ExoDx prostate test as a predictor of outcomes of high-grade prostate cancer - an interim analysis.

BACKGROUND: Patient outcomes were assessed based on a pre-biopsy ExoDx Prostate (EPI) score at 2.5 years of the 5-year follow-up of ongoing prostate biopsy Decision Impact Trial of the ExoDx Prostate (IntelliScore). METHODS: Prospective, blinded, randomized, multisite clinical utility study was conducted from June 2017 to May 2018 (NCT03235687). Urine samples were collected from 1049 men (≥50 years old) with a PSA 2-10 ng/mL being considered for a prostate biopsy. Patients were randomized to EPI vs. standard of care (SOC). All had an EPI test, but only EPI arm received results during biopsy decision process. Clinical outcomes, time to biopsy and pathology were assessed among low (<15.6) or high (≥15.6) EPI scores. RESULTS: At 2.5 years, 833 patients had follow-up data. In the EPI arm, biopsy rates remained lower for low-risk EPI scores than high-risk EPI scores (44.6% vs 79.0%, p < 0.001), whereas biopsy rates were identical in SOC arm regardless of EPI score (59.6% vs 58.8%, p = 0.99). Also in the EPI arm, the average time from EPI testing to first biopsy was longer for low-risk EPI scores compared to high-risk EPI scores (216 vs. 69 days; p < 0.001). Similarly, the time to first biopsy was longer with EPI low-risk scores in EPI arm compared to EPI low-risk scores in SOC arm (216 vs 80 days; p < 0.001). At 2.5 years, patients with low-risk EPI scores from both arms had less HGPC than high-risk EPI score patients (7.9% vs 26.8%, p < 0.001) and the EPI arm found 21.8% more HGPC than the SOC arm. CONCLUSIONS: This follow-up analysis captures subsequent biopsy outcomes and demonstrates that men receiving EPI low-risk scores (<15.6) significantly defer the time to first biopsy and remain at a very low pathologic risk by 2.5-years after the initial study. The EPI test risk stratification identified low-risk patients that were not found with the SOC.

Rural and racial disparities in colorectal cancer incidence and mortality in South Carolina, 1996 - 2016.

PURPOSE: Colorectal cancer (CRC) is the third leading cause of cancer mortality among men and women in the United States and South Carolina (SC). Since SC has one of the highest proportions of Black (27.9%) and rural residents (33.7%), the purpose of this investigation was to describe the burden of CRC on racial disparities in rural populations. METHODS: Count data from 2012 to 2016 were obtained from the state central cancer registry using an online data retrieval system. Rural-urban status was determined using Urban Influence Codes (1-2 = urban; 3-12 = rural). Chi-square tests were calculated to examine differences in CRC stage by rurality and race. Annual percent change and annual average percent change (AAPC) were calculated to examine trends in incidence and mortality rates across rural-urban and racial groups between 1996 and 2016. RESULTS: Areas with high mortality-to-incidence ratios tended to be in rural counties. Furthermore, rural residents had higher proportions of distant stage CRC compared to urban residents, and Black populations had higher proportions of distant stage CRC compared to White populations (22.7% vs. 26.3% and 29.3% vs. 23.7%, respectively; P value < 0.05). From 1996 to 2016, Black and White urban-dwelling residents experienced a significant decline in incidence. Urban White, urban Black, and rural White populations experienced significant declines in mortality (AAPC = -2.6% vs -2.4% vs -1.6% vs -0.9%, respectively). CONCLUSIONS: Despite improvements in CRC screening in recent decades, focused evidenced-based interventions for lowering incidence and mortality among rural and Black populations in South Carolina are necessary.

A Bivariate Mapping Tutorial for Cancer Control Resource Allocation Decisions and Interventions.

Bivariate choropleth mapping is a straightforward but underused method for displaying geographic health information to use in public health decision making. Previous studies have recommended this approach for state comprehensive cancer control planning and similar efforts. In this method, 2 area-level variables of interest are mapped simultaneously, often as overlapping quantiles or by using other classification methods. Variables to be mapped may include area-level (eg, county level) measures of disease burden, health care use, access to health care services, and sociodemographic characteristics. We demonstrate how geographic information systems software, specifically ArcGIS, can be used to develop bivariate choropleth maps to inform resource allocation and public health interventions. We used 2 types of county-level public health data: South Carolina's Behavioral Risk Factor Surveillance System estimates of ever having received cervical cancer screening, and a measure of availability of cervical cancer screening providers that are part of South Carolina's Breast and Cervical Cancer Early Detection Program. Identification of counties with low screening rates and low access to care may help inform where additional resources should be allocated to improve access and subsequently improve screening rates. Similarly, identifying counties with low screening rates and high access to care may help inform where educational and behavioral interventions should be targeted to improve screening in areas of high access.