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Comparative Study
Journal Article
Adult glioma incidence trends in the United States, 1977-2000.
Cancer 2004 November 16
BACKGROUND: Several authors have reported an increase in the incidence of brain tumors, especially among the elderly. A more complete understanding of adult glioma incidence trends might provide indications of risk factors for gliomas and contribute to the search for improved therapies.
METHODS: The authors used the Surveillance, Epidemiology, and End Results (SEER) registry public use data tapes, which included data on patients with cancer diagnosed between 1973 and 2000. For 3 histologies as well as for 12 histology categories combined, the authors used Poisson regression to model incidence as a function of year of diagnosis, age at diagnosis, race (white or African American), and gender. They used cubic splines to fit age at diagnosis and year of diagnosis and tested for all pair-wise interactions.
RESULTS: The interaction between year of diagnosis and age at diagnosis was significant in all four groups modeled. In glioblastoma, there was also a significant interaction between gender and age at diagnosis. In anaplastic astrocytoma, there was a significant interaction between gender and year of diagnosis. In oligodendroglioma, there was a significant interaction between race and gender. In the 12 histology categories combined, there was a significant interaction between gender and age at diagnosis.
CONCLUSIONS: The results in the current study were consistent with other published reports that showed an increase in the incidence of brain tumors using SEER data. Although others have observed increasing incidence trends among the elderly, the authors formally tested and found a statistically significant interaction between age at diagnosis and year of diagnosis.
METHODS: The authors used the Surveillance, Epidemiology, and End Results (SEER) registry public use data tapes, which included data on patients with cancer diagnosed between 1973 and 2000. For 3 histologies as well as for 12 histology categories combined, the authors used Poisson regression to model incidence as a function of year of diagnosis, age at diagnosis, race (white or African American), and gender. They used cubic splines to fit age at diagnosis and year of diagnosis and tested for all pair-wise interactions.
RESULTS: The interaction between year of diagnosis and age at diagnosis was significant in all four groups modeled. In glioblastoma, there was also a significant interaction between gender and age at diagnosis. In anaplastic astrocytoma, there was a significant interaction between gender and year of diagnosis. In oligodendroglioma, there was a significant interaction between race and gender. In the 12 histology categories combined, there was a significant interaction between gender and age at diagnosis.
CONCLUSIONS: The results in the current study were consistent with other published reports that showed an increase in the incidence of brain tumors using SEER data. Although others have observed increasing incidence trends among the elderly, the authors formally tested and found a statistically significant interaction between age at diagnosis and year of diagnosis.
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