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)

J 2023

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)

NYSSEN, Olga, Pietro PRATESI, Miguel SPINOLA, Laimas JONAITIS, Angeles PEREZ-AISA et. al.

Základní údaje

Originální název

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)

Autoři

NYSSEN, Olga, Pietro PRATESI, Miguel SPINOLA, Laimas JONAITIS, Angeles PEREZ-AISA, Dino VAIRA, Ilaria Maria SARACINO, Matteo PAVONI, Giulia FIORINI, Bojan TEPES, Dmitry BORDIN, Irina VOYNOVAN, Angel LANAS, Samuel MARTINEZ-DOMINGUEZ, Enrique ALFARO, Luis BUJANDA, Manuel PABON-CARRASCO, Luis HERNANDEZ, Antonio GASBARRINI, Juozas KUPCINSKAS, Frode LERANG, Sinead SMITH, Oleksiy GRIDNYEV, Marcis LEJA, Theodore ROKKAS, Ricardo MARCOS-PINTO, Antonio MESTROVIC, Wojciech MARLICZ, Vladimir MILIVOJEVIC, Halis SIMSEK, Lumír KUNOVSKÝ (203 Česká republika, domácí), Veronika PAPP, Perminder PHULL, Marino VENERITO, Lyudmila BOYANOVA, Doron BOLTIN, Yaron NIV, Tamara MATYSIAK-BUDNIK, Michael DOULBERIS, Daniela DOBRU, Vincent LAMY, Lisette CAPELLE, Emilijia Nikolovska TRPCHEVSKA, Leticia MOREIRA, Anna CANO-CATALIA, Pablo PARRA, Francis MEGRAUD, Colm MORAIN, Guillermo ORTEGA, Javier GISBERT a Hp EuReg INVESTIGATORS

Vydání

Antibiotics-Basel, BASEL, MDPI, 2023, 2079-6382

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30104 Pharmacology and pharmacy

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 4.800 v roce 2022

Kód RIV

RIV/00216224:14110/23:00132561

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.3390/antibiotics12091427

UT WoS

001074506900001

Klíčová slova anglicky

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

Štítky

14110223, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 2. 2. 2024 09:54, Mgr. Tereza Miškechová

Anotace

V originále

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.

Citovat

NYSSEN, Olga, Pietro PRATESI, Miguel SPINOLA, Laimas JONAITIS, Angeles PEREZ-AISA, Dino VAIRA, Ilaria Maria SARACINO, Matteo PAVONI, Giulia FIORINI, Bojan TEPES, Dmitry BORDIN, Irina VOYNOVAN, Angel LANAS, Samuel MARTINEZ-DOMINGUEZ, Enrique ALFARO, Luis BUJANDA, Manuel PABON-CARRASCO, Luis HERNANDEZ, Antonio GASBARRINI, Juozas KUPCINSKAS, Frode LERANG, Sinead SMITH, Oleksiy GRIDNYEV, Marcis LEJA, Theodore ROKKAS, Ricardo MARCOS-PINTO, Antonio MESTROVIC, Wojciech MARLICZ, Vladimir MILIVOJEVIC, Halis SIMSEK, Lumír KUNOVSKÝ, Veronika PAPP, Perminder PHULL, Marino VENERITO, Lyudmila BOYANOVA, Doron BOLTIN, Yaron NIV, Tamara MATYSIAK-BUDNIK, Michael DOULBERIS, Daniela DOBRU, Vincent LAMY, Lisette CAPELLE, Emilijia Nikolovska TRPCHEVSKA, Leticia MOREIRA, Anna CANO-CATALIA, Pablo PARRA, Francis MEGRAUD, Colm MORAIN, Guillermo ORTEGA, Javier GISBERT a Hp EuReg INVESTIGATORS. 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). Antibiotics-Basel. BASEL: MDPI, 2023, roč. 12, č. 9, s. 1-18. ISSN 2079-6382. Dostupné z: https://dx.doi.org/10.3390/antibiotics12091427.

