Schechtman Edna
Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beer Sheva, Israel.
Value Health. 2002 Sep-Oct;5(5):431-6. doi: 10.1046/J.1524-4733.2002.55150.x.
Statistical analyses of data and making sense of medical data have received much attention in the medical literature, but nevertheless have caused confusion among practitioners. Each researcher provides a different method for comparing treatments. For example, when the end point is binary, such as disease versus no disease, the common measures are odds ratios, relative risk, relative risk reduction, absolute risk reduction, and the number needed to treat. The question faced by the practitioner is then: Which one will help me in choosing the best treatment for my patient?
The purpose of this paper is to illustrate, using examples, how each measure is used, what it means, and what are its advantages and disadvantages.
Some pairs of measures present equivalent information. Furthermore, it is shown that different measures result in different impressions.
It is recommended that researchers report both a relative and an absolute measure and present these with appropriate confidence intervals.
数据的统计分析以及理解医学数据在医学文献中受到了广泛关注，但仍在从业者中引发了困惑。每位研究者都提供了不同的治疗比较方法。例如，当终点是二元的，如患病与未患病时，常用的指标有比值比、相对危险度、相对危险度降低率、绝对危险度降低率以及治疗所需人数。那么从业者面临的问题是：哪一个指标能帮助我为患者选择最佳治疗方案？
本文旨在通过实例说明每个指标是如何使用的、其含义是什么以及优缺点。
有些指标对呈现的是等效信息。此外，研究表明不同指标会产生不同的印象。
建议研究者同时报告相对指标和绝对指标，并给出适当的置信区间。
