Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications
Epidemiology
Sequence Analysis, RNA
Gene Expression Profiling
610
Breast Neoplasms
Genomics
Middle Aged
Immunohistochemistry
name=SDG 3 - Good Health and Well-being
3. Good health
Gene Expression Regulation, Neoplastic
03 medical and health sciences
Age Distribution
0302 clinical medicine
Biomarkers, Tumor
/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Humans
Female
/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being
Age of Onset
Aged
DOI:
10.1007/s10549-019-05442-2
Publication Date:
2019-09-18T17:05:41Z
AUTHORS (14)
ABSTRACT
Female breast cancer demonstrates bimodal age frequency distribution patterns at diagnosis, interpretable as two main etiologic subtypes or groupings of tumors with shared risk factors. While RNA-based methods including PAM50 have identified well-established clinical subtypes, diagnosis a proxy for subtype are not established molecular and genomic tumor classifications.We evaluated smoothed distributions Carolina Breast Cancer Study cases within immunohistochemistry-based expression categories. Akaike information criterion (AIC) values compared the fit single density versus two-component mixture models. Two-component models estimated proportion early-onset late-onset categories by ER (n = 2860), ESR1 1965). findings were validated using pooled publicly available data 8103).Breast cancers best characterized incidence peaks near 45 65 years, regardless characteristics. However, proportional composition varied Higher ER-protein ESR1-RNA showed greater late age-at-onset. Similarly, shifting age-at-onset distribution, most pronounced found in Basal-like Luminal A, respectively.Bimodal was detected Study, similar to national registry data. Our support fundamental age-defined that persist across Better criteria distinguish could improve understanding etiology contribute prevention efforts.
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