Saltaji H, Armijo-Olivo S, Cummings G G, Amin M, da Costa B R, Flores-Mir C
1 Orthodontic Graduate Program, School of Dentistry, University of Alberta, Edmonton, Canada.
2 Faculty of Rehabilitation Medicine/Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
J Dent Res. 2018 Jan;97(1):5-13. doi: 10.1177/0022034517725049. Epub 2017 Aug 16.
Emerging evidence suggests that design flaws of randomized controlled trials can result in over- or underestimation of the treatment effect size (ES). The objective of this study was to examine associations between treatment ES estimates and adequacy of sequence generation, allocation concealment, and baseline comparability among a sample of oral health randomized controlled trials. For our analysis, we selected all meta-analyses that included a minimum of 5 oral health randomized controlled trials and used continuous outcomes. We extracted data, in duplicate, related to items of selection bias (sequence generation, allocation concealment, and baseline comparability) in the Cochrane Risk of Bias tool. Using a 2-level meta-meta-analytic approach with a random effects model to allow for intra- and inter-meta-analysis heterogeneity, we quantified the impact of selection bias on the magnitude of ES estimates. We identified 64 meta-analyses, including 540 randomized controlled trials analyzing 137,957 patients. Sequence generation was judged to be adequate (at low risk of bias) in 32% ( n = 173) of trials, and baseline comparability was judged to be adequate in 77.8% of trials. Allocation concealment was unclear in the majority of trials ( n = 458, 84.8%). We identified significantly larger treatment ES estimates in trials that had inadequate/unknown sequence generation (difference in ES = 0.13; 95% CI: 0.01 to 0.25) and inadequate/unknown allocation concealment (difference in ES = 0.15; 95% CI: 0.02 to 0.27). In contrast, baseline imbalance (difference in ES = 0.01, 95% CI: -0.09 to 0.12) was not associated with inflated or underestimated ES. In conclusion, treatment ES estimates were 0.13 and 0.15 larger in trials with inadequate/unknown sequence generation and inadequate/unknown allocation concealment, respectively. Therefore, authors of systematic reviews using oral health randomized controlled trials should perform sensitivity analyses based on the adequacy of sequence generation and allocation concealment.
新出现的证据表明，随机对照试验的设计缺陷可能导致对治疗效应大小（ES）的高估或低估。本研究的目的是在一组口腔健康随机对照试验样本中，检验治疗ES估计值与序列产生的充分性、分配隐藏和基线可比性之间的关联。在我们的分析中，我们选择了所有至少纳入5项口腔健康随机对照试验并使用连续结局的荟萃分析。我们重复提取了与Cochrane偏倚风险工具中选择偏倚项目（序列产生、分配隐藏和基线可比性）相关的数据。采用二级元荟萃分析方法和随机效应模型，以考虑元分析内和元分析间的异质性，我们量化了选择偏倚对ES估计值大小的影响。我们识别出64项荟萃分析，包括540项随机对照试验，分析了137,957名患者。32%（n = 173）的试验中序列产生被判定为充分（偏倚风险低），77.8%的试验中基线可比性被判定为充分。大多数试验（n = 458，84.8%）的分配隐藏情况不明。我们发现在序列产生不充分/未知（ES差异 = 0.13；95% CI：0.01至0.25）和分配隐藏不充分/未知（ES差异 = 0.15；95% CI：0.02至0.27）的试验中，治疗ES估计值显著更大。相比之下，基线不平衡（ES差异 = 0.01，95% CI：-0.09至0.12）与ES的高估或低估无关。总之，在序列产生不充分/未知和分配隐藏不充分/未知的试验中，治疗ES估计值分别大0.13和0.15。因此，使用口腔健康随机对照试验的系统评价作者应根据序列产生和分配隐藏的充分性进行敏感性分析。
