Literature DB >> 33977390

Concentration-QTc analysis with two or more correlated baselines.

Yasushi Orihashi1,2, Yuji Kumagai3.   

Abstract

The relationship between drug concentration and QTc interval is typically evaluated by applying the standard analysis model proposed in a scientific whitepaper by Garnett et al. ( https://doi.org/10.1007/s10928-017-9558-5 ). The model is a mixed effects model in which a baseline QTc interval is included as a covariate. Two or more baseline QTc intervals are sometimes observed for a study participant, such as time-matched baselines on a baseline day in parallel studies, or pre-dose baselines in each period in crossover studies. In such situations, the baseline adjustments are not straightforward because these baselines correlate with not only the corresponding QTc intervals after drug administration, but also other QTc intervals at different timepoints for parallel studies, or those in different periods for crossover studies. In this study, we compared three analysis models through simulations and clinical study examples in settings in which two or more baselines were observed for a subject. We compared a model without baseline adjustment, a model with baseline adjustment, and a model in which baseline and baseline mean were included as covariates. In the simulations and clinical study examples, the model with baseline and baseline mean as covariates demonstrated higher accuracy and power than the other models. This model assumed a specific covariance structure in QTc intervals, which well approximated the correlations between QTc intervals within and between days. When there are two or more baselines in concentration-QTc analyses, the baseline mean should be included as a covariate in addition to the corresponding baseline.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Baseline; Concentration-QTc model; ICH E14; Mixed effects model; QTc interval

Mesh:

Substances:

Year:  2021        PMID: 33977390     DOI: 10.1007/s10928-021-09758-9

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  19 in total

Review 1.  Concentration-QT relationships play a key role in the evaluation of proarrhythmic risk during regulatory review.

Authors:  Christine E Garnett; Nhi Beasley; V Atul Bhattaram; Pravin R Jadhav; Rajanikanth Madabushi; Norman Stockbridge; Christoffer W Tornøe; Yaning Wang; Hao Zhu; Jogarao V Gobburu
Journal:  J Clin Pharmacol       Date:  2008-01       Impact factor: 3.126

2.  Sample size calculations in thorough QT studies.

Authors:  Lu Zhang; Alex Dmitrienko; George Luta
Journal:  J Biopharm Stat       Date:  2008       Impact factor: 1.051

3.  The use of baseline covariates in crossover studies.

Authors:  Michael G Kenward; James H Roger
Journal:  Biostatistics       Date:  2009-11-13       Impact factor: 5.899

4.  Mixed models for data from thorough QT studies: part 1. assessment of marginal QT prolongation.

Authors:  Robert Schall; Arne Ring
Journal:  Pharm Stat       Date:  2010-10-26       Impact factor: 1.894

5.  Novel concentration-QTc models for early clinical studies with parallel placebo controls: A simulation study.

Authors:  Yasushi Orihashi; Yuji Kumagai; Kazuhito Shiosakai
Journal:  Pharm Stat       Date:  2020-12-08       Impact factor: 1.894

6.  An efficient and robust analysis of covariance model for baseline adjustment in parallel-group thorough QT/QTc studies.

Authors:  Kaifeng Lu
Journal:  Stat Med       Date:  2012-09-19       Impact factor: 2.373

7.  Various varying variances: The challenge of nuisance parameters to the practising biostatistician.

Authors:  Stephen Senn
Journal:  Stat Methods Med Res       Date:  2014-02-02       Impact factor: 3.021

8.  An efficient analysis of covariance model for crossover thorough QT studies with period-specific pre-dose baselines.

Authors:  Kaifeng Lu
Journal:  Pharm Stat       Date:  2014-10-06       Impact factor: 1.894

Review 9.  Scientific white paper on concentration-QTc modeling.

Authors:  Christine Garnett; Peter L Bonate; Qianyu Dang; Georg Ferber; Dalong Huang; Jiang Liu; Devan Mehrotra; Steve Riley; Philip Sager; Christoffer Tornoe; Yaning Wang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-12-05       Impact factor: 2.745

10.  Assay sensitivity in "Hybrid thorough QT/QTc (TQT)" study.

Authors:  Dalong Patrick Huang; Janell Chen; Qianyu Dang; Yi Tsong
Journal:  J Biopharm Stat       Date:  2018-10-22       Impact factor: 1.051

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.