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International Urology and Nephrology

, Volume 50, Issue 4, pp 733–743 | Cite as

Comparative evaluation of technetium-99m-diethylenetriaminepentaacetic acid renal dynamic imaging versus the Modification of Diet in Renal Disease equation and the Chronic Kidney Disease Epidemiology Collaboration equation for the estimation of GFR

  • Qi Huang
  • Yunshuang Chen
  • Min Zhang
  • Sihe Wang
  • Weiguang Zhang
  • Guangyan Cai
  • Xiangmei Chen
  • Xuefeng Sun
Nephrology - Original Paper
First Online:
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Accepted:

Abstract

Purpose

We compared the performance of technetium-99m-diethylenetriaminepentaacetic acid (99mTc-DTPA) renal dynamic imaging (RDI), the MDRD equation, and the CKD EPI equation to estimate glomerular filtration rate (GFR).

Methods

A total of 551 subjects, including CKD patients and healthy individuals, were enrolled in this study. Dual plasma sample clearance method of 99mTc-DTPA was used as the true value for GFR (tGFR). RDI and the MDRD and CKD EPI equations for estimating GFR were compared and evaluated.

Results

Data indicate that RDI and the MDRD equation underestimated GFR and CKD EPI overestimated GFR. RDI was associated with significantly higher bias than the MDRD and CKD EPI equations. The regression coefficient, diagnostic precision, and consistency of RDI were significantly lower than either equation. RDI and the MDRD equation underestimated GFR to a greater degree in subjects with tGFR ≥ 90 ml/min/1.73 m2 compared with the results obtained from all subjects. In the tGFR60-89 ml/min/1.73 m2 group, the precision of RDI was significantly lower than that of both equations. In the tGFR30-59 ml/min/1.73 m2 group, RDI had the least bias, the most precision, and significantly higher accuracy compared with either equation. In tGFR < 30 ml/min/1.73 m2, the three methods had similar performance and were not significantly different.

Conclusions

RDI significantly underestimates GFR and performs no better than MDRD and CKD EPI equations for GFR estimation; thus, it should not be recommended as a reference standard against which other GFR measurement methods are assessed. However, RDI better estimates GFR than either equation for individuals in the tGFR30-59 ml/min/1.73 m2 group and thus may be helpful to distinguish stage 3a and 3b CKD.

Keywords

Renal dynamic imaging (RDI) Glomerular filtration rate (GFR) Modification of Diet in Renal Disease (MDRD) equation Chronic Kidney Disease Epidemiology Collaboration (CKD EPI) equation 
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Notes

