Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics

What is known?

Cancer atlases often provide estimates of cancer incidence, mortality or survival across small areas of a region or country.

What is new?

The usefulness of a multivariate Bayesian meta-analysis model, which can model multiple cancers jointly using summary measures without requiring access to the unit record data, was demonstrated using published results from the Australian Cancer Atlas.

There was substantial correlation between the geographical patterns of cancer incidence for different cancer types.

The level of correlation varied depending on the level of geographical remoteness.

What does this mean?

Publicly available spatially smoothed disease estimates can be used to explore additional research questions by modelling multiple cancer types jointly.

These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements.

Contact: Peter Baade

Reference: Jahan F, Duncan EW, Cramb SM, Baade PD, Mengersen KL. Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics. International Journal of Health Geographics. 2020; 19(1):42.

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