Howards Penelope P, Hertz-Picciotto Irva, Poole Charles
Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, Rockville, MD 20852, USA.
Am J Epidemiol. 2007 Feb 15;165(4):444-52. doi: 10.1093/aje/kwk027. Epub 2006 Dec 5.
Spontaneous abortion studies that recruit pregnant women are left truncated because an unknown proportion of the source population experiences losses prior to enrollment. Unconditional logistic regression, commonly used in such studies, ignores left truncation, whereas survival analysis can accommodate left truncation and is therefore more appropriate. This study assessed the magnitude of bias introduced by fitting logistic versus Cox models using left-truncated data from a 1998 US pregnancy cohort study (n = 5,104) of trihalomethanes and spontaneous abortion. In addition, the conditions producing bias were explored by using simulated exposure data. The odds ratios and hazard ratios from the actual study differed by 10% or less. However, when the exposed women entered observation earlier on average than those unexposed, the hazard ratio was closer to the null than the odds ratio, whereas the reverse was true when the exposed entered later. The simulation suggests that bias in the odds ratio will exceed 20% when average gestational age at entry for the exposed versus the unexposed differs by 10 days or more, as has been observed regarding some socioeconomic factors, such as education and ethnicity. Cox regression can correct for left truncation and is no more difficult to perform than logistic regression.
招募孕妇的自然流产研究存在左截断问题，因为在源人群中有未知比例的人在入组前就经历了流产。此类研究中常用的无条件逻辑回归忽略了左截断，而生存分析可以处理左截断，因此更为合适。本研究使用来自1998年美国一项关于三卤甲烷与自然流产的妊娠队列研究（n = 5104）的左截断数据，评估了拟合逻辑模型与Cox模型所引入的偏差程度。此外，通过使用模拟暴露数据探讨了产生偏差的条件。实际研究中的比值比和风险比相差10%或更少。然而，当暴露组女性平均比未暴露组女性更早进入观察时，风险比比比值比更接近无效值，而当暴露组女性进入观察更晚时情况则相反。模拟结果表明，当暴露组与未暴露组的平均入组孕周相差10天或更多时，比值比的偏差将超过20%，就像在一些社会经济因素（如教育程度和种族）方面所观察到的那样。Cox回归可以校正左截断，并且执行起来并不比逻辑回归更困难。
