Bayesian Approach to Assay Sensitivity Analysis of Thorough QT Trials
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作者:
Dong, Xiaoyu
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US FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USAUS FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
Dong, Xiaoyu
[1
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Ding, Xiao
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US FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USAUS FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
Ding, Xiao
[1
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Tsong, Yi
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US FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USAUS FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
Tsong, Yi
[1
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[1] US FDA, Off Biostat, Off Translat Sci, Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
One of the analyses recommended in ICH E14 Guidance (International Conference on Harmonisation, ) after the test drug is shown to be negative in QT interval prolongation after subjects treated with the test drug is an assay sensitivity analysis of a positive control drug with known effect on QT prolongation. The assay sensitivity is validated if the response profile is shown to be expected and the QT interval after administration of the positive control drug is shown to be at least 5 ms more than placebo. The negative result of the test treatment is validated if the prolongation of the positive control is verified among the study subjects. One of the most frequently used positive control drugs in thorough QT (TQT) trials is moxifloxacin. In order to improve the efficiency of the study and to reduce the number of subjects exposed to moxifloxacin, we explore the potential sample size reduction with a Bayesian approach to the assay sensitivity utilizing the data of historical TQT trials. We derived the distribution of moxifloxacin-induced QT prolongation based on 14 crossover trials and six parallel trials. The estimated distribution is used as a prior distribution to assess the posterior probability that the moxifloxacin-induced QT prolongation is larger than 5 ms. Sample size based on such Bayesian approach will be compared with the conventional frequentist approach for efficiency assessment.
机构:
Statistik Georg Ferber, Cagliostrostrasse 14, RiehenStatistik Georg Ferber, Cagliostrostrasse 14, Riehen
Ferber G.
Johannesen L.
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Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD
Department of Clinical Physiology, Karolinska Institutet and Karolinska University Hospital, StockholmStatistik Georg Ferber, Cagliostrostrasse 14, Riehen
机构:
Univ Sheffield, Dept Probabil & Stat, Sheffield S3 7RH, S Yorkshire, EnglandUniv Sheffield, Dept Probabil & Stat, Sheffield S3 7RH, S Yorkshire, England
Oakley, JE
O'Hagan, A
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Univ Sheffield, Dept Probabil & Stat, Sheffield S3 7RH, S Yorkshire, EnglandUniv Sheffield, Dept Probabil & Stat, Sheffield S3 7RH, S Yorkshire, England
机构:
US FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USAUS FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
Ye, Jingjing
Reaman, Gregory
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US FDA, Oncol Ctr Excellence, Silver Spring, MD USAUS FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
Reaman, Gregory
De Claro, R. Angelo
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US FDA, Div Hematol Malignancies DHM1 1, Off Oncol Dis, Ctr Drug Evaluat & Res, Silver Spring, MD USAUS FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA
De Claro, R. Angelo
Sridhara, Rajeshwari
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US FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USAUS FDA, Div Biometr 5, Off Biostat, Off Translat Sci,Ctr Drug Evaluat & Res, Silver Spring, MD 20993 USA