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Updated: Oct 26, 2026

Detection of Helicobacter pylori Infection and Antibiotic Resistance via Stool Quantitative Polymerase Chain Reaction Analysis
Published on: May 16, 2025
Meta-analysis of diagnostic validation studies on noninvasive methods for detecting Helicobacter pylori in the
M A Montoya-Arango1, E A Figueredo-Carmona1, S Y Zapata2
1Escuela de Microbiología, Universidad de Antioquia, Medellín, Colombia.
Introduction And Aim:
Early detection and eradication of Helicobacter pylori in high-prevalence regions are effective for reducing the incidence of gastric cancer, but evidence supporting its detection in the pediatric population is less robust. Our aim was to evaluate the diagnostic validity of noninvasive methods for detecting Helicobacter pylori in pediatric patients based on studies published in the medical literature.
Methods:
Following the PRISMA guideline, a systematic review using the Pubmed, ScienceDirect, SciELO, and Embase databases was carried out. Study quality was evaluated using the QUADAS tool. A random-effects meta-analysis was conducted to estimate sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and ROC curves, with 95% confidence intervals. Heterogeneity was evaluated with the DerSimonian-Laird Q(X2) statistic and the I2 index.
Results:
The sensitivity of serum enzyme-linked immunosorbent assay (ELISA) tests was higher for IgG (89%) than for IgA (49%), whereas specificity was similar, at 97% for IgG and 98% for IgA. Stool antigen ELISA tests had 88% sensitivity and 93% specificity.
Conclusion:
Our meta-analysis found variable accuracy in the noninvasive tests for detecting Helicobacter pylori in children. The 13C urea breath test and stool antigen ELISA showed the best diagnostic performance, with the latter standing out as the most practical and reliable option for pediatric use. Despite the promising results, methodological limitations and study variability highlight the need for more robust research to support said diagnostic tools in high-prevalence settings.
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