“De-Shrinking” EBEs: The Solution for Bayesian Therapeutic Drug Monitoring

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Baklouti, Sarah | Gandia, Peggy | Concordet, Didier

Edité par CCSD ; Springer Verlag -

International audience. Background Therapeutic drug monitoring (TDM) aims at individualising a dosage regimen and is increasingly being performed by estimating individual pharmacokinetic parameters via empirical Bayes estimates (EBEs). However, EBEs suffer from shrinkage that makes them biased. This bias is a weakness for TDM and probably a barrier to the acceptance of drug dosage adjustments by prescribers. Objective The aim of this article is to propose a methodology that allows a correction of EBE shrinkage and an improvement in their precision. Methods As EBEs are defined, they can be seen as a special case of ridge estimators depending on a parameter usually denoted λ. After a bias correction depending on λ, we chose λ so that the individual pharmacokinetic estimations have minimal imprecision. Our estimate is by construction always better than EBE with respect to bias (i.e. shrinkage) and precision. Results We illustrate the performance of this approach with two different drugs: iohexol and isavuconazole. Depending on the patient's actual pharmacokinetic parameter values, the improvement given by our approach ranged from 0 to 100%. Conclusion This innovative methodology is promising since, to the best of our knowledge, no other individual shrinkage correction has been proposed.

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