@article{2351162,
   author = {Nyssen, Olga and Pratesi, Pietro and Spinola, Miguel and Jonaitis, Laimas and PerezandAisa, Angeles and Vaira, Dino and Saracino, Ilaria Maria and Pavoni, Matteo and Fiorini, Giulia and Tepes, Bojan and Bordin, Dmitry and Voynovan, Irina and Lanas, Angel and MartinezandDominguez, Samuel and Alfaro, Enrique and Bujanda, Luis and PabonandCarrasco, Manuel and Hernandez, Luis and Gasbarrini, Antonio and Kupcinskas, Juozas and Lerang, Frode and Smith, Sinead and Gridnyev, Oleksiy and Leja, Marcis and Rokkas, Theodore and MarcosandPinto, Ricardo and Mestrovic, Antonio and Marlicz, Wojciech and Milivojevic, Vladimir and Simsek, Halis and Kunovský, Lumír and Papp, Veronika and Phull, Perminder and Venerito, Marino and Boyanova, Lyudmila and Boltin, Doron and Niv, Yaron and MatysiakandBudnik, Tamara and Doulberis, Michael and Dobru, Daniela and Lamy, Vincent and Capelle, Lisette and Trpchevska, Emilijia Nikolovska and Moreira, Leticia and CanoandCatalia, Anna and Parra, Pablo and Megraud, Francis and Morain, Colm and Ortega, Guillermo and Gisbert, Javier and Investigators, Hp EuReg},
   article_location = {BASEL},
   article_number = {9},
   doi = {http://dx.doi.org/10.3390/antibiotics12091427},
   keywords = {Helicobacter pylori; clustering; phenotyping; machine learning; treatment; eradication},
   language = {eng},
   issn = {2079-6382},
   journal = {Antibiotics-Basel},
   title = {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)},
   url = {https://www.mdpi.com/2079-6382/12/9/1427},
   volume = {12},
   year = {2023}
}

TY  - JOUR
ID  - 2351162
AU  - Nyssen, Olga - Pratesi, Pietro - Spinola, Miguel - Jonaitis, Laimas - Perez-Aisa, Angeles - Vaira, Dino - Saracino, Ilaria Maria - Pavoni, Matteo - Fiorini, Giulia - Tepes, Bojan - Bordin, Dmitry - Voynovan, Irina - Lanas, Angel - Martinez-Dominguez, Samuel - Alfaro, Enrique - Bujanda, Luis - Pabon-Carrasco, Manuel - Hernandez, Luis - Gasbarrini, Antonio - Kupcinskas, Juozas - Lerang, Frode - Smith, Sinead - Gridnyev, Oleksiy - Leja, Marcis - Rokkas, Theodore - Marcos-Pinto, Ricardo - Mestrovic, Antonio - Marlicz, Wojciech - Milivojevic, Vladimir - Simsek, Halis - Kunovský, Lumír - Papp, Veronika - Phull, Perminder - Venerito, Marino - Boyanova, Lyudmila - Boltin, Doron - Niv, Yaron - Matysiak-Budnik, Tamara - Doulberis, Michael - Dobru, Daniela - Lamy, Vincent - Capelle, Lisette - Trpchevska, Emilijia Nikolovska - Moreira, Leticia - Cano-Catalia, Anna - Parra, Pablo - Megraud, Francis - Morain, Colm - Ortega, Guillermo - Gisbert, Javier - Investigators, Hp EuReg
PY  - 2023
TI  - 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)
JF  - Antibiotics-Basel
VL  - 12
IS  - 9
SP  - 1-18
EP  - 1-18
PB  - MDPI
SN  - 20796382
KW  - Helicobacter pylori
KW  - clustering
KW  - phenotyping
KW  - machine learning
KW  - treatment
KW  - eradication
UR  - https://www.mdpi.com/2079-6382/12/9/1427
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.
ER  -

NYSSEN, Olga, Pietro PRATESI, Miguel SPINOLA, Laimas JONAITIS, Angeles PEREZ-AISA, Dino VAIRA, Ilaria Maria SARACINO, Matteo PAVONI, Giulia FIORINI, Bojan TEPES, Dmitry BORDIN, Irina VOYNOVAN, Angel LANAS, Samuel MARTINEZ-DOMINGUEZ, Enrique ALFARO, Luis BUJANDA, Manuel PABON-CARRASCO, Luis HERNANDEZ, Antonio GASBARRINI, Juozas KUPCINSKAS, Frode LERANG, Sinead SMITH, Oleksiy GRIDNYEV, Marcis LEJA, Theodore ROKKAS, Ricardo MARCOS-PINTO, Antonio MESTROVIC, Wojciech MARLICZ, Vladimir MILIVOJEVIC, Halis SIMSEK, Lumír KUNOVSKÝ, Veronika PAPP, Perminder PHULL, Marino VENERITO, Lyudmila BOYANOVA, Doron BOLTIN, Yaron NIV, Tamara MATYSIAK-BUDNIK, Michael DOULBERIS, Daniela DOBRU, Vincent LAMY, Lisette CAPELLE, Emilijia Nikolovska TRPCHEVSKA, Leticia MOREIRA, Anna CANO-CATALIA, Pablo PARRA, Francis MEGRAUD, Colm MORAIN, Guillermo ORTEGA, Javier GISBERT a Hp EuReg INVESTIGATORS. 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). \textit{Antibiotics-Basel}. BASEL: MDPI, 2023, roč.~12, č.~9, s.~1-18. ISSN~2079-6382. Dostupné z: https://dx.doi.org/10.3390/antibiotics12091427.

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