Jovanovic B D, Zalenski R J
Center for Health Services Research, School of Public Health, University of Illinois at Chicago, USA.
Ann Emerg Med. 1997 Sep;30(3):301-6. doi: 10.1016/s0196-0644(97)70165-3.
A common objective in many clinical studies is to determine the safety of a diagnostic test or therapeutic intervention. In these evaluations, serious adverse effects are either rare or not encountered. In this setting, the estimation of the confidence interval (CI) for the unknown proportion of adverse events has special importance. When no adverse events are encountered, commonly used approximate methods for calculating CIs cannot be applied, and such information is not commonly reported. Furthermore, when only a few adverse events are encountered, the approximate methods for calculation of CIs can be applied, but are neither appropriate nor accurate. In both situations, CIs should be computed with the use of the exact binomial distribution. We discuss the need for such estimation and provide correct methods and rules of thumb for quick computations of accurate approximations of the 95% and 99.9% CIs when the observed number of adverse events is zero.
许多临床研究的一个共同目标是确定诊断测试或治疗干预的安全性。在这些评估中，严重不良反应要么罕见，要么未被发现。在这种情况下，对不良事件未知比例的置信区间（CI）进行估计尤为重要。当未遇到不良事件时，常用的计算CI的近似方法无法应用，而且此类信息通常也不会被报告。此外，当仅遇到少数不良事件时，可以应用计算CI的近似方法，但这些方法既不合适也不准确。在这两种情况下，都应使用精确的二项分布来计算CI。我们讨论了这种估计的必要性，并提供了正确的方法和经验法则，以便在观察到的不良事件数量为零时快速计算95%和99.9%CI的准确近似值。
