对偏倚风险工具达成共识的真实世界评估:使用非随机干预研究中的偏倚风险(ROBINS-I)进行案例研究

Samer Saadi, Bashar Hasan, Adel Kanaan, Mohamed Abusalih, Zin Tarakji, Mustafa Sadek, Ayla Shamsi Basha, Mohammed Firwana, Zhen Wang, M. Hassan Murad
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引用次数: 0

摘要

背景偏倚风险(RoB)工具在系统综述中至关重要,并影响后续决策。RoB工具应具有足够的研究者间可靠性和共识性。我们提出了一种利用与系统综述重叠的重复研究对 RoB 工具进行事后评估的方法。 方法 采用反向引用法,我们确定了使用非随机干预研究中的偏倚风险(ROBINS-I)工具的系统综述,并检索了所有纳入的主要研究。我们选择了由一篇以上系统综述评估的研究,并计算了比较不同系统综述评估的观察一致度和非加权卡帕值。 结果 我们确定了 903 篇使用该工具的系统综述,共引用了 51676 篇参考文献,最终从中分析出 171 篇由不同系统综述作者使用 ROBINS-I 评估的重复研究。观察到的 ROBINS-I 领域的一致性从 54.9%(数据缺失领域)到 70.3%(偏离预期干预领域)不等,对研究的整体 RoB 评估的一致性为 63.0%。Kappa 系数从 0.131(结果测量域)到 0.396(混杂域和偏离预期干预域)不等,研究的整体 RoB 评估为 0.404。 结论 通过关注与系统审查重叠的重复研究,对 RoB 工具进行事后评估是可行的。ROBINS-I 评估表明,在评估同一研究和结果的不同系统综述中,共识之间的一致性存在很大差异,这表明需要开展更深入的前期工作,以校准系统综述者如何识别特定背景信息并就如何判断这些信息达成一致。
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Real-world evaluation of interconsensus agreement of risk of bias tools: A case study using risk of bias in nonrandomized studies-of interventions (ROBINS-I)

Background

Risk of bias (RoB) tools are critical in systematic reviews and affect subsequent decision-making. RoB tools should have adequate interrater reliability and interconsensus agreement. We present an approach of post hoc evaluation of RoB tools using duplicated studies that overlap systematic reviews.

Methods

Using a back-citation approach, we identified systematic reviews that used the Risk Of Bias In Nonrandomized Studies-of Interventions (ROBINS-I) tool and retrieved all the included primary studies. We selected studies that were appraised by more than one systematic review and calculated observed agreement and unweighted kappa comparing the different systematic reviews' assessments.

Results

We identified 903 systematic reviews that used the tool with 51,676 cited references, from which we eventually analyzed 171 duplicated studies assessed using ROBINS-I by different systematic reviewers. The observed agreement on ROBINS-I domains ranged from 54.9% (missing data domain) to 70.3% (deviations from intended interventions domain), and was 63.0% for overall RoB assessment of the study. Kappa coefficient ranged from 0.131 (measurement of outcome domain) to 0.396 (domains of confounding and deviations from intended interventions), and was 0.404 for overall RoB assessment of the study.

Conclusion

A post hoc evaluation of RoB tools is feasible by focusing on duplicated studies that overlap systematic review. ROBINS-I assessments demonstrated considerable variation in interconsensus agreement among various systematic reviewes that assessed the same study and outcome, suggesting the need for more intensive upfront work to calibrate systematic reviewers on how to identify context-specific information and agree on how to judge it.

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