Department of Neurosurgery and Chinese Evidence-Based Medicine Center and Cochrane China, Center and MAGIC China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, Sichuan, China.
President & Dean's Office, West China Hospital, Sichuan University, Chengdu, China.
BMC Med Res Methodol. 2024 Sep 27;24(1):219. doi: 10.1186/s12874-024-02347-7.
There is a growing trend to include non-randomised studies of interventions (NRSIs) in rare events meta-analyses of randomised controlled trials (RCTs) to complement the evidence from the latter. An important consideration when combining RCTs and NRSIs is how to address potential bias and down-weighting of NRSIs in the pooled estimates. The aim of this study is to explore the use of a power prior approach in a Bayesian framework for integrating RCTs and NRSIs to assess the effect of rare events.
We proposed a method of specifying the down-weighting factor based on judgments of the relative magnitude (no information, and low, moderate, serious and critical risk of bias) of the overall risk of bias for each NRSI using the ROBINS-I tool. The methods were illustrated using two meta-analyses, with particular interest in the risk of diabetic ketoacidosis (DKA) in patients using sodium/glucose cotransporter-2 (SGLT-2) inhibitors compared with active comparators, and the association between low-dose methotrexate exposure and melanoma.
No significant results were observed for these two analyses when the data from RCTs only were pooled (risk of DKA: OR = 0.82, 95% confidence interval (CI): 0.25-2.69; risk of melanoma: OR = 1.94, 95%CI: 0.72-5.27). When RCTs and NRSIs were directly combined without distinction in the same meta-analysis, both meta-analyses showed significant results (risk of DKA: OR = 1.50, 95%CI: 1.11-2.03; risk of melanoma: OR = 1.16, 95%CI: 1.08-1.24). Using Bayesian analysis to account for NRSI bias, there was a 90% probability of an increased risk of DKA in users receiving SGLT-2 inhibitors and an 91% probability of an increased risk of melanoma in patients using low-dose methotrexate.
Our study showed that including NRSIs in a meta-analysis of RCTs for rare events could increase the certainty and comprehensiveness of the evidence. The estimates obtained from NRSIs are generally considered to be biased, and the possible influence of NRSIs on the certainty of the combined evidence needs to be carefully investigated.
将干预措施的非随机研究（NRSI）纳入随机对照试验（RCT）的罕见事件荟萃分析中，以补充后者的证据，这种趋势日益明显。在合并 RCT 和 NRSI 时，一个重要的考虑因素是如何解决潜在的偏倚，并对汇总估计值中 NRSI 的权重进行下调。本研究旨在探讨在贝叶斯框架中使用功效先验方法来整合 RCT 和 NRSI，以评估罕见事件的效果。
我们提出了一种方法，根据 ROBINS-I 工具对每个 NRSI 的总体偏倚风险（无信息、低、中、高和严重偏倚风险）进行判断，来指定权重下调因子。该方法通过两个荟萃分析进行说明，特别关注使用钠/葡萄糖共转运蛋白-2（SGLT-2）抑制剂的患者发生糖尿病酮症酸中毒（DKA）的风险与活性对照相比，以及低剂量甲氨蝶呤暴露与黑色素瘤之间的关联。
仅汇总 RCT 数据时，这两项分析均未观察到显著结果（DKA 风险：OR=0.82，95%置信区间（CI）：0.25-2.69；黑色素瘤风险：OR=1.94，95%CI：0.72-5.27）。当直接在同一荟萃分析中无区别地合并 RCT 和 NRSI 时，这两项荟萃分析均显示出显著结果（DKA 风险：OR=1.50，95%CI：1.11-2.03；黑色素瘤风险：OR=1.16，95%CI：1.08-1.24）。使用贝叶斯分析来解释 NRSI 偏倚，使用 SGLT-2 抑制剂的患者发生 DKA 的风险增加的概率为 90%，使用低剂量甲氨蝶呤的患者发生黑色素瘤的风险增加的概率为 91%。
本研究表明，将 NRSI 纳入 RCT 罕见事件荟萃分析中，可以提高证据的确定性和全面性。从 NRSI 中获得的估计值通常被认为存在偏倚，需要仔细研究 NRSI 对综合证据确定性的可能影响。
