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dc.contributor.authorCook, James Phillip
dc.date.accessioned2015-08-26T12:42:35Z
dc.date.available2015-08-26T12:42:35Z
dc.date.issued2014-07-01
dc.identifier.citationCook, J,P. 2014. Investigating Clustering in Trisomy 18 and Trisomy 13. Queen Mary University of Londonen_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/8316
dc.descriptionPhDen_US
dc.description.abstractTrisomies 18 and 13 are rare genetic conditions (occurring around 1 in 6,000 and 10,000 newborns respectively) which are caused by an extra copy of either chromosome 18 or 13, similar to trisomy 21 (Down syndrome). The only known risk factor for these syndromes is maternal age, however previous cluster analyses have linked trisomy risk to a number of alternate factors, including radiation exposure and infection. Cases of trisomies 18 and 13 from the National Down Syndrome Cytogenetic Register (NDSCR) were scanned for temporal and spatial clusters throughout England and Wales between 2004 and 2010. No temporal clusters were detected, however there were multiple significant spatial clusters detected for both trisomies in London. These clusters were likely caused by advanced maternal age in the region, and it is also possible that regional differences in gestational age at the time of prenatal screening could have contributed to these clusters. In order to account for maternal age and gestational age at diagnosis, a novel method was developed in R to directly weight cases based on these factors. Applying weights to cases directly allowed both factors to be simultaneously accounted for by multiplying weights together. This method was evaluated using synthetic data and compared with an alternate method in the widely used program SaTScan. Both programs returned similar results when the weighting method was mild, but when extreme weights were applied at random significant clusters were observed in SaTScan but not in R. The NDSCR data was weighted and then rescanned for spatial clusters in both programs. No evidence of clustering was detected using the novel method, while SaTScan returned multiple highly significant clusters. These findings, combined with those obtained using the synthetic data, indicate that the novel method produces more reliable results than SaTScan when extreme adjustment is applied.en_US
dc.language.isoenen_US
dc.publisherQueen Mary University of Londonen_US
dc.subjectgestational ageen_US
dc.subjectDown Syndromeen_US
dc.titleInvestigating Clustering in Trisomy 18 and Trisomy 13en_US
dc.typeThesisen_US
dc.rights.holderThe 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


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