ArticleClinical pharmacokinetics2015
A Prediction Model of Drug Exposure in Cirrhotic Patients According to Child-Pugh Classification.
Article in Clinical pharmacokinetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives.Clinical pharmacokinetics · 2018Pooled it
- Evaluating the safety and dosing of drugs in patients with liver cirrhosis by literature review and expert opinion.BMJ open · 2016Pooled it
- Quantitative prediction of intravenous drug interactions caused by cytochromes P450 inhibitors and inducers.British journal of clinical pharmacology · 2026Article
- Proton Pump Inhibitors in Patients with Cirrhosis: Pharmacokinetics, Benefits and Drawbacks.Current gastroenterology reports · 2024Review
- Evaluation of Renal Impairment Influence on Metabolic Drug Clearance using a Modelling Approach.Clinical pharmacokinetics · 2023Article
- Drug-Drug-Gene Interactions in Cardiovascular Medicine.Pharmacogenomics and personalized medicine · 2022Review
- Does DDI-Predictor Help Pharmacists to Detect Drug-Drug Interactions and Resolve Medication Issues More Effectively?Metabolites · 2021Article
- Safe use of proton pump inhibitors in patients with cirrhosis.British journal of clinical pharmacology · 2018Article
- Evidence-Based Recommendations to Improve the Safe Use of Drugs in Patients with Liver Cirrhosis.Drug safety · 2018Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivePrediction 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.
methodsThe 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.
resultsAmong 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.
conclusionsFor 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.
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