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Licensed Unlicensed Requires Authentication Published by De Gruyter January 11, 2020

Assessment of the glomerular filtration rate (GFR) in kidney transplant recipients using Bayesian estimation of the iohexol clearance

Camille Riff , Joevin Besombes , Philippe Gatault , Christelle Barbet , Matthias Büchler , Hélène Blasco , Jean-Michel Halimi , Chantal Barin-Le Guellec ORCID logo EMAIL logo and Isabelle Benz-de Bretagne

Abstract

Background

Plasma iohexol clearance (CLiohexol) is a reference technique for glomerular filtration rate (GFR) determination. In routine practice, CLiohexol is calculated using one of several formulas, which have never been evaluated in kidney transplant recipients. We aimed to model iohexol pharmacokinetics in this population, evaluate the predictive performance of three simplified formulas and evaluate whether a Bayesian algorithm improves CLiohexol estimation.

Methods

After administration of iohexol, six blood samples were drawn from 151 patients at various time points. The dataset was split into two groups, one to develop the population pharmacokinetic (POPPK) model (n = 103) and the other (n = 48) to estimate the predictive performances of the various GFR estimation methods. GFR reference values (GFRref) in the validation dataset were obtained by non-compartmental pharmacokinetic (PK) analysis. Predictive performances of each method were evaluated in terms of bias (ME), imprecision (root mean square error [RMSE]) and number of predictions out of the ±10% or 15% error interval around the GFRref.

Results

A two-compartment model best fitted the data. The Bayesian estimator with samples drawn at 30, 120 and 270 min allowed accurate prediction of GFRref (ME = 0.47%, RMSE = 3.42%), as did the Brøchner-Mortensen (BM) formula (ME = − 0.0425%, RMSE = 3.40%). With both methods, none of the CL estimates were outside the ±15% interval and only 2.4% were outside the ±10% for the BM formula (and none for the Bayesian estimator). In patients with GFR ≤30 mL/min/1.73 m2, the BM formula performed very well, while the Bayesian method could not be evaluated in depth due to too small a number of patients with adequate sampling times.

Conclusions

GFR can be estimated with acceptable accuracy in kidney transplant patients using the BM formula, but also using a Bayesian algorithm.


Corresponding author: Chantal Barin-Le Guellec, PharmD, PhD, Laboratoire de Biochimie et de Biologie Moléculaire, CHU de Tours, 2 boulevard Tonnellé, 37044 Tours cedex, France; FHU SUPPORT, Tours, France; and INSERM U1248, IPPRITT, Université de Limoges, Limoges, France, Phone: +33 247 478 060
aCamille Riff and Joevin Besombes contributed equally to this work as co-first authors.

Acknowledgments

The authors would like to acknowledge the patients who participated in this study, as well as the investigators and on-site staff who made this study possible. We warmly thank Prof. Pierre Marquet for his careful reading of this paper and Karen Poole for correcting our English.

  1. Author contributions: Joevin Besombes/Camille Riff: acquisition of data, analysis and interpretation; writing, review and/or revision of the manuscript. Hélène Blasco: conception and design; writing, review and/or revision of the manuscript. Philippe Gatault: conception and design; acquisition of data, review and/or revision of the manuscript. Christelle Barbet: acquisition of data, review and/or revision of the manuscript. Matthias Büchler: conception and design; acquisition of data, review and/or revision of the manuscript. Jean-Michel Halimi: conception and design; acquisition of data, review and/or revision of the manuscript. Chantal Barin-Le Guellec: conception and design; analysis and interpretation; writing; study supervision; review and/or revision of the manuscript. Isabelle Benz-de Bretagne: conception and design; acquisition of data, analysis and interpretation; writing, review and/or revision of the manuscript. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006;145:247–54.10.7326/0003-4819-145-4-200608150-00004Search in Google Scholar PubMed

2. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–12.10.7326/0003-4819-150-9-200905050-00006Search in Google Scholar PubMed PubMed Central

3. Luis-Lima S, Marrero-Miranda D, González-Rinne A, Torres A, González-Posada JM, Rodríguez A, et al. Estimated glomerular filtration rate in renal transplantation: the nephrologist in the mist. Transplantation 2015;99:2625–33.10.1097/TP.0000000000000786Search in Google Scholar PubMed

4. Shaffi K, Uhlig K, Perrone RD, Ruthazer R, Rule A, Lieske JC, et al. Performance of creatinine-based GFR estimating equations in solid-organ transplant recipients. Am J Kidney Dis 2014;63:1007–18.10.1053/j.ajkd.2014.01.436Search in Google Scholar PubMed PubMed Central

5. Masson I, Flamant M, Maillard N, Rule AD, Vrtovsnik F, Peraldi M-N, et al. MDRD versus CKD-EPI equation to estimate glomerular filtration rate in kidney transplant recipients. Transplantation 2013;95:1211–7.10.1097/TP.0b013e318288caa6Search in Google Scholar PubMed

