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Experience of working in clinical trials (which could be as a recruiter, a Trial Manager, a reviewer of ethical applications of trials) ranged from 3 to 20 years.
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This article reviews the statistical differences between superiority, equivalence, and noninferiority design schemes, which pose specific ethical questions and have important implications for interpretation and clinical application of trial results.
There has lately been a growing level of interest in assessing the quality of clinical trials, not only with regard to internal validity, but also in terms of a host of parameters that might guide the application of trial results to informing decisions about the development of medical products, medical practice, or health policy.
Hence application of trial based predictions of treatment effect to the general population may be suboptimal.
As in all models, limitations occur due to application of trial findings to real-world clinical practice, data assumptions, and structural choices.
In this common situation, observational studies provide useful information for application of trial results to clinical practice (Vijan et al, 2000).
Thus one might imagine that legal suits could arise from the application of trial methodology or clinical practice that does not meet international standards.
While randomised controlled trials are the strongest design for determining treatment efficacy, the application of trial results may be limited when trial conditions differ from clinical practice (Fletcher, 2002).
Discussions regarding the generalisability of trial findings (item #21) were lacking in the majority of the Korean RCTs, which may interfere with the application of trial results to actual clinical situations.
For the application of trial sequential analysis to severe hypoglycaemia, the protocol assumed an increase in relative risk of 30%, equivalent to a number needed to harm of 50, to construct the trial sequential monitoring boundaries.
In addition, we reduced the risk of random error in the meta-analyses with the application of trial sequential analysis using predefined variables to increase the robustness of this analysis.
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