T淋巴细胞亚群、B淋巴细胞及NK细胞水平与高危型HPV感染预后的相关性

Correlation of T lymphocyte subsets, B lymphocytes and NK cell levels with the prognosis of high-risk HPV infection

  • 摘要:
    目的  探究T淋巴细胞亚群(CD3+T淋巴细胞、CD4+T淋巴细胞、CD8+T淋巴细胞)、CD19+ B淋巴细胞及自然杀伤(NK)细胞水平与高危型人乳头状瘤病毒(HR-HPV)感染患者预后的相关性。
    方法  回顾性选取2021年1月至2022年2月广州市红十字会医院收治的子宫颈HR-HPV患者210例。根据随访2年内,患者HR-HPV感染的转归情况,分为阴性组(n = 94)与阳性组(n = 116)。另选取2022年3月至2023年1月间收治的子宫颈HR-HPV患者90例为验证集。通过单因素及多因素Logistic逐步回归分析各因素对HR-HPV转归的影响,基于随访24个月转归构建的子宫颈HR-HPV患者转阴概率绘制列线图。采用受试者操作特征(ROC)曲线评估免疫细胞联合预测、临床指标和Logistic模型对HR-HPV转归的相关价值。采用校准曲线和临床决策曲线分析评估Logistic模型的预测效能及临床应用价值,并在验证集中进行验证。
    结果  年龄、既往阴道微生态异常史、HPV感染型别、宫颈细胞学检查结果、CD3+T淋巴细胞、CD4+T淋巴细胞、CD8+T淋巴细胞、CD19+B淋巴细胞及NK细胞为HR-HPV患者随访24个月预后的相关因素(均P < 0.05)。Logistic模型的AUC值高于仅含临床特征的模型,表明免疫学指标能提升对HR-HPV感染转归的预测效能。Logistic模型在训练集及验证集中均表现出良好的校准度和临床获益。
    结论 CD3+T淋巴细胞、CD4+T淋巴细胞、CD8+T淋巴细胞、CD19+B淋巴细胞、NK细胞为子宫颈HR-HPV转归的相关因素。

     

    Abstract:
    Objective  To investigate the correlation of T lymphocyte subsets, including CD3+T lymphocytes, CD4+T lymphocytes and CD8+T lymphocytes, CD19+B lymphocytes, and natural killer (NK) cell levels with the prognosis of patients with high-risk human papillomavirus (HR-HPV) infection.
    Methods A total of 210 patients with cervical HR-HPV infection admitted to Guangzhou Red Cross Hospital from January 2021 to February 2022 were retrospectively selected. According to the outcome of HR-HPV infection during two years of follow-up, the patients were divided into a negative group (n = 94) and a positive group (n = 116). Another 90 patients with cervical HR-HPV infection admitted between March 2022 and January 2023 were selected as the validation set. Univariate and multivariate stepwise Logistic regression analyses were used to analyze the effects of various factors on HR-HPV outcomes. A nomogram for the probability of HR-HPV clearance in patients with cervical HR-HPV infection was constructed based on the outcomes after 24 months of follow-up. Receiver operating characteristic (ROC) curves were used to evaluate the value of combined immune cell prediction, clinical indicators, and the Logistic model in relation to HR-HPV outcomes. Calibration curves and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical application value of the Logistic model, which was further validated in the validation set.
    Results Age, history of vaginal microecological abnormality, HPV infection type, cervical cytology results, CD3+ T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes, CD19+ B lymphocytes, and NK cells were factors associated with the 24-month prognosis of patients with HR-HPV infection (all P < 0.05). The area under the curve (AUC) of the Logistic model was higher than that of the model containing only clinical features, indicating that immunological indicators could improve the predictive performance for the outcome of HR-HPV infection. The Logistic model showed good calibration and clinical benefit in both the training set and the validation set.
    Conclusions CD3+ T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes, CD19+ B lymphocytes, and NK cells are factors associated with the outcome of cervical HR-HPV infection.

     

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