Disparities in Access to Liver Transplant Referral and Evaluation among Patients with Hepatocellular Carcinoma in Georgia.

Liver transplantation offers the best survival for patients with early-stage hepatocellular carcinoma (HCC). Prior studies have demonstrated disparities in transplant access; none have examined the early steps of the transplant process. We identified determinants of access to transplant referral and evaluation among patients with HCC with a single tumor either within Milan or meeting downstaging criteria in Georgia.Population-based cancer registry data from 2010 to 2019 were linked to liver transplant centers in Georgia. Primary cohort: adult patients with HCC with a single tumor ≤8 cm in diameter, no extrahepatic involvement, and no vascular involvement. Secondary cohort: primary cohort plus patients with multiple tumors confined to one lobe. We estimated time to transplant referral, evaluation initiation, and evaluation completion, accounting for the competing risk of death. In sensitivity analyses, we also accounted for non-transplant cancer treatment.Among 1,379 patients with early-stage HCC in Georgia, 26% were referred to liver transplant. Private insurance and younger age were associated with increased likelihood of referral, while requiring downstaging was associated with lower likelihood of referral. Patients living in census tracts with ≥20% of residents in poverty were less likely to initiate evaluation among those referred [cause-specific hazard ratio (csHR): 0.62, 95% confidence interval (CI): 0.42-0.94]. Medicaid patients were less likely to complete the evaluation once initiated (csHR: 0.53, 95% CI: 0.32-0.89).Different sociodemographic factors were associated with each stage of the transplant process among patients with early-stage HCC in Georgia, emphasizing unique barriers to access and the need for targeted interventions at each step. SIGNIFICANCE: Among patients with early-stage HCC in Georgia, age and insurance type were associated with referral to liver transplant, race, and poverty with evaluation initiation, and insurance type with evaluation completion. Opportunities to improve transplant access include informing referring providers about insurance requirements, addressing barriers to evaluation initiation, and streamlining the evaluation process.

Epidemiology beyond its limits.

In 1995, journalist Gary Taubes published an article in Science titled "Epidemiology faces its limits," which questioned the utility of nonrandomized epidemiologic research and has since been cited more than 1000 times. He highlighted numerous examples of research topics he viewed as having questionable merit. Studies have since accumulated for these associations. We systematically evaluated current evidence of 53 example associations discussed in the article. Approximately one-quarter of those presented as doubtful are now widely viewed as causal based on current evaluations of the public health consensus. They include associations between alcohol consumption and breast cancer, residential radon exposure and lung cancer, and the use of tanning devices and melanoma. This history should inform current debates about the reproducibility of epidemiologic research results.

Factors Associated With Geographic Disparities in Gastrointestinal Cancer Mortality in the United States.

BACKGROUND & AIMS: Significant geographic variability in gastrointestinal (GI) cancer-related death has been reported in the United States. We aimed to evaluate both modifiable and nonmodifiable factors associated with intercounty differences in mortality due to GI cancer. METHODS: Data from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research platform were used to calculate county-level mortality from esophageal, gastric, pancreatic, and colorectal cancers. Multivariable linear regression models were fit to adjust for county-level covariables, considering both patient (eg, sex, race, obesity, diabetes, alcohol, and smoking) and structural factors (eg, specialist density, poverty, insurance prevalence, and colon cancer screening prevalence). Intercounty variability in GI cancer-related mortality explained by these covariables was expressed as the multivariable model R2. RESULTS: There were significant geographic disparities in GI cancer-related county-level mortality across the US from 2010-2019 with the ratio of mortality between 90th and 10th percentile counties ranging from 1.5 (pancreatic) to 2.1 (gastric cancer). Counties with the highest 5% mortality rates for gastric, pancreatic, and colorectal cancer were primarily in the Southeastern United States. Multivariable models explained 43%, 61%, 14%, and 39% of the intercounty variability in mortality rates for esophageal, gastric, pancreatic, and colorectal cancer, respectively. Cigarette smoking and rural residence (independent of specialist density) were most strongly associated with GI cancer-related mortality. CONCLUSIONS: Both patient and structural factors contribute to significant geographic differences in mortality from GI cancers. Our findings support continued public health efforts to reduce smoking use and improve care for rural patients, which may contribute to a reduction in disparities in GI cancer-related death.

Understanding gastrointestinal cancer mortality disparities in a racially and geographically diverse population.

BACKGROUND: Gastrointestinal (GI) cancers represent a diverse group of diseases. We assessed differences in geographic and racial disparities in cancer-specific mortality across subtypes, overall and by patient characteristics, in a geographically and racially diverse US population. METHODS: Clinical, sociodemographic, and treatment characteristics for patients diagnosed during 2009-2014 with colorectal cancer (CRC), pancreatic cancer, hepatocellular carcinoma (HCC), or gastric cancer in Georgia were obtained from the Surveillance, Epidemiology, and End Results Program database. Patients were classified by geography (rural or urban county) and race and followed for cancer-specific death. Multivariable Cox proportional hazards models were used to calculate stratified hazard ratios (HR) and 95% confidence intervals (CIs) for associations between geography or race and cancer-specific mortality. RESULTS: Overall, 77% of the study population resided in urban counties and 33% were non-Hispanic Black (NHB). For all subtypes, NHB patients were more likely to reside in urban counties than non-Hispanic White patients. Residing in a rural county was associated with an overall increased hazard of cancer-specific mortality for HCC (HR = 1.15, 95% CI = 1.02-1.31), pancreatic (HR = 1.11, 95% CI = 1.03-1.19), and gastric cancer (HR = 1.17, 95% CI = 1.03-1.32) but near-null for CRC. Overall racial disparities were observed for CRC (HR = 1.18, 95% CI = 1.11-1.25) and HCC (HR = 1.12, 95% CI = 1.01-1.24). Geographic disparities were most pronounced among HCC patients receiving surgery. Racial disparities were pronounced among CRC patients receiving any treatment. CONCLUSION: Geographic disparities were observed for the rarer GI cancer subtypes, and racial disparities were pronounced for CRC. Treatment factors appear to largely drive both disparities.

County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care.

BACKGROUND AND AIMS: Data have demonstrated state-wide variability in mortality rates from liver disease (cirrhosis + hepatocellular carcinoma), but data are lacking at the local level (eg, county) to identify factors associated with variability in liver disease-related mortality and hotspots of liver disease mortality. METHODS: We used Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research data from 2009 to 2018 to calculate county-level, age-adjusted liver disease-related death rates. We fit multivariable linear regression models to adjust for county-level covariates related to demographics (ie, race and ethnicity), medical comorbidities (eg, obesity), access to care (eg, uninsured rate), and geographic (eg, distance to closest liver transplant center) variables. We used optimized hotspot analysis to identify clusters of liver disease mortality hotspots based on the final multivariable models. RESULTS: In multivariable models, 61% of the variability in among-county mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the closest transplant center, and local rates of obesity, diabetes, and alcohol use. Despite adjustment, significant within-state variability in county-level mortality rates was found. Of counties in the top fifth percentile (ie, highest mortality) of fully adjusted mortality, 60% were located in 3 states: Oklahoma, Texas, and New Mexico. Adjusted mortality rates were highly spatially correlated, representing 5 clusters: South Florida; Appalachia and the eastern part of the Midwest; Texas and Oklahoma; New Mexico, Arizona, California, and southern Oregon; and parts of Washington and Montana. CONCLUSIONS: Our data demonstrate significant intrastate differences in liver disease-related mortality, with more than 60% of the variability explained by patient demographics, clinical risk factors for liver disease, and access to specialty liver care.