Not-in-trial simulation I: Bridging cardiovascular risk from clinical trials to real-life conditions

Abstract

Aims: The assessment of heart rate-corrected QT (QTc) interval prolongation relies on the evidence of drug effects in healthy subjects. This study demonstrates the relevance of pharmacokinetic-pharmacodynamic (PKPD) relationships to characterize drug-induced QTc interval prolongation and explore the discrepancies between clinical trials and real-life conditions.

Methods: d,l-Sotalol data from healthy subjects and from the Rotterdam Study cohort were used to assess treatment response in a phase I setting and in a real-life conditions, respectively. Using modelling and simulation, drug effects at therapeutic doses were predicted in both populations.

Results: Inclusion criteria were shown to restrict the representativeness of the trial population in comparison to real-life conditions. A significant part of the typical patient population was excluded from trials due to weight and baseline QTc interval criteria. Relative risk was significantly different between sotalol users with and without heart failure, hypertension, diabetes and myocardial infarction (P < 0.01). Although drug effects do cause an increase in the relative risk of QTc interval prolongation, the presence of diabetes represented an increase from 4.0 [95% confidence interval (CI) 2.7-5.8] to 6.5 (95% CI 1.6-27.1), whilst for myocardial infarction it increased from 3.4 (95% CI 2.3-5.13) to 15.5 (95% CI 4.9-49.3).

Conclusions: Our findings show that drug effects on QTc interval do not explain the observed QTc values in the population. The prevalence of high QTc values in the real-life population can be assigned to co-morbidities and concomitant medications. These findings substantiate the need to account for these factors when evaluating the cardiovascular risk of medicinal products.

Keywords: QTc interval prolongation; model-based drug development, risk management; observational cohorts; pharmacokinetic-pharmacodynamic modelling; sotalol.

Figure 1

Baseline QTc interval distribution of males and females in the Rotterdam Study. The vertical lines represent the inclusion and exclusion cut-off values for healthy subjects in a thorough QT study. Numbers in the encircled area indicate the proportion of patients in the tails of the distribution

Figure 2

Weight distribution of males and females in the Rotterdam Study. The vertical lines represent the inclusion and exclusion cut-off values for healthy subjects in a thorough QT study. Numbers in the encircled area indicate the proportion of patients in the tails of the distribution

Figure 3

(A) Not-in-trial simulation results show overlapping distributions and discrepancies between observed and predicted QTc interval in the male (M) (left panel) and female (F) population (right panel). The darker colours represent the predicted drug-induced QTc values and the light colours represent the observed overall QTc intervals. The medium shades denote the overlapping areas. (B) QQ plots comparing the distributions of the QTc values for the male (left panel) and female population (right panel). The deviation from the line of identity reflects the residual difference between the observed QTc intervals and model-predicted sotalol effects under the assumption of comparable pharmacokinetic–pharmacodynamic relationship, as determined in phase I clinical trials