TI Methods Speaker Series
The TI Methods Speaker Series are offered free of charge and everyone is welcome. The event is held at noon on the last Wednesday of each month and used to take place in Rudy North Lecture Theatre (CBH 101) in the Centre for Brain Health, UBC Point Grey Campus. During the COVID-19 pandemic, while physical distancing measures are in effect, the TI Methods Speaker Series are offered via videoconference. The presentations are recorded and the video recordings are posted online.
This webinar has already taken place. Scroll down to view a video recording of the event.
WHEN: Wednesday, March 31st, 2021 from 12:00 to 1:00 PM PDT [click here to convert to your local time]
WHERE: Offered online using Zoom.
TITLE: The development of a risk of bias tool for network meta-analysis
SPEAKER: Dr. Carole Lunny, Postdoctoral Research Fellow, Knowledge Synthesis Team, at Unity Health, University of Toronto, ON.
About the topic: In this presentation, Dr. Lunny will describe tools that are currently used to assess the quality and risk of bias in systematic reviews with or without meta-analysis, and justify why a new risk of bias tool for NMAs is needed. She will also describe the way to choose a quality assessment tool based on rigorous methodology and describe proposed methods for the development of a risk of bias tool for NMAs. Scroll down to read the abstract for this presentation.
About the speaker: Dr. Carole Lunny is a postdoc research methodologist with the Knowledge Synthesis Team, at Unity Health, University of Toronto, and a Methodology Editor with the Cochrane Hypertension Review Group, the Therapeutics Initiative at the University of British Columbia. She specializes in methods for research synthesis and critical appraisal of systematic reviews with pairwise and network meta-analysis, overviews of reviews, randomised controlled trials, and observational studies (cohort, case control). Her current research focuses on the development of a risk of bias tool for network meta-analyses, methods issues in clinical practice guidelines and ‘overviews of reviews’. Her list of publications can be found at: https://scholar.google.com/citations?user=YaJAbZsAAAAJ&hl=en&oi=ao She completed her PhD training as an epidemiologist in 2018 with Cochrane Australia at Monash University and recently completed a postdoctoral research fellowship with the Therapeutics Initiative (Cochrane Hypertension Group) at the University of British Columbia. She is a member of the several methods groups at Cochrane, academic board advisor for Researchsquare.com, and academic editor for PeerJ.
About the TI Methods Speaker Series: The TI Methods Speaker Series are offered free of charge and everyone is welcome. The event is held at noon on the last Wednesday of each month. During the COVID-19 pandemic, while physical distancing measures are in effect, the TI Methods Speaker Series are offered via videoconference. The presentations are recorded and the video recordings are posted online. Click here to view the scheduled topics for 2021 and click here to view a list of TI Methods Speaker Series talks offered in 2020.
Methodological review of items for assessing the risk of bias in network meta-analyses provides groundwork for the development of a new risk of bias tool for network meta-analysis
Authors: Lunny C, Andrea T, Veroniki A, Wright J, White I, Dias S, Salanti G, Hutton B, Higgins J, Whiting P
Background: To decide the best treatment for a patient, healthcare providers and patients need a synthesis of evidence for all possible treatments for a given condition. Network meta-analysis (NMA) emerged due to the limitations of pairwise meta-analyses to provide comparative effectiveness of multiple treatments for the same condition. Conventional meta-analyses only average the randomised trials comparing two treatments. NMA can help patients and their care providers choose the treatment that is most important to them based on side effects and efficacy of all treatments. Tools are available for most study designs to make quality assessment easier for a knowledge user. For example, ROBIS can be used to assess the risk of bias of systematic reviews (SRs). However, there is currently no risk of bias tool for reviews with network meta-analyses (NMA).
Study objectives: The first step in the development of a tool to assess the risk of bias in network meta-analyses is to conduct a methodological review. Its aim is to develop a list of items relating to risk of bias in reviews with network meta-analyses. Our subsequent objectives are to: decide on the structure of the tool; conduct a Delphi process to refine the tool; and pilot test the tool.
Methods: A steering group of experts in tool development, bias and NMAs was convened. We follow the methods proposed by Whiting (2013) to develop the tool. For the methodological review, we included tools, scientific papers and editorial standards that present items related to bias, reporting, or methodological quality, or articles that assess the methodological quality of reviews with NMA. We searched MEDLINE, the Cochrane library, and difficult to locate/unpublished literature. Once all items were extracted, we combined conceptually similar items, classifying them as referring to bias or to other aspects of quality (e.g. reporting). When relevant, items related to reporting were re-worded into items related to bias in NMA review conclusions, and then re-worded as signalling questions. The steering group reviewed and refined the list of items.
Next methodological steps: Feedback from a larger expert group will be obtained via a Delphi survey. Participants will be asked to rate whether items should be included. All agreed-upon items, additional or aggregated items, will be included in a second and possibly a third round of the Delphi survey (depending on the level of agreement). An explanation and elaboration guidance statement will be written for each item included in the final tool version. The tool will be piloted.
Presentation agenda: In this presentation, I will describe tools that are currently used to assess the quality and risk of bias in systematic reviews with or without meta-analysis, and justify why a new risk of bias tool for NMAs is needed. I will also describe the way to choose a quality assessment tool based on rigorous methodology. I will also describe our methods for the development of a risk of bias tool for NMAs.