Hepatology 2021 Sep 8. Epub 2021 Sep 8.
Division of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA, United States.
Background & Aims: Chronic hepatitis B (CHB) affects over 290 million people globally and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression and machine learning (random forest) models to accurately identify patients with HBV, using only easily-obtained demographic data from a population-based data set.
Approach & Results: We identified participants with data on hepatitis B surface antigen (HBsAg), birth year, sex, race/ethnicity, and birthplace from 10 cycles of the National Health and Nutrition Examination Survey (NHANES, 1999-2018) and divided them into two cohorts: training (cycles 2, 3, 5, 6, 8, 10; n = 39,119) and validation (cycles 1, 4, 7, 9; n = 21,569). Read More