dc.contributor.author | Cavadino, Alana | |
dc.date.accessioned | 2018-02-28T12:29:58Z | |
dc.date.available | 2018-02-28T12:29:58Z | |
dc.date.issued | 05/02/2018 | |
dc.date.submitted | 2018-02-27T12:55:22.198Z | |
dc.identifier.citation | Cavadinoi, A. 2018. Hierarchical models in the analysis of trends in prevalence of congenital anomalies and risks associated with first trimester medications. Queen Mary University of London | en_US |
dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/33946 | |
dc.description | PhD | en_US |
dc.description.abstract | Abstract
Background
Early identification of risk factors, in particular first trimester teratogenic medications, for
congenital anomalies (CAs) is essential. Despite similarities between different CAs and
between different medications, current surveillance methods in Europe examine each CA
and each medication separately. This thesis aims to investigate whether the use of
hierarchical statistical methods combining information in groups can improve CA
surveillance methods.
Methods
EUROCAT is a European network of population-based CA registries, with EUROmediCAT
comprising those registries with additional information on medication use in pregnancy.
Trends in CAs from 2003-2012 in 18 EUROCAT registries (n=81,147) were analysed using
Poisson regression models considering each CA separately and using hierarchical models
combining related subgroups. First trimester medication exposures from 1995-2011 in 13
EUROmediCAT registries (n=15,058) were analysed. Firstly, groupings of medications and/or
CAs were considered when determining the statistical significance of each medication-CA
combination, using False Discovery Rate (FDR) procedures to adjust for multiple testing.
Secondly, Bayesian hierarchical models were applied to directly model the group effects.
The Australian classification system for prescribing medicines in pregnancy was used to
independently identify “high risk” medications. The number of “high risk” medications
identified by the FDR methods and Bayesian models were compared.
Results
For analysis of trends, grouping EUROCAT CA subgroups using hierarchical models did not
provide additional information over that obtained from independent analyses of each
subgroup. The double FDR method grouping medications by ATC3 level codes performed
better than other FDR methods. Use of Bayesian hierarchical models did not produce
enough of an improvement to justify the increased effort of implementing such models. | en_US |
dc.description.sponsorship | This work was supported by the Medical Research Council [Award reference: 1504916] and
the Wolfson Institute of Preventive Medicine. | |
dc.language.iso | en | en_US |
dc.publisher | Queen Mary University of London | |
dc.subject | Engineering | en_US |
dc.subject | Solidification technology | en_US |
dc.subject | Carbonation | en_US |
dc.subject | Waste materials disposal | en_US |
dc.title | Hierarchical models in the analysis of trends in prevalence of congenital anomalies and risks associated with first trimester medications. | en_US |
dc.type | Thesis | en_US |
dc.rights.holder | The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author | |