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Low agreement between various eGFR formulae in pediatric and young adult ADPKD patients

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Abstract

Background

Young autosomal dominant polycystic kidney disease (ADPKD) patients are becoming the new target population for the development of new treatment options. Determination of a reliable equation for estimated glomerular filtration rate (eGFR) from early stages is needed with the promising potential interventional therapies.

Methods

Prospective and longitudinal study on a cohort of 68 genotyped ADPKD patients (age range 0–23 years) with long-term follow-up. Commonly used equations for eGFR were compared for their relative performance.

Results

The revised Schwartz formula (CKiD) showed a highly significant decline in eGFR with aging (− 3.31 mL/min/1.73 m2/year, P < 0.0001). The recently updated equation by the Schwartz group (CKiDU25) showed a smaller (− 0.90 mL/min/1.73 m2/year) but significant (P = 0.001) decline in eGFR with aging and also showed a significant sex difference (P < 0.0001), not observed by the other equations. In contrast, the full age spectrum (FAS) equations (FAS-SCr, FAS-CysC, and the combined) showed no age and sex dependency. The prevalence of hyperfiltration is highly dependent on the formula used, and the highest prevalence was observed with the CKiD Equation (35%).

Conclusions

The most widely used methods to calculate eGFR in ADPKD children (CKiD and CKiDU25 equations) were associated with unexpected age or sex differences. The FAS equations were age- and sex-independent in our cohort. Hence, the switch from the CKiD to CKD-EPI equation at the transition from pediatric to adult care causes implausible jumps in eGFR, which could be misinterpreted. Having reliable methods to calculate eGFR is indispensable for clinical follow-up and clinical trials.

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Data availability

The data underlying this article cannot be shared publicly due to the privacy of the individuals who participated in the study. The data will be shared on reasonable request to the corresponding author.

Abbreviations

ADPKD:

Autosomal dominant polycystic kidney disease

CKD:

Chronic kidney disease

TKV:

Total kidney volume

EGFR:

Estimated glomerular filtration rate

FAS:

Full age spectrum

SCr:

Serum creatinine

SCysC:

Serum cystatin C

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Acknowledgements

The authors thank Sarah Kerselaers and Ariadne van Hulle. Above all, the authors wish to thank the participating children and their parents, as well as the nurses involved in the care of the patients.

Funding

This work was supported by the Research Foundation Flanders (FWO) (G0C8920N) (1804123N) and UZ Leuven.

Author information

Authors and Affiliations

  1. PKD Research Group, Department of Cellular and Molecular Medicine, KU Leuven, Louvain, Belgium

    Pieter Schellekens, Peter Janssens, Angélique Dachy, Stéphanie De Rechter & Djalila Mekahli

  2. Department of Microbiology, Immunology and Transplantation, Nephrology and Renal Transplantation Research Group, KU Leuven, Louvain, Belgium

    Pieter Schellekens & Bert Bammens

  3. Department of Nephrology, Dialysis and Renal Transplantation, University Hospitals Leuven, Louvain, Belgium

    Pieter Schellekens & Bert Bammens

  4. Department of Pediatric Nephrology, University Hospitals Leuven, Louvain, Belgium

    Marcelien Verjans, Stéphanie De Rechter & Djalila Mekahli

  5. Department of Nephrology and Arterial Hypertension, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel, Brussels, Belgium

    Peter Janssens

  6. Department of Pediatrics, U Liège Academic Hospital, Liège, Belgium

    Angélique Dachy

  7. Department of Radiology, University Hospitals Leuven, Louvain, Belgium

    Luc Breysem

  8. Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000, Louvain, Belgium

    Karel Allegaert

  9. Woman and Child, Department of Development and Regeneration, KU Leuven, 3000, Louvain, Belgium

    Karel Allegaert

  10. Department of Clinical Pharmacy, Erasmus MC, 3000, CA, Rotterdam, the Netherlands

    Karel Allegaert

  11. Department of Cellular and Molecular Medicine, VIB Centre for Brain and Disease Research, Laboratory of Ion Channel Research, KU Leuven, Louvain, Belgium

    Rudi Vennekens

  12. Department of Laboratory of Laboratory Medicine, University Hospitals Leuven, Louvain, Belgium

    Pieter Vermeersch

  13. Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium

    Hans Pottel

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  1. Pieter Schellekens
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Corresponding author

Correspondence to Djalila Mekahli.

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Ethics approval

The study was approved by the local ethical board (Ethical Committee Research KU/UZ Leuven, S59500) and in accordance with the Declaration of Helsinki. Written informed consent was obtained from either the parents or patients.

Conflict of interest

The Research Foundation Flanders (F.W.O.) supports Pieter Schellekens. DM reports research grants from Otsuka and serves in advisory boards for Otsuka, Sanofi Genzyme and Reata, all outside the submitted work and all paid to her institutions UZ Leuven and KU Leuven, Belgium. The other authors have no conflict of interest to declare related to this manuscript.

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Supplementary Information

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Graphical Abstract (PPTX 338 KB)

467_2023_5926_MOESM2_ESM.pdf

Supplementary file2 (PDF 463 KB) Supplementary Table S1. Formulas for the different eGFR equations [e.g. (PDF)]. Supplementary Table S2. Results of the Bland-Altman correlation analysis comparing FAS-Age with the different equations [e.g. (PDF)].

467_2023_5926_MOESM3_ESM.pptx

Supplementary file3 (PPTX 183 KB) Supplementary Figure 1 (a) Bland-Altman plot of the difference (FAS-Age – CKiD) vs. the mean (FAS-Age + CKiD)/2. (b) Bland-Altman plot of the difference (FAS-Age – CkiDU25) vs. the mean (FAS-Age + CKiDU25)/2. (c) Bland-Altman plot of the difference (FAS-Age – FAS-Height) vs. the mean (FAS-Age + FAS-Height)/2. (d) Bland-Altman plot of the difference (FAS-Age – EFKC) vs. the mean (FAS-Age + EFKC)/2. (e) Bland-Altman plot of the difference (FAS-Age – LMR18) vs. the mean (FAS-Age + LMR18)/2. (f) Bland-Altman plot of the difference (FAS-Age – CKD-EPI40) vs. the mean (FAS-Age + CKD-EPI40)/2. (g) Bland-Altman plot of the difference (FAS-Age – FAS-CysC) vs. the mean (FAS-Age + FAS-CysC)/2. (h) Bland-Altman plot of the difference (FAS-Age – FAS-combi) vs. the mean (FAS-Age + FAS-combi)/2. (i) Bland-Altman plot of the difference (FAS-Age – FAS-Combi-Height) vs. the mean (FAS-Age + FAS-Combi-Height)/2 [e.g. (PDF)].

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Schellekens, P., Verjans, M., Janssens, P. et al. Low agreement between various eGFR formulae in pediatric and young adult ADPKD patients. Pediatr Nephrol 38, 3043–3053 (2023). https://doi.org/10.1007/s00467-023-05926-w

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