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.
Currently there is no tool designed specifically to assess the risk of bias in the design, conduct or analysis of systematic reviews. ROBIS (Risk Of Bias In Systematic reviews), which was developed lately, aims mainly to assess the risk of bias in the conduct and result interpretation of systematic reviews relating to interventions, etiology, diagnosis and prognosis, as well as the relevance of the systematic review questions and the practice questions that their users want to address. This paper aims to introduce the ROBIS tool to Chinese systematic review developers, guideline developers and other researchers to promote the comprehension of it and its application, so as to improve the quality of systematic reviews in China.
Measurement properties studies of patient-reported outcome measures (PROMs) aims to validate the measurement properties of PROMs. In the process of designing and statistical analysis of these measurement properties studies, bias will occur if there are any defects, which will affect the quality of PROMs. Therefore, the COSMIN (consensus-based standards for the selection of health measurement instruments) team has developed the COSMIN risk of bias (COSMIN-RoB) checklist to evaluate risk of bias of studies on measurement properties of PROMs. The checklist can be used to develop systematic reviews of PROMs measurement properties, and for PROMs developers, it can also be used to guide the research design in the measurement tool development process for reducing bias. At present, similar assessment tools are lacking in China. Therefore, this article aims to introduce the primary contents of COSMIN-RoB checklist and to interpret how to evaluate risk of bias of the internal structure studies of PROMs with examples.
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.
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.
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.
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.
At present, there are many items/checklists used to assess the methodological quality of animal studies. Yet, no tool has been specifically designed for assessing internal validity of animal studies. This articles introduce and interprets SYRCLE's risk of bias tool for animal studies in detail for Chinese scholars to accurately assess the methodological quality of animal studies when they develop systematic reviews on animal studies, so as to provide references for scientific design and implementation of animal studies.
ObjectivesTo comprehensively evaluate the methodological quality and applicability of the results of systematic reviews on acupuncture treatment for primary depression.MethodsWeb of Science, EMbase, PubMed, The Cochrane Library, CNKI, CBM, WanFang Data and VIP databases were electronically searched to collect systematic reviews/meta-analyses on acupuncture treatment for primary depression from inception to December 5th, 2018. Two researchers independently screened and extracted data by using tools of AMSTAR 2 to evaluate the methodological quality, using ROBIS to assess risk of bias, and using CASP-S.R to evaluate the applicability of the results.ResultsA total of 18 systematic reviews/meta-analyses were included, and all focused on acupuncture intervention, including 2 primary outcome indicators. According to AMSTAR 2 evaluation results, there were 4 high quality studies, 12 medium quality studies and 2 low quality studies; ROBIS results found 10 high bias risk studies, 7 low bias risk studies and 1 unclear; CASP-S.R showed only 4 design studies applicable to local individuals, and there were no studies on the relationship between design benefits, hazards and costs.ConclusionsThe quality of systematic reviews/meta-analyses for acupuncture treatment of primary depression is moderate, however with a certain bias. Most studies may not directly benefit local individuals. All studies have no relationship with cost hazards. It is expected for further reviewers to strictly follow systematic evaluation method to improve research quality and reduce bias, while the applicability of the systematic review to individuals from different regions should be considered as well as the relationship between the benefit and cost hazard. In addition, more valid RCTs are required to provide higher quality evidence and explore correlated and comprehensive mechanism.