Geospatial analysis of cyanobacterial exposure and liver cancer in the contiguous United States.

BACKGROUND AND AIMS: Cyanobacteria are commonly found in water bodies and their production of hepatotoxins can contribute to liver damage. However, the population health effects of cyanobacteria exposure (CE) are unknown. Our objectives were to determine the effect of chronic exposure to cyanobacteria through proximity to water bodies with high cyanobacteria counts on the incidence and mortality of liver cancers, as well as to identify location-based risk factors. APPROACH AND RESULTS: Across the contiguous United States, regions with high cyanobacteria counts in water bodies were identified using satellite remote sensing data. The data were geospatially mapped to county boundaries, and disease mortality and incidence rates were analyzed. Distinctive spatial clusters of CE and mortality related to liver diseases or cancer were identified. There was a highly significant spatial association between CE, liver disease, and liver cancer but not between CE and all cancers. Hot spots of CE and mortality were identified along the Gulf of Mexico, eastern Texas, Louisiana, and Florida, and cold spots across the Appalachians. The social vulnerability index was identified as a major location-based determinant by logistic regression, with counties in the fourth or fifth quintiles having the highest prevalence of hot spots of CE and mortality from liver cancer. CONCLUSIONS: These findings emphasize the importance of environmental exposure to cyanobacteria as a location-based determinant of mortality from liver cancer. Public health initiatives addressing CE may be considered to reduce mortality, particularly in areas of high social vulnerability.

Poverty traps and mortality from liver diseases in the United States.

INTRODUCTION: Poverty traps, locations with multigenerational poverty, result from structural and economic factors that can impact health of residents within these locations. The aim of this study was to define poverty traps within the contiguous United States and their impact on outcomes from liver diseases or cancers. METHODS: A systematic census-tract level analysis was used to define spatially defined regions that encompassed poverty traps. Clusters of prevalent poverty and mortality from chronic liver diseases or liver cancers were identified. Temporal trends and the relationship between race and ethnicity, type of space and escape from poverty traps on disease mortality within hot spots were determined. RESULTS: The proportion of census tracts enduring multigenerational poverty within counties was strongly associated with mortality from liver disease or cancer. There was a highly significant clustering of persistent poverty and increased mortality. Hot-spots of high-mortality areas correlated with factors related to income, ethnicity, and access to healthcare. Location or non-economic individual factors such as race and ethnicity were important determinants of disparities within hot spots. Distinct groups of poverty traps were defined. The highly characteristic demographics and disease outcomes within each of these groups underscored the need for location-specific interventions. DISCUSSION: Poverty traps are a major and important spatially determined risk factor for mortality from liver diseases and cancers. Targeted location-specific interventions as well as economic development aimed at addressing the underlying causes of poverty and enhancing prosperity will be required to reduce mortality from liver diseases within poverty traps.

Predictors of Survival in Patients With Hepatocellular Cancer Receiving Atezolizumab and Bevacizumab.

OBJECTIVES: In randomized clinical trials in patients with hepatocellular cancer (HCC), combination therapy with atezolizumab and bevacizumab (Atezo-Bev) prolonged survival, and these treatments have become the standard first-line therapy for advanced HCC. However, clinical trials may not reflect real-life clinical practice due to treatment selection criteria. Thus, our aim was to understand predictors of HCC outcomes with these treatments in a real-world, multicenter setting. METHODS: A retrospective review of all patients 18 years of age or older treated for advanced primary liver cancer between February 2020 and August 2022 was conducted to assess the relationship between overall survival and clinical and biochemical variables before or during treatment. Univariate and multivariate Cox regression survival analyses were performed to identify predictors of survival following treatment. RESULTS: One hundred and eleven eligible patients with unresectable HCC received Atezo-Bev over a consecutive 30-month period. Cox regression identified several significant ( P <0.05) predictors of survival, including pretreatment albumin (hazard ratios [HR]: 0.2; CI: 0.1-0.4), total bilirubin (HR: 1.3; CI: 1.2-1.5), and international normalized ratio (HR: 5.6; CI: 2.5-12.5). In multivariate analyses, these were significantly associated as predictors of mortality, and patients with pretreatment albumin <3.5 mg/dL had significantly lower survival than those ≥3.5 (153 vs. 522 d, P <0.0001). CONCLUSIONS: Pretreatment hypoalbuminemia, high bilirubin, and biochemical tests indicative of hepatic or renal dysfunction can independently predict short-term mortality in advanced HCC patients receiving Atezo-Bev.

Therapeutic biliary stents: applications and opportunities.

INTRODUCTION: Biliary stents are used to optimize ductal patency and enable bile flow in the management of obstruction or injury related to biliary tract tumors, strictures, stones, or leaks. Although direct therapeutic applications of biliary stents are less well developed, stents can be used to deliver drugs, radioisotopes, and photodynamic therapy. AREAS COVERED: This report provides an in-depth overview of the clinical indications, and therapeutic utility of biliary stents. Unique considerations for the design of biliary stents are described. The properties and functionalities of materials used for stents such as metal alloys, plastic polymers, or biodegradable materials are described, and opportunities for design of future stents are outlined. Current and potential applications of stents for therapeutic applications for biliary tract diseases are described. EXPERT OPINION: Therapeutic biliary stents could be used to minimize inflammation, prevent stricture formation, reduce infections, or provide localized anti-cancer therapy for biliary tract cancers. Stents could be transformed into therapeutic platforms using advanced materials, 3D printing, nanotechnology, and artificial intelligence. Whilst clinical study and validation will be required for adoption, future advances in stent design and materials are expected to expand the use of therapeutic biliary stents for the treatment of biliary tract disorders.

A deep learning approach for detecting liver cirrhosis from volatolomic analysis of exhaled breath.

Liver disease such as cirrhosis is known to cause changes in the composition of volatile organic compounds (VOC) present in patient breath samples. Previous studies have demonstrated the diagnosis of liver cirrhosis from these breath samples, but studies are limited to a handful of discrete, well-characterized compounds. We utilized VOC profiles from breath samples from 46 individuals, 35 with cirrhosis and 11 healthy controls. A deep-neural network was optimized to discriminate between healthy controls and individuals with cirrhosis. A 1D convolutional neural network (CNN) was accurate in predicting which patients had cirrhosis with an AUC of 0.90 (95% CI: 0.75, 0.99). Shapley Additive Explanations characterized the presence of discrete, observable peaks which were implicated in prediction, and the top peaks (based on the average SHAP profiles on the test dataset) were noted. CNNs demonstrate the ability to predict the presence of cirrhosis based on a full volatolomics profile of patient breath samples. SHAP values indicate the presence of discrete, detectable peaks in the VOC signal.