Hak E, Verheij Th J M, Grobbee D E, Nichol K L, Hoes A W
Julius Centre for General Practice and Patient Oriented Research, University Medical Centre Utrecht, Netherlands.
J Epidemiol Community Health. 2002 Dec;56(12):951-5. doi: 10.1136/jech.56.12.951.
Randomised allocation of vaccine or placebo is the preferred method to assess the effects of the vaccine on clinical outcomes relevant to the individual patient. In the absence of phase 3 trials using clinical end points, notably post-influenza complications, alternative non-experimental designs to evaluate vaccine effects or safety are often used. The application of these designs may, however, lead to invalid estimates of vaccine effectiveness or safety. As patients with poor prognosis are more likely to be immunised, selection for vaccination is confounded by patient factors that are also related to clinical end points. This paper describes several design and analytical methods aimed at limiting or preventing this confounding by indication in non-experimental studies. In short, comparison of study groups with similar prognosis, restriction of the study population, and statistical adjustment for dissimilarities in prognosis are important tools and should be considered. Only if the investigator is able to show that confounding by indication is sufficiently controlled for, results of a non-experimental study may be of use to direct an evidence based vaccine policy.
随机分配疫苗或安慰剂是评估疫苗对个体患者相关临床结局影响的首选方法。在缺乏使用临床终点(尤其是流感后并发症)的3期试验的情况下,常采用替代的非实验性设计来评估疫苗效果或安全性。然而,这些设计的应用可能导致对疫苗有效性或安全性的无效估计。由于预后较差的患者更有可能接种疫苗,疫苗接种的选择受到与临床终点也相关的患者因素的混杂影响。本文描述了几种旨在限制或防止非实验性研究中这种指征性混杂的设计和分析方法。简而言之,比较预后相似的研究组、限制研究人群以及对预后差异进行统计调整是重要的工具,应予以考虑。只有当研究者能够证明指征性混杂得到充分控制时,非实验性研究的结果才可能有助于指导基于证据的疫苗政策。