School of Social and Community Medicine, University of Bristol, Bristol, UK.
Ann Intern Med. 2012 Sep 18;157(6):429-38. doi: 10.7326/0003-4819-157-6-201209180-00537.
Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.
已有证据表明，试验设计的某些方面会导致干预效果估计存在偏差，但不同研究的结果并不一致。本研究结合了 7 项荟萃流行病学研究的数据，并去除了重叠部分，最终得出了一个包含 234 项独特荟萃分析的数据集，其中包含 1973 项试验。结局指标分为“死亡率”、“其他客观指标”或“主观指标”，并使用贝叶斯层次模型来估计试验特征与平均偏差和试验间异质性之间的关联。在随机序列生成（比值比，0.89 [95%可信区间{CrI}，0.82 至 0.96]）或分配隐藏（比值比，0.93 [CrI，0.87 至 0.99]）不充分或不清楚（相对于充分）的试验中，干预效果估计似乎被夸大了。缺乏或不清楚的双盲法（相对于双盲法）与干预效果平均夸大 13%（比值比，0.87 [CrI，0.79 至 0.96]）相关，且此类研究的试验间异质性增加（异质性的标准差增加，0.14 [CrI，0.02 至 0.30]）。对于每种特征，平均偏差和试验间异质性的增加主要是由主观结局的试验驱动的，而在客观结局和死亡率结局的试验中几乎没有发现偏差的证据。本研究受到试验报告不完整的限制，并且研究结果可能受到其他研究设计特征的混杂。与研究设计特征相关的偏倚可能导致报告主观评估结局的试验中干预效果估计的夸大和试验间异质性的增加。