Funding

This work was supported by the grants from the Major State Basic Research Development Program of China (2013CB530800), National Natural Science Foundation of China (81270819), National Key Technology R&D Program (2011BAI10B00). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  1. 1.
    Blaufox MD, Aurell M, Bubeck B, Fommei E, Piepsz A, Russell C et al (1996) Report of the Radionuclides in Nephrourology Committee on renal clearance. J Nucl Med 37:1883–1890PubMedGoogle Scholar
  2. 2.
    Gates GF (1983) Split renal function testing using Tc-99m DTPA. A rapid technique for determining differential glomerular filtration. Clin Nucl Med 8:400–407CrossRefPubMedGoogle Scholar
  3. 3.
    Frennby B, Almén T, Lilja B, Eriksson LG, Hellsten S, Lindblad B et al (1995) Determination of the relative glomerular filtration rate of each kidney in man. Comparison between iohexol CT and 99mTc-DTPA scintigraphy. Acta Radiol 36:410–417PubMedGoogle Scholar
  4. 4.
    Xie P, Huang JM, Liu XM, Wu WJ, Pan LP, Lin HY (2013) (99m)Tc-DTPA renal dynamic imaging method may be unsuitable to be used as the reference method in investigating the validity of CDK-EPI equation for determining glomerular filtration rate. PLoS ONE 8:e62328CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Uribe D, Krawiec DR, Twardock AR, Gelberg HB (1992) Quantitative renal scintigraphic determination of the glomerular filtration rate in cats with normal and abnormal kidney function, using 99mTc-diethylenetriaminepentaacetic acid. Am J Vet Res 53:1101–1107PubMedGoogle Scholar
  6. 6.
    Barthez PY, Hornof WJ, Cowgill LD, Neal LA, Mickel P (1998) Comparison between the scintigraphic uptake and plasma clearance of 99mTc-diethylenetriaminepentacetic acid (DTPA) for the evaluation of the glomerular filtration rate in dogs. Vet Radiol Ultrasound 39:470–474CrossRefPubMedGoogle Scholar
  7. 7.
    De Santo NG, Anastasio P, Cirillo M, Santoro D, Spitali L, Mansi L et al (1999) Measurement of glomerular filtration rate by the 99mTc-DTPA renogram is less precise than measured and predicted creatinine clearance. Nephron 81:136–140CrossRefPubMedGoogle Scholar
  8. 8.
    Itoh K (2003) Comparison of methods for determination of glomerular filtration rate: Tc-99m-DTPA renography, predicted creatinine clearance method and plasma sample method. Ann Nucl Med 17:561–565CrossRefPubMedGoogle Scholar
  9. 9.
    Goates JJ, Morton KA, Whooten WW, Greenberg HE, Datz FL, Handy JE et al (1990) Comparison of methods for calculating glomerular filtration rate: technetium-99m-DTPA scintigraphic analysis, protein-free and whole-plasma clearance of technetium-99m-DTPA and iodine-125-iothalamate clearance. J Nucl Med 31:424–429PubMedGoogle Scholar
  10. 10.
    Liao Y, Liao W, Liu J, Xu G, Zeng R (2011) Assessment of the CKD EPI equation to estimate glomerular filtration rate in adults from a Chinese CKD population. J Int Med Res 39:2273–2280CrossRefPubMedGoogle Scholar
  11. 11.
    Li JT, Xun C, Cui CL, Wang HF, Wu YT, Yun AH et al (2012) Relative performance of two equations for estimation of glomerular filtration rate in a Chinese population having chronic kidney disease. Chin Med J (Engl) 125:599–603Google Scholar
  12. 12.
    Zhu Y, Ye X, Zhu B, Pei X, Wei L, Wu J et al (2014) Comparisons between the 2012 new CKD EPI (Chronic Kidney Disease Epidemiology Collaboration) equations and other four approved equations. PLoS ONE 9:e84688CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Trimarchi H, Muryan A, Martino D, Toscano A, Iriarte R, Campolo-Girard V et al (2012) Creatinine- vs. cystatin C-based equations compared with 99mTcDTPA scintigraphy to assess glomerular filtration rate in chronic kidney disease. J Nephrol 25:1003–1015CrossRefPubMedGoogle Scholar
  14. 14.
    Pei XH, He J, Liu Q, Zhu B, Bao LH, Yan CJ et al (2012) Evaluation of serum creatinine- and cystatin C-based equations for the estimation of glomerular filtration rate in a Chinese population. Scand J Urol Nephrol 46:223–231CrossRefPubMedGoogle Scholar
  15. 15.
    Foundation National Kidney, Initiative Kidney Disease Outcomes Quality (2002) Clinical practice guidelines for chronic kidney disease: evaluation classification, and stratification. Am J Kidney Dis 39:S1–S266Google Scholar
  16. 16.
    Levey AS, Stevens LA (2010) Estimating GFR using the CKD Epidemiology Collaboration (CKD EPI) creatinine equation: more accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis 55:622–627CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI et al (2009) CKD EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Stevens LA, Schmid CH, Greene T, Zhang YL, Beck GJ, Froissart M et al (2010) Comparative performance of the CKD Epidemiology Collaboration (CKD EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 ml/min/1.73 m2. Am J Kidney Dis 56:486–495CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    White CA, Akbari A, Doucette S, Fergusson D, Knoll GA (2010) Estimating glomerular filtration rate in kidney transplantation: is the new chronic kidney disease epidemiology collaboration equation any better? Clin Chem 56:474–477CrossRefPubMedGoogle Scholar
