The International Council for Harmonisation (ICH) guidelines have been revised allowing for modeling of concentration-QT (C-QT) data from Phase I dose-escalation studies to be used as primary analysis for QT prolongation risk assessment of new drugs. This work compares three commonly used Phase I dose-escalation study designs regarding their efficiency to accurately identify drug effects on QT interval through C-QT modeling. Parallel group design and 4-period crossover designs with sequential or interleaving cohorts were evaluated. Clinical trial simulations were performed for each design and across different scenarios (e.g. different magnitudes of drug effect, QT variability), assuming a pre-specified linear mixed effect (LME) model for the relationship between drug concentration and change from baseline QT (ΔQT). Analyses suggest no systematic bias in either the predictions of placebo-adjusted ΔQT (ΔΔQT) or the LME model parameter estimates across all evaluated designs. Additionally, false negative rates remained similar and adequately controlled across all evaluated designs. However, compared to the crossover designs, the parallel design had significantly less power to correctly exclude a clinically significant QT effect, especially in the presence of substantial intercept inter-individual variability. In such cases, parallel design is associated with increased uncertainty around ΔΔQT prediction, mainly attributed to the uncertainty around the estimation of the treatment-specific intercept in the model. Throughout all the evaluated scenarios, the crossover design with interleaving cohorts had consistently the best performance characteristics. The results from this investigation will further facilitate informed decision-making during Phase I study design and the interpretation of the associated C-QT modeling output.

中文翻译：

---

使用暴露-反应分析的1期研究设计对QT间期延长风险评估的影响。

国际协调委员会（ICH）指南已进行了修订，允许对第一阶段剂量递增研究中的浓度QT（C-QT）数据进行建模，以用作新药QT延长风险评估的主要分析方法。这项工作比较了三种常用的I期剂量递增研究设计，这些设计通过C-QT建模准确识别药物对QT间隔的影响。评估了平行组设计和具有顺序或交错队列的4周期交叉设计。假设预先设定的线性混合效应（LME）模型用于药物浓度和基线QT变化（ΔQT）之间的关系，并针对每种设计并在不同情况下（例如，不同的药物作用幅度，QT变异性）进行了临床试验模拟。 。分析表明，在所有评估设计中，安慰剂调整后的ΔQT（ΔΔQT）或LME模型参数估计值的预测均无系统偏差。此外，在所有评估设计中，假阴性率保持相似并得到充分控制。但是，与交叉设计相比，并行设计的功率明显不足，无法正确排除临床上显着的QT效应，尤其是在个体之间存在明显的变异性的情况下。在这种情况下，并行设计与围绕ΔΔQT预测的不确定性增加有关，这主要归因于模型中特定于治疗的截距的估计周围的不确定性。在所有评估的场景中，具有交错队列的交叉设计始终具有最佳性能特征。