Institute for Evidence in Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Straße 86, 79110, Freiburg, Germany.
Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
BMC Med. 2022 May 11;20(1):174. doi: 10.1186/s12916-022-02369-2.
BACKGROUND: Randomized controlled trials (RCTs) and cohort studies are the most common study design types used to assess the treatment effects of medical interventions. To evaluate the agreement of effect estimates between bodies of evidence (BoE) from randomized controlled trials (RCTs) and cohort studies and to identify factors associated with disagreement. METHODS: Systematic reviews were published in the 13 medical journals with the highest impact factor identified through a MEDLINE search. BoE-pairs from RCTs and cohort studies with the same medical research question were included. We rated the similarity of PI/ECO (Population, Intervention/Exposure, Comparison, Outcome) between BoE from RCTs and cohort studies. The agreement of effect estimates across BoE was analyzed by pooling ratio of ratios (RoR) for binary outcomes and difference of mean differences for continuous outcomes. We performed subgroup analyses to explore factors associated with disagreements. RESULTS: One hundred twenty-nine BoE pairs from 64 systematic reviews were included. PI/ECO-similarity degree was moderate: two BoE pairs were rated as "more or less identical"; 90 were rated as "similar but not identical" and 37 as only "broadly similar". For binary outcomes, the pooled RoR was 1.04 (95% CI 0.97-1.11) with considerable statistical heterogeneity. For continuous outcomes, differences were small. In subgroup analyses, degree of PI/ECO-similarity, type of intervention, and type of outcome, the pooled RoR indicated that on average, differences between both BoE were small. Subgroup analysis by degree of PI/ECO-similarity revealed high statistical heterogeneity and wide prediction intervals across PI/ECO-dissimilar BoE pairs. CONCLUSIONS: On average, the pooled effect estimates between RCTs and cohort studies did not differ. Statistical heterogeneity and wide prediction intervals were mainly driven by PI/ECO-dissimilarities (i.e., clinical heterogeneity) and cohort studies. The potential influence of risk of bias and certainty of the evidence on differences of effect estimates between RCTs and cohort studies needs to be explored in upcoming meta-epidemiological studies.
背景：随机对照试验（RCT）和队列研究是评估医学干预治疗效果最常用的研究设计类型。评估来自随机对照试验（RCT）和队列研究的证据体（BoE）之间效应估计的一致性，并确定与不一致相关的因素。
方法：通过 MEDLINE 搜索，确定了影响因子最高的 13 种医学期刊，并发表了系统评价。纳入了具有相同医学研究问题的 RCT 和队列研究的 BoE 配对。我们对 RCT 和队列研究 BoE 的 PI/ECO（人群、干预/暴露、比较、结局）相似性进行评分。通过汇总比值比（RoR）分析二分类结局和均数差值（MD）分析连续性结局的效应估计值来分析 BoE 之间的一致性。我们进行了亚组分析，以探讨与不一致相关的因素。
结果：纳入了 64 项系统评价的 129 对 BoE。PI/ECO 的相似性程度为中度：2 对 BoE 被评为“或多或少相同”；90 对被评为“相似但不相同”，37 对被评为“仅大致相似”。对于二分类结局，汇总的 RoR 为 1.04（95%CI 0.97-1.11），具有相当大的统计学异质性。对于连续性结局，差异较小。在亚组分析中，PI/ECO 相似性程度、干预类型和结局类型，汇总的 RoR 表明，平均而言，这两个 BoE 之间的差异较小。PI/ECO 相似性程度的亚组分析显示，PI/ECO 不相似（即临床异质性）和队列研究的 BoE 配对存在高统计学异质性和宽预测区间。
结论：平均而言，RCT 和队列研究之间的汇总效应估计值没有差异。统计异质性和宽预测区间主要由 PI/ECO 不相似（即临床异质性）和队列研究驱动。在即将进行的荟萃流行病学研究中，需要探讨偏倚风险和证据确定性对 RCT 和队列研究之间效应估计值差异的影响。
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