A Prediction Model of Drug Exposure in Cirrhotic Patients According to Child–Pugh Classification

• Published in: Clinical pharmacokinetics Vol. 54; no. 12; pp. 1245 - 1258
• Main Authors: Steelandt, Julie, Jean-Bart, Elodie, Goutelle, Sylvain, Tod, Michel
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2015; Springer Nature B.V; Springer Verlag
• Subjects: Area Under Curve; Cytochrome P-450 Enzyme System - metabolism; Dose-Response Relationship, Drug; Drug Interactions; Humans; Internal Medicine; Life Sciences; Liver Cirrhosis - drug therapy; Liver Cirrhosis - genetics; Liver Cirrhosis - metabolism; Medicine; Medicine & Public Health; Metabolic Clearance Rate; Models, Biological; Original Research Article; Pharmacokinetics; Pharmacology/Toxicology; Pharmacotherapy; Polymorphism, Genetic; Predictive Value of Tests; Cirrhotic Patient; Cirrhosis Patient; Dronedarone; Pugh Score; Pugh Class
• ISSN: 0312-5963; 1179-1926; 1179-1926
• DOI: 10.1007/s40262-015-0288-9

Background and Objective Prediction of drug clearance in liver cirrhosis patients is currently based on in vitro–in vivo extrapolation and physiologically-based pharmacokinetic models. No static model for this purpose has been described. The objectives of this study were to (1) derive a static model for predicting drug exposure in cirrhotic patients, and (2) to evaluate the model on a large set of published data. Methods The impact of cirrhosis was characterized by the ratio of the total and unbound drug area under the concentration–time curve (AUC) in cirrhotic patients to the AUC measured in healthy subjects These ratios were predicted for Child–Pugh classes A, B, and C. The AUC ratios observed in published data were compared with AUC ratios predicted by the model. Results Among 171 drugs examined, 83 published AUC ratios for 45 drugs in cirrhotic patients were available for analysis. The mean ± standard deviation relative prediction error for the total and unbound AUC ratios was 0.22 ± 0.58 and 0.24 ± 0.56, respectively. There were four outliers among the 83 predicted values. Simulations showed that the prediction error was negligible provided that the hepatic extraction coefficient was less than 0.8. Conclusions For mild and moderate cirrhosis (classes A and B), the predicted unbound AUC ratio is typically approximately 2 and 3.5, respectively, for most drugs. In the absence of data in cirrhotic patients, the drug dose might be empirically reduced by these factors. In severe cirrhosis (class C), our model may help clinicians to adjust their prescriptions.