Multi-model averaging improves the performance of model-guided infliximab dosing in patients with inflammatory bowel diseases.

ABSTRACT: Infliximab dosage de-escalation without prior knowledge of drug concentrations may put patients at risk for underexposure and trigger the loss of response. A single-model approach for model-informed precision dosing during infliximab maintenance therapy has proven its clinical benefit in patients with inflammatory bowel diseases. We evaluated the predictive performances of two multi-model approaches, a model selection algorithm and a model averaging algorithm, using 18 published population pharmacokinetic models of infliximab for guiding dosage de-escalation. Data of 54 patients with Crohn's disease and ulcerative colitis who underwent infliximab dosage de-escalation after an earlier escalation were used. A priori prediction (based solely on covariate data) and maximum a posteriori predict

SUBMITTER: Kantasiripitak W 

PROVIDER: S-EPMC9381887 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature