Article type
Year
Abstract
Background:
Policy makers and guideline developers face challenges in evaluating the level of confidence in the evidence from systematic reviews with multiple interventions. We previously developed a framework to judge the confidence in results obtained from a network meta-analysis (NMA), expanding on the GRADE domains: study limitations, indirectness, inconsistency (including heterogeneity and incoherence), imprecision and publication bias. However, the process is cumbersome and time-consuming for large networks.
Objectives:
To present a web application, CINeMA (Confidence In Network Meta-Analysis), which considerably simplifies the evaluation of confidence in the findings from NMA via semi-automation.
Description:
CINeMA provides an interactive online process to determine the degree of confidence that can be placed in NMA results. Users upload a dataset (in .csv format) and are guided through the steps of the evaluation process. CINeMA optionally automates several of the methodological steps involved, e.g. by providing heterogeneity and incoherence metrics and appropriate reference values for their interpretation. For example, information about study-level risk of bias assessments can be included in the uploaded data, and CINeMA combines these assessments about direct evidence with their statistical contribution to the network meta-analysis to form judgements about each NMA effect size. Standard NMA output (such as the network plot, NMA effect sizes) is also provided. Using networks of different sizes and complexity, we will show that CINeMA can greatly simplify the evaluation of the credibility of NMA results. Participants are encouraged to bring their laptops (with internet connection) to test the web application and provide feedback.
Policy makers and guideline developers face challenges in evaluating the level of confidence in the evidence from systematic reviews with multiple interventions. We previously developed a framework to judge the confidence in results obtained from a network meta-analysis (NMA), expanding on the GRADE domains: study limitations, indirectness, inconsistency (including heterogeneity and incoherence), imprecision and publication bias. However, the process is cumbersome and time-consuming for large networks.
Objectives:
To present a web application, CINeMA (Confidence In Network Meta-Analysis), which considerably simplifies the evaluation of confidence in the findings from NMA via semi-automation.
Description:
CINeMA provides an interactive online process to determine the degree of confidence that can be placed in NMA results. Users upload a dataset (in .csv format) and are guided through the steps of the evaluation process. CINeMA optionally automates several of the methodological steps involved, e.g. by providing heterogeneity and incoherence metrics and appropriate reference values for their interpretation. For example, information about study-level risk of bias assessments can be included in the uploaded data, and CINeMA combines these assessments about direct evidence with their statistical contribution to the network meta-analysis to form judgements about each NMA effect size. Standard NMA output (such as the network plot, NMA effect sizes) is also provided. Using networks of different sizes and complexity, we will show that CINeMA can greatly simplify the evaluation of the credibility of NMA results. Participants are encouraged to bring their laptops (with internet connection) to test the web application and provide feedback.