Abstract B20: Geospatial analysis of hepatocellular carcinoma and its risk factors in Texas (1995-2010)
Authors: Manuel Laura , Munoz Edgar , Parma Dorothy Long , Ramirez Amelie 
Published: October 2015

Abstract
Introduction: Between 1995 and 2010 there have been 1.4 million incident cancer cases in Texas. While Hepatocellular Carcinoma (HCC) accounted for a small proportion (ranked 21st in incidence), it ranked 9th by cause of death attributed to the tumor. Mortality rate was 68%, with average overall survival time 16.6 months. Unlike most cancers, HCC has resisted attempts to reduce its impact; incidence rates continue to increase especially among those &lt; 65 years of age. We investigated the ecological relationships between HCC and 16 known/potential risk factors (PRFs) in all 254 Texas (TX) counties in order to specifically target health promotion and HCC prevention efforts.
Methods: County-level data on PRFs was obtained from the TX Department of State Health Services--Reportable Diseases, County Health Rankings, TX Cancer Registry, and the Centers for Disease Control and Prevention. HCC cases were defined using the International Classification of Diseases (ICDO-3 topography C22.0 and morphologies 8170–8175). Incidence rates were calculated using the Surveillance, Epidemiology and End Results (SEER) Stat Statistical software version 8.1.5.
Correlation analysis between HCC rates and each PRF was conducted using ordinary least squares linear regression (p&lt;0.05). Choynowski's double-sided Poisson probability map was used to identify counties with rates significantly different than expected on all PRFs and HCC.
Comparisons were performed by overlapping areas showing high probabilities in variable pairs, and indicating whether they were concordant (both high, both low), or discordant (one high, one low).
Using GeoDa, Univariate Moran's I was calculated to evaluate spatial autocorrelation of HCC and all PRFs. Bivariate Moran's I was used to determine which PRFs clustered geographically with HCC. Contiguity-based spatial weights were calculated using the Rook's and Queen's method of first and second order. Spatial Lag regression analysis was performed to test spatial relationships of HCC and multiple PRFs. Due to the inverse relationship between population proportions of Non-Hispanic whites (NHW) and Hispanics, these variables were run in separate linear models.
Results: Correlation analysis showed 12 PRFs significantly associated to HCC. All 12 PRFs were spatially auto correlated (p&lt;0.05), and 8 (Diabetes, Chlamydia, NHW, Hispanics, physical inactivity, High School graduation rates, age over 65, violent crime rate) retained significant geographic clustering with HCC under all contiguity methods. Excessive alcohol consumption (EAC) remained significant only in Rook contiguity, likely due to low n (63) of counties with data. Spatial regression analysis showed strong spatial correlations between HCC and ethnicity (NHW, Hispanics) (p&lt;0.001), HIV (p&lt;0.001) and EAC (p&lt;0.01). P values did not vary across all contiguity methods for all 3 PRFs.
Conclusion: Several PRFs clustered spatially and varied geographically with HCC rates, particularly in areas with low NHW/high Hispanic populations and counties along the South TX/Mexico border. HIV's significant spatial correlation with HCC is important, as co-infection with known HCC risk factor Hepatitis C virus (HCV) accelerates liver fibrosis development vs. HCV infection alone. This study highlights the need for interventions targeted to multiple HCC PRFs including EAC and HIV, particularly in South TX.
Citation Format: Laura Manuel, Edgar Munoz, Dorothy Long Parma, Amelie Ramirez. Geospatial analysis of hepatocellular carcinoma and its risk factors in Texas (1995-2010). [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B20.