Detection of an Outlier and Evaluation of its Influence in Chronic Toxicity Studies
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0092-8615/98 Copyright 0 1998 Drug Information Association Inc.
DETECTION OF AN OUTLIER AND EVALUATION OF ITS INFLUENCE IN CHRONIC TOXICITY STUDIES CHIKUMA HAMADA,MS Department of Pharmacoepidemiology, Faculty of Medicine, University of Toyko, Tokyo, Japan
KEI YOSHINO Toxicology Research Laboratories. Central Pharmaceutical Research Institute, Japan Tobacco Inc.. Kanagawa, Japan
IKUMI ABE Toxicology Laboratory, Yokohama Research Center, Mitsubishi Chemical CO. LTD., Kanagawa, Japan
KAZUHIKOMATSUMOTO, PHD Toxicology Research Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., Kanagawa, Japan
MAMORUNOMURA,DVM Drug Safety Research Laboratory, Dai-ichi Pharmaceutical CO. LTD., Tokyo, Japan
ISAO YOSHIMURA, PHD Faculty of Engineering, Science University of Tokyo, Tokyo, Japan
Targeting quantitative data in repeated-dose toxicity studies using rodents, a method for detecting an outlier and a selection problem between parametric and nonparametric approaches, based on actual toxicity data, was investigated. The consistency between the judgments of veteran toxicologists and several statistical methods (skewness, kurtosis, and the studentized residual) to detect an outlier was evaluated. The stua'entized residual had the highest consistency with the judgments of toxicologists and was the most effective method for detecting an outlier: The performance of the parametric (regression) method and the nonparametric method (Jonckheere test)for detecting dose-dependency was evaluated. Parametric and nonparametric approaches had a different result when outliers existed. Parametric methods are sensitive to the presence of outliers and they lose statistical power: In contrast, nonparametric approaches are robust to outliers. The identification of extreme individual measures is, however, a different objective for safety studies versus the detection of dose-dependency, and it may require different methods. Detecting an outlier, and investigating its impact on statistical analysis and biological interpretation, is very important and requires the use of appropriate methods. Key Words: Outlier; Studentized residual; Toxicological evaluation; Parametric method and nonparametric method
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C. Hamada, K. Yoshino, I, Abe, K. Matsumoto, M.Nomura, and I. Yoshimura
INTRODUCTION
lT IS OBVIOUS THAT biostatistics plays a basic role in adequate toxicity assessment. The biostatistical evaluation of repeated toxicity studies should support the decision for whether a finding is positive or negative and the magnitude of the toxic effects quantitatively. Statistical analysis in repeated toxicity studies possesses confirmatory and exploratory characteristics simultaneously. Appropriate statistical methodology in toxicity studies have been discussed, and many statistical methods have already been proposed Over the last two decades* Many practical problems, however, still remain unresolved. Therefore, targeting quantitative data in repeated-dos
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