Prediction of true Helicobacter pylori-uninfected status using a combination of age, serum antibody and pepsinogen: Logistic regression analysis

Abstract

Introduction To prevent gastric cancer, it is important to accurately determine the presence of Helicobacter pylori (HP) infection. However, correctly identifying HP-uninfected individuals is difficult when using the combination of HP antibody and pepsinogen (PG). Objective The aim of this study was to discriminate true HP-uninfected individuals from others without the need for endoscopic examination. Methods A total of 684 subjects with no history of HP eradication who underwent a medical checkup at our hospital were enrolled. The “true uninfected individuals” were determined by a negative stool antigen test and no endoscopic findings of HP-associated gastritis. HP antibody was measured by the latex immunoassay method. Logistic regression analysis using a combination of noninvasive parameters was performed to develop a formula for predicting true uninfected individuals. Results A total of 528 subjects were classified as true uninfected individuals. Logistic regression analysis showed that statistically significant factors for true uninfected individuals were age (p < 0.001), HP antibody (p <0.001), PGI (p <0.001), and PGII (p = 0.012). The areas under the curve (AUCs) for true uninfected individuals were the highest (0.944) upon applying the prediction formula including four parameters: age, HP antibody, PGI, and PGII. Both the sensitivity and the specificity of the four-parameter prediction formula were higher than those of the traditional three-parameter model using HP antibody, PGI, and PGI/II ratio (sensitivity: 93.2% vs. 86.6% and specificity: 88.5% vs. 82.7%). Conclusions Our findings suggest that a model with a combination of four noninvasive parameters is useful for predicting true HP-uninfected individuals without the need for endoscopic examination.