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dc.contributor.authorRenehan, Andrew G
dc.contributor.authorLuebeck, G
dc.date.accessioned2009-06-19T13:52:17Z
dc.date.available2009-06-19T13:52:17Z
dc.date.issued2007-06
dc.identifier.citationColorectal cancer prevention: choosing the most effective population strategy using bio-mathematical approaches. 2007, 9 (5):393-6 Colorectal Disen
dc.identifier.issn1462-8910
dc.identifier.pmid17477853
dc.identifier.doi10.1111/j.1463-1318.2007.01214.x
dc.identifier.urihttp://hdl.handle.net/10541/71019
dc.description.abstractColorectal cancer is a leading cause of cancer-related death globally, though in theory at least, it is eminently preventable in many cases. Preventive strategies are either primary or secondary, but for population strategists, choosing the 'best' approach is not straightforward. Here, we summarize the potential role of bio-mathematical modelling, specifically focusing on a model that combines known details of crypt cell kinetics with stochastic models of cell birth and death processes. Examples are discussed of the potential population effects of an agent that modulates cell kinetics, such as aspirin, vs one that merely reduces mutational rates.
dc.language.isoenen
dc.subjectColorectal Canceren
dc.subject.meshAdenoma
dc.subject.meshAspirin
dc.subject.meshColorectal Neoplasms
dc.subject.meshFemale
dc.subject.meshFood Habits
dc.subject.meshHumans
dc.subject.meshMale
dc.subject.meshMass Screening
dc.subject.meshModels, Biological
dc.subject.meshRandomized Controlled Trials as Topic
dc.subject.meshSEER Program
dc.titleColorectal cancer prevention: choosing the most effective population strategy using bio-mathematical approaches.en
dc.typeArticleen
dc.contributor.departmentDepartment of Surgery, Academic Division of Cancer Studies, Christie Hospital NHS Trust, Manchester M20 4BX, UK. arenehan@picr.man.ac.uken
dc.identifier.journalColorectal Diseaseen
html.description.abstractColorectal cancer is a leading cause of cancer-related death globally, though in theory at least, it is eminently preventable in many cases. Preventive strategies are either primary or secondary, but for population strategists, choosing the 'best' approach is not straightforward. Here, we summarize the potential role of bio-mathematical modelling, specifically focusing on a model that combines known details of crypt cell kinetics with stochastic models of cell birth and death processes. Examples are discussed of the potential population effects of an agent that modulates cell kinetics, such as aspirin, vs one that merely reduces mutational rates.


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