GeMTC for evidence synthesis

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.

It is powered using an R statistical software package called gemtc, which uses methods recommended by the NICE decision support unit (see TSD 2, TSD 3 and TSD 4) and other methodologists.

GeMTC can be used alone (see the gemtc website), or through the ADDIS data management and analysis tool.

GeMTC uses Bayesian methods; those who prefer to use frequentist methods may wish to consider using EPPI-Reviewer.

GeMTC software

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 here and here) 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 here).

Key contributor

Gert van Valkenhoef, University Medical Center Groningen