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Importance and objective: Self-reported caffeine consumption has been widely used in research while it may be subject to bias. We sought to investigate the associations between self-reported caffeine consumption and plasma levels of caffeine and its two main metabolites (paraxanthine and theophylline) in the community. Methods: Data from two population-based studies (SKIPOGH1 and 2 (N = 1246) and CoLaus|PsyCoLaus (N = 4461)) conducted in Switzerland were used. Self-reported caffeine consumption was assessed using questionnaires. Plasma levels of caffeine and its metabolites were quantified by ultra-high performance liquid chromatography coupled to a tandem quadrupole mass spectrometer. Results: In both studies, mean log plasma levels of caffeine and its two metabolites were over 6.48 (plasma levels = 652 ng/ml) when no caffeine consumption was reported. Subsequently, nonlinear associations between log plasma levels and self-reported caffeine consumption were observed in SKIPOGH, with a change of the slope at 3–5 cups of espresso per day in SKIPOGH1 but not SKIPOGH2. In CoLaus|PsyCoLaus, increased daily consumption of caffeinated beverages was associated with increased log plasma levels with a change of the slope at 3 cups. In both studies, declared caffeine consumption higher than 3–5 cups per day was not associated with higher plasma levels of caffeine and its metabolites. Conclusion: Self-reports of no or low caffeine consumption and consumption of more than 3–5 cups of coffee should be interpreted with caution, with possible under- or over-estimation. Quantifying plasma levels of caffeine and its metabolites may contribute to a better estimation of caffeine intake. [ABSTRACT FROM AUTHOR]

Background and Objectives: Methadone is a μ-opioid agonist widely used for the treatment of pain, and for detoxification or maintenance treatment in opioid addiction. It has been shown to exhibit large pharmacokinetic variability and concentration-QTc relationships. In this study we investigated the relative influence of genetic polymorphism and other variables on the dose concentration-QTc relationship.Patients and Methods: A population model for methadone enantiomers in 251 opioid-dependent patients was developed using non-linear mixed effect modeling (NONMEM®). Various models were tested to characterize the pharmacokinetics of (R)- and (S)-methadone and the pharmacokinetic-pharmacodynamic relationship, while including demographics, physiological conditions, co-medications, and genetic variants as covariates. Model-based simulations were performed to assess the relative increase in QTc with dose upon stratification according to genetic polymorphisms involved in methadone disposition.Results: A two-compartment model with first-order absorption and lag time provided the best model fit for (R)- and (S)-methadone pharmacokinetics. (S)-methadone clearance was influenced by cytochrome P450 (CYP) 2B6 activity, ABCB1 3435C>T, and α-1 acid glycoprotein level, while (R)-methadone clearance was influenced by CYP2B6 activity, POR*28, and CYP3A4*22. A linear model described the methadone concentration-QTc relationship, with a mean QTc increase of 9.9 ms and 19.2 ms per 1000 ng/ml of (R)- and (S)-methadone, respectively. Simulations with different methadone doses up to 240 mg/day showed that <8 % of patients presented with a QTc interval above 450 ms; however, this might reach 12 to 18 % for (R)- and (S)-methadone, respectively, in patients with a genetic status associated with a decreased methadone elimination at doses exceeding 240 mg/day.Conclusion: Risk factor assessment, electrocardiogram monitoring, and therapeutic drug monitoring are beneficial to optimize treatment in methadone patients, especially for those who have low levels despite high methadone doses, or who are at risk of overdosing. [ABSTRACT FROM AUTHOR]

To assess tobacco, alcohol, cannabis and benzodiazepine use in methadone maintenance treatment (MMT) as potential sources of variability in methadone pharmacokinetics. Trough plasma ( R)- and ( S)-methadone concentrations were measured on 77 Australian and 74 Swiss MMT patients with no additional medications other than benzodiazepines. Simple and multiple regression analyses were performed for the primary metric, plasma methadone concentration/dose. Cannabis and methadone dose were significantly associated with lower 24-h plasma ( R)- and ( S)-methadone concentrations/dose. The models containing these variables explained 14–16% and 17–25% of the variation in ( R)- and ( S)-methadone concentration/dose, respectively. Analysis of 61 patients using only CYP3A4 metabolised benzodiazepines showed this class to be associated with higher (R)-concentration/dose, which is consistent with a potential competitive inhibition of CYP3A4. Cannabis use and higher methadone doses in MMT could in part be a response to—or a cause of—more rapid methadone clearance. The effects of cannabis and benzodiazepines should be controlled for in future studies on methadone pharmacokinetics in MMT. [ABSTRACT FROM AUTHOR]