Liu Lin, Chen Shunqiang
Department of Painology, Henan Provincial People's Hospital, Zhengzhou, China.
Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China.
Front Med (Lausanne). 2025 Jun 18;12:1619157. doi: 10.3389/fmed.2025.1619157. eCollection 2025.
To explore the feasibility and clinical value of establishing a prediction model of post-herpetic neuralgia (PHN) based on T cell functional indicators (CD4+/CD8+ ratio, Treg cell ratio) and inflammatory factors (IL-6, TNF-, and IL-10).
A total of 260 patients with herpes zoster who were admitted to our hospital from June 2022 to November 2024 were included in the study. The 7:3 score was used as the training set ( = 182) and verification set ( = 78). The clinical data were collected and the peripheral blood T cell subsets and inflammatory factor levels were detected. Risk factors were screened by univariate and multivariate Logistic regression, and a nomogram model was constructed for efficacy evaluation and verification.
The incidence of PHN in the training set was 29.67%(54/182) and the verification set was 30.77%(24/78). Multivariate regression analysis showed that age, CD4+/CD8+ ratio, Treg cell ratio, IL-6, TNF-, and IL-10 were the independent risk factors ( < 0.05). The C-index values for the nomogram models in the training and validation sets were 0.804 and 0.789, respectively, the AUC values were 0.802 (95% CI: 0.722-0.882) and 0.790 (95% CI: 0.642-0.938), and the sensitivity and specificity values were 0.634, 0.875, and 0.462 and 0.875, respectively. The calibration curve showed good agreement between the predicted and actual values with mean absolute errors of 0.164 and 0.146, respectively, which was good by the Hosmer-Lemeshow test.
The nomogram model based on T cell function and inflammatory factors can effectively predict the risk of PHN and provide the basis for early clinical intervention.
探讨基于T细胞功能指标（CD4+/CD8+比值、调节性T细胞比例）和炎症因子（白细胞介素-6、肿瘤坏死因子-α和白细胞介素-10）建立带状疱疹后神经痛（PHN）预测模型的可行性及临床价值。
选取2022年6月至2024年11月我院收治的260例带状疱疹患者纳入研究。采用7:3比例分为训练集（n = 182）和验证集（n = 78）。收集临床资料，检测外周血T细胞亚群及炎症因子水平。通过单因素和多因素Logistic回归筛选危险因素，并构建列线图模型进行效能评估及验证。
训练集PHN发生率为29.67%（54/182），验证集为30.77%（24/78）。多因素回归分析显示，年龄、CD4+/CD8+比值、调节性T细胞比例、白细胞介素-6、肿瘤坏死因子-α和白细胞介素-10为独立危险因素（P < 0.05）。训练集和验证集列线图模型的C指数值分别为0.804和0.789，AUC值分别为0.802（95%CI：0.722 - 0.882）和0.790（95%CI：0.642 - 0.938），敏感度和特异度值分别为0.634、0.875以及0.462和0.875。校准曲线显示预测值与实际值一致性良好，平均绝对误差分别为0.164和0.146，经Hosmer-Lemeshow检验结果良好。
基于T细胞功能和炎症因子的列线图模型可有效预测PHN风险，为临床早期干预提供依据。
