Analysis of Clinical Phenotypes through Machine Learning of First-Line H. pylori Treatment in Europe during the Period 2013-2022: Data from the European Registry on H. pylori Management (Hp-EuReg).

ABSTRACT: The segmentation of patients into homogeneous groups could help to improve eradication therapy effectiveness. Our aim was to determine the most important treatment strategies used in Europe, to evaluate first-line treatment effectiveness according to year and country. Data collection: All first-line empirical treatments registered at AEGREDCap in the European Registry on Helicobacter pylori management (Hp-EuReg) from June 2013 to November 2022. A Boruta method determined the "most important" variables related to treatment effectiveness. Data clustering was performed through multi-correspondence analysis of the resulting six most important variables for every year in the 2013-2022 period. Based on 35,852 patients, the average overall treatment effectiveness increased from 87%

SUBMITTER: Nyssen OP 

PROVIDER: S-EPMC10525558 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature