使用广义估计方程的物质使用临床试验的纵向缺失数据策略：以丁丙诺啡试验为例
Longitudinal missing data strategies for substance use clinical trials using generalized estimating equations: an example with a buprenorphine trial.
作者信息
McPherson Sterling, Barbosa-Leiker Celestina, McDonell Michael, Howell Donelle, Roll John
机构信息
College of Nursing, Washington State University, Spokane, Washington, USA; Department of Psychology, Washington State University, Pullman, Washington, USA; Program of Excellence in the Addictions, Washington State University, Spokane, Washington, USA; Program for Rural Mental Health and Substance Abuse Treatment, Washington State University, Spokane, Washington, USA; Translational Addictions Research Center, Washington State University, Spokane, Washington, USA.
出版信息
Hum Psychopharmacol. 2013 Sep;28(5):506-15. doi: 10.1002/hup.2339.
OBJECTIVE
A review of substance use clinical trials indicates that sub-optimal methods are the most commonly used procedures to deal with longitudinal missing information.
METHODS
Listwise deletion (i.e., using complete cases only), positive urine analysis (UA) imputation, and multiple imputation (MI) were used to evaluate the effect of baseline substance use and buprenorphine/naloxone tapering schedule (7 or 28 days) on the probability of a positive UA (UA+) across the 4-week treatment period.
RESULTS
The listwise deletion generalized estimating equations (GEE) model demonstrated that those in the 28-day taper group were less likely to submit a UA+ for opioids during the treatment period (odds ratios (OR) = 0.57, 95% confidence interval (CI): 0.39-0.83), as did the positive UA imputation model (OR = 0.43, CI: 0.34-0.55). The MI model also demonstrated a similar effect of taper group (OR = 0.57, CI: 0.42-0.77), but the effect size was more similar to that of the listwise deletion model.
CONCLUSIONS
Future researchers may find utilization of the MI procedure in conjunction with the common method of GEE analysis as a helpful analytic approach when the missing at random assumption is justifiable.
目的
对物质使用临床试验的回顾表明，次优方法是处理纵向缺失信息最常用的程序。
方法
采用删除法（即仅使用完整病例）、阳性尿液分析（UA）插补法和多重插补法（MI），以评估基线物质使用情况和丁丙诺啡/纳洛酮逐渐减量方案（7天或28天）对4周治疗期内尿液分析呈阳性（UA+）概率的影响。
结果
删除法广义估计方程（GEE）模型表明，28天逐渐减量组的患者在治疗期间提交阿片类药物UA+的可能性较小（优势比（OR）=0.57，95%置信区间（CI）：0.39 - 0.83），阳性UA插补模型也是如此（OR = 0.43，CI：0.34 - 0.55）。MI模型也显示了逐渐减量组的类似效果（OR = 0.57，CI：0.42 - 0.77），但效应大小与删除法模型更相似。
结论
当随机缺失假设合理时，未来的研究人员可能会发现将MI程序与GEE分析的常用方法结合使用是一种有用的分析方法。
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