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Clarithromycin Resistance Patterns of Helicobacter pylori across Different Gastric Diseases in Uzbekistan

Abrorjon YusupbekovRepublican Specialized Scientific and Practical Medical Center of Oncology and Radiology (National Cancer Center of Uzbekistan), Tashkent, Uzbekistan; Department of Oncology, Oncohematology and Medical Radiology, Tashkent State Medical University, Tashkent, Uzbekistan. [email protected]Takahiro ShinozukaDepartment of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan. [email protected]Jadida IsmailovaRepublican Specialized Scientific and Practical Center for Therapy and Medical Rehabilitation, Tashkent, Uzbekistan; Department of Internal Medicine, Tashkent State Medical University, Tashkent, Uzbekistan. [email protected]Otabek TuychievDepartment of Oncology, Oncohematology and Medical Radiology, Tashkent State Medical University, Tashkent, Uzbekistan; Department of Thoracic Surgical Oncology, Republican Specialized Scientific and Practical Medical Center of Oncology and Radiology (National Cancer Center of Uzbekistan), Tashkent, Uzbekistan. [email protected]Mitsuro KandaDepartment of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan. [email protected]Junichi SakamotoTokai Central Hospital, Kakamigahara, Japan. [email protected]Yanfang ZhengGuangzhou Medical University

2026en

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Litsenziya: cc-by-nc-nd

ABI

Annotatsiya

BACKGROUND AND AIMS: Helicobacter pylori (H. pylori) eradication is crucial for gastric cancer (GC) prevention. However, increasing clarithromycin (CLR) resistance (CLRR) poses significant challenges. This study aimed to investigate CLRR patterns across different gastric diseases in Uzbekistan. METHODS: We retrospectively analyzed 279 H. pylori-infected patients with chronic non-atrophic gastritis (CNAG), chronic atrophic gastritis (CAG), gastric ulcer (GU), mucosa-associated lymphoid tissue lymphoma (MALT-L), or GC between 2020-2022. Among 194 cagA-positive patients who received eradication therapy, CLRR was defined by 23S rRNA mutations (A2142G, A2142C, A2143G) or treatment failure with CLR-based regimens. Logistic regression identified factors associated with CLRR, evaluated by univariate and multivariate analysis, and predicted probability models were generated based on disease type and patient characteristics. RESULTS: The overall CLRR rate was 44.8% (87/194), with 41.2% showing genotypic resistance. CLRR rates increased with disease severity: CNAG (33.3%), CAG (31.7%), GU (59.3%), MALT-L (54.1%), and GC (69.6%). Multivariate analysis identified older age (OR=2.27, 95%CI: 1.05-5.10), GU (OR=2.65, 95%CI: 1.04-6.96), and GC (OR=3.73, 95%CI: 1.34-11.2) as independent CLRR predictors. Disease-specific patterns emerged: GU and GC showed positive associations between age / body mass index and CLRR probability, while MALT-L demonstrated inverse relationships. CONCLUSIONS: High CLRR rates in Uzbekistan correlate with gastric disease severity. The disease-specific CLRR probability patterns identified in our study provide a practical framework for optimizing empirical therapy selection when comprehensive resistance testing is unavailable.

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DOI: 10.15403/jgld-6653

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