Schneeweiss Sebastian, Setoguchi Soko, Brookhart M Alan, Kaci Liljana, Wang Philip S
Division of Pharmacoepidemiology and Pharmacoeconomics, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA.
CNS Drugs. 2009;23(2):171-80. doi: 10.2165/00023210-200923020-00006.
Nonrandomised studies on the causal effects of psychotropic medications may be biased by patient characteristics that are not fully adjusted.
Studies using linked claims databases found that typical antipsychotic medications were associated with increased short-term mortality compared with atypical antipsychotics. It has been suggested that such results may be due to residual confounding by factors that cannot be measured in claims databases. Using detailed survey data we identified the direction and magnitude of such residual confounding.
Cross-sectional survey data.
17 776 participants aged > or =65 years from the Medicare Current Beneficiary Survey (MCBS).
To determine the association between typical antipsychotic use and potential confounding factors we assessed five factors not measured in Medicare claims data but in the MCBS, i.e. body mass index, smoking, activities of daily living (ADL) score, cognitive impairment and Rosow-Breslau physical impairment scale. We estimated adjusted associations between these factors and antipsychotic use. Combined with literature estimates of the independent effect of confounders on death, we computed the extent of residual confounding caused by a failure to adjust for these factors.
Comparing typical antipsychotic users with atypical antipsychotic users, we found that not adjusting for impairments in the ADL score led to an underestimation of the association with death (-13%), as did a failure to adjust for cognitive impairment (-7%). The combination of all five unmeasured confounders resulted in a net confounding of -5% (range -19% to +2%). After correction, the reported association between typical antipsychotic use and death compared with atypical antipsychotic use was slightly increased from a relative risk (RR) of 1.37 to 1.44 (95% CI 1.33, 1.56). Comparing any antipsychotic use with non-users would result in overestimations of >50% if cognitive impairment remained unadjusted.
Claims data studies tend to underestimate the association of typical antipsychotics with death compared with atypical antipsychotics because of residual confounding by measures of frailty. Studies comparing antipsychotic use with non-users may substantially overestimate harmful effects of antipsychotics.
关于精神药物因果效应的非随机研究可能因未充分调整的患者特征而存在偏差。
利用关联索赔数据库进行的研究发现,与非典型抗精神病药物相比,典型抗精神病药物与短期死亡率增加相关。有人认为,此类结果可能是由于索赔数据库中无法测量的因素导致的残余混杂所致。我们使用详细的调查数据确定了此类残余混杂的方向和程度。
横断面调查数据。
来自医疗保险当前受益人调查(MCBS)的17776名年龄≥65岁的参与者。
为了确定典型抗精神病药物使用与潜在混杂因素之间的关联,我们评估了医疗保险索赔数据中未测量但在MCBS中测量的五个因素,即体重指数、吸烟、日常生活活动(ADL)评分、认知障碍和罗索-布雷斯劳身体损伤量表。我们估计了这些因素与抗精神病药物使用之间的调整后关联。结合混杂因素对死亡独立影响的文献估计值,我们计算了因未对这些因素进行调整而导致的残余混杂程度。
将典型抗精神病药物使用者与非典型抗精神病药物使用者进行比较,我们发现未对ADL评分中的损伤进行调整会导致与死亡关联的低估(-13%),未对认知障碍进行调整时也是如此(-7%)。所有五个未测量的混杂因素综合起来导致净混杂为-5%(范围为-19%至+2%)。校正后,报告的典型抗精神病药物使用与死亡之间的关联(与非典型抗精神病药物使用相比)从相对风险(RR)1.37略微增加至1.44(95%CI 1.33,1.56)。如果未对认知障碍进行调整,将任何抗精神病药物使用者与非使用者进行比较会导致高估>50%。
由于虚弱测量导致的残余混杂,索赔数据研究往往低估了典型抗精神病药物与非典型抗精神病药物相比与死亡的关联。将抗精神病药物使用者与非使用者进行比较的研究可能会大幅高估抗精神病药物的有害影响。