Sample size calculations for crossover thorough QT studies: Satisfaction of regulatory threshold and assay sensitivity

Journal of Biopharmaceutical Statistics

Volumn 20, Issue 3, 2010, Pages 563-579

  Anand, Suraj P ^a   Murray, Sharon C ^b   Koch, Gary G ^c  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b GLAXOSMITHKLINE   (United States)

^c University of North Carolina at Chapel Hill   (United States)

Author keywords

Correlation structure; ICH E14; Monte Carlo simulation; Power and sample size; QTc prolongation; Thorough QT QTc study

Indexed keywords

ANALYTIC METHOD; ARTICLE; ASSAY; CALCULATION; CROSSOVER PROCEDURE; HUMAN; METHODOLOGY; PRIORITY JOURNAL; QT INTERVAL; SAMPLE SIZE; SATISFACTION; STATISTICAL MODEL;

EID: 77951683693     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400903582000     Document Type: Article

References (16)

1. Abt, K. (1991). Planning controlled clinical trials on the basis of descriptive data analysis. Stat. Med. 10:777-795.
2. Anand, S. P., Ghosh, S. K. (2009). A Bayesian approach for investigating the risk of QT prolongation. J. Stat. Theory Pract. 3(2):445-454.
3. Anand, S. P., Murray, S. C., Koch, G. G. (2008). A multivariate approach to sample size calculations for thorough QT studies. Institute of Statistics Mimeo Series number 2608. Available at: www.stat.ncsu.edu/library/papers/ ISMS2608.pdf
4. Boos, D., Hoffman, D., Kringle, R., Zhang, J. (2007). New confidence bounds for QT studies. Stat. Med. 26:3801-3817.
5. Chow, S., Cheng, B., Cosmatos, D. (2008). On power and sample size calculation for QT studies with recording replicates at given time point. J. Biopharm. Stat. 18(3):483-493.
6. Eaton, M. L., Muirhead, R. J., Mancuso, J. Y., Lolluri, S. (2006). A confidence interval for the maximal mean QT interval change due drug effect. Drug Information J. 40:267-271.
7. Hailperin, T. (1965). Best possible inequalities for the probability of a logical function of events. Am. Math. Monthly 72:343-359.
8. Hosmane, B., Locke, C. (2005). A simulation study of power in thorough QT/QTc studies and a normal approximation for planning purposes. Drug Information J. 39:447-455.
9. International Conference on Harmonisation. (2005). Guidance for Industry: E14 Clinical Evaluation of QT/QTc Interval Prolongation and Proarrythmic Potential for Non-Antiarrythmic Drugs. Available at: www.fda.gov/cber/gdlns/ iche14qtc.htm
10. Patterson, S., Agin, M., Anziano, R., et al. (2005). Investigating drug-induced QT and QTc prolongation in the clinic: a review of statistical design and analysis considerations: Report from the pharmaceutical research and manufacturers of America QT statistics expert team. Drug Information J. 9:243-266.
11. Rüger, B. (1978). Das maximale signifikanzniveau des tests: "Lehne H ab, wenn k unter n gegebenen Tests zur Ablehnung führen." Metrika 25:171-178.
12. Senn, S. J. (2002). Cross-Over Trials in Clinical Research. Chichester, UK: John Wiley.
13. Tsong, Y., Zhong, J., Chen, W. J. (2008). Validation testing in thorough QT/QTc clinical trials. J. Biopharm. Stat. 18(3):529-541.
14. Zhang, J. (2008). Testing for positive control activity in a thorough QTc study. J. Biopharm. Stat. 18(3):517-528.
15. Zhang, J., Machado, S. G. (2008). Statistical issues including design and sample size calculation in thorough QT/QTc studies. J. Biopharm. Stat. 18(3):451-467.
16. Zhang, L., Dmitrienko, A., Luta, G. (2008). Sample size calculations in thorough QT studies. J. Biopharm. Stat. 18(3):468-482.