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dc.contributor.authorPatumrat Sripanen_US
dc.contributor.authorHutcha Sriplungen_US
dc.contributor.authorDonsuk Pongnikornen_US
dc.contributor.authorShama Viranien_US
dc.contributor.authorSurichai Bilheemen_US
dc.contributor.authorUdomlak Chaisaengkhaumen_US
dc.contributor.authorPuttachart Maneesaien_US
dc.contributor.authorNarate Waisrien_US
dc.contributor.authorChirapong Hanpragopsuken_US
dc.contributor.authorPanrada Tansirien_US
dc.contributor.authorVarunee Khamsanen_US
dc.contributor.authorMalisa Poungsombaten_US
dc.contributor.authorAumnart Mawooten_US
dc.contributor.authorImjai Chitapanaruxen_US
dc.date.accessioned2018-09-05T03:30:00Z-
dc.date.available2018-09-05T03:30:00Z-
dc.date.issued2017-05-01en_US
dc.identifier.issn2476762Xen_US
dc.identifier.issn15137368en_US
dc.identifier.other2-s2.0-85020388049en_US
dc.identifier.other10.22034/APJCP.2017.18.5.1411en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020388049&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/56766-
dc.description.abstractObjectives: This study was conducted to determine incidence trends of female breast cancer according to age groups and to predict future change in Chiang Mai women through 2028. Method: Data were collected from all hospitals in Chiang Mai in northern Thailand, from 1989 through 2013, and used to investigate effects of age, year of diagnosis (period) and year of birth (cohort) on female breast cancer incidences using an age-period-cohort model. This model features geometric cut trends to predict change by young (< 40 years), middle-aged (40-59) and elderly (≥ 60) age groups. Result: Of 5, 417 female breast cancer patients with a median age of 50 years (interquartile range: 43 to 59 years), 15%, 61% and 24% were young, middle-aged and elderly, respectively. Seventy nine percent of cancer cases in this study were detected at advanced stage. The trend in stage classification showed an increase in percentage of early stage and a decrease in metastatic cancers. Linear trends for cohort and period were not found in young females but were observed in middle-aged and elderly groups. Age-standardized rates (ASR) can be expected to remain stable around 6.8 per 100,000 women-years in young females. In the other age groups, the ASR trends were calculated to increase and reach peaks in 2024 of 120.2 and 138.2 per 100,000 women-years, respectively. Conclusion: Cohort effects or generation-specific effects, such as life style factors and the year of diagnosis (period) might have impacted on increased incidence in women aged over 40 years but not those under 40 years. A budget should be provided for treatment facilities and strategies to detect early stage cancers. The cost effectiveness of screening measures i.e. mammographic screening may need to be reconsidered for women age over 40 years.en_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.subjectMedicineen_US
dc.titleTrends in female breast cancer by age group in the Chiang Mai populationen_US
dc.typeJournalen_US
article.title.sourcetitleAsian Pacific Journal of Cancer Preventionen_US
article.volume18en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsPrince of Songkla Universityen_US
article.stream.affiliationsLampang Cancer Hospitalen_US
article.stream.affiliationsUniversity of Michigan, Ann Arboren_US
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