6. Fauvel J-P, Hadj-Aissa A, Buron F, Morelon E, Ducher M. Performance of estimated glomerular filtration rates to monitor change in renal function in kidney transplant recipients. Nephrol Dial Transplant 2013;28:3096–100.10.1093/ndt/gft047Search in Google Scholar PubMed

7. White CA, Akbari A, Doucette S, Fergusson D, Knoll GA. Estimating glomerular filtration rate in kidney transplantation: is the new chronic kidney disease epidemiology collaboration equation any better? Clin Chem 2010;56:474–7.10.1373/clinchem.2009.135111Search in Google Scholar PubMed

8. White CA, Huang D, Akbari A, Garland J, Knoll GA. Performance of creatinine-based estimates of GFR in kidney transplant recipients: a systematic review. Am J Kidney Dis 2008;51:1005–15.10.1053/j.ajkd.2008.02.308Search in Google Scholar PubMed

9. Lamb EJ, Stevens PE. Estimating and measuring glomerular filtration rate: methods of measurement and markers for estimation. Curr Opin Nephrol Hypertens 2014;23:258–66.10.1097/01.mnh.0000444813.72626.88Search in Google Scholar PubMed

10. Fleming JS, Zivanovic MA, Blake GM, Burniston M, Cosgriff PS, British Nuclear Medicine Society. Guidelines for the measurement of glomerular filtration rate using plasma sampling. Nucl Med Commun 2004;25:759–69.10.1097/01.mnm.0000136715.71820.4aSearch in Google Scholar PubMed

11. Gaspari F, Perico N, Ruggenenti P, Mosconi L, Amuchastegui CS, Guerini E, et al. Plasma clearance of nonradioactive iohexol as a measure of glomerular filtration rate. J Am Soc Nephrol 1995;6:257–63.10.1681/ASN.V62257Search in Google Scholar PubMed

12. Björk J, Grubb A, Larsson A, Hansson L-O, Flodin M, Sterner G, et al. Accuracy of GFR estimating equations combining standardized cystatin C and creatinine assays: a cross-sectional study in Sweden. Clin Chem Lab Med 2015;53:403–14.10.1515/cclm-2014-0578Search in Google Scholar PubMed

13. Gaspari F, Ferrari S, Stucchi N, Centemeri E, Carrara F, Pellegrino M, et al. Performance of different prediction equations for estimating renal function in kidney transplantation. Am J Transplant 2004;4:1826–35.10.1111/j.1600-6143.2004.00579.xSearch in Google Scholar PubMed

14. Goerdt PJ, Heim-Duthoy KL, Macres M, Swan SK. Predictive performance of renal function estimate equations in renal allografts. Br J Clin Pharmacol 1997;44:261–5.10.1046/j.1365-2125.1997.t01-1-00567.xSearch in Google Scholar PubMed PubMed Central

15. Delanaye P, Ebert N, Melsom T, Gaspari F, Mariat C, Cavalier E, et al. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: How to measure glomerular filtration rate with iohexol? Clin Kidney J 2016;9:682–99.10.1093/ckj/sfw070Search in Google Scholar PubMed PubMed Central

16. Bröchner-Mortensen J. A simple method for the determination of glomerular filtration rate. Scand J Clin Lab Invest 1972;30:271–4.10.3109/00365517209084290Search in Google Scholar PubMed

17. Christensen AB, Groth S. Determination of 99mTc-DTPA clearance by a single plasma sample method. Clin Physiol 1986;6:579–88.10.1111/j.1475-097X.1986.tb00790.xSearch in Google Scholar

18. Watson WS. A simple method of estimating glomerular filtration rate. Eur J Nucl Med 1992;19:827.10.1007/BF00182829Search in Google Scholar PubMed

19. Blaufox MD, Aurell M, Bubeck B, Fommei E, Piepsz A, Russell C, et al. Report of the Radionuclides in Nephrourology Committee on renal clearance. J Nucl Med 1996;37:1883–90.Search in Google Scholar

20. Jacobsson L. A method for the calculation of renal clearance based on a single plasma sample. Clin Physiol Oxf Engl 1983;3:297–305.10.1111/j.1475-097X.1983.tb00712.xSearch in Google Scholar PubMed

21. Delanaye P, Flamant M, Dubourg L, Vidal-Petiot E, Lemoine S, Cavalier E, et al. Single- versus multiple-sample method to measure glomerular filtration rate. Nephrol Dial Transplant 2018;33:1778–85.10.1093/ndt/gfx345Search in Google Scholar PubMed

22. Samara E, Granneman R. Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective. Clin Pharmacokinet 1997;32:294–312.10.2165/00003088-199732040-00003Search in Google Scholar

23. Woillard J-B, Saint-Marcoux F, Debord J, Åsberg A. Pharmacokinetic models to assist the prescriber in choosing the best tacrolimus dose. Pharmacol Res 2018;130:316–21.10.1016/j.phrs.2018.02.016Search in Google Scholar

24. Sheiner LB, Beal SL. Evaluation of methods for estimating population pharmacokinetic parameters II. Biexponential model and experimental pharmacokinetic data. J Pharmacokinet and Biopharm 1981;9:635–51.10.1007/BF01061030Search in Google Scholar

