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Santen G et al. – Results show that data simulated using the DREM closely match individual patient data, including real–life dropout scenarios. In addition, parameterization in terms of interindividual variability ensures easier explanation of findings to clinical scientists, who ultimately make the relevant decisions.

Exclusive Author Commentary
O Della Pasqua, 08/08/09

This is the first of two articles on the relevance of clinical trial simulations in drug development and clinical research. The first article focuses on the requirements for statistical models which have clinical predictive value (i.e., describe patient response profiles), rather than just for the purpose of hypothesis testing. In the second paper, we show the advantages of clinical trial simulation over meta-analysis as the 'gold standard' method for assessing overall treatment effects or comparing differences between treatments. Statistical tools should not be left to statisticians alone. It is time physicians learn how to assess clinical relevance, rather than dwell solely on statistical significance.

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