Assessing the impact of attrition in randomized controlled trials
Assessing the impact of attrition in randomized controlled trials
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DOI：
10.1016/j.jclinepi.2010.01.010
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发表时间：
2010-11-01
影响因子：
7.2
通讯作者：
Torgerson, David J.
中科院分区：
文献类型：
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作者：
Hewitt, Catherine E.;Kumaravel, Bharathy;Torgerson, David J.
目标：一项随机对照试验调查发现，近四分之一的试验在主要结局方面缺少超过 10% 的反应。数据丢失的方式有很多种：受试者无法提供数据，或者他们退出，或者失去后续追踪。这种损耗意味着，在具有结果数据的子样本中，可能无法维持随机分组的基线特征的平衡。对于个别试验，如果损耗是系统性的并且与结果相关，那么这将导致对总体效果的估计存在偏差。由此可见，如果将这些试验合并到荟萃分析中，就会导致对总体效果的估计存在偏差并产生误导。本研究的目的是调查单项试验和多项试验中自然减员对基线失衡的影响。 研究设计和设置：在本文中，我们使用了来自 10 项评估肌肉骨骼疾病干预措施的试验的方便样本的个体患者数据。使用这些试验中的个体患者数据进行了使用试验组之间基线平均差异的荟萃分析。首先使用所有随机参与者进行分析，其次仅包括具有生活质量评分结果数据的参与者。进行元回归以评估基线失衡水平是否与自然流失水平相关。结果：生活质量评分的总体自然流失率在随机患者总数的 4% 至 28% 之间。所有试验均显示治疗组之间存在一定程度的磨损差异，范围为 1% 至 14%。对照组的人员流失率为 3% 至 25%，干预组的人员流失率为 0% 至 31%。对于个别试验，没有迹象表明磨损会改变结果，有利于治疗或对照。森林图强调，随着引入更多异质性，磨损对主要结果评分的基线不平衡产生了一些影响（初始数据集的 I 平方值为 0.4%，分析数据集的 I 平方值为 16.9%）。然而，标准化平均差异仅略有增加（从 0.01 增加到 0.03，95% 置信区间 [CI]：-0.05、0.10）。荟萃回归显示，很少或没有证据表明磨损水平与基线失衡之间存在显着的剂量反应关系（系数 0.73，95% CI：-0.81，2.28）。 结论：虽然理论上，磨损会在随机试验中引入选择偏倚，但我们在我们的方便试验样本中没有找到足够的证据来支持这一说法。然而，纳入的试验数量相对较少，这可能导致结果上的微小但重要的差异被遗漏。此外，纳入的 10 项试验中只有 2 项的磨损率超过 15%，表明潜在偏倚水平较低。荟萃分析和系统评价应始终考虑磨损对基线不平衡的影响，并在可能的情况下考虑分析数据集中的任何基线不平衡及其对报告结果的影响。 (C) 2010 Elsevier Inc. 保留所有权利。
Objectives: A survey of randomized controlled trials found that almost a quarter of trials had more than 10% of responses missing for the primary outcome. There are a number of ways in which data could be missing: the subject is unable to provide it, or they withdraw, or become lost to follow-up. Such attrition means that balance in baseline characteristics for those randomized may not be maintained in the subsample who has outcome data. For individual trials, if the attrition is systematic and linked to outcome, then this will result in biased estimates of the overall effect. It then follows that if such trials are combined in a meta-analysis, it will result in a biased estimate of the overall effect and be misleading. The aim of this study was to investigate the impact of attrition on baseline imbalance within individual trials and across multiple trials.Study Design and Setting: In this article, we used individual patient data from a convenience sample of 10 trials evaluating interventions for the treatment of musculoskeletal disorders. Meta-analyses using the mean difference at baseline between the trial arms were carried out using individual patient data from these trials. The analyses were first carried out using all randomized participants and secondly only including participants with outcome data on the quality-of-life score. Meta-regression was carried out to evaluate whether the level of baseline imbalance was associated with the level of attrition.Results: The overall attrition rates for the quality-of-life score ranged between 4% and 28% of the total randomized patients. All trials showed some level of differential attrition between the treatment arms, ranging from 1% to 14%. Attrition within the control group ranged from 3% to 25% and within the intervention group, it ranged from 0% to 31%. For individual trials, there was no indication that attrition altered the results in favor of either the treatment or the control. Forest plots highlighted that the attrition had some impact on the baseline imbalance for the primary outcome score as more heterogeneity was introduced (I-squared value of 0.4% for the initial data set vs. I-squared value of 16.9% for the analyzed data set). However, the standardized mean difference increased only slightly (from 0.01 to 0.03 with 95% confidence interval [CI]: -0.05, 0.10). Meta-regression showed little or no evidence of a significant dose response relationship between the level of attrition and the baseline imbalance (coefficient 0.73, 95% CI: -0.81, 2.28).Conclusion: Although, in theory, attrition can introduce selection bias in randomized trials, we did not find sufficient evidence to support this claim in our convenience sample of trials. However, the number of trials included was relatively small, which may have led to small but important differences in outcomes being missed. In addition, only 2 of 10 trials included had attrition levels greater than 15% suggesting a low level of potential bias. Meta-analyses and systematic reviews should always consider the impact of attrition on baseline imbalances and where possible any baseline imbalances in the analyzed data set and their impact on the outcomes reported. (C) 2010 Elsevier Inc. All rights reserved.