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The Evaluation of Multiple Linear Regression-Based Limited Sampling Strategies for Mycophenolic Acid in Children with Nephrotic Syndrome.
- Source :
-
Molecules (Basel, Switzerland) [Molecules] 2021 Jun 18; Vol. 26 (12). Date of Electronic Publication: 2021 Jun 18. - Publication Year :
- 2021
-
Abstract
- We evaluated mycophenolic acid (MPA) limited sampling strategies (LSSs) established using multiple linear regression (MLR) in children with nephrotic syndrome treated with mycophenolate mofetil (MMF). MLR-LSS is an easy-to-determine approach of therapeutic drug monitoring (TDM). We assessed the practicability of different LSSs for the estimation of MPA exposure as well as the optimal time points for MPA TDM. The literature search returned 29 studies dated 1998-2020. We applied 53 LSSs ( n = 48 for MPA, n = 5 for free MPA [fMPA]) to predict the area under the time-concentration curve (AUC <subscript>pred</subscript> ) in 24 children with nephrotic syndrome, for whom we previously determined MPA and fMPA concentrations, and compare the results with the determined AUC (AUC <subscript>total</subscript> ). Nine equations met the requirements for bias and precision ±15%. The MPA AUC in children with nephrotic syndrome was predicted the best by four time-point LSSs developed for renal transplant recipients. Out of five LSSs evaluated for fMPA, none fulfilled the ±15% criteria for bias and precision probably due to very high percentage of bound MPA (99.64%). MPA LSS for children with nephrotic syndrome should include blood samples collected 1 h, 2 h and near the second MPA maximum concentration. MPA concentrations determined with the high performance liquid chromatography after multiplying by 1.175 may be used in LSSs based on MPA concentrations determined with the immunoassay technique. MPA LSS may facilitate TDM in the case of MMF, however, more studies on fMPA LSS are required for children with nephrotic syndrome.
Details
- Language :
- English
- ISSN :
- 1420-3049
- Volume :
- 26
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Molecules (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 34207320
- Full Text :
- https://doi.org/10.3390/molecules26123723