title: Evaluation of the mycophenolic acid exposure estimation methods used in the APOMYGERE, FDCC, and Opticept trials.
abstract: BACKGROUND
  Three randomized-controlled trials have examined the utility of mycophenolic acid (MPA) therapeutic drug monitoring in kidney transplant recipients. Each used a different methodology to estimate MPA exposure (predose concentrations [C(0)], multiple regression-derived limited sampling strategies [LSSs], and Bayesian estimation in Opticept, FDCC [fixed dose versus concentration controlled] and APOMYGERE [adaption de Posologie du MMF en Greffe Renale] trials, respectively). Results were conflicting. This study aimed to compare the ability of these methodologies to predict AUC(0-12) in an independent cohort of kidney transplant recipients.
  
  
  METHODS
  Sixty-nine full AUC (AUCf) profiles were collected from 45 subjects. C(0) and AUC(0-12) predicted by the LSSs and Bayesian estimation (AUCp) were compared with AUCf.
  
  
  RESULTS
  Correlation between C(0) and AUCf was poor. There was better correlation between LSSs and AUCf, and correlation was higher again between Bayesian estimates and AUCf. Bias and precision associated with the LSS and Bayesian-forecasting methods fell close to the level considered acceptable in clinical studies (<15%). However, neither method quite achieved this, and regardless of whether LSSs or Bayesian forecasting were applied, only 45% to 47% of AUCp values fell within 15% of AUCf. Discordance between C(0) and AUCp and AUCf occurred in 15% to 27% of cases.
  
  
  CONCLUSIONS
  This study highlights the difficulties of MPA therapeutic drug monitoring. Bayesian estimations showed slight superiority over C(0) and LSS predictions, suggesting that this may be the preferable methodology.
authors.affiliation: Department of Renal Medicine, University of Queensland at the Princess Alexandra Hospital, Woolloongabba, Brisbane, Australia. katherine_barraclough@health.qld.gov.au
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Barraclough
authors.forename: Nicole M
authors.initials: NM
authors.lastname: Isbel
authors.forename: Christine E
authors.initials: CE
authors.lastname: Staatz
mesh_terms: D000328:Adult; D000900:Anti-Bacterial Agents / Q000493:pharmacokinetics / Q000627:therapeutic use; D019540:Area Under Curve; D001499:Bayes Theorem; D002102:Cadaver; D016572:Cyclosporine / Q000493:pharmacokinetics / Q000627:therapeutic use; D016903:Drug Monitoring / Q000379:methods / Q000592:standards*; D004359:Drug Therapy, Combination; D005260:Female; D006801:Humans; D007166:Immunosuppressive Agents / Q000493:pharmacokinetics / Q000627:therapeutic use*; D016030:Kidney Transplantation / Q000276:immunology / Q000379:methods*; D019520:Living Donors; D008297:Male; D008875:Middle Aged; D009173:Mycophenolic Acid / Q000493:pharmacokinetics / Q000627:therapeutic use*; D011237:Predictive Value of Tests; D016032:Randomized Controlled Trials as Topic; D012494:Sampling Studies; D014019:Tissue Donors
chemical_list: D000900:Anti-Bacterial Agents; D007166:Immunosuppressive Agents; D016572:Cyclosporine; D009173:Mycophenolic Acid