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Abstract:
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Appropriate monitoring of safety data during the conduct of a clinical trial can ensure timely alteration or termination of the trial to protect patients from potentially harmful treatment. Quantitative evaluation in safety monitoring is important for safety reporting and timely decisions making on trial conducting. Bayesian predictive probability approach are naturally appealing for safety monitoring in early safety signal detecting because it directly address the relevant question, that is, whether a safety measurement cross threshold boundary at the end of trial given the current accumulated information. Threshold boundaries during the trial and at the end of trial can be adjusted to achieve desired sensitivity and specificity. In this research, we describe evaluation criteria to choose the threshold boundaries and statistical methods. Furthermore, we propose a Bayesian predictive approach for safety monitoring when treatment information is blinded. Extensive simulation studies are conducted to investigate operation characteristics and sensitiveness for the prop
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