Interval estimation of quantile ratios applied to anti-cancer drug screening by xenograft experiments

Authors

  • Cheng Cheng,

    Corresponding author
    1. Department of Biostatistics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-2794, U.S.A.
    • Department of Biostatistics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-2794, U.S.A.
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  • Jianrong Wu

    1. Department of Biostatistics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-2794, U.S.A.
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Abstract

The current practice in analyzing data from anti-cancer drug screening by xenograft experiments lacks statistical consideration to account for experimental noise, and a sound inference procedure is necessary. A novel confidence bound and interval procedure for estimating quantile ratios developed in this paper fills the void. Justified by rigorous large-sample theory and a simulation study of small-sample performance, the proposed method performs well in a wide range of scenarios involving right-skewed distributions. By providing rigorous inference and much more interpretable statistics that account for experimental noise, the proposed method improves the current practice of analyzing drug activity data in xenograft experiments. The proposed method is fully nonparametric, simple to compute, performs equally well or better than known nonparametric methods, and is applicable to any statistical inference of a ‘fold change’ that can be formulated as a quantile ratio. Copyright © 2010 John Wiley & Sons, Ltd.

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