External evaluation of population pharmacokinetic models of tacrolimus in adult heart transplant recipients

Background. Numerous population pharmacokinetic (popPK) models of tacrolimus (TAC) in adult transplant recipients have been published. However, data on the accuracy of Bayesian forecasting with concomitant azole therapy or extrapolation to other transplant cohorts are scarce.

Aims. To externally validate the predictive performances of relevant popPK models of TAC in adult heart transplant (HTX) recipients with concurrent azole therapy (Phase 1) and without azole therapy (Phase 2).

Methods. Published popPK models of TAC (n=66) were identified and a subset was selected based on specific criteria. Models were transcribed and predictions performed in NONMEM v7.4. Data from 39 HTX recipients (1705 concentrations) in 2017 treated with TAC at St Vincent’s Hospital, Sydney were obtained immediately post-HTX up to 3 months post-azole cessation. Bayesian forecasting was used to establish the predictive performance (bias [median prediction error] and precision [median absolute prediction error]) of the models to predict TAC concentrations in each phase. Clinically acceptable bias was between ±20% and precision was ≤20%.

Results. Of the 15 models evaluated, the model by Lu et al. (2019), Storset et al. (2014a & 2014b) displayed the best predictive performance in Phase 1 (1345 concentrations). However, all models were unsatisfactory in predicting TAC concentrations in Phase 2 (360 concentrations).

Discussion. Three models demonstrated clinically acceptable accuracy to predict TAC concentrations in post-HTX recipients with concomitant azole therapy. Predictive performance of relevant population PK models for TAC in post-HTX recipients varied substantially without azole therapy. The incorporation of azole therapy as a covariate may improve the accuracy of Bayesian forecasting. The applicability of extrapolating popPK models between different solid organ transplant populations warrants further investigation.

Lu et al (2019) Br. J. Clin Pharmacol 85(8), 1692-1703; Storset et al (2014a) Br. J. Clin Pharmacol 78(3), 509-523; Storset et al (2014b) Eur. J. Clin Pharmacol 70(1), 65-77.

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