Tsukuba Preventive Medical Research Center, University of Tsukuba Hospital, Tsukuba, Japan.
Department of Gastroenterology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.
Medicine (Baltimore). 2024 Mar 1;103(9):e36335. doi: 10.1097/MD.0000000000036335.
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.
ABC 分类法根据血清幽门螺杆菌(H pylori)抗体和胃蛋白酶原水平对胃癌风险进行分类,但存在将高危个体错误分类为低危的局限性。为了解决这个问题,我们之前使用逻辑回归分析开发了一个四参数预测公式(年龄、血清 H pylori 抗体、PGI 和 PGII),以准确识别低危真正未感染状态。与基于乳胶免疫测定试剂盒的改良 ABC 分类法(传统三参数模型)相比,我们的预测公式在区分低危真正未感染个体和高危当前/自发根除状态个体方面具有更高的敏感性和特异性。本研究旨在在新的、不同的研究人群中重新验证预测公式的诊断准确性。我们将预测公式应用于目标人群,并将其敏感性和特异性与传统三参数模型进行比较。共分析了 788 名参与者:根据粪便抗原检测和内镜检查结果,703 名被分类为真正未感染,45 名当前感染,40 名自发根除。预测公式和传统三参数模型的敏感性和特异性分别为 89.5%和 87.1%与 89.8%和 80.0%。在 70 至 89 岁年龄范围和 H pylori 抗体<3 U/mL 组中,预测公式的特异性更高。预测公式的特异性优于传统三参数模型。这些结果应该有助于通过预测 H pylori 感染状态来提高胃癌筛查的效率。