Abstract
The ABC classification, which categorizes gastric cancer risk based on serum Helicobacter pylori (H pylori) antibody and pepsinogen levels, has a limitation of potentially misclassifying high-risk individuals as low risk. To overcome the problem, we previously developed a 4-parameter predictive formula (age, serum H pylori antibody, PGI, and PGII) using logistic regression analysis to accurately identify low-risk truly H pylori-uninfected status. Our predictive formula demonstrated superior sensitivity and specificity in distinguishing between low-risk truly uninfected individuals and high-risk currently/spontaneously eradicated status individuals, compared to the modified ABC classification based on latex immunoassay kits (traditional 3-parameter model). This study aimed to revalidate the diagnostic accuracy of the predictive formula in a new and different study population. We applied the predictive formula to the target population and compared the sensitivity and specificity with those of the traditional 3-parameter model. A total of 788 enrollees were analyzed: 703 were classified as truly uninfected, 45 as currently infected, and 40 as spontaneously eradicated according to the results of stool antigen testing and endoscopic findings. The sensitivities and specificities of the predictive formula and the traditional 3-parameter model were 89.5% and 87.1% versus 89.8% and 80.0%, respectively. The specificity of the predictive formula was superior in the 70 to 89 age range and H pylori antibody < 3 U/mL groups. The predictive formula had higher specificity than the traditional 3-parameter model. The results should contribute to efficient gastric cancer screening by predicting H pylori infection status.