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)

Olga P. Nyssen, Pietro Pratesi, Miguel A. Spínola, Laimas Jonaitis, Ángeles Pérez-Aísa, Dino Vaira, Ilaria Maria Saracino, Matteo Pavoni, Giulia Fiorini, Bojan Tepes, Dmitry S. Bordin, Irina Voynovan, Ángel Lanas, Samuel J. Martínez-Domínguez, Enrique Alfaro, Luis Bujanda, Manuel Pabón-Carrasco, Luis Hernández, Antonio Gasbarrini, Juozas KupcinskasFrode Lerang, Sinead M. Smith, Oleksiy Gridnyev, Mārcis Leja, Theodore Rokkas, Ricardo Marcos-Pinto, Antonio Meštrović, Wojciech Marlicz, Vladimir Milivojevic, Halis Simsek, Lumir Kunovsky, Veronika Papp, Perminder S. Phull, Marino Venerito, Lyudmila Boyanova, Doron Boltin, Yaron Niv, Tamara Matysiak-Budnik, Michael Doulberis, Daniela Dobru, Vincent Lamy, Lisette G. Capelle, Emilija Nikolovska Trpchevska, Leticia Moreira, Anna Cano-Català, Pablo Parra, Francis Mégraud, Colm O’Morain, Guillermo J. Ortega*, Javier P. Gisbert

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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% in 2013 to 93% in 2022. The lowest effectiveness (80%) was obtained in 2016 in cluster #3 encompassing Slovenia, Lithuania, Latvia, and Russia, treated with 7-day triple therapy with amoxicillin–clarithromycin (92% of cases). The highest effectiveness (95%) was achieved in 2022, mostly in Spain (81%), with the bismuth–quadruple therapy, including the single-capsule (64%) and the concomitant treatment with clarithromycin–amoxicillin–metronidazole/tinidazole (34%) with 10 (69%) and 14 (32%) days. Cluster analysis allowed for the identification of patients in homogeneous treatment groups assessing the effectiveness of different first-line treatments depending on therapy scheme, adherence, country, and prescription year.

Original languageEnglish
Article number1427
JournalAntibiotics
Volume12
Issue number9
DOIs
StatePublished - Sep 2023

Funding

FundersFunder number
AEG
European Helicobacter
European Union programme EU4Health101101252
Mayoly and Allergan
Spanish Association of Gastroenterology
UK Research and Innovation10058099
UK Research and Innovation
European Commission101095359
European Commission
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas

    Keywords

    • Helicobacter pylori
    • clustering
    • eradication
    • machine learning
    • phenotyping
    • treatment

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