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Multistage carcinogenesis and the incidence of thyroid cancer in the US by sex, race, stage and histology

Overview of attention for article published in BMC Public Health, August 2015
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Title
Multistage carcinogenesis and the incidence of thyroid cancer in the US by sex, race, stage and histology
Published in
BMC Public Health, August 2015
DOI 10.1186/s12889-015-2108-4
Pubmed ID
Authors

Rafael Meza, Joanne T. Chang

Abstract

Thyroid cancer has the fastest growing incidence in the US. However, the underlying causes are still under debate. We analyzed thyroid cancer incidence in the SEER-9 registry from 1973-2010 using multistage carcinogenesis and age-period-cohort models. Multistage models were used to investigate differences in initiation, promotion and malignant conversion rates of thyroid tumors by sex, race, stage, and histology. Models were adjusted for period and cohort trends to investigate the contributions of each factor, and determine whether birth- or diagnosis-year better correlate with observed incidence patterns. Significant increases in thyroid cancer incidence by period or calendar-year were found for all sex, race, stage and histology combinations, particularly for localized cases (a 3- and 4-fold increase from 1973-2010 for females and males, respectively). Multistage analyses suggest that the 3-fold higher incidence in women could be explained by 1.5-fold higher initiation and promotion rates. Analyses by race suggest that the lower incidence in blacks can be attributed to lower promotion rates versus whites. Analysis by histology showed considerable decreases in follicular cancer incidence by birth-cohort since the early 1900s. Multistage modeling suggests that variations in thyroid cancer initiation and promotion can explain the observed differences in incidence by sex, race and histology. The consistent increases in incidence by calendar-year for all sex-race-histology-stage combinations suggest that the rise may be predominantly due to more intensive screening-diagnostics, although an environmental factor may be also at play. Our analyses constitute a first step towards the development of thyroid cancer natural history models.

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Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 17%
Student > Ph. D. Student 7 17%
Student > Master 6 14%
Professor > Associate Professor 5 12%
Student > Doctoral Student 4 10%
Other 4 10%
Unknown 9 21%
Readers by discipline Count As %
Medicine and Dentistry 13 31%
Agricultural and Biological Sciences 3 7%
Nursing and Health Professions 3 7%
Biochemistry, Genetics and Molecular Biology 2 5%
Environmental Science 1 2%
Other 6 14%
Unknown 14 33%