ASO Visual Abstract: The Influence of Disparities on Prostate Cancer at Diagnosis in the Charlotte Metropolitan Area

Introduction Prostate cancer (PCa) is the most diagnosed noncutaneous malignancy and second leading-cause of cancer death in men, yet screening is decreasing. As PCa screening has become controversial, socioeconomic disparities in PCa diagnosis and outcomes widen. This study was designed to determine the current disparities influencing PCa diagnosis in Charlotte, NC. Methods The Levine Cancer Institute database was queried for patients with PCa, living in metropolitan Charlotte. Socioeconomic status (SES) was determined by the Area Deprivation Index (ADI); higher ADI indicated lower SES. Patients were compared by their National Comprehensive Cancer Network risk stratification. Artificial intelligence predictive models were trained and heatmaps were created, demonstrating the geographic and socioeconomic disparities in late-stage PCa. Results Of the 802 patients assessed, 202 (25.2%) with high-risk PCa at diagnosis were compared with 198 (24.7%) with low-risk PCa. High-risk PCa patients were older (69.8 +/- 9.0 vs. 64.0 +/- 7.9 years; p < 0.001) with lower SES (ADI block: 98.4 +/- 20.9 vs. 92.1 +/- 19.8; p = 0.004) and more commonly African-American (White: 66.2% vs. 78.3%, African-American: 31.3% vs. 20.7%; p = 0.009). On regression, ADI block was an independent predictor (odds ratio [OR] = 1.013, 95% confidence interval [CI] 1.002-1.024; p = 0.024) of high-risk PCa at diagnosis, whereas race was not (OR = 1.312, 95% CI 0.782-2.201; p = 0.848). A separate regression demonstrated higher ADI (OR = 1.016, 95% CI 1.004-1.027; p = 0.006) and older age (OR = 1.083, 95% CI 1.054-1.114; p < 0.001) were independent predictors for high-risk PCa. Findings, depicted in heatmaps, demonstrated the geographic locations where men with PCa were predicted to have high-risk disease based on their age and SES. Conclusions Socioeconomic status was more closely associated with high-risk PCa at diagnosis than race. Although, of any variable, age was most predictive. The heatmaps identified areas that would benefit from increased awareness, education, and screening to facilitate an earlier PCa diagnosis.