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工具变量 II:工具变量应用——在 25 种变化中,医生的处方偏好通常很强,从而减少了协变量的不平衡。

Instrumental variables II: instrumental variable application-in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance.

机构信息

Brigham & Women's Hospital, Boston, MA 02120, USA.

出版信息

J Clin Epidemiol. 2009 Dec;62(12):1233-41. doi: 10.1016/j.jclinepi.2008.12.006. Epub 2009 Apr 5.

Abstract

OBJECTIVE

An instrumental variable (IV) is an unconfounded proxy for a study exposure that can be used to estimate a causal effect in the presence of unmeasured confounding. To provide reliably consistent estimates of effect, IVs should be both valid and reasonably strong. Physician prescribing preference (PPP) is an IV that uses variation in doctors' prescribing to predict drug treatment. As reduction in covariate imbalance may suggest increased IV validity, we sought to examine the covariate balance and instrument strength in 25 formulations of the PPP IV in two cohort studies.

STUDY DESIGN AND SETTING

We applied the PPP IV to assess antipsychotic medication (APM) use and subsequent death among two cohorts of elderly patients. We varied the measurement of PPP, plus performed cohort restriction and stratification. We modeled risk differences with two-stage least square regression. First-stage partial r(2) values characterized the strength of the instrument. The Mahalanobis distance summarized balance across multiple covariates.

RESULTS

Partial r(2) ranged from 0.028 to 0.099. PPP generally alleviated imbalances in nonpsychiatry-related patient characteristics, and the overall imbalance was reduced by an average of 36% (+/-40%) over the two cohorts.

CONCLUSION

In our study setting, most of the 25 formulations of the PPP IV were strong IVs and resulted in a strong reduction of imbalance in many variations. The association between strength and imbalance was mixed.

摘要

目的

工具变量(instrumental variable,IV)是研究暴露的一种无偏估计,可用于在存在未测量混杂的情况下估计因果效应。为了提供可靠一致的效应估计,IV 应该既有效又具有相当的强度。医生处方偏好(physician prescribing preference,PPP)是一种使用医生处方的变异性来预测药物治疗的 IV。由于减少协变量不平衡可能表明 IV 的有效性增加,我们试图在两项队列研究中的 25 种 PPP IV 中检查协变量平衡和工具强度。

研究设计和设置

我们应用 PPP IV 来评估两个老年患者队列中抗精神病药物(antipsychotic medication,APM)的使用和随后的死亡。我们改变了 PPP 的测量方式,同时进行了队列限制和分层。我们使用两阶段最小二乘法回归来对风险差异进行建模。第一阶段部分 r(2)值描述了工具的强度。马氏距离总结了多个协变量的平衡情况。

结果

部分 r(2) 值范围为 0.028 至 0.099。PPP 通常可以缓解与非精神病相关的患者特征的不平衡,并且在两个队列中,总体不平衡平均减少了 36%(+/-40%)。

结论

在我们的研究环境中,25 种 PPP IV 的大部分都是强有力的 IV,并且在许多变化中都能强有力地减少不平衡。强度与不平衡之间的关联是混杂的。

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