occurrence Handle10.1111/j.1523-1755.2005.00365.x

    PubMed  Article  Google Scholar 

  3. 3

    J Coresh B Astor T Greene G Eknoyan A Levey (2003) ArticleTitlePrevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey Am J Kidney Dis 41 1–2 Occurrence Handle12500213 Occurrence Handle10.1053/ajkd.2003.50007

    PubMed  Article  Google Scholar 

  4. 4

    A Levey J Bosch J Lewis T Green N Rogers D Roth (1999) ArticleTitleA more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation Ann Intern Med 130 461–70 Occurrence Handle10075613 Occurrence Handle1:CAS:528:DyaK1MXitFChs7k%3D

    PubMed  CAS  Google Scholar 

  5. 5

    J Lewis L Agodoa D Cheek T Green J Middleton D O'Connor et al. (2001) ArticleTitleComparison of cross-sectional renal function measurements in African-Americans with hypertensive nephrosclerosis and of primary formulas for estimating glomerular filtration rate Am J Kidney Dis 38 744–53 Occurrence Handle11576877 Occurrence Handle1:STN:280:DC%2BD3MrivF2ntg%3D%3D

    PubMed  CAS  Google Scholar 

  6. 6

    E Poggio X Wang T Greene F Van Lente P Hall (2005) ArticleTitlePerformance of the modification of diet in renal disease and Cockcroft-Gault equations in the estimation of GFR in health and in chronic kidney disease J Am Soc Nephrol 16 459–66 Occurrence Handle15615823 Occurrence Handle10.1681/ASN.2004060447

    PubMed  Article  Google Scholar 

  7. 7

    A Rule T Larson E Bergstralh J Slezak S Jacobsen F Cosio (2004) ArticleTitleUsing serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease Ann Intern Med 141 929–37 Occurrence Handle15611490 Occurrence Handle1:CAS:528:DC%2BD2MXks1Kmuw%3D%3D

    PubMed  CAS  Google Scholar 

  8. 8

    L Stevens J Coresh T Greene A Levey (2006) ArticleTitleAssessing kidney function N Engl J Med 354 2473–83 Occurrence Handle16760447 Occurrence Handle10.1056/NEJMra054415 Occurrence Handle1:CAS:528:DC%2BD28XlsVaiurk%3D

    PubMed  Article  CAS  Google Scholar 

  9. 9

    Y Orita F Gejyo M Sakatsume T Shiigai Y Maeda E Imai et al. (2005) ArticleTitleEstimation of glomerular filtration rate by inulin clearance: comparison with creatinine clearance Jpn J Nephrol 47 804–12 Occurrence Handle1:CAS:528:DC%2BD2MXht1CqsbrM

    CAS  Google Scholar 

  10. 10

    J Coresh BC Astor G McQuillan J Kusek T Greene F van Lente AS Levery (2002) ArticleTitleCalibration and random variation of the serum creatine assay as critical elements of using Equations to estimate glomerular filtration rate Am J Kidney Dis 39 920–2 Occurrence Handle11979335 Occurrence Handle10.1053/ajkd.2002.32765 Occurrence Handle1:CAS:528:DC%2BD38XktFWms7g%3D

    PubMed  Article  CAS  Google Scholar 

  11. 11

    Y Ma L Zuo J Chen Q Luo X Yu Y Li et al. (2006) ArticleTitleModified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease J Am Soc Nephrol 17 2937–44 Occurrence Handle16988059 Occurrence Handle10.1681/ASN.2006040368

    PubMed  Article  Google Scholar 

  12. 12

    GL Myers WG Miller J Coresh J Fleming N Greenberg T Greene et al. (2006) ArticleTitleRecommendations for improving serum cereatinine measurement: A report from the laboratory working group of the national kidney disease education program Clin Chem 52 5–18 Occurrence Handle16332993 Occurrence Handle10.1373/clinchem.2005.0525144 Occurrence Handle1:CAS:528:DC%2BD28XitlyhtQ%3D%3D

    PubMed  Article  CAS  Google Scholar 

  13. 13

    K Murthy L Stevens P Stark A Levey (2005) ArticleTitleVariation in the serum creatiine assay calibration: a practical application to glomerular filtration rate estimation Kidney Int 68 1884–7 Occurrence Handle16164667 Occurrence Handle10.1111/j.1523-1755.2005.00608.x Occurrence Handle1:CAS:528:DC%2BD2MXhtFequ7jM

    PubMed  Article  CAS  Google Scholar 

  14. 14

    L Zuo Y Ma Y Zhou M Wang G Xu H Wang (2005) ArticleTitleApplication of GFR-estimating equations in Chinese patients with chronic kidney disease Am J Kidney Dis 45 463–72 Occurrence Handle15754268 Occurrence Handle10.1053/j.ajkd.2004.11.012

    PubMed  Article  Google Scholar 

  15. 15

    T Jafer C Schmid A Levey (2005) ArticleTitleSerum creatinine as marker of of kidney function in south Asians: a study of reduced GFR in adults in Pakistan J Am Soc Nephrol 16 1413–9 Occurrence Handle10.1681/ASN.2004121100

    Article  Google Scholar 

  16. 16

    Y Kang K Han S Han H Kim D Cha (2005) ArticleTitleCharacteristics of population with normal serum creatinine and impared renal function: the validation of a MDRD formula in a healthy general general population Clin Nephrol 63 258–66 Occurrence Handle15847252 Occurrence Handle1:STN:280:DC%2BD2M3ht1yksg%3D%3D