25. Kopple JD. National kidney foundation K/DOQI clinical practice guidelines for nutrition in chronic renal failure. Am J Kidney Dis 2001;37:S66–70.10.1053/ajkd.2001.20748Search in Google Scholar

26. Castagnet S, Blasco H, Vourc’h P, Benz-De-Bretagne I, Veyrat-Durebex C, Barbet C, et al. Routine determination of GFR in renal transplant recipients by HPLC quantification of plasma iohexol concentrations and comparison with estimated GFR. J Clin Lab Anal 2012;26:376–83.10.1002/jcla.21537Search in Google Scholar

27. Yafune A, Ishiguro M. Bootstrap approach for constructing confidence intervals for population pharmacokinetic parameters. II: a bootstrap modification of standard two-stage (STS) method for phase I trial. Stat Med 1999;18:601–12.10.1002/(SICI)1097-0258(19990315)18:5<601::AID-SIM48>3.0.CO;2-LSearch in Google Scholar

28. Savic RM, Karlsson MO. Importance of shrinkage in empirical Bayes estimates for diagnostics: problems and solutions. AAPS J 2009;11:558–69.10.1208/s12248-009-9133-0Search in Google Scholar

29. Ebert N, Loesment A, Martus P, Jakob O, Gaedeke J, Kuhlmann M, et al. Iohexol plasma measurement in older adults with chronic kidney disease: sampling time matters. Nephrol Dial Transplant 2015;30:1307–14.10.1093/ndt/gfv116Search in Google Scholar

30. Gaspari F, Guerini E, Perico N, Mosconi L, Ruggenenti P, Remuzzi G. Glomerular filtration rate determined from a single plasma sample after intravenous iohexol injection: is it reliable? J Am Soc Nephrol 1996;7:2689–93.10.1681/ASN.V7122689Search in Google Scholar

31. Luis-Lima S, Gaspari F, Porrini E, García-González M, Batista N, Bosa-Ojeda F, et al. Measurement of glomerular filtration rate: internal and external validations of the iohexol plasma clearance technique by HPLC. Clin Chim Acta 2014;430:84–5.10.1016/j.cca.2013.12.028Search in Google Scholar

32. Mafham MM, Niculescu-Duvaz I, Barron J, Emberson JR, Dockrell ME, Landray MJ, et al. A practical method of measuring glomerular filtration rate by iohexol clearance using dried capillary blood spots. Nephron Clin Pract 2007;106:c104–12.10.1159/000102997Search in Google Scholar PubMed

33. Stolz A, Hoizey G, Toupance O, Lavaud S, Vitry F, Chanard J, et al. Evaluation of sample bias for measuring plasma iohexol clearance in kidney transplantation. Transplantation 2010;89:440–5.10.1097/TP.0b013e3181ca7d1bSearch in Google Scholar PubMed

34. Peters AM, Glass DM, Bird NJ. Slope-only glomerular filtration rate and single-sample glomerular filtration rate as measurements of the ratio of glomerular filtration rate to extracellular fluid volume. Nephrology 2010;15:281–7.10.1111/j.1440-1797.2009.01252.xSearch in Google Scholar PubMed

35. Sterner G, Frennby B, Hultberg B, Almen T. Iohexol clearance for GFR-determination in renal failure – single or multiple plasma sampling? Nephrol Dial Transplant 1996;11:521–5.10.1093/ndt/11.3.521Search in Google Scholar

36. Fleming JS. An improved equation for correcting slope-intercept measurements of glomerular filtration rate for the single exponential approximation. Nucl Med Commun 2007;28:315–20.10.1097/MNM.0b013e328014a14aSearch in Google Scholar PubMed

37. US FDA. Guidance for industry: population pharmacokinetics, 2019; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/population-pharmacokinetics.Search in Google Scholar

38. Friedman AN, Strother M, Quinney SK, Hall S, Perkins SM, Brizendine EJ, et al. Measuring the glomerular filtration rate in obese individuals without overt kidney disease. Nephron Clin Pract 2010;116:c224–34.10.1159/000317203Search in Google Scholar PubMed PubMed Central

39. Taubert M, Ebert N, Martus P, van der Giet M, Fuhr U, Schaeffner E. Using a three-compartment model improves the estimation of iohexol clearance to assess glomerular filtration rate. Sci Rep 2018;8:17723.10.1038/s41598-018-35989-xSearch in Google Scholar PubMed PubMed Central

40. Agarwal R, Bills JE, Yigazu PM, Abraham T, Gizaw AB, Light RP, et al. Assessment of iothalamate plasma clearance: duration of study affects quality of GFR. Clin J Am Soc Nephrol 2009;4:77–85.10.2215/CJN.03720708Search in Google Scholar PubMed PubMed Central


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2019-0904).


Received: 2018-11-05
Accepted: 2019-11-17
Published Online: 2020-01-11
Published in Print: 2020-03-26

©2020 Walter de Gruyter GmbH, Berlin/Boston

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