Knowledge user survey and Delphi process to inform development of a new risk of bias tool to assess systematic reviews with network meta-analysis (RoB NMA tool).

BACKGROUND: Network meta-analysis (NMA) is increasingly used in guideline development and other aspects of evidence-based decision-making. We aimed to develop a risk of bias (RoB) tool to assess NMAs (RoB NMA tool). An international steering committee recommended that the RoB NMA tool to be used in combination with the Risk of Bias in Systematic reviews (ROBIS) tool (i.e. because it was designed to assess biases only) or other similar quality appraisal tools (eg, A MeaSurement Tool to Assess systematic Reviews 2 [AMSTAR 2]) to assess quality of systematic reviews. The RoB NMA tool will assess NMA biases and limitations regarding how the analysis was planned, data were analysed and results were presented, including the way in which the evidence was assembled and interpreted. OBJECTIVES: Conduct (a) a Delphi process to determine expert opinion on an item's inclusion and (b) a knowledge user survey to widen its impact. DESIGN: Cross-sectional survey and Delphi process. METHODS: Delphi panellists were asked to rate whether items should be included. All agreed-upon item were included in a second round of the survey (defined as 70% agreement). We surveyed knowledge users' views and preferences about the importance, utility and willingness to use the RoB NMA tool to evaluate evidence in practice and in policymaking. We included 12 closed and 10 open-ended questions, and we followed a knowledge translation plan to disseminate the survey through social media and professional networks. RESULTS: 22 items were entered into a Delphi survey of which 28 respondents completed round 1, and 22 completed round 2. Seven items did not reach consensus in round 2. A total of 298 knowledge users participated in the survey (14% respondent rate). 75% indicated that their organisation produced NMAs, and 78% showed high interest in the tool, especially if they had received adequate training (84%). Most knowledge users and Delphi panellists preferred a tool to assess both bias in individual NMA results and authors' conclusions. Response bias in our sample is a major limitation as knowledge users working in high-income countries were more represented. One of the limitations of the Delphi process is that it depends on the purposive selection of experts and their availability, thus limiting the variability in perspectives and scientific disciplines. CONCLUSIONS: This Delphi process and knowledge user survey informs the development of the RoB NMA tool.

Over half of clinical practice guidelines use non-systematic methods to inform recommendations: A methods study.

INTRODUCTION: Assessing the process used to synthesize the evidence in clinical practice guidelines enables users to determine the trustworthiness of the recommendations. Clinicians are increasingly dependent on guidelines to keep up with vast quantities of medical literature, and guidelines are followed to avoid malpractice suits. We aimed to assess whether systematic methods were used when synthesizing the evidence for guidelines; and to determine the type of review cited in support of recommendations. METHODS: Guidelines published in 2017 and 2018 were retrieved from the TRIP and Epistemonikos databases. We randomly sorted and sequentially screened clinical guidelines on all topics to select the first 50 that met our inclusion criteria. Our primary outcomes were the number of guidelines using either a systematic or non-systematic process to gather, assess, and synthesise evidence; and the numbers of recommendations within guidelines based on different types of evidence synthesis (systematic or non-systematic reviews). If a review was cited, we looked for evidence that it was critically appraised, and recorded which quality assessment tool was used. Finally, we examined the relation between the use of the GRADE approach, systematic review process, and type of funder. RESULTS: Of the 50 guidelines, 17 (34%) systematically synthesised the evidence to inform recommendations. These 17 guidelines clearly reported their objectives and eligibility criteria, conducted comprehensive search strategies, and assessed the quality of the studies. Of the 29/50 guidelines that included reviews, 6 (21%) assessed the risk of bias of the review. The quality of primary studies was reported in 30/50 (60%) guidelines. CONCLUSIONS: High quality, systematic review products provide the best available evidence to inform guideline recommendations. Using non-systematic methods compromises the validity and reliability of the evidence used to inform guideline recommendations, leading to potentially misleading and untrustworthy results.

Impact and use of reviews and 'overviews of reviews' to inform clinical practice guideline recommendations: protocol for a methods study.

INTRODUCTION: Guidelines are systematically developed recommendations to assist practitioner and patient decisions about treatments for clinical conditions. High quality and comprehensive systematic reviews and 'overviews of systematic reviews' (overviews) represent the best available evidence. Many guideline developers, such as the WHO and the Australian National Health and Medical Research Council, recommend the use of these research syntheses to underpin guideline recommendations. We aim to evaluate the impact and use of systematic reviews with and without pairwise meta-analysis or network meta-analyses (NMAs) and overviews in clinical practice guideline (CPG) recommendations. METHODS AND ANALYSIS: CPGs will be retrieved from Turning Research Into Practice and Epistemonikos (2017-2018). The retrieved citations will be sorted randomly and then screened sequentially by two independent reviewers until 50 CPGs have been identified. We will include CPGs that provide at least two explicit recommendations for the management of any clinical condition. We will assess whether reviews or overviews were cited in a recommendation as part of the development process for guidelines. Data extraction will be done independently by two authors and compared. We will assess the risk of bias by examining how each guideline developed clinical recommendations. We will calculate the number and frequency of citations of reviews with or without pairwise meta-analysis, reviews with NMAs and overviews, and whether they were systematically or non-systematically developed. Results will be described, tabulated and categorised based on review type (reviews or overviews). CPGs reporting the use of the Grading of Recommendations, Assessment, Development and Evaluation approach will be compared with those using a different system, and pharmacological versus non-pharmacological CPGs will be compared. ETHICS AND DISSEMINATION: No ethics approval is required. We will present at the Cochrane Colloquium and the Guidelines International Network conference.

Validation of five search filters for retrieval of clinical practice guidelines produced low precision.

OBJECTIVES: The aim of the study was to validate search filters for retrieval of clinical practice guidelines (CPGs) in MEDLINE, Embase, and PubMed. STUDY DESIGN AND SETTING: A search for filters for identifying CPGs was conducted in Google and the InterTASC Information Specialists Sub-Group Search Filter Resource. To retrieve a random sample of CPGs to test sensitivity and precision of the filters, we used the TRIP and Epistemonikos databases. The citations were screened independently by two researchers. The sensitivity and precision were calculated. RESULTS: Five search filters were retrieved: two from the Canadian Agency for Drugs and Technologies in Health (CADTH), two from the University of Texas, and one from the MD Anderson Cancer Center Library. A total of 478 records were screened to identify 109 CPGs, which comprised the sample for testing sensitivity and precision. The sensitivity ranged from 87% to 98% for the five search filters and very low precision (<1%) across all databases. CONCLUSION: Knowledge users who are interested in retrieving all relevant CPGs can use the CADTH broad filter with the highest sensitivity. However, our analysis shows that it remains difficult to efficiently identify CPGs because of low precision of five search filters. We recommend searching guideline-specific resources as a more time-efficient approach than searching bibliographic databases.