Collins R, MacMahon S
Nuffield Department of Clinical Medicine, Radcliffe Infirmary, Oxford, UK.
Lancet. 2001 Feb 3;357(9253):373-80. doi: 10.1016/S0140-6736(00)03651-5.
This two-part review is intended principally for practising clinicians who want to know why some types of evidence about the effects of treatment on survival, and on other major aspects of chronic disease outcome, are much more reliable than others. Although there are a few striking examples of treatments for serious disease which really do work extremely well, most claims for big improvements turn out to be evanescent. Unrealistic expectations about the chances of discovering large treatment effects could misleadingly suggest that evidence from small randomised trials or from non-randomised studies will suffice. By contrast, the reliable assessment of any more moderate effects of treatment on major outcomes--which are usually all that can realistically be expected from most treatments for most common serious conditions--requires studies that guarantee both strict control of bias (which, in general, requires proper randomisation and appropriate analysis, with no unduly data-dependent emphasis on specific parts of the overall evidence) and strict control of random error (which, in general, requires large numbers of deaths or of some other relevant outcome). Past failures to produce such evidence, and to interpret it appropriately, have already led to many premature deaths and much unnecessary suffering.
这篇分为两部分的综述主要面向那些想要了解为何某些关于治疗对生存以及慢性病结局其他主要方面影响的证据比其他证据更为可靠的临床执业医师。尽管有一些针对严重疾病的治疗方法确实效果极佳的显著例子,但大多数关于大幅改善的说法最终都消失了。对发现重大治疗效果可能性的不切实际期望可能会误导性地表明,来自小型随机试验或非随机研究的证据就足够了。相比之下,要对治疗对主要结局的任何更适度的影响进行可靠评估(这通常是大多数针对大多数常见严重病症的治疗所能实际期望的全部),需要保证严格控制偏倚(一般而言,这需要适当的随机化和恰当的分析,不能过度依赖数据而片面强调整体证据的特定部分)以及严格控制随机误差(一般而言,这需要大量的死亡病例或其他一些相关结局)的研究。过去未能产生此类证据并对其进行恰当解读,已经导致了许多过早死亡和诸多不必要的痛苦。