TY - JOUR
T1 - Analysis of Clinical Phenotypes through Machine Learning of First-Line H. pylori Treatment in Europe during the Period 2013–2022
T2 - Data from the European Registry on H. pylori Management (Hp-EuReg)
AU - Nyssen, Olga P.
AU - Pratesi, Pietro
AU - Spínola, Miguel A.
AU - Jonaitis, Laimas
AU - Pérez-Aísa, Ángeles
AU - Vaira, Dino
AU - Saracino, Ilaria Maria
AU - Pavoni, Matteo
AU - Fiorini, Giulia
AU - Tepes, Bojan
AU - Bordin, Dmitry S.
AU - Voynovan, Irina
AU - Lanas, Ángel
AU - Martínez-Domínguez, Samuel J.
AU - Alfaro, Enrique
AU - Bujanda, Luis
AU - Pabón-Carrasco, Manuel
AU - Hernández, Luis
AU - Gasbarrini, Antonio
AU - Kupcinskas, Juozas
AU - Lerang, Frode
AU - Smith, Sinead M.
AU - Gridnyev, Oleksiy
AU - Leja, Mārcis
AU - Rokkas, Theodore
AU - Marcos-Pinto, Ricardo
AU - Meštrović, Antonio
AU - Marlicz, Wojciech
AU - Milivojevic, Vladimir
AU - Simsek, Halis
AU - Kunovsky, Lumir
AU - Papp, Veronika
AU - Phull, Perminder S.
AU - Venerito, Marino
AU - Boyanova, Lyudmila
AU - Boltin, Doron
AU - Niv, Yaron
AU - Matysiak-Budnik, Tamara
AU - Doulberis, Michael
AU - Dobru, Daniela
AU - Lamy, Vincent
AU - Capelle, Lisette G.
AU - Nikolovska Trpchevska, Emilija
AU - Moreira, Leticia
AU - Cano-Català, Anna
AU - Parra, Pablo
AU - Mégraud, Francis
AU - O’Morain, Colm
AU - Ortega, Guillermo J.
AU - Gisbert, Javier P.
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/9
Y1 - 2023/9
N2 - 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.
AB - 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.
KW - Helicobacter pylori
KW - clustering
KW - eradication
KW - machine learning
KW - phenotyping
KW - treatment
UR - http://www.scopus.com/inward/record.url?scp=85172216208&partnerID=8YFLogxK
U2 - 10.3390/antibiotics12091427
DO - 10.3390/antibiotics12091427
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C2 - 37760723
AN - SCOPUS:85172216208
SN - 2079-6382
VL - 12
JO - Antibiotics
JF - Antibiotics
IS - 9
M1 - 1427
ER -