Thomas R, Muliyil J, Paul P
Department of Ophthalmology, Christian Medical College, Vellore.
J Indian Med Assoc. 2001 Oct;99(10):561-4, 566.
Ophthalmologists are frequently confronted with treatment options that claim to be better than those currently in use. Statistically significant P values are invariably provided by way of proof. For many ophthalmologists a simple look at this revered P value is enough evidence that a statistically significant result has indeed been obtained. Unfortunately, traditional interpretation of a study based on the P value at an arbitrary cut-off (P<0.05 or any other value) limits the ability to fully appreciate clinical implications. In this article the authors introduce the reader to and illustrate the use of "confidence intervals" as opposed to P values in examining the applicability of study results. Further, what is statistically significant may not necessarily be clinically significant; perhaps not enough for the practitioner to change from the currently preferred method of treatment. To resolve this, the authors have also used common ophthalmic examples to introduce the "number needed to treat", as a simple clinical approach for the practising ophthalmologist wishing to assess the clinical significance of treatment options.
眼科医生经常面临声称比现有治疗方法更好的治疗选择。这些方法总会提供具有统计学意义的P值作为证据。对于许多眼科医生来说,只需看一眼这个备受尊崇的P值,就足以证明确实获得了具有统计学意义的结果。不幸的是,基于任意临界值(P<0.05或其他任何值)的P值对研究进行传统解读,限制了全面理解临床意义的能力。在本文中,作者向读者介绍并举例说明了“置信区间”在检验研究结果适用性方面的应用,以替代P值。此外,具有统计学意义的结果不一定具有临床意义;可能还不足以让从业者改变当前首选的治疗方法。为了解决这个问题,作者还通过常见的眼科实例引入了“需治疗人数”,作为一种简单的临床方法,供执业眼科医生评估治疗选择的临床意义。