Abstract
Graphical data exploration of clinical trial results is an imperative step prior to any model-based analyses. Thorough understanding of the raw data and the biological and statistical significances will certainly increase the likelihood of constructing a useful model and evade excessive complex data representation and overfitting. In this work, we use graphical data exploration to assess the cardiovascular safety of Drug X by estimating the propensity for the drug to alter the duration of the QT interval. We also identify model building strategies and the potential models that may be tested incrementally. Insights gained from this exercise will improve the efficiency of the model building process, communicate a clear and simple representation for complex data, and provide a useful decision making instrument for the drug development program.
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Acknowledgments
The authors thank Dr. Douglas A. Marsteller for his help during his summer internship at J&J.
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© 2012 Springer Science+Business Media, New York
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Girgis, I.G., Mohanty, S. (2012). Graphical Data Exploration in QT Model Building and Cardiovascular Drug Safety. In: Krause, A., O'Connell, M. (eds) A Picture is Worth a Thousand Tables. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5329-1_13
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DOI: https://doi.org/10.1007/978-1-4614-5329-1_13
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