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Sample Size and Data Monitoring for Clinical Trials With Extremely Low Incidence Rates

机译:发生率极低的临床试验的样本量和数据监控

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摘要

In clinical trials, statistical analyses on incidence rates detect significant differences between the responses from groups. Sample size estimation is always one of the key aspects in clinical trials that have limited budgets. A prestudy power analysis for sample size calculation is often performed to select an appropriate sample size that will achieve a desired power (ie, the probability of correctly detecting the significant difference if such a difference truly exists) at a prespecified level of significance. In practice, it is expected that a greater sample size is needed to detect a smaller difference. A much larger sample size is required to detect a relatively small difference, especially for those clinical studies with extremely low incidence rates. Thus, sample size calculation based on prestudy power analysis may not be feasible in practice. In this case, as an alternative, the authors propose to justify a selected sample size based on a precision analysis and a sensitivity analysis. A recommended step-by-step procedure for sample size determination in clinical trials with extremely low incidence rate is given. A statistical procedure for data safety monitoring based on the probability statement during the conduct of the clinical trial is also proposed.
机译:在临床试验中,对发病率的统计分析发现两组反应之间存在显着差异。在预算有限的情况下,样本量估算始终是临床试验中的关键方面之一。通常进行用于样本量计算的研究前功效分析,以选择适当的样本量,该样本量将以预定的显着性水平实现期望的功效(即,如果这种差异确实存在,则可以正确检测到显着差异的概率)。在实践中,预期需要更大的样本量来检测较小的差异。需要较大的样本量来检测相对较小的差异,尤其是对于那些发生率极低的临床研究。因此,基于预研究能力分析的样本量计算在实践中可能不可行。在这种情况下,作为替代方案,作者建议根据精确度分析和敏感性分析来证明所选样本量的合理性。给出了在极低发生率的临床试验中确定样品量的推荐分步方法。还提出了在临床试验过程中基于概率陈述进行数据安全监控的统计程序。

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