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.
Evidence synthesis serves as a bridge between clinical practice and the best available evidence. Evidence synthesis based on high-quality randomized controlled trials is generally considered the highest level of evidence, but its external validity is limited. In some scenarios, the inclusion of non-randomized intervention studies (NRSI) in evidence synthesis may further supplement or even replace randomized controlled trial evidence, such as assessing intervention effectiveness and rare events in a broader population to provide more information for health care decision-making. With the rapid development of real-world data and the improvement of statistical analysis methods, real-world evidence, as an important source of evidence for NRSI, has accelerated the development of high-quality NRSI. However, there are numerous challenges in integrating evidence from randomized and non-randomized intervention studies due to selection and confounding biases caused by the lack of randomization. Based on previous studies, this paper systematically examines the current status of integrated randomized and non-randomized intervention studies, including integration premise, timing, methods, and result interpretation, in order to provide references for researchers and policy-makers to correctly use non-randomized research evidence and further promote optimal evidence generation and clinical practice translation.
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 biggest advantages of network meta-analysis (NMA) are to compare the effectiveness of different interventions about one conditions using a quantitative way, pool the results of direct comparison and indirect comparison, and rank the effectiveness based on outcomes, so as to select the best decision for patients. In the paper we introduce the methods of applying GRADE system to NMAs based on the papers published by GRADE working group and other relative studies. The steps of using GRADE to NMAs are mainly based on four aspects: firstly, presenting direct and indirect effect estimates and 95% CI; secondly, rating of quality of direct and indirect estimates; thirdly, presenting the results of NMAs; and the last step is to rating the quality of NMA effect estimates. The methods of rating the quality of direct comparison are the same to use GRADE in traditional meta-analysis. The rating of the quality of the indirect estimates is based on the ratings of the two pairwise estimates that contributes to the indirect estimate of the comparison of interest. The lower confidence rating of the two direct comparisons constitutes the confidence rating of the indirect comparison. When both direct and indirect evidence are available, we suggest using the higher of the two quality ratings as the quality rating for NMA estimate. The four steps of rating the quality of NMA from GRADE working group have promoted the theoretical system of NMA. But the process requires the evaluators to be familiar with GRADE system, and conduct pilot test to make sure the evaluators had understood the items of GRADE system correctly. In addition, we also need to concern that the non-transitivity among different groups and the inconsistency between direct comparison and indirect comparison.
GRADE方法中，随机试验起评即为高质量证据，观察性研究起评即为低质量证据；但若证据本身存在高发表偏倚风险，则两者证据质量级别都应降低。即使最佳证据汇总表纳入的各项研究仅有低发表偏倚风险，发表偏倚仍会极大高估效应值。当可得证据来自小样本研究、且多数由厂商资助时，作者应怀疑存在发表偏倚。若干基于检验数据类型的方法可用于评价发表偏倚，其中最常用的为漏斗图，但这些方法都有较大局限。发表偏倚可能较常见，必须特别关注早期结果、对样本量与事件数都很小的早期试验结果尤需小心。
GRADE（Grades of Recommendation, Assessment, Development，and Evaluation）方法为卫生保健中的证据质量评价与推荐强度评级提供指导。对那些为系统评价、卫生技术评估及临床实践指南总结证据的人而言，GRADE具有重要意义。GRADE提供了一个系统而透明的框架用以明确问题，确定所关注的结局，总结针对某问题的证据，以及从证据到形成推荐或作出决策。GRADE方法的广泛传播与应用，获全球50余个组织认可，这些组织大多有很强的影响力（http://www.gradeworkinggroup.org/），足以证明该工作的重要性。本文介绍临床流行病学杂志将刊出的20篇系列文章，为如何使用GRADE方法提供指导。
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.
本文是GRADE（Grading of Recommendations Assessment，Development，and Evaluation）系列文章的导论。该系列文章为使用GRADE系统提供指导，介绍如何将该系统用于系统评价、卫生技术评估（HTAs）及临床实践指南中备选方案的证据质量评价和推荐强度评级。GRADE方法始于提出一个明晰的问题，包括对所有重要结果的详细说明。证据被收集和汇总后，GRADE提供了明确的标准来评价其质量，包括研究设计、偏倚风险、不精确性、不一致性、间接性及效应量大小。
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.
GRADE要求明确说明相关的背景、人群、干预措施和对照，同时要求不论研究结果能否形成证据，均需详述所有重要结果。对某一特定管理问题，人群、干预措施及结果应在不同研究间足够类似，才能认为得到相似的效应量合乎情理。指南制定者在收集证据前应先详细说明各结局的相对重要性，同样地，证据总结完成时也需要详细说明这一点。考虑到替代结局的重要性，对采用替代指标描述且对患者很重要的结局，作者应评估其重要性，并进而降低这种间接结果的证据质量等级。