Department of Medicine, Section of Rheumatology, Boston University School of Medicine, 72 E Concord St, E-533, Boston, MA 02118, USA.
Biomark Med. 2012 Oct;6(5):691-703. doi: 10.2217/bmm.12.57.
Researchers often decide whether to average multiple results in order to produce more precise data, and clinicians often decide whether to repeat a laboratory test in order to confirm its validity or to follow a trend. Some of the major sources of variation in laboratory tests (analytical imprecision, within-subject biological variation and between-subject variation) and the effects of averaging multiple results from the same sample or from the same person over time are discussed quantitatively in this article. This analysis leads to the surprising conclusion that the strategy of averaging multiple results is only necessary and effective in a limited range of research studies. In clinical practice, it may be important to repeat a test in order to eliminate the possibility of a rare type of error that has nothing to do analytical imprecision or within-subject variation, and for this reason, paradoxically, it may be most important to repeat tests with the highest sensitivity and/or specificity (i.e., ones that are critical for clinical decision-making).
研究人员经常决定是否平均多个结果,以产生更精确的数据,临床医生经常决定是否重复实验室测试,以确认其有效性或跟踪趋势。本文定量讨论了实验室测试中的一些主要变异来源(分析不精密度、个体内生物学变异和个体间变异)以及随时间从同一样本或同一人平均多个结果的影响。这一分析得出了一个令人惊讶的结论,即平均多个结果的策略仅在有限的研究范围内是必要和有效的。在临床实践中,为了消除与分析不精密度或个体内变异无关的罕见类型错误的可能性,重复测试可能很重要;出于这个原因,具有讽刺意味的是,重复具有最高灵敏度和/或特异性的测试(即对临床决策至关重要的测试)可能是最重要的。