Schneeweiss Sebastian, Patrick Amanda R, Stürmer Til, Brookhart M Alan, Avorn Jerry, Maclure Malcolm, Rothman Kenneth J, Glynn Robert J
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Med Care. 2007 Oct;45(10 Supl 2):S131-42. doi: 10.1097/MLR.0b013e318070c08e.
The goal of restricting study populations is to make patients more homogeneous regarding potential confounding factors and treatment effects and thereby achieve less biased effect estimates.
This article describes increasing levels of restrictions for use in pharmacoepidemiology and examines to what extent they change rate ratio estimates and reduce bias in a study of statin treatment and 1-year mortality.
: The study cohort was drawn from a population of seniors age 65 years and older enrolled in both Medicare and the Pennsylvania Pharmaceutical Assistance Contract for the Elderly (PACE) between 1995 and 2002. We identified all users of statins during the study period and assessed the time until death within 1 year. The following progressive restrictions were applied: (1) study incident drug users only, (2) choose a comparison group most similar to the intervention group, (3) exclude patients with contraindications, (4) exclude patients with low adherence, and (5) restrict to specific high-risk/low-risk subgroups represented in randomized trails (RCTs).
The basic cohort comprised 122,406 statin users, who were on average 78 years old and predominantly white (93%) and showed an unadjusted rate ratio of 0.32 for statin users. When all 5 restrictions were applied (N = 11,673), the unadjusted rate ratio had increased to 0.72. Multivariable Cox regression adjusted rate ratios increased from 0.62 [95% confidence interval (CI), 0.58-0.66] to 0.79 (95% CI, 0.60-1.03). However, after the first 3 restrictions the effect size changed little. The final estimate is similar to that obtained as a pooled estimate of 3 pravastatin RCTs in patients age 65 years and older. We argue that restrictions 1 through 4 compromised generalizability little.
In our example of a large database study, restricting to incident drug users, similar comparison groups, patients without contraindication, and to adherent patients was a practical strategy, which limited the effect of confounding, as these approaches yield results closer to those seen in RCTs.
限制研究人群的目的是使患者在潜在混杂因素和治疗效果方面更加同质化,从而获得偏差较小的效应估计值。
本文描述了在药物流行病学中使用的限制水平的提高,并研究了它们在他汀类药物治疗与1年死亡率的研究中在多大程度上改变率比估计值并减少偏差。
研究队列来自1995年至2002年期间同时参加医疗保险和宾夕法尼亚州老年人药物援助合同(PACE)的65岁及以上老年人。我们确定了研究期间所有他汀类药物使用者,并评估了1年内直至死亡的时间。应用了以下逐步限制:(1)仅研究新使用药物的患者,(2)选择与干预组最相似的对照组,(3)排除有禁忌症的患者,(4)排除依从性低的患者,以及(5)限制在随机试验(RCT)中代表的特定高风险/低风险亚组。
基本队列包括122,406名他汀类药物使用者,他们的平均年龄为78岁,主要为白人(93%),他汀类药物使用者的未调整率比为0.32。当应用所有5项限制时(N = 11,673),未调整率比增加到0.72。多变量Cox回归调整后的率比从0.62 [95%置信区间(CI),0.58 - 0.66]增加到0.79(95% CI,0.60 - 1.03)。然而,在前3项限制之后,效应大小变化不大。最终估计值与在65岁及以上患者中对3项普伐他汀RCT进行汇总估计所获得的值相似。我们认为限制1至4对普遍性的影响很小。
在我们的大型数据库研究示例中,限制为新使用药物的患者、相似的对照组、无禁忌症的患者以及依从性好的患者是一种实用策略,它限制了混杂因素的影响,因为这些方法产生的结果更接近RCT中所见的结果。