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

Abstract

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.