Background Few in-depth reports on cancer epidemiology in New Mexico or the United States-Mexico border region exist. We aim to quantify cancer incidence and survival in New Mexico and the United States-Mexico border region in New Mexico. Methods Incidence and survival were obtained using SEER*Stat 8.3. The data were divided into either New Mexico, or SEER 18 (comprised of the 17 remaining regions) and then further divided by county in New Mexico and by time period. Incidence rates were age-standardized to the 2000 US census. Five-year survival was calculated for each cancer type. Kaplan-Meier survival plots were produced, and significance was determined using log-rank analysis. Results Analysis demonstrated that cancers in New Mexico are diagnosed at a lower rate with the exception of thyroid, liver, and ovarian. Survival is generally lower in New Mexico with 10 of the 14 cancers having worse survival in New Mexico. Only uterine cancer had improved survival in New Mexico (77.9% vs 74.9%, P < .001). Additionally, breast (82.2%), prostate (83.3%), lung and bronchus (13.7%), colorectal (53.7%), melanoma (80.1%), kidney and renal pelvis (61.2%), uterine (78.5%), and ovarian (41.6%) all had lower survival in the border counties. Conclusion Comparing New Mexico to the other regions in the SEER 18 database, both cancer incidence and survival are consistently lower; these findings could be explained by lower access to healthcare, which can result in underreporting and delays in diagnosis.

Objectives: To describe and compare the incidence, stage at diagnosis, and survival for genitourinary cancers in the border regions and in Hispanic-Americans. Materials and methods: A population-based search was performed using the Surveillance, Epidemiology, and End Results Program 18 database and the Texas Cancer Registry from 2000 to 2017. Cox regression models were performed with adjusted for age, gender, race, cancer type, cancer stage, insurance status, and cause of death were used to compare cancer-specific survival. Results: A total of 63,236 kidney and renal pelvis, 38,398 bladder, 170,640 prostate, 24,313 testicular cancer cases were identified. Cancer-specific survival was found to be improved in Hispanic-Americans in kidney and renal pelvis (hazard ratio [HR], 0.903, 95% confidence interval [CI], 0.856-0.952, p = 0.0001), and bladder cancers (HR, 0.817, 95% CI, 0.743-0.898, p < 0.001), despite a more advanced stage at diagnosis in Hispanics with bladder cancer ( p < 0.0074). Testicular cancer has a survival disadvantage for individuals living in the border region (HR, 1.315, 95% CI, 1.124-1.539, p = 0.0006). Conclusions: Disparities exist between Hispanic-Americans and Non-Hispanic White and also between individuals living in the border counties when compared to other regions. This is most significant in individuals with testicular cancer residing in the border region who demonstrate worse overall survival.

Objective: To examine incidence and survival of testicular cancer in New Mexico, overall and separately for border and non-border counties.Methods: Incidence and 5-year survival rates for testicular cancer were obtained from the SEER18 database using the SEER*Stat program following established NCI protocols. Incidence data were com­pared using Student’s t-test. Age-adjusted 5-year survival and Kaplan-Meier method were used to estimate survival. Log-rank tests were used to compare survival for New Mexico to the remaining17 geographi­cal areas of the SEER 18 and for the New Mexico border counties to the New Mexico non-border counties. Odds ratios were used to compare testicular stage at diagnosis. Cox proportional hazards regression was performed to account for race/ethnicity, and border status.Results: From 2000-2015, New Mexico had a testicular cancer incidence rate of 6.3 per 100,000 people, significantly higher than SEER18 (P<.001). The 5-year survival rate in New Mexico did not differ signifi­cantly from the SEER18 (P=.3). Border His­panics had a lower survival rate than border non-Hispanic populations (P=.03). From 2000-2018, New Mexico had a significantly higher proportion of distant cancers than the SEER18 (OR: 1.29, 95% CI: 1.08 to 1.53, P=.005).Conclusions: The higher incidence of testicular cancer in New Mexico does not appear to have a clear explanation based on the current understanding of risk factors; however, the increased incidence in New Mexico does not appear to be associated with increased mortality. The higher propor­tion of advanced testicular cancers in New Mexico may represent a delay in diagnosis. The increased mortality rate seen in Hispan­ic border populations may be due in part to barriers to care.Ethn Dis. 2020;30(2):357- 364; doi:10.18865/ed.30.2.357

392 Background: Industrial byproducts and environmental pollutants (IBP/EP) are associated with the development of urothelial carcinoma (UC). While tobacco exposure (TE) is the major risk factor for UC, the interaction between sources of IBP/EP and incidence of UC in surrounding communities has been infrequently explored. We seek to identify high-density microregions of UC prevalence and spatially-related industrial and environmental risk factors. Methods: We queried a multi-institutional database for patients diagnosed with UC between 2008-2018. Geocoded addresses and ArcGIS software were used to calculate the Getis-Ord-Gi* statistic and perform hotspot analysis on the census-block level to identify UC hotspots. Demographics, clinicopathologic disease characteristics, and proximity to sources of IBP/EP were compared using Pearson’s chi-square and Student’s T-test. Univariate analyses and multivariable multilevel logistic random-intercept regression models were fitted to test the association between patient and census block-level factors and living in a UC hot spot. Results: Of 5,080 patients meeting inclusion/exclusion criteria, 148 patients (2.9%) were associated with one of three UC hotspots. In univariate analyses, hotspot patients were less likely to be tobacco users (OR 0.24, p=0.004) or of white race (OR 0.10, p<0.001) and less likely to have higher income (OR 0.73, p=0.005). They were more likely to be associated with IBP/EP exposure (OR 8.24, p=0.001) (Table). Multivariable analysis confirmed increased likelihood of residing in a UC hotspot and proximity to high-traffic density (OR >999, p=<0.001) and sites of IBP/EP contamination (OR 106.90, p=0.009), with decreased likelihood of tobacco use (OR 0.11, p=0.045) and white race (OR 0.02, p=0.004). Conclusions: Patients residing in geospatial hotspots of UC prevalence are less likely to be white, higher income or tobacco users and more likely to reside in proximity to sources of IBP/EP. Further research is necessary to investigate the interplay between socioeconomic status, race and environmental risk factors in order to better identify at-risk populations and improve screening, referral, diagnosis and timely intervention. [Table: see text]

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