A Prostate Cancer Composite Score to Identify High Burden Neighborhoods.

This study presents a novel geo-based metric to identify neighborhoods with high burdens of prostate cancer, and compares this metric to other methods to prioritize neighborhoods for prostate cancer interventions. We geocoded prostate cancer patient data (n = 10,750) from the Pennsylvania cancer registry from 2005 to 2014 by Philadelphia census tract (CT) to create standardized incidence ratios (SIRs), mortality ratios (SMRs), and mean prostate cancer aggressiveness. We created a prostate cancer composite (PCa composite) variable to describe CTs by mean-centering and standard deviation-scaling the SMR, SIR, and mean aggressiveness variables and summing them. We mapped CTs with the 25 highest PCa composite scores and compared these neighborhoods to CTs with the 25 highest percent African American residents and the 25 lowest median household incomes. The mean PCa composite score among the 25 highest CTs was 4.65. Only seven CTs in Philadelphia had both one of the highest PCa composite scores and the highest percent African American residents. Only five CTs had both the highest PCa composites and the lowest median incomes. Mean PCa composite scores among CTs with the highest percent African American residents and lowest median incomes were 2.08 and 1.19, respectively. The PCa composite score is an accurate metric for prioritizing neighborhoods based on burden. If neighborhoods were prioritized based on percent African American or median income, priority neighborhoods would have been very different and not based on PCa burden. These methods can be utilized by public health decision-makers when tasked to prioritize and select neighborhoods for cancer interventions. [ABSTRACT FROM AUTHOR]