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目的 分析人类免疫缺陷病毒(human immunodeficiency virus, HIV)感染者合并乙型肝炎病毒(hepatitis B virus, HBV)感染的相关影响因素，基于临床特征及T细胞亚群构建并验证列线图风险预测模型。方法 采用回顾性研究方法，选取2017年1月至2022年6月南通市第三人民医院收治的150例HIV感染者作为研究对象，根据是否合并HBV感染分为合并感染组与未合并感染组。收集并比较两组患者的临床资料及实验室指标，对单因素分析中存在差异的指标进行共线性诊断，将不存在共线性的变量纳入多因素Logistic回归分析，筛选HIV感染者合并HBV感染的独立影响因素。利用R语言基于回归分析中有统计学意义的变量构建列线图预测模型，并进行内部验证。结果 在150例HIV感染者中，合并HBV感染者22例(14.67%)，未合并感染128例(85.33%)。两组在年龄、HBV家族史、乙型肝炎疫苗接种史、CD4~+T淋巴细胞、CD4+/CD8+水平方面差异均有统计学意义(均P<0.05)，且这些变量间均无共线性问题(VIF≤10，容忍度≥0.1)。多因素Logistic回归分析显示，年龄(OR=3.846,P=0.029)、HBV家族史(OR=46.750,P=0.001)、无乙型肝炎疫苗接种史(OR=3.278,P=0.035)是合并HBV感染的危险因素(均P<0.01)，而CD4~+T淋巴细胞(OR=0.942,P=0.001)和CD4+/CD8+(OR=0.004,P=0.001)为保护因素(均P<0.01)。基于上述6个预测因子构建列线图预测模型，内部验证显示受试者工作特征曲线下面积为0.955(95%CI:0.913～0.998)，校准曲线拟合良好(P=0.353),Cox-Snell R2=0.689,Nagelkerke R2=0.39，提示模型区分度与校准度良好，未出现过拟合；决策曲线分析显示该列线图在较大阈值范围内具有较高的临床净收益。结论 年龄、HBV家族史、乙型肝炎疫苗接种史、CD4~+T淋巴细胞、CD4+/CD8+均为影响HIV感染者合并HBV感染的独立影响因素，基于上述因素构建的列线图预测模型具有良好的预测效能，可用于HIV感染者合并HBV感染风险的早期分层筛查。
Abstract：Objective To analyze the factors associated with co-infection with hepatitis B virus(HBV) in human immunodeficiency virus(HIV)-infected patients, and to develop and validate a nomogram prediction model based on clinical characteristics and T-cell subsets. Methods A retrospective study was conducted on 150 HIV-infected patients admitted to Nantong Third People's Hospital between January 2017 and June 2022. Based on their HBV co-infection status, the patients were divided into co-infected group and non-co-infected group. Clinical data and laboratory indicators of patients were collected and compared between the 2 groups. Variables that showed significant differences in univariate analysis were screened for multicollinearity, and those without collinearity were included in multivariate logistic regression analysis to identify predictors factors for HBV co-infection. Using R software, a nomogram prediction model was constructed based on statistically significant variables from the multivariate logistic analysis, and internal validation was performed. Results Among the 150 HIV-infected individuals, 22 cases(14.67%) were co-infected with HBV and 128 cases(85.33%) were not co-infected. There were statistically significant differences between the 2 groups in terms of age, family history of HBV, history of hepatitis B vaccination, CD4+ T lymphocytes, and CD4+/CD8+ levels(P<0.05), and there was no collinearity problem among these variables(VIF≤10, tolerance≥0.1). Multivariate Logistic regression analysis showed that Age(OR=3.846, P=0.029), family history of HBV(OR=46.750, P=0.001), and no history of hepatitis B vaccination(OR=3.278, P=0.035) were risk factors for concurrent HBV infection(P<0.01). CD4+ T lymphocytes(OR=0.942, P=0.001) and CD4+/CD8+(OR=0.004, P=0.001) were protective factors(P<0.01). A nomogram prediction model was constructed based on the above 5 predictors. Internal validation showed that the area under the receiver operating characteristic curve was 0.955(95%CI: 0.913-0.998), the calibration curve fitted well(P=0.353), Cox-Snell R2=0.689, Nagelkerke R2=0.39, suggesting that the model had good discrimination and calibration, and no overfitting occurred. Decision curve analysis shows that this nomogram has a relatively high clinical net benefit within a large threshold range. Conclusion Age, family history of HBV, history of hepatitis B vaccination, CD4+ T lymphocytes, and CD4+/CD8+ are all independent influencing factors affecting HBV infection in HIV-infected individuals. The nomogram prediction model constructed based on the above factors has good predictive efficacy. It can provide quantitative tools for the early stratified screening of the risk of HBV infection in HIV-infected individuals.
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基本信息:
中图分类号:R512.62;R512.91
引用信息:
[1]吴丛霞,徐晶晶,文小平,等.基于临床特征与T细胞亚群构建HIV感染者合并HBV感染列线图风险预测模型[J].传染病信息,2026,39(01):7-13.
基金信息:
南通市科技计划项目（MSZ2023129）
2026-02-28
2026-02-28