Combinations of QTc-prolonging drugs: towards disentangling pharmacokinetic and pharmacodynamic effects in their potentially additive nature

Figures

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  Figure 1.. Predicted change in corrected QT (QTc) interval duration for different AZCERT drug categories. To predict QTc values, the AZCERT drug counts of ‘known’ (■, solid line) and ‘conditional’ risk (•, dotted line) were varied, while other covariates were fixed. Predictions were based on weighted regression models (black), which accounted for individual drug doses and pharmacokinetic drug–drug interaction modulating drug exposure, and on unweighted regression models (gray). The left plot (A) predicts QTc duration in the presence of the number of drugs from the respective AZCERT category only, while the right plot (B) depicts the predicted QTc intervals in the presence of one drug from the other category. AZCERT, Arizona Center for Education and Research on Therapeutics; ms, milliseconds.

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  Figure 2.. Relative change in corrected QT (QTc) interval duration upon presence of drugs from different AZCERT categories (■ solid line: ‘known’ risk; • dotted line: ‘conditional’ risk). The frequencies of AZCERT drugs were categorized into groups of ‘zero’, ‘one’, and ‘more’ (at least two) drugs. Pair-wise many-to-many comparisons (Tukey contrasts) and trend tests (Marcus contrasts)26 were applied in corresponding linear models with these categorical predictors (gray: standard linear model; black: weighted linear model with relative drug exposure weights).