    PubMed  CAS  Google Scholar 

  17. 17

    S Mahajan G Mukhiya R Singh S Tiwari V Kalra D Bhowmik et al. (2005) ArticleTitleAssessing glomerular filtration rate in healthy Indian adults: a comparison of various prediction equations J Nephrol 18 257–61 Occurrence Handle16013012

    PubMed  Google Scholar 

  18. 18

    R Lee Z Wang M Heo R Ross I Janssen S Heymsfield (2000) ArticleTitleTotal-body skeletal muscle mass: development and cross-validation of anthropometric prediction models Am J Clin Nutr 72 796–803 Occurrence Handle10966902 Occurrence Handle1:CAS:528:DC%2BD3cXmsFGrt7w%3D

    PubMed  CAS  Google Scholar 

  19. 19

    S Vickery P Stevens R Dalton F van Lante E Lamb (2006) ArticleTitleDoes the ID-MS traceable MDRD equation work and is it suitable for use with compensated Jaffé and enzymatic creatinine assay? Nephrol Dial Transplant 21 2439–45 Occurrence Handle16720592 Occurrence Handle10.1093/ndt/gfl249 Occurrence Handle1:CAS:528:DC%2BD28XhtVWlt77I

    PubMed  Article  CAS  Google Scholar 

  20. 20

    M Froissart J Rossert C Jacquot M Paillard P Houillier (2005) ArticleTitlePredictive performance of the modification of diet in renal disease and Cockcroft-Gault equations for estimating renal function J Am Soc Nephrol 16 763–73 Occurrence Handle15659562 Occurrence Handle10.1681/ASN.2004070549

    PubMed  Article  Google Scholar 

  21. 21

    R Perrone T Steinman G Beck C Skibinski H Royal M Lawlor L Hunsicker (1990) ArticleTitleUtility of radioisotopic filtration markers in chronic renal insufficiency: simultaneous comparison of 125I-iothalamate, 160Yb-DPTA, 99mTC-DTPA and inulin Am J Kidney Dis 16 224–35 Occurrence Handle2205098 Occurrence Handle1:CAS:528:DyaK3MXhvVWgu7g%3D

    PubMed  CAS  Google Scholar 

Download references

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Affiliations

  1. Department of Nephrology, Osaka University Graduate School of Medicine, Suita, Osaka, 565-0871, Japan

    Enyu Imai

  2. Department of Functional Diagnostic Science, Osaka University Graduate School of Medicine, Suita, Osaka, Japan

    Masaru Horio

  3. Fourth Department of Medicine, Tokyo Women's University of Medicine, Tokyo, Japan

    Kosaku Nitta

  4. Department of Nephrology, Institute of Clinical Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki, Japan

    Kunihiro Yamagata

  5. Dialysis Unit, University Hospital of The Ryukyus, Okinawa, Japan

    Kunitoshi Iseki

  6. Health Medical Center, Toranomon Hospital, Tokyo, Japan

    Shigeko Hara

  7. Second Department of Internal Medicine, Sapporo Medical University School of Medicine, Hokkaido, Japan

    Nobuyuki Ura

  8. Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

    Yutaka Kiyohara

  9. Nephrology and Dialysis Center, Fukuoka Red Cross Hospital, Fukuoka, Japan

    Hideki Hirakata

  10. Third Department of Medicine, Fukushima Medical University, Fukushima, Japan

    Tsuyoshi Watanabe

  11. Healthcare Center, Osaka University, Osaka, Japan

    Toshiki Moriyama

  12. Department of Nephrology, Jichi Medical School, Tochigi, Japan

    Yasuhiro Ando

  13. Tosei Hospital, Aichi, Japan

    Daiki Inaguma

  14. Division of Nephrology and Rheumatology, Niigata University, Niigata, Japan

    Ichiei Narita

  15. Department of Public Health, Osaka University Graduate School of Medicine, Osaka, Japan

    Hiroyasu Iso

  16. Aichi Cancer Institute, Aichi, Japan

    Kenji Wakai

  17. Department of Nephrology, Nagoya University Graduate School of Medicine, Aichi, Japan

    Yoshinari Yasuda & Seiichi Matsuo

  18. Syuwa General Hospital, Saitama, Japan

    Yusuke Tsukamoto

  19. Division of Nephrology, Endocrinology and Vascular Medicine, Tohoku University Graduate School of Medicine, Miyagai, Japan

    Sadayoshi Ito

  20. Department of Medicine and Clinical Science, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan

    Hirofumi Makino

  21. First Department of Medicine, Hamamatsu University School of Medicine, Shizuoka, Japan

    Akira Hishida

Authors
  1. Enyu Imai
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  2. Masaru Horio
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  3. Kosaku Nitta
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  5. Kunitoshi Iseki
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  8. Yutaka Kiyohara
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  13. Daiki Inaguma
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  14. Ichiei Narita
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  15. Hiroyasu Iso
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  16. Kenji Wakai
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  17. Yoshinari Yasuda
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  18. Yusuke Tsukamoto
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  19. Sadayoshi Ito
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  20. Hirofumi Makino
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  21. Akira Hishida
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  22. Seiichi Matsuo
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Corresponding author

Correspondence to Enyu Imai.

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Imai, E., Horio, M., Nitta, K. et al. Estimation of glomerular filtration rate by the MDRD study equation modified for Japanese patients with chronic kidney disease. Clin Exp Nephrol 11, 41–50 (2007). https://doi.org/10.1007/s10157-006-0453-4

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Key words

  • Serum creatinine
  • Inulin clearance
  • Glomerular filtration rate
  • Chronic kidney disease