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
]
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:
Univ Claude Bernard Lyon 1, Univ Lyon, IFSTTAR, LBMC UMR T9406, F-69622 Villeurbanne, FranceUniv Claude Bernard Lyon 1, Univ Lyon, IFSTTAR, LBMC UMR T9406, F-69622 Villeurbanne, France
机构:
Univ Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Univ Rochester, Sch Med & Dent, Dept Neurol, Rochester, NY 14642 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Dworkin, Robert H.
Turk, Dennis C.
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Univ Washington, Dept Anesthesiol & Pain Med, Seattle, WA 98195 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Turk, Dennis C.
Peirce-Sandner, Sarah
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Univ Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Peirce-Sandner, Sarah
He, Hua
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Univ Rochester, Sch Med & Dent, Dept Biostat & Computat Biol, Rochester, NY USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
He, Hua
McDermott, Michael P.
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Univ Rochester, Sch Med & Dent, Dept Biostat & Computat Biol, Rochester, NY USA
Univ Rochester, Sch Med & Dent, Dept Neurol, Rochester, NY 14642 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
McDermott, Michael P.
Farrar, John T.
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Univ Penn, Dept Clin Epidemiol & Biostat, Philadelphia, PA 19104 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Farrar, John T.
Katz, Nathaniel P.
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Analges Solut, Natick, MA USA
Tufts Univ, Boston, MA 02111 USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Katz, Nathaniel P.
Lin, Allison H.
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US FDA, Div Anesthesia Analgesia & Addict Prod, Silver Spring, MD USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Lin, Allison H.
Rappaport, Bob A.
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US FDA, Div Anesthesia Analgesia & Addict Prod, Silver Spring, MD USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA
Rappaport, Bob A.
Rowbotham, Michael C.
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Calif Pacific Med Ctr, Ctr Res Inst, San Francisco, CA USAUniv Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14627 USA