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dc.contributor.authorVänskä, Simopekka
dc.contributor.authorBogaards, Johannes A
dc.contributor.authorAuranen, Kari
dc.contributor.authorLehtinen, Matti
dc.contributor.authorBerkhof, Johannes
dc.date.accessioned2019-02-18T07:45:52Z
dc.date.available2019-02-18T07:45:52Z
dc.date.issued2019-01-16
dc.identifier.issn1879-3134
dc.identifier.pmid30659822
dc.identifier.doi10.1016/j.mbs.2019.01.006
dc.identifier.urihttp://hdl.handle.net/10029/622733
dc.description.abstractCervical cancer arises differentially from infections with up to 14 high-risk human papillomavirus (HPV) types, making model-based evaluations of cervical cancer screening strategies computationally heavy and structurally complex. Thus, with the high number of HPV types, microsimulation is typically used to investigate cervical cancer screening strategies. We developed a feasible deterministic model that integrates varying natural history of cervical cancer by the different high-risk HPV types with compressed mixture representations of the screened population, allowing for fast computation of screening interventions. To evaluate the method, we built a corresponding microsimulation model. The outcomes of the deterministic model were stable over different levels of compression and agreed with the microsimulation model for all disease states, screening outcomes, and levels of cancer incidence. The compression reduced the computation time more than 1000 fold when compared to microsimulation in a cohort of 1 million women. The compressed mixture representations enable the assessment of uncertainties surrounding the natural history of cervical cancer and screening decisions in a computationally undemanding way.en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen
dc.subjectCervical canceren_US
dc.subjectDeterministic modelen_US
dc.subjectDisease progressionen_US
dc.subjectHuman papillomavirusen_US
dc.subjectMultiple typesen_US
dc.subjectScreeningen_US
dc.titleFast approximate computation of cervical cancer screening outcomes by a deterministic multiple-type HPV progression model.en_US
dc.typeArticleen_US
dc.identifier.journalMath Biosci 2019; 309:92-106en_US
dc.source.journaltitleMathematical biosciences


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