Back to Journals » Neuropsychiatric Disease and Treatment » Volume 7 » Issue 1

Performance of Cpred/Cobs concentration ratios as a metric reflecting adherence to antidepressant drug therapy

Authors Feng Y, Gastonguay MR, Pollock B, Frank E, Kepple GH, Bies RR

Published 17 March 2011 Volume 2011:7(1) Pages 117—125

DOI https://doi.org/10.2147/NDT.S15921

Review by Single-blind

Peer reviewer comments 2


Yan Feng1, Marc R Gastonguay2, Bruce G Pollock3,5, Ellen Frank3, Gail H Kepple4, Robert R Bies5,6,7
1Discovery Medicine and Clinical Pharmacology, Bristol-Myers Squibb, Lawrenceville, NJ, USA; 2Metrum Institute, Tariffville, CT, USA; 3Department of Psychiatry, School of Medicine, 4Department of Depression Prevention, University of Pittsburgh, PA, USA; 5Centre for Addiction and Mental Health, University of Toronto, Toronto, Canada; 6Division of Clinical Pharmacology, School of Medicine and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA; 7Indiana Clinical Translational Research Institute, Indiana University School of Medicine, IN, USA

Background: Nonadherence is very common among subjects undergoing pharmacotherapy for schizophrenia and depression. This study aimed to evaluate the performance of the ratio of the nonlinear mixed effects pharmacokinetic model predicted concentration to observed drug concentration (ratio of population predicted to observed concentration (Cpred/Cobs) and ratio of individual predicted to observed concentration (Cipred/Cobs) as a measure of erratic drug exposure, driven primarily by variable execution of the dosage regimen and unknown true dosage history.
Methods: Modeling and simulation approaches in conjunction with dosage history information from the Medication Event Monitoring System (MEMS, provided by the “Depression: The search for treatment relevant phenotypes” study), was applied to evaluate the consistency of exposure via simulation studies with scenarios representing a long half-life drug (escitalopram). Adherence rates were calculated based on the percentage of the prescribed doses actually taken correctly during the treatment window of interest. The association between Cpred/Cobs, Cipred/Cobs ratio, and adherence rate was evaluated under various assumptions of known dosing history.
Results: Simulations for those scenarios representing a known dosing history were generated from historical MEMS data. Simulations of a long half-life drug exhibited a trend for overprediction of concentrations in patients with a low percentage of doses taken and underprediction of concentrations in patients taking more than their prescribed number of doses. Overall, the ratios did not predict adherence well, except when the true adherence rates were extremely high (greater than 100% of prescribed doses) or extremely low (complete nonadherence). In general, the Cipred/Cobs ratio was a better predictor of adherence rate than the Cpred/Cobs ratio. Correct predictions of extreme (high, low) 7-day adherence rates using Cipred/Cobs were 73.8% and 64.0%.
Conclusion: This simulation study demonstrated the limitations of the Cpred/obs and Cipred/obs ratios as metrics for actual dosage intake history, and identified that use of MEMS dosing history monitoring combined with sparse pharmacokinetic sampling is a more reliable approach.


Keywords: adherence, Medication Event Monitoring System, dosing history, modeling and simulation

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]  View Full Text [HTML][Machine readable]