Network meta-analysis services for comparative evidence questions
Synthesa conducts frequentist and Bayesian network meta-analyses for healthcare and life sciences teams that need to compare multiple interventions, devices, procedures, or treatment approaches across a connected evidence base.
1,000,000+
abstracts screened
20,000+
outcomes meta-analysed
7 to 14 days
average project delivery
When direct comparisons are not enough
Healthcare evidence is often incomplete. Some interventions have been compared directly. Others have only been compared through shared comparators. In many cases, decision-makers need to understand comparative performance across a broader evidence network.
A network meta-analysis can help answer questions such as:
- How do multiple interventions compare when direct head-to-head evidence is limited?
- Is the evidence network connected enough for quantitative synthesis?
- Which treatments, devices, or procedures appear more favourable for specific outcomes?
- How consistent is the direct and indirect evidence?
- What uncertainty remains around comparative estimates?
Synthesa helps teams move from fragmented comparative evidence to structured statistical synthesis, with expert review and clear interpretation.
Frequentist and Bayesian NMA, delivered as a specialist service
Synthesa can support network meta-analysis as part of a full systematic review or as a statistical synthesis work package using an existing dataset.
We support
- Network meta-analysis feasibility assessment
- Evidence network construction
- Frequentist network meta-analysis
- Bayesian network meta-analysis
- Indirect treatment comparison
- Comparative effect estimates
- Consistency and heterogeneity assessment
- Sensitivity analyses
- Subgroup analyses where appropriate
- Ranking outputs where appropriate
- Network diagrams
- Publication-ready tables and figures
- Structured interpretation of results
Typical outputs include
- NMA feasibility summary
- Evidence network diagrams
- Model specification and methods text
- Comparative effect estimates
- League tables, where appropriate
- Ranking plots or summaries, where appropriate
- Forest plots and interval plots
- Sensitivity analysis outputs
- Interpretation of uncertainty, heterogeneity, and consistency
- Publication-ready figures and tables
Comparative evidence synthesis for complex decisions
Compare multiple interventions across a connected evidence base
Synthesa supports teams that need to understand comparative outcomes across treatments, therapy classes, populations, or clinical endpoints.
Useful when you need to
- Compare interventions where direct evidence is incomplete
- Understand relative effects across multiple outcomes
- Support publication planning or scientific communication
- Assess uncertainty across a comparative evidence network
- Generate structured comparative evidence outputs
Relevant services: Network Meta-Analysis, Meta-Analysis, Systematic Reviews
Compare devices, procedures, or device categories
Medical device evidence can be fragmented across generations, procedures, comparators, and clinical settings. Synthesa can assess whether an evidence network supports comparative synthesis and conduct NMA where appropriate.
Useful when you need to
- Compare device categories or procedures
- Understand indirect comparative evidence
- Evaluate outcomes across heterogeneous studies
- Support medical, commercial, or market access discussions
- Identify where comparative evidence remains weak
Relevant services: Network Meta-Analysis, Systematic Reviews, Rapid Evidence Synthesis
Add specialist NMA capability without hiring
Synthesa supports CROs and medcomms agencies that need advanced statistical synthesis for client projects, publications, or evidence generation programmes.
Useful when you need to
- Assess whether NMA is feasible
- Analyse an extracted comparative dataset
- Deliver publication-ready NMA outputs
- Support a client project with advanced synthesis needs
- Add Bayesian or frequentist NMA capacity without expanding your team
Relevant services: Network Meta-Analysis, Meta-Analysis
Already have extracted data? We can assess and analyse it
If your team already has a dataset from a systematic review, Synthesa can review the data structure, assess network connectivity, recommend an analysis approach, and conduct the NMA where feasible.
Useful when you need to
- Check whether your evidence network is analysable
- Harmonise outcomes and comparators
- Review assumptions before modelling
- Run frequentist or Bayesian NMA
- Produce publication-ready figures and methods text
Relevant services: Network Meta-Analysis, Meta-Analysis
Start with the right question: is NMA appropriate?
Not every comparative evidence question is suitable for network meta-analysis.
