High-quality randomized controlled trials are the best source of evidence to explain the relationship between health interventions and outcomes. However, in cases where they are insufficient, indirect, or inappropriate, researchers may need to include non-randomized studies of interventions to strengthen the evidence body and improve the certainty (quality) of evidence. The latest research from the GRADE working group provides a way for researchers to integrate randomized and non-randomized evidence. The present paper introduced the relevant methods to provide guidance for systematic reviewers, health technology assessors, and guideline developers.
The COSMIN-RoB checklist includes three sections with a total of 10 boxes, which is used to evaluate risk of bias of studies on content validity, internal structure, and other measurement properties. COSMIN classifies reliability, measurement error, criteria validity, hypothesis testing for construct validity, and responsiveness as other measurement properties, which primarily focus on the quality of the (sub)scale as a whole, rather than on the item level. Among the five measurement properties, reliability, measurement error and criteria validity are the most widely used in the studies. Therefore, this paper aims to interpret COSMIN-RoB checklist with examples to guide researchers to evaluate the risk of bias of the studies on reliability, measurement error and criteria validity of PROMs.
The QUADAS-2, QUIPS, and PROBAST tools are not specific for prognostic accuracy studies and the use of these tools to assess the risk of bias in prognostic accuracy studies is prone to bias. Therefore, QUAPAS, a risk of bias assessment tool for prognostic accuracy studies, has recently been developed. The tool combines QUADAS-2, QUIPS, and PROBAST, and consists of 5 domains, 18 signaling questions, 5 risk of bias questions, and 4 applicability questions. This paper will introduce the content and usage of QUAPAS to provide inspiration and references for domestic researchers.
ObjectiveTo interpret ROBIS, a new tool to evaluate the risk of bias in systematic reviews, to promote the comprehension of it and its proper application. MethodsWe explained each item of ROBIS tool, used it to evaluate the risk of bias of a selected intervention review whose title was Cyclophosphamide for Primary Nephrotic Syndrome of Children: A Systematic Review, and judged the risk of bias in the review. ResultsThe selected systematic review as a whole was rated as “high risk of bias”, because there existed high risk of bias in domain 2 to 4, namely identification and selection of studies, data collection and study appraisal, synthesis and findings. The risk of bias in domain 1 (study eligibility criteria) was low. The relevance of identified studies and the review’s research question was appropriately considered and the reviewers avoided emphasizing results on the basis of their statistical significance. ConclusionROBIS is a new tool worthy of being recommended to evaluate risk of bias in systematic reviews. Reviewers should use ROBIS items as standards to conduct and produce high quality systematic reviews.
The COSMIN community updated the COSMIN-RoB checklist on reliability and measurement error in 2021. The updated checklist can be applied to the assessment of all types of outcome measurement studies, including clinician-reported outcome measures (ClinPOMs), performance-basd outcome measurement instruments (PerFOMs), and laboratory values. In order to help readers better understand and apply the updated COSMIN-RoB checklist and provide methodological references for conducting systematic reviews of ClinPOMs, PerFOMs and laboratory values, this paper aimed to interpret the updated COSMIN-RoB checklist on reliability and measurement error studies.
ObjectiveTo systematically interpret the updated risk of bias in non-randomized studies of interventions version 2 (ROBINS-I V2) in 2024, summarizing its key improvements, operational procedures, and clinical application value. MethodsThrough literature review and case studies, the improvements of ROBINS-I V2 were compared with the 2016 version, including the expansion of bias domains, refinement of signaling questions, and optimization of decision flowcharts. A retrospective study in stomatology was used to demonstrate the practical application of the tool. ResultsThe ROBINS-I V2 tool has restructured the hierarchy and refined the definitions of bias domains, optimized the evaluation processes across seven risk-of-bias dimensions, and minimized subjective judgment errors through standardized decision flowcharts. ConclusionROBINS-I V2 significantly improves the rigor of bias assessment in non-randomized intervention studies through its scientific design and standardized workflow. It is recommended for evidence quality grading and decision-making support in clinical research.
The current issue of air pollution has pushed the development of the corresponding observational air pollution studies. The World Health Organization has developed a new risk of bias (RoB) assessment instrument and a related guideline for assessing the risk of potential bias in observational air pollution studies. This study introduced the background, methods, uses, advantages and disadvantages, precautions, and usage scenarios of the RoB instrument. It is expected to provide researchers with corresponding quality evaluation tools when writing related systematic review and meta-analysis, which will also help provide reporting standards for observational air pollution studies, thereby improving the quality of studies.
This paper introduces the main contents of ROB-ME (Risk Of Bias due to Missing Evidence), including backgrounds, scope of the tool, signal questions and the operation process. The ROB-ME tool has the advantages of clear logic, complete details, simple operation and good applicability. The ROB-ME tool offers considerable advantages for assessing the risk of non-reporting biases and will be useful to researchers, thus being worth popularizing and applying.
RoB2 (revised version 2019), an authoritative tool for assessing the risk of bias in randomized controlled trials, has been updated and improved based on the original version. This article elaborated and interpreted the background and main content of RoB2 (revised version 2019), as well as the operation process of the new software. Compared with the previous version of RoB2 (revised version 2018), RoB2 (revised version 2019) has the advantages of rich content, complete details, accurate questions, and simple operation, etc. Additionally, it is more user-friendly for researchers and beginners. The risk bias assessment of randomized controlled trials is more comprehensive and accurate, and it is an authoritative, trustworthy, and popular tool for evaluating the risk of bias in randomized controlled studies in medical practice.
The risk of bias assessment tool 2.0 (RoB 2.0) for analyzing cluster randomized trials and crossover trials (revised version 2021) has been updated. The current paper briefly delineates the history of the RoB 2.0 tool and includes an explanation and interpretation of the updated contents and software operation process for use with cluster randomized trials and crossover trials. Compared with the previous versions, the updated RoB 2.0 tool (revised version 2021) has the advantage of precise language and is easily understood. Thus, the updated RoB 2.0 tool merits popularization and further general application.