  20. 20.
    Cirillo M, Lombardi C, Luciano MG, Bilancio G, Anastasio P, De Santo NG (2010) Estimation of GFR: a comparison of new and established equations. Am J Kidney Dis 56:802–804CrossRefPubMedGoogle Scholar
  21. 21.
    Lane BR, Demirjian S, Weight CJ, Larson BT, Poggio ED, Campbell SC (2010) Performance of the chronic kidney disease-epidemiology study equations for estimating glomerular filtration rate before and after nephrectomy. J Urol 183:896–901CrossRefPubMedGoogle Scholar
  22. 22.
    Michels WM, Grootendorst DC, Verduijn M, Elliott EG, Dekker FW, Krediet RT (2010) Performance of the Cockcroft-Gault, MDRD, and new CKD EPI formulas in relation to GFR, age, and body size. Clin J Am Soc Nephrol 5:1003–1009CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Murata K, Baumann NA, Saenger AK, Larson TS, Rule AD, Lieske JC (2011) Relative performance of the MDRD and CKD EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations. Clin J Am Soc Nephrol 6:1963–1972CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Kemperman FA, Surachno J, Krediet RT, Arisz L (2002) Cimetidine improves prediction of the glomerular filtration rate by the Cockcroft-Gault formula in renal transplant recipients. Transplantation 73:770–774CrossRefPubMedGoogle Scholar
  25. 25.
    Berglund F, Killander J, Pompeius R (1975) Effect of trimethoprim-sulfamethoxazole on the renal excretion of creatinine in man. J Urol 114:802–808CrossRefPubMedGoogle Scholar
  26. 26.
    Ligthart GJ, Corberand JX, Geertzen HG, Meinders AE, Knook DL, Hijmans W (1990) Necessity of the assessment of health status in human immunogerontological studies: evaluation of the SENIEUR protocol. Mech Ageing Dev 55:89–105CrossRefPubMedGoogle Scholar
  27. 27.
    Blaufox MD, Aurell M, Bubeck B, Fommei E, Piepsz A, Russell C et al (1996) Report of the Radionuclides in Nephrourology Committee on renal clearance. J Nucl Med 37:1883–1890PubMedGoogle Scholar
  28. 28.
    Du Bois D, Du Bois EF (1989) A formula to estimate the approximate surface area if height and weight be known. Nutrition 5:303–311PubMedGoogle Scholar
  29. 29.
    Assadi M, Eftekhari M, Hozhabrosadati M, Saghari M, Ebrahimi A, Nabipour I et al (2008) Comparison of methods for determination of glomerular filtration rate: low and high-dose Tc-99m-DTPA renography, predicted creatinine clearance method, and plasma sample method. Int Urol Nephrol 40:1059–1065CrossRefPubMedGoogle Scholar
  30. 30.
    Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461–470CrossRefPubMedGoogle Scholar
  31. 31.
    Rehling M, Møller ML, Thamdrup B, Lund JO, Trap-Jensen J (1984) Simultaneous measurement of renal clearance and plasma clearance of 99mTc-labelled diethylenetriaminepenta-acetate, 51Cr-labelled ethylenediaminetetra-acetate and inulin in man. Clin Sci (Lond) 66:613–619CrossRefGoogle Scholar
  32. 32.
    Cousins C, Gunasekera RD, Mubashar M, Mohammadtaghi S, Strong R, Myers MJ et al (1997) Comparative kinetics of microvascular inulin and 99mTc-labelled diethylenetriaminepenta-acetic acid exchange. Clin Sci (Lond) 93:471–477CrossRefGoogle Scholar
  33. 33.
    Rehling M, Nielsen LE, Marqversen J (2001) Protein binding of 99Tcm-DTPA compared with other GFR tracers. Nucl Med Commun 22:617–623CrossRefPubMedGoogle Scholar
  34. 34.
    Buijs WC, Siegel JA, Boerman OC, Corstens FH (1998) Absolute organ activity estimated by five different methods of background correction. J Nucl Med 39:2167–2172PubMedGoogle Scholar
  35. 35.
    Horio M, Imai E, Yasuda Y, Watanabe T, Matsuo S (2010) Modification of the CKD epidemiology collaboration (CKD EPI) equation for Japanese: accuracy and use for population estimates. Am J Kidney Dis 56:32–38CrossRefPubMedGoogle Scholar
  36. 36.
    Matsushita K, Mahmoodi BK, Woodward M, Emberson JR, Jafar TH, Jee SH et al (2012) Chronic Kidney Disease Prognosis Consortium. Comparison of risk prediction using the CKD EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA 307:1941–1951CrossRefPubMedGoogle Scholar
  37. 37.
    Matsushita K, Selvin E, Bash LD, Astor BC, Coresh J (2010) Risk implications of the new CKD Epidemiology Collaboration (CKD EPI) equation compared with the MDRD Study equation for estimated GFR: the Atherosclerosis Risk in Communities (ARIC) Study. Am J Kidney Dis 55:648–659CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    White SL, Polkinghorne KR, Atkins RC, Chadban SJ (2010) Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. Am J Kidney Dis 55:660–670CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Qi Huang
    • 1
    • 2
  • Yunshuang Chen
    • 1
  • Min Zhang
    • 1
  • Sihe Wang
    • 3
  • Weiguang Zhang
    • 1
  • Guangyan Cai
    • 1
  • Xiangmei Chen
    • 1
  • Xuefeng Sun
    • 1
  1. 1.Department of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney DiseasesNational Clinical Research Center for Kidney DiseasesBeijingChina
  2. 2.Department of NephrologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
  3. 3.Department of Clinical PathologyCleveland ClinicClevelandUSA

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