How to manage medications in the setting of liver disease with the application of six questions

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

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.

Medication prescribing in liver dysfunction

Patients with mental illness often have co-occurring substance abuse which increases the risk for developing cirrhosis, particularly with common etiologies such as hepatitis and alcoholic liver disease. As such, knowledge of how the disease may impact medication prescribing is important. Unfortunately, there is a paucity of data to guide medication prescribing in these patients. Product labeling information should be used in the clinical decision making process. Additionally, clinicians should consider the etiology of disease, adverse effect profile, and pharmacokinetic parameters including solubility, product formulation, protein binding, hydrophilicity, metabolism, bioavailability, extraction ratios, excretion route, and half-life. Thoughtful consideration should be given when prescribing potentially hepatotoxic medications, and those which may increase bleeding risk in patients with coagulopathy. It is essential to ensure every medication has an appropriate indication and carefully evaluate the need for each medication. Overall, more research is necessary to support clinical decision-making with outcomes based research in patients with chronic liver disease.

Management of infections in cirrhotic patients: report of a consensus conference

The statements produced by the consensus conference on infection in end-stage liver disease promoted by the Italian Association for the Study of the Liver, are here reported. The topics of epidemiology, risk factors, diagnosis, prophylaxis, and treatment of infections in patient with compensated and decompensated liver cirrhosis were reviewed by a scientific board of experts who proposed 26 statements that were graded according to level of evidence and strength of recommendation, and approved by an independent jury. Each topic was explored focusing on the more relevant clinical questions. By systematic literature search of available evidence, comparison and discussion of expert opinions, pertinent statements answering specific questions were presented and approved. Short comments were added to explain the basis for grading evidence particularly on case of controversial areas.