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)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F23%3A00078394" target="_blank" >RIV/65269705:_____/23:00078394 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14110/23:00132561 RIV/00098892:_____/23:10158059 RIV/00209805:_____/23:00079429

Výsledek na webu

<a href="https://www.mdpi.com/2079-6382/12/9/1427" target="_blank" >https://www.mdpi.com/2079-6382/12/9/1427</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/antibiotics12091427" target="_blank" >10.3390/antibiotics12091427</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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)

Popis výsledku v původním jazyce

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 &quot;most important&quot; 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.

Název v anglickém jazyce

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)

Popis výsledku anglicky

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 &quot;most important&quot; 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30303 - Infectious Diseases

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Antibiotics-Basel

ISSN

2079-6382

e-ISSN

2079-6382

Svazek periodika

12

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

18

Strana od-do

1427

Kód UT WoS článku

001074506900001

EID výsledku v databázi Scopus

2-s2.0-85172216208