Racial and ethnic disparities in incidence and mortality for the five most common gastrointestinal cancers in the United States.

BACKGROUND: Gastrointestinal cancers account for a significant burden of cancers in the United States. We sought to measure relative incidence of and mortality from the five most common gastrointestinal malignancies by race and ethnicity. METHODS: We used data from the National Cancer Institute Surveillance, Epidemiology, and End Results Cancer Registry and the National Center for Health Statistics to calculate incidence and mortality rates for colorectal, pancreatic, liver, esophageal, and gastric cancer from 2013 to 2017 (incidence) and 2014 to 2018 (mortality). We then calculated incidence and mortality rate ratios, comparing each racial/ethnic group (non-Hispanic Black, non-Hispanic Asian/Pacific Islander, non-Hispanic American Indian/Alaska Native, and Hispanic) to non-Hispanic White. RESULTS: Colorectal cancer had highest overall incidence and mortality. When compared to non-Hispanic White individuals, all other racial/ethnic groups had significantly higher incidence of liver and gastric cancer but lower incidence of esophageal cancer. Non-Hispanic Black individuals had higher incidence of colorectal and pancreatic cancer than non-Hispanic White individuals, while Hispanic and non-Hispanic Asian/Pacific Island individuals had lower incidence of these two cancers compared to non-Hispanic White individuals. Disparity patterns were similar for mortality. CONCLUSIONS: Liver and gastric cancer have the greatest differences in incidence and mortality by race/ethnicity. Non-Hispanic Black individuals carry the highest burden of gastrointestinal malignancies overall.

Automated identification and assignment of colonoscopy surveillance recommendations for individuals with colorectal polyps.

BACKGROUND AND AIMS: Determining surveillance intervals for patients with colorectal polyps is critical but time-consuming and challenging to do reliably. We present the development and assessment of a pipeline that leverages natural language processing techniques to automatically extract and analyze relevant polyp findings from free-text colonoscopy and pathology reports. Using this information, we categorized individual patients into 6 postcolonoscopy surveillance intervals defined by the U.S. Multi-Society Task Force on Colorectal Cancer. METHODS: Using a set of 546 randomly selected colonoscopy and pathology reports from 324 patients in a single health system, we used a combination of statistical classifiers and rule-based methods to extract polyp properties from each report type, associate properties with unique polyps, and classify a patient into 1 of 6 risk categories by integrating information from both report types. We then assessed the pipeline's performance by determining the positive predictive value (PPV), sensitivity, and F-score of the algorithm, compared with the determination of surveillance intervals by a gastroenterologist. RESULTS: The pipeline was developed using 346 reports (224 colonoscopy and 122 pathology) from 224 patients and evaluated on an independent test set of 200 reports (100 colonoscopy and 100 pathology) from 100 patients. We achieved an average PPV, sensitivity, and F-score of .92, .95, and .93, respectively, across targeted entities for colonoscopy. Pathology extraction achieved a PPV, sensitivity, and F-score of .95, .97, and .96. The system achieved an overall accuracy of 92% in assigning the recommended interval for surveillance colonoscopy. CONCLUSIONS: This study demonstrates the feasibility of using machine learning to automatically extract findings and classify patients to appropriate risk categories and corresponding surveillance intervals. Incorporating this system can facilitate proactive and timely follow-up after screening colonoscopy and enable real-time quality assessment of prevention programs and providers.

Identifying Quality Gaps in Preventive Care for Outpatients With Cirrhosis Within a Large, Academic Health Care System.

We sought to identify specific gaps in preventive care provided to outpatients with cirrhosis and to determine factors associated with high quality of care (QOC), to guide quality improvement efforts. Outpatients with cirrhosis who received care at a large, academic tertiary health care system in the United States were included. Twelve quality indicators (QIs), including preventive care processes for ascites, esophageal varices, hepatic encephalopathy, hepatocellular carcinoma (HCC), and general cirrhosis care, were measured. QI pass rates were calculated as the proportion of patients eligible for a QI who received that QI during the study period. We performed logistic regression to determine predictors of high QOC (≥ 75% of eligible QIs) and receipt of HCC surveillance. Of the 439 patients, the median age was 63 years, 59% were male, and 19% were Hispanic. The median Model for End-Stage Liver Disease-Sodium score was 11, 64% were compensated, and 32% had hepatitis C virus. QI pass rates varied by individual QIs, but were overall low. For example, 24% received appropriate HCC surveillance, 32% received an index endoscopy for varices screening, and 21% received secondary prophylaxis for spontaneous bacterial peritonitis. In multivariable analyses, Asian race (odds ratio [OR]: 3.7, 95% confidence interval [CI]: 1.3-10.2) was associated with higher QOC, and both Asian race (OR: 3.3, 95% CI: 1.2-9.0) and decompensated status (OR: 2.1, 95% CI: 1.1-4.2) were associated with receipt of HCC surveillance. A greater number of specialty care visits was not associated with higher QOC. Conclusion: Receipt of outpatient preventive cirrhosis QIs was variable and overall low in a diverse cohort of patients with cirrhosis. Variation in care by race/ethnicity and illness trajectory should prompt further inquiry into identifying modifiable factors to standardize care delivery and to improve QOC.

H+ and Pi Byproducts of Glycosylation Affect Ca2+ Homeostasis and Are Retrieved from the Golgi Complex by Homologs of TMEM165 and XPR1.

Glycosylation reactions in the Golgi complex and the endoplasmic reticulum utilize nucleotide sugars as donors and produce inorganic phosphate (Pi) and acid (H+) as byproducts. Here we show that homologs of mammalian XPR1 and TMEM165 (termed Erd1 and Gdt1) recycle luminal Pi and exchange luminal H+ for cytoplasmic Ca2+, respectively, thereby promoting growth of yeast cells in low Pi and low Ca2+ environments. As expected for reversible H+/Ca2+ exchangers, Gdt1 also promoted growth in high Ca2+ environments when the Golgi-localized V-ATPase was operational but had the opposite effect when the V-ATPase was eliminated. Gdt1 activities were negatively regulated by calcineurin signaling and by Erd1, which recycled the Pi byproduct of glycosylation reactions and prevented the loss of this nutrient to the environment via exocytosis. Thus, Erd1 transports Pi in the opposite direction from XPR1 and other EXS family proteins and facilitates byproduct removal from the Golgi complex together with Gdt1.