Individualized diagnosis and eradication therapy for Helicobacter pylori infection based on gene detection of clarithromycin resistance in stool specimens: A systematic review and meta‐analysis

Abstract

AbstractBackgroundEmpiric therapy for Helicobacter pylori infection results in significantly increased antibiotic resistance and decreased eradication efficacy. The genotypic testing of clarithromycin resistance from stool specimens is a promising method for individualized diagnosis and treatment. This study aimed to determine the status of research and application on this method through a systematic review and meta‐analysis.MethodsPubMed, Embase, MEDLINE, and WAN FANG database were searched for relevant literature. The quality of included diagnostic articles was evaluated using the quality Assessment of Diagnostic Accuracy Studies‐2 tool. A bivariate random‐effect model was conducted to calculate the diagnostic accuracy of genotypic testing of clarithromycin resistance.ResultsA total of 16 diagnostic‐related were included and analyzed after exclusions. The pooled sensitivity and specificity of diagnostic meta‐analysis were 0.93 (95% confidence interval [CI]: 0.90–0.96) and 0.98 (95% CI: 0.93–1.00), respectively. The area under the curve (AUC) of the summary receiver operating characteristic was 0.97 (95% CI: 0.95–0.98). The genotypic testing in stool samples had heterogeneous sensitivity (Q = 37.82, p < .01, I2 = 37.82) and specificity (Q = 60.34, p < .01, I2 = 93.72) in detecting clarithromycin resistance. Purification method, stool sample weight, real‐time PCR, and antimicrobial susceptibility testing as reference accounted for the heterogeneity of pooled sensitivity, while patient age, purification method, stool sample weight, and real‐time PCR for the heterogeneity of pooled specificity.ConclusionThe genotypic testing of clarithromycin resistance from stool specimens is an accurate, convenient, noninvasive, and rapid detection technology, providing a definitive diagnosis of clarithromycin resistance and guiding the rational antibiotic selection.