Improved Statistical Modeling of Tumor Growth and Treatment Effect in Preclinical Animal Studies with Highly Heterogeneous Responses In Vivo

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dc.contributor.authorLaajala TD
dc.contributor.authorCorander J
dc.contributor.authorSaarinen NM
dc.contributor.authorMakela K
dc.contributor.authorSavolainen S
dc.contributor.authorSuominen MI
dc.contributor.authorAlhoniemi E
dc.contributor.authorMakela S
dc.contributor.authorPoutanen M
dc.contributor.authorAittokallio T
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=fysiologia|en=Physiology|
dc.contributor.organizationfi=matemaattis-luonnontieteellinen tiedekunta|en=Faculty of Science|
dc.contributor.organizationfi=ravitsemus- ja ruokatutkimuskeskus|en=Nutrition and Food Research Center (NuFo)|
dc.contributor.organizationfi=tietotekniikan laitos|en=Department of Computing|
dc.contributor.organization-code1.2.246.10.2458963.20.12007811941
dc.contributor.organization-code1.2.246.10.2458963.20.36798383026
dc.contributor.organization-code1.2.246.10.2458963.20.77381963311
dc.contributor.organization-code1.2.246.10.2458963.20.85312822902
dc.contributor.organization-code2607100
dc.converis.publication-id1537350
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/1537350
dc.date.accessioned2022-10-28T14:26:26Z
dc.date.available2022-10-28T14:26:26Z
dc.description.abstract<p> Conclusions: In general, the modeling framework enables identification of such biologically significant differences in tumor growth profiles that would have gone undetected or had required considerably higher number of animals when using traditional statistical methods. Clin Cancer Res; 18(16); 4385-96. (C) 2012 AACR.</p>
dc.format.pagerange4385
dc.format.pagerange4396
dc.identifier.jour-issn1078-0432
dc.identifier.olddbid188278
dc.identifier.oldhandle10024/171372
dc.identifier.urihttps://www.utupub.fi/handle/11111/51492
dc.identifier.urnURN:NBN:fi-fe2021042714162
dc.language.isoen
dc.okm.affiliatedauthorMäkelä, Sari
dc.okm.affiliatedauthorSaarinen-Aaltonen, Niina
dc.okm.affiliatedauthorPoutanen, Matti
dc.okm.affiliatedauthorAittokallio, Tero
dc.okm.affiliatedauthorLaajala, Daniel
dc.okm.affiliatedauthorAlhoniemi, Esa
dc.okm.discipline112 Statistics and probabilityen_GB
dc.okm.discipline112 Tilastotiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherAMER ASSOC CANCER RESEARCH
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.doi10.1158/1078-0432.CCR-11-3215
dc.relation.ispartofjournalClinical Cancer Research
dc.relation.issue16
dc.relation.volume18
dc.source.identifierhttps://www.utupub.fi/handle/10024/171372
dc.titleImproved Statistical Modeling of Tumor Growth and Treatment Effect in Preclinical Animal Studies with Highly Heterogeneous Responses In Vivo
dc.year.issued2012

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