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There are several generalized linear mixed models to combine direct and indirect evidence on several diagnostic tests from related but independent diagnostic studies simultaneously also known as network meta-analysis. The popularity of these models is due to the attractive features of the normal distribution and the availability of statistical software to obtain parameter estimates. However, modeling the latent sensitivity and specificity using the normal distribution after transformation is neither natural nor computationally convenient.

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Procedures combining and summarising direct and indirect evidence from independent studies assessing the diagnostic accuracy of different tests for the same disease are referred to network meta-analysis. Network meta-analysis provides a unified inference framework and uses the data more efficiently. Nonetheless, handling the inherent correlation between sensitivity and specificity continues to be a statistical challenge.

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Article Synopsis
  • Concerns about public health related to nuclear activities date back to the 1980s, with most research focusing on childhood leukemia, while thyroid cancer is also a potential health issue due to exposure to radioactive iodine isotopes from these sites.
  • This ecological study aimed to assess whether there is a higher incidence of thyroid cancer among residents living near nuclear sites, using statistical methods to analyze cancer rates within a defined proximity area of 20 km around the plants.
  • The findings indicated no significant increase in thyroid cancer rates near major plants like Doel and Tihange, but showed higher-than-expected rates around the Mol-Dessel and Fleurus sites, suggesting a need for further investigation into localized nuclear activities and their health impacts.
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