Lee Peter N, Fry John S, Thornton Alison J
P N Lee Statistics and Computing Ltd, Sutton, Surrey, United Kingdom.
P N Lee Statistics and Computing Ltd, Sutton, Surrey, United Kingdom.
Regul Toxicol Pharmacol. 2014 Feb;68(1):85-95. doi: 10.1016/j.yrtph.2013.11.013. Epub 2013 Nov 26.
We attempted to quantify the decline in stroke risk following quitting using the negative exponential model, with methodology previously employed for IHD. We identified 22 blocks of RRs (from 13 studies) comparing current smokers, former smokers (by time quit) and never smokers. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We tried to estimate the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block. The method failed to converge or produced very variable estimates of H in nine blocks with a current smoker RR <1.40. Rejecting these, and combining blocks by amount smoked in one study where problems arose in model-fitting, the final analyses used 11 blocks. Goodness-of-fit was adequate for each block, the combined estimate of H being 4.78(95%CI 2.17-10.50) years. However, considerable heterogeneity existed, unexplained by any factor studied, with the random-effects estimate 3.08(1.32-7.16). Sensitivity analyses allowing for reverse causation or differing assumed times for the final quitting period gave similar results. The estimates of H are similar for stroke and IHD, and the individual estimates similarly heterogeneous. Fitting the model is harder for stroke, due to its weaker association with smoking.
我们尝试使用负指数模型来量化戒烟后中风风险的下降情况,该模型的方法学曾用于缺血性心脏病(IHD)的研究。我们从13项研究中确定了22组相对风险(RR),比较了当前吸烟者、既往吸烟者(按戒烟时间)和从不吸烟者。相应的病例和对照/处于风险中的伪数量构成了模型拟合的数据。我们试图估计每组的半衰期(H,即戒烟后风险降至持续吸烟者风险一半时的时间)。在当前吸烟者RR<1.40的9组中,该方法未能收敛或产生了非常不稳定的H估计值。剔除这些组,并在一项模型拟合出现问题的研究中按吸烟量合并组,最终分析使用了11组。每组的拟合优度都足够,合并后的H估计值为4.78(95%可信区间2.17 - 10.50)年。然而,存在相当大的异质性,所研究的任何因素都无法解释,随机效应估计值为3.08(1.32 - 7.16)。考虑反向因果关系或最终戒烟期不同假设时间的敏感性分析得出了类似的结果。中风和IHD的H估计值相似,但个体估计值同样具有异质性。由于中风与吸烟的关联较弱,对中风进行模型拟合更困难。