Abstract
Individual-level data from the Florida Cancer Data System (1981–2007) were analyzed to explore temporal trends of prostate cancer late-stage diagnosis, and how they vary based on race, income and age. Annual census-tract rates were computed for two races (white and black) and two age categories (40–65, >65) before being aggregated according to census tract median household incomes. Joinpoint regression and a new disparity statistic were applied to model temporal trends and detect potential racial and socio-economic differences. Multi-dimensional scaling was used as an innovative way to visualize similarities among temporal trends in a 2-D space. Analysis of time-series indicated that late-stage diagnosis was generally more prevalent among blacks, for age category 40–64 compared to older patients covered by Medicare, and among classes of lower socio-economic status. Joinpoint regression also showed that the rate of decline in late-stage diagnosis was similar among older patients. For younger patients, the decline occurred at a faster pace for blacks with rates becoming similar to whites in the late 1990s, in particular for higher incomes. Both races displayed distinct spatial patterns with higher rates of late-stage diagnosis in the Florida Panhandle for whites whereas high rates clustered in South-eastern Florida for blacks.
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