Author:
Jeyaraman Maya M.,Al-Yousif Nameer,Robson Reid C.,Copstein Leslie,Balijepalli Chakrapani,Hofer Kimberly,Fazeli Mir S.,Ansari Mohammed T.,Tricco Andrea C.,Rabbani Rasheda,Abou-Setta Ahmed M.
Abstract
Abstract
Background
A new tool, “risk of bias (ROB) instrument for non-randomized studies of exposures (ROB-NRSE),” was recently developed. It is important to establish consistency in its application and interpretation across review teams. In addition, it is important to understand if specialized training and guidance will improve the reliability in the results of the assessments. Therefore, the objective of this cross-sectional study is to establish the inter-rater reliability (IRR), inter-consensus reliability (ICR), and concurrent validity of the new ROB-NRSE tool. Furthermore, as this is a relatively new tool, it is important to understand the barriers to using this tool (e.g., time to conduct assessments and reach consensus—evaluator burden).
Methods
Reviewers from four participating centers will apprise the ROB of a sample of NRSE publications using ROB-NRSE tool in two stages. For IRR and ICR, two pairs of reviewers will assess the ROB for each NRSE publication. In the first stage, reviewers will assess the ROB without any formal guidance. In the second stage, reviewers will be provided customized training and guidance. At each stage, each pair of reviewers will resolve conflicts and arrive at a consensus. To calculate the IRR and ICR, we will use Gwet’s AC1 statistic.
For concurrent validity, reviewers will appraise a sample of NRSE publications using both the Newcastle-Ottawa Scale (NOS) and ROB-NRSE tool. We will analyze the concordance between the two tools for similar domains and for the overall judgments using Kendall’s tau coefficient.
To measure evaluator burden, we will assess the time taken to apply ROB-NRSE tool (without and with guidance), and the NOS. To assess the impact of customized training and guidance on the evaluator burden, we will use the generalized linear models. We will use Microsoft Excel and SAS 9.4, to manage and analyze study data, respectively.
Discussion
The quality of evidence from systematic reviews that include NRSE depends partly on the study-level ROB assessments. The findings of this study will contribute to an improved understanding of ROB-NRSE and how best to use it.
Publisher
Springer Science and Business Media LLC
Reference33 articles.
1. Treadwell JR, Singh S, Talati R, McPheeters ML, Reston JT. A framework for “Best Evidence” approaches in systematic reviews. Rockville (MD)2011.
2. Schunemann HJ, Cuello C, Akl EA, et al. GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. Journal of clinical epidemiology. 2018.
3. Norris S, Atkins D, Bruening W, et al. Selecting observational studies for comparing medical interventions. Rockville (MD): Methods Guide for Effectiveness and Comparative Effectiveness Reviews; 2008.
4. O’Neil M, Berkman N, Hartling L, et al. Observational evidence and strength of evidence domains: case examples. Systematic reviews. 2014;3:35.
5. Hartling L, Milne A, Hamm MP, et al. Testing the Newcastle Ottawa Scale showed low reliability between individual reviewers. Journal of clinical epidemiology. 2013;66(9):982–93.
Cited by
20 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献