Objective To evaluate the quality of evidence of systematic reviews or meta-analyses regarding outcomes in nursing field in China using the Grade system, so as to get known of the status of the quality of evidence and promote the application of the evaluation of the quality of evidence of systematic reviews. Methods The quality of evidence regarding the included outcomes was input, extracted and qualitatively graded, using GRADEpro 3.6 software. Then, we carefully analyzed and elaborated the factors of downgrading and upgrading that affects the quality of evidence in the process of evaluation. Results 53 systematic reviews or meta-analyses involving 188 outcomes were identified and evaluated. The results showed that high, moderate, low and very low levels of quality of evidence were 2.7%, 27.1%, 51.1%, and 19.1%, respectively; and low-level quality of evidence accounted for the most. Conclusion The quality of evidence produced by systematic reviews or meta-analyses in nursing field in China is poor and urgently needs improvement. The reviewers should abide by the methodological standards in the process of making systematic reviews or meta-analyses. The quality of evidence in terms of each outcome should be evaluated and fully reported.
The methodology of conducting systematic review of prognostic studies has received a great deal of interest in recent years. Using GRADE for systematic review of prognostic studies, five aspects should be considered:risk of bias, indirectness, inconsistency, imprecision and publication bias. The methods of using GRADE system in systematic review of prognostic studies are similar to systematic review of interventional studies, meanwhile, there are differences. Not only the uniqueness of prognostic study but also the repeating downgrade should be taken into consideration in the GRADE process. Applying GRADE to systematic review of prognostic studies would be widely accepted along with the methodology development and quality improvement of systematic review of prognostic studies.
ObjectiveTo investigate the recommendations on imaging diagnosis in Chinese clinical practice guidelines (CPGs). MethodsWe electronically searched WanFang Data, VIP, CNKI and CBM databases from inception to December 31, 2014. Two reviewers independently screened literature and extracted data. The method of bibliometrics was used to analyze the data (including basic characteristics, strength of recommendation, quality of evidence, etc.). ResultsA total of 341 CPGs formulating the recommendations on diagnosis were included. 48.7% (166/341) guidelines developed the recommendations on imaging diagnosis (a total of 534). 25.7% (137/534) recommendations were with the symbols of quality of evidence and strength of recommendation, and 18.9% (101/534) with special words such as recommend, suggest. 22.3% (119/534) recommendations reported the strength of recommendation. Of which, 38.7% (46/119) were strong and 16.0% (19/119) were weak. However, 23.9% (11/46) strong recommendations were based on low quality of evidence. And 42.1% (8/19) weak recommendations were based on high quality of evidence. ConclusionAmong Chinese CPGs formulating the recommendations on diagnosis, the number of CPGs with recommendations on imaging is about 50%. And the quantity increases by years. The proportions of recommendations on imaging which report the strength of recommendation and/or quality of evidence are low. Meanwhile, the rating systems are uniform. Then the developers do not report the explanation for the strong recommendations based on low quality of evidence or the weak recommendations based on high quality of evidence in guideline.
ObjectiveTo evaluate the risk of bias and reliability of conclusions of systematic reviews (SRs) of lung cancer screening. MethodsWe searched PubMed, EMbase, The Cochrane Library (Issue 2, 2016), Web of Knowledge, CBM, WanFang Data and CNKI to collect SRs of lung cancer screening from inception to February 29th, 2016. The ROBIS tool was applied to assess the risk of bias of included SRs, and then GRADE system was used for evidence quality assessment of outcomes of SRs. ResultsA total of 11 SRs involving 5 outcomes (mortality, detection rate, survival rate, over-diagnosis and potential benefits and harms) were included. The results of risk of bias assessment by ROBIS tool showed:Two studies completely matched the 4 questions of phase 1. In the phase 2, 6 studies were low risk of bias in the including criteria field; 8 studies were low risk of bias in the literature search and screening field; 3 studies were low risk of bias in the data abstraction and quality assessment field; and 5 studies were low risk of bias in the data synthesis field. In the phase 3 of comprehensive risk of bias results, 5 studies were low risk. The results of evidence quality assessment by GRADE system showed:three studies had A level evidence on the outcome of mortality; 1 study had A level evidence on detection; 1 study had A level evidence on survival rate; 3 studies on over-diagnosis had C level evidence; and 2 studies on potential benefits and harms had B level evidence. ConclusionThe risk of bias of SRs of lung cancer screening is totally modest; however, the evidence quality of outcomes of these SRs is totally low. Clinicians should cautiously use these evidence to make decision based on local situation.
It is a complex and time-consuming process to rate the certainty (quality) of evidence from network meta-analysis. This paper aims to introduce a web application for rating the certainty of network meta-analysis-the CINeMA. CINeMA is based on GRADE framework and contribution matrix of network meta-analysis, which considers 6 domains including within-study bias, across-studies bias, indirectness, imprecision, heterogeneity, and incoherence.
In 2014, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group published guidance in BMJ to evaluate the certainty of the evidence (confidence in evidence, quality of evidence) from network meta-analysis. GRADE working group suggested rating the certainty of direct evidence, indirect evidence, and network evidence, respectively. Recently, GRADE working group has published a series of papers to improve and supplement this approach. This paper introduces the frontiers and advancement of GRADE approach to rate the certainty of evidence from network meta-analysis.
ObjectiveTo systematically review the researches on grading criteria for quality of evidence and strength of recommendations of traditional Chinese medicine (TCM). MethodsPubMed, EMbase, Web of Science, CNKI, WanFang Data and VIP databases were electronically searched to collect researches on grading criteria for quality of evidence and strength of recommendations of traditional Chinese medicine from inception to June 2021. Two reviewers independently screened literature, extracted data; and then, descriptive analysis was performed using qualitative methods. ResultsA total of 18 studies were included. Specifically, 8 studies presented both the level of evidence and the strength of recommendations, 9 presented the level of evidence, and 1 presented the strength of recommendations. Thirteen studies considered both TCM evidence and modern medical evidence sources, 3 included only evidence from ancient literature, 1 focused only on post-marketing safety evaluation of Chinese medicine, and 1 focused only on real-world studies of TCM. ConclusionCurrently, there are numerous criteria for TCM related quality of evidence and strength of recommendations, and some are developed only for TCM characteristic evidence. Most researchers of TCM guidelines expect to fully value the significance of ancient literature and expert experience or opinion in guideline development.
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.
Previous methods of grading evidence for systematic reviews of diagnostic test accuracy have generally focused on assessing the certainty (quality) of evidence at the level of diagnostic indicators. When the question is not limited to follow the diagnostic test accuracy results themselves, the grading results may be inaccurate due to the lack of consideration of the downstream effects of the test accuracy in specific settings. To address these challenges, the GRADE working group conducted a series of studies focused on updating methods to explore or simulate important downstream effects of diagnostic test accuracy outcomes within a contextual framework. This paper aimed to introduce advances in the contextual framework of the GRADE approach to rate the certainty of evidence from systematic reviews of single diagnostic test accuracy.