Before modelling, Synthesa can assess whether the available studies form a connected network, whether outcomes are sufficiently comparable, and whether the assumptions needed for NMA are reasonable.
NMA feasibility assessment can include:
- Intervention and comparator mapping
- Outcome availability review
- Network connectivity assessment
- Timepoint and endpoint harmonisation review
- Initial recommendation on frequentist or Bayesian approach
- Initial recommendation on frequentist or Bayesian approach
- Identification of gaps that may limit synthesis
Why this matters
A strong NMA starts before the model is run. It depends on whether the evidence base can support a valid comparative synthesis. Synthesa helps teams avoid overextending the data and instead select an analysis approach that fits the evidence.
Frequentist and Bayesian approaches, selected for the evidence question
Synthesa supports both frequentist and Bayesian network meta-analysis. The choice depends on the project objective, network structure, outcome type, evidence volume, and required interpretation.
Frequentist network meta-analysis
A frequentist approach may be suitable when the network is well structured, the project requires conventional comparative estimates, and reporting expectations align with standard statistical outputs.
- Comparative effect estimation
- Standard publication outputs
- Larger or well-connected evidence networks
- Sensitivity analyses and heterogeneity assessment
Bayesian network meta-analysis
A Bayesian approach may be suitable when probabilistic interpretation is valuable, the evidence network is complex, or uncertainty needs to be communicated in a flexible way.
- Complex or sparse evidence networks
- Probabilistic interpretation
- Ranking probabilities, where appropriate
- Advanced random-effects modelling
- Comparative synthesis across multiple outcomes
Specialist comparative synthesis without building internal capability
Network meta-analysis requires statistical expertise, careful dataset preparation, evidence network judgement, and clear interpretation.
For many teams, building this capability internally is impractical, especially when NMA projects are occasional, urgent, or client-specific.
Synthesa gives your team access to specialist support without requiring new hires, statistical programming infrastructure, or new software adoption.
- Frequentist and Bayesian NMA capability
- Feasibility assessment before modelling
- Evidence network construction and interpretation
- Publication-ready outputs
- Flexible support for existing datasets or full evidence projects
- No new software for your team to learn
- Expert review of assumptions, outputs, and interpretation
NMA can be delivered as part of a full evidence synthesis workflow
Network meta-analysis depends on the quality and structure of the underlying evidence base. Synthesa can support the full pathway from literature search and screening through extraction and comparative synthesis.
Full workflow support can include:
- Research question and PICO alignment
- Search strategy review
- Abstract screening
- Full-text review support
- Data extraction
- Evidence network mapping
- Feasibility assessment
- Statistical modelling
- Publication-ready figures and tables
- Structured interpretation
Or bring us your dataset
If your team has already completed the review and extraction, Synthesa can step in at the analysis stage.
Frenquently Asked Questions
Can Synthesa assess whether network meta-analysis is feasible?
Yes. Synthesa can review the intervention network, outcome availability, population comparability, study designs, and dataset structure before recommending whether NMA is appropriate.
Do you support Bayesian network meta-analysis?
Yes. Synthesa supports Bayesian and frequentist network meta-analysis, including random-effects models where appropriate.
Can you work with an existing extracted dataset?
Yes. If you already have extracted data, Synthesa can assess network connectivity, review data structure, advise on modelling choices, and conduct the analysis where feasible.
Can you produce publication-ready outputs?
Yes. Outputs can include network diagrams, comparative estimates, league tables where appropriate, ranking summaries where appropriate, methods text, interpretation, and publication-ready figures.
Can Synthesa support CRO or medcomms client projects?
Yes. Synthesa can act as a specialist NMA partner for CROs and medcomms agencies that need advanced synthesis capability for client work.
Do we need to use any software?
No. Synthesa delivers NMA as a service. Your team receives the outputs without needing to learn or operate statistical software or AI tools.
Need to compare multiple interventions, devices, or procedures?
Send us your research question, included studies, extracted dataset, or project context. We can assess whether network meta-analysis is feasible and recommend the right synthesis approach.