Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA.
Moores Cancer Center, University of California, San Diego, La Jolla, CA.
J Natl Cancer Inst. 2018 Jun 1;110(6):581-587. doi: 10.1093/jnci/djx240.
Despite strong efficacy in randomized trials, the population effectiveness of pharmaceutical aids in long-term smoking cessation is lacking, possibly because of confounding (factors that are associated with both pharmaceutical aid use and difficulty quitting). Matching techniques in longitudinal studies can remove this confounding bias.
Using the nationally representative Tobacco Use Supplement to the Current Population Survey (TUS-CPS), we assessed the effectiveness of medications to aid quitting among baseline adult smokers who attempted to quit prior to one year of follow-up in two longitudinal studies: 2002-2003 and 2010-2011. Pharmaceutical aid users and nonusers with complete data (n = 2129) were matched using propensity score models with 12 potential confounders (age, sex, race-ethnicity, education, smoking intensity, nicotine dependence, previous quit history, self-efficacy to quit, smoke-free homes, survey year, and cessation aid use). Using matched data sets, logistic regression models were fit to assess whether use of any individual pharmaceutical aid increased the proportion of patients who were abstinent for 30 days or more at follow-up.
Propensity score matching markedly improved balance on the potential confounders between the pharmaceutical aid use groups. Using matched samples to provide a balanced comparison, there was no evidence that use of varenicline (adjusted risk difference [aRD] = 0.01, 95% confidence interval [CI] = -0.07 to 0.11), bupropion (aRD = 0.02, 95% CI = -0.04 to 0.09), or nicotine replacement (aRD = 0.01, 95% CI = -0.03 to 0.06) increased the probability of 30 days or more smoking abstinence at one-year follow-up.
The lack of effectiveness of pharmaceutical aids in increasing long-term cessation in population samples is not an artifact caused by confounded analyses. A possible explanation is that counseling and support interventions provided in efficacy trials are rarely delivered in the general population.
尽管随机试验显示药物辅助在长期戒烟方面具有显著疗效，但在人群中其效果仍存在争议，这可能是因为存在混杂因素（即与药物辅助使用和戒烟难度均相关的因素）。在纵向研究中，匹配技术可消除这种混杂偏差。
我们利用具有全国代表性的《当前人口调查中的烟草使用补充调查》（TUS-CPS），在两项纵向研究中评估了药物辅助戒烟在基线时尝试戒烟且在随访前一年尚未戒烟的成年吸烟者中的有效性：2002-2003 年和 2010-2011 年。对于有完整数据的药物辅助使用者和非使用者（n=2129），我们使用倾向评分模型和 12 种潜在混杂因素（年龄、性别、种族-民族、教育程度、吸烟强度、尼古丁依赖程度、既往戒烟史、戒烟自我效能、无烟家庭、调查年份和戒烟辅助使用）进行匹配。使用匹配数据集，我们拟合逻辑回归模型，以评估任何一种单一药物辅助的使用是否会增加在随访时 30 天或更长时间戒烟的患者比例。
倾向评分匹配显著改善了药物辅助使用组之间潜在混杂因素的平衡。在使用匹配样本进行均衡比较时，没有证据表明使用伐伦克林（调整后的风险差异[aRD] = 0.01，95%置信区间[CI] = -0.07 至 0.11）、安非他酮（aRD = 0.02，95% CI = -0.04 至 0.09）或尼古丁替代（aRD = 0.01，95% CI = -0.03 至 0.06）会增加一年随访时 30 天或更长时间的戒烟概率。
在人群样本中，药物辅助在增加长期戒烟率方面的效果不佳并非由混杂分析引起的人为偏差。一种可能的解释是，在疗效试验中提供的咨询和支持干预措施在普通人群中很少实施。
