Network Meta-analysis Workshop
Why Choose Network Meta-analysis Workshop?
At Research Nexus, we offer a diverse range of programs designed to empower your research journey and align with your goals.
Comprehensive Network Meta-Analysis Workshop
Course Outline
Module 1: Foundations of Network Meta-Analysis
Introduction to Network Meta-Analysis (NMA)
- What is NMA? Definition and purpose
- Distinguishing NMA from pairwise meta-analysis
- When to use NMA in clinical and policy decision-making contexts
Core Concepts
- Direct vs. indirect evidence
- Transitivity assumption and its importance
- Consistency vs. inconsistency in networks
- Understanding network geometry and graphs
Module 2: Formulating the Research Question
Extending PICO for NMA
- Defining populations, interventions, comparators, and outcomes
- Handling multiple interventions and multi-arm trials
Protocol Development
- Registering NMA protocols (PROSPERO, OSF)
- PRISMA-NMA extension for reporting standards
Module 3: Systematic Review for NMA
Literature Search Strategies
- Comprehensive search across multiple databases:
- PubMed
- Cochrane Library
- Embase
- Others
- Identifying trials with multiple intervention arms
- Searching for unpublished and ongoing trials
Study Selection and Data Extraction
- Screening using Rayyan AI or Covidence
- Extracting data for multiple comparisons
Handling correlated data from multi-arm trials
Module 4: Risk of Bias and Quality Assessment
Assessing Individual Studies
- Using ROB-2 (Risk of Bias 2.0) for randomized trials
- ROBINS-I for non-randomized studies
Assessing Confidence in NMA Evidence
- CINeMA (Confidence in Network Meta-Analysis) framework
- GRADE approach for NMA
Module 5: Statistical Foundations
Understanding Effect Measures
- Odds ratios
- Risk ratios
- Mean differences
- Standardized mean differences
Fixed-Effect vs. Random-Effects Models in NMA
- When to use each approach
Heterogeneity in NMA
- Measuring and addressing heterogeneity
Module 6: R Programming for Network Meta-Analysis
Introduction to R for NMA
- Installing and loading NMA packages:
- netmeta
- gemtc
- BUGSnet
Data Preparation
- Structuring long-format data for NMA
- Handling multi-arm trials
Conducting NMA in R
- Generating network graphs
- Running fixed-effect and random-effects models
- Obtaining league tables and ranking probabilities
Advanced R Applications
- Node-splitting analysis for inconsistency assessment
- Meta-regression in NMA
- Generating:
- Forest plots
- Rankograms
- SUCRA (Surface Under the Cumulative Ranking) plots
Module 7: Interpreting and Presenting NMA Results
Network Graphs
- Visualizing treatment networks
League Tables
- Presenting pairwise comparisons with confidence intervals
Ranking Metrics
- Understanding SUCRA and P-scores
- Presenting rankograms
Inconsistency Assessment
- Global and local inconsistency testing
Module 8: Advanced Topics (Optional / Extended)
Bayesian Network Meta-Analysis
- Introduction to Bayesian methods using gemtc or BUGSnet
- Understanding priors, convergence, and model diagnostics
Network Meta-Analysis of Diagnostic Test Accuracy
- Special considerations for diagnostic studies
Individual Patient Data (IPD) Network Meta-Analysis
- Overview and applications
Module 9: Publication and Dissemination
Manuscript Preparation
- Structuring an NMA manuscript
- PRISMA-NMA checklist
Targeting High-Impact Journals
- Journals that publish NMA:
- BMJ
- JAMA Network
- Lancet specialty journals
Team Management
- Distributing tasks among team members
- Timeline management for submission within 45–60 days