What is it?
GeMTC is a web application used for combining and summarising the results of individual trials (evidence synthesis). It uses advanced evidence synthesis methods, such as network meta-analysis and network meta-regression.
GeMTC uses Bayesian methods; those who prefer to use frequentist methods may wish to consider using EPPI-Reviewer.
Why is it useful?
- State-of-the-art methods for evidence synthesis of aggregated data: averaged estimates of the differences between treatments as listed in the page describing the ADDIS software.
- Enables analysis of different forms of data: data on individual arms, comparative data or a combination of both types of data can be analysed. Data are provided as CSV (comma-separated values) files. See the GeMTC manual for details.
- User-friendly interface to complex analytical methods: enabling broader access to these methods.
- Encourages best practice: helps analysts adhere to best practice guidelines.
When is it useful?
- Use GeMTC if you have data that cannot be analysed in ADDIS, or you are not interested in using the data management, data sharing, and benefit-risk analysis functionality in ADDIS.
- If greater flexibility is needed in defining the analyses, the gemtc package for the R statistical software can be used instead of the user interface.
What are the limitations of GeMTC?
- Some analytical techniques are not supported by GeMTC: analysis of individual participant data (IPD) (as used by GetReal – see Methods for Network Meta-Analysis using Individual Participant Data: a case study in depression and Incorporating Non-Randomised Studies in NMA of RCTs: a case study in schizophrenia) is not directly supported by GeMTC. However, it is possible to use GeMTC in the second stage of a two-stage approach to analysing IPD. Each trial needs to be analysed using appropriate statistical methods and the summary estimates can then be meta-analysed using GeMTC (see the GetReal review of methods using IPD for meta-analysis by Debray et al., 2016). Disadvantages of the two-stage method include reduced statistical power and the risk of ecological bias.
- GeMTC cannot analyse datasets with missing values.
- Interpretation of methods requires a high level of understanding.
- As with ADDIS, data entered into GeMTC are public (see ADDIS).
Gert van Valkenhoef, University Medical Center Groningen