Sato Yasunori, Gosho Masahiko, Toshimori Kiyotaka
Clinical Research Center Chiba University Hospital 1-8-1 Inohana, Chuo-ku 260-8677 Chiba Japan.
Department of Biostatistics Harvard School of Public Health Boston MA USA.
Reprod Med Biol. 2011 Aug 5;11(1):49-58. doi: 10.1007/s12522-011-0106-5. eCollection 2012 Jan.
During the last decade, evidence-based medicine has been described as a paradigm shift in clinical practice, and as "the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients". Appropriate statistical methods for analyzing data are critical for the correct interpretation of the results in proof of the evidence. However, in the medical literature, these statistical methods are often incorrectly interpreted or misinterpreted, leading to serious methodological errors and misinterpretations. This review highlights several important aspects related to the design and statistical analysis for evidence-based reproductive medicine. First, we clarify the distinction between ratios, proportions, and rates, and then provide a definition of pregnancy rate. Second, we focus on a special type of bias called 'confounding bias', which occurs when a factor is associated with both the exposure and the disease but is not part of the causal pathway. Finally, we present concerns regarding misuse of statistical software or application of inappropriate statistical methods, especially in medical research.
在过去十年中，循证医学被描述为临床实践中的一种范式转变，并且被定义为“在为个体患者的治疗做出决策时，审慎、明确且明智地运用当前最佳证据”。用于分析数据的适当统计方法对于正确解读证据证明中的结果至关重要。然而，在医学文献中，这些统计方法常常被错误解读或误解，从而导致严重的方法学错误和错误解读。本综述强调了与循证生殖医学的设计和统计分析相关的几个重要方面。首先，我们阐明比率、比例和率之间的区别，然后给出妊娠率的定义。其次，我们关注一种特殊类型的偏倚，即“混杂偏倚”，当一个因素与暴露和疾病都相关但并非因果路径的一部分时就会出现这种偏倚。最后，我们提出了对统计软件滥用或不适当统计方法应用的担忧，尤其是在医学研究中。
