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dc.contributor.authorNg, Shu-Kay
dc.date.accessioned2017-05-03T15:26:14Z
dc.date.available2017-05-03T15:26:14Z
dc.date.issued2010
dc.date.modified2010-09-21T06:56:10Z
dc.identifier.issn1012-9367
dc.identifier.urihttp://hdl.handle.net/10072/33146
dc.description.abstractStudies on genetic profilingdemonstrate its potential utility for classifying tumours, leading to a 'genetic-staging' system for predicting disease outcomes. A precise prediction of individual disease outcome is important to identify patients who have a high risk of disease recurrence, and to tailor treatments to the individual patient. Genes, however, are not the sole determinants of disease outcomes. Non-genetic factors have roles in many stages of tumourigenesis, and the simultaneous use of genetic-staging and clinical risk factors may therefore improve the prediction of disease ouctome. In this paper, we aim to quantify the prognostic value of genetic-staging from gene expressions by using mixture model-based clustering methods. We also investigate via the use of logistric regression whether a more accurate prediction of disease outcome can be obtained by using geneticstaging in conjunction with clinical risk factors. The proposed method is illustrated using a real example of breast cancer data. It shows that genetic-staging provides significant additional prognostic information when it is obtained by applying sophisticated modelbsed clustering method for the identification of marker-genes that are relevant to predict disease outcomes.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent303584 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherPakistan Journal of Statistics
dc.publisher.placePakistan
dc.publisher.urihttp://www.pakjs.com/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom171
dc.relation.ispartofpageto185
dc.relation.ispartofissue1
dc.relation.ispartofjournalPakistan Journal of Statistics
dc.relation.ispartofvolume26
dc.rights.retentionY
dc.subject.fieldofresearchStatistics
dc.subject.fieldofresearchcode4905
dc.titleTo predict disease outcome: clinical risk factors plus genetic-staging for cancer
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Health, School of Medicine
gro.rights.copyright© 2010 Pakistan Journal of Statistics. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
gro.date.issued2010
gro.hasfulltextFull Text
gro.griffith.authorNg, Shu Kay Angus


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