Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/75704
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dc.contributor.authorDonsuk Pongnikornen_US
dc.contributor.authorPhichayut Phinyoen_US
dc.contributor.authorJayanton Patumanonden_US
dc.contributor.authorKarnchana Daopraserten_US
dc.contributor.authorPachaya Phothongen_US
dc.contributor.authorBoonying Siribumrungwongen_US
dc.date.accessioned2022-10-16T07:02:01Z-
dc.date.available2022-10-16T07:02:01Z-
dc.date.issued2021-04-01en_US
dc.identifier.issn20726694en_US
dc.identifier.other2-s2.0-85103092670en_US
dc.identifier.other10.3390/cancers13071567en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85103092670&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/75704-
dc.description.abstractPrognostic models for breast cancer developed from Western countries performed less accurately in the Asian population. We aimed to develop a survival prediction model for overall survival (OS) and disease‐free survival (DFS) for Thai patients with breast cancer. We conducted a prognostic model research using a multicenter hospital‐based cancer clinical registry from the Network of National Cancer Institutes of Thailand. All women diagnosed with breast cancer who un-derwent surgery between 1 January 2010 and 31 December 2011 were included in the analysis. A flexible parametric survival model was used for developing the prognostic model for OS and DFS prediction. During the study period, 2021 patients were included. Of these, 1386 patients with 590 events were available for a complete‐case analysis. The newly derived individualized prediction of breast cancer survival or the IPBS model consists of twelve routinely available predictors. The C‐ statistics from the OS and the DFS model were 0.72 and 0.70, respectively. The model showed good calibration for the prediction of five‐year OS and DFS. The IPBS model provides good performance for the prediction of OS and PFS for breast cancer patients. A further external validation study is required before clinical implementation.en_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectMedicineen_US
dc.titleIndividualized prediction of breast cancer survival using flexible parametric survival modeling: Analysis of a hospital‐based national clinical cancer registryen_US
dc.typeJournalen_US
article.title.sourcetitleCancersen_US
article.volume13en_US
article.stream.affiliationsThammasat Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsLampang Cancer Hospitalen_US
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