Raboud J M, Montaner J S, Thorne A, Singer J, Schechter M T
Department of Health Care and Epidemiology, University of British Columbia, Vancouver, Canada.
J Acquir Immune Defic Syndr Hum Retrovirol. 1996 May 1;12(1):46-55. doi: 10.1097/00042560-199605010-00007.
To evaluate the impact of missing data due to nonrandom dropout on estimates of the effect of treatment on the CD4 count in a clinical trial of antiretroviral therapy for HIV infected individuals.
The effect of treatment on CD4 counts in a recent study of continued ZDV versus ddI in HIV-infected individuals was estimated from the observed data and after imputing missing CD4 counts for patients who dropped out of the study. Imputation methods studied were (a) carrying forward the last observed CD4 count, (b) predicting missing CD4 counts from regression models, and (c) assuming that CD4 counts of patients who dropped out declined at a rate of 100 cells per year.
Of the 245 patients enrolled in the study, 52% completed the planned 48 weeks of follow-up. Patients with lower CD4 counts were more likely to drop out of the study (RR = 1.77; p = 0.0001). Patients receiving ZDV had a greater tendency to drop out than patients receiving ddI (p = 0.07). Mean CD4 counts calculated after imputing missing data were lower than those obtained from the observed data at all follow-up times for both treatment groups. Imputing CD4 counts with regression models yielded higher estimates of the effect of treatment than were obtained using the observed data.
Missing outcome data due to dropouts can result in an underestimation of the treatment effect and overly optimistic statements about the outcome of participants on both treatment arms due to the selective dropout of participants with lower or decreasing CD4 counts. When there are significant dropout rates in randomized trials, imputation is a useful technique to assess the range of plausible values of the treatment effect.
在一项针对HIV感染者的抗逆转录病毒治疗临床试验中，评估因非随机失访导致的数据缺失对治疗效果（以CD4细胞计数衡量）估计值的影响。
在一项近期的关于HIV感染者持续使用齐多夫定（ZDV）与去羟肌苷（ddI）对比研究中，根据观察到的数据以及对失访患者缺失的CD4细胞计数进行插补后，估计治疗对CD4细胞计数的影响。所研究的插补方法包括：（a）沿用最后一次观察到的CD4细胞计数；（b）通过回归模型预测缺失的CD4细胞计数；（c）假设失访患者的CD4细胞计数以每年100个细胞的速度下降。
在该研究纳入的245例患者中，52%完成了计划的48周随访。CD4细胞计数较低的患者更有可能退出研究（相对危险度=1.77；p=0.0001）。接受ZDV治疗的患者比接受ddI治疗的患者有更高的退出倾向（p=0.07）。在两个治疗组的所有随访时间点，对缺失数据进行插补后计算出的平均CD4细胞计数均低于从观察数据中获得的计数。用回归模型插补CD4细胞计数得出的治疗效果估计值高于使用观察数据得出的估计值。
由于CD4细胞计数较低或呈下降趋势的参与者选择性失访，因失访导致的结局数据缺失可能会低估治疗效果，并对两个治疗组参与者的结局做出过于乐观的表述。当随机试验中有显著的失访率时，插补是一种评估治疗效果合理值范围的有用技术。
