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

Abstract

Background: Whether arrhythmia risks will increase if drugs with electrocardiographic (ECG) QT-prolonging properties are combined is generally supposed but not well studied. Based on available evidence, the Arizona Center for Education and Research on Therapeutics (AZCERT) classification defines the risk of QT prolongation for exposure to single drugs. We aimed to investigate how combining AZCERT drug categories impacts QT duration and how relative drug exposure affects the extent of pharmacodynamic drug-drug interactions.

Methods: In a cohort of 2558 psychiatric inpatients and outpatients, we modeled whether AZCERT class and number of coprescribed QT-prolonging drugs correlates with observed rate-corrected QT duration (QTc) while also considering age, sex, inpatient status, and other QTc-prolonging risk factors. We concurrently considered administered drug doses and pharmacokinetic interactions modulating drug clearance to calculate individual weights of relative exposure with AZCERT drugs. Because QTc duration is concentration-dependent, we estimated individual drug exposure with these drugs and included this information as weights in weighted regression analyses.

Results: Drugs attributing a 'known' risk for clinical consequences were associated with the largest QTc prolongations. However, the presence of at least two versus one QTc-prolonging drug yielded nonsignificant prolongations [exposure-weighted parameter estimates with 95% confidence intervals for 'known' risk drugs + 0.93 ms (-8.88;10.75)]. Estimates for the 'conditional' risk class increased upon refinement with relative drug exposure and co-administration of a 'known' risk drug as a further risk factor.

Conclusions: These observations indicate that indiscriminate combinations of QTc-prolonging drugs do not necessarily result in additive QTc prolongation and suggest that QT prolongation caused by drug combinations strongly depends on the nature of the combination partners and individual drug exposure. Concurrently, it stresses the value of the AZCERT classification also for the risk prediction of combination therapies with QT-prolonging drugs.

Keywords: QT interval; cohort study; drug–drug interactions; electrocardiography; psychiatry.

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.

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) were applied in corresponding linear models with these categorical predictors (gray: standard linear model; black: weighted linear model with relative drug exposure weights).