Peripheral blood lymphocytes influence human papillomavirus infection and clearance: a retrospective cohort study

There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers...

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Published inVirology journal Vol. 20; no. 1; p. 80
Main Authors Li, Ye, Feng, Yebin, Chen, Yanlin, Lin, Wenyu, Gao, Hangjing, Chen, Ming, Osafo, Kelvin Stefan, Mao, Xiaodan, Kang, Yafang, Huang, Leyi, Liu, Dabin, Xu, Shuxia, Huang, Lixiang, Dong, Binhua, Sun, Pengming
Format Journal Article
LanguageEnglish
Published England BioMed Central Ltd 01.05.2023
BioMed Central
BMC
Subjects
Accuracy
Biomarkers
Blood
Cancer therapies
CD4 antigen
CD4-Positive T-Lymphocytes
CD8 antigen
Cervix
Childrens health
Cohort analysis
cohort studies
Colposcopy
Female
Hepatitis
HPV clearance
Human papillomavirus
Human Papillomavirus Viruses
Human papillomavirus, peripheral lymphocyte subsets, HPV infection
Humans
Identification and classification
Immune clearance
Immune status
Immunology
Infections
Influence
Lymphocytes
Lymphocytes T
Maternal & child health
Natural killer cells
Papillomaviridae
Papillomavirus Infections
patients
Peripheral blood
prediction
Prediction model
Prediction models
Regression analysis
Retrospective Studies
risk
risk assessment
Risk factors
Risk groups
T-lymphocytes
Tumors
Womens health
China
Prediction model
HPV clearance
Human papillomavirus, peripheral lymphocyte subsets, HPV infection
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Abstract There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
AbstractList There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan-Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
BackgroundThere is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term.MethodsThis study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values.ResultsLower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16–2.15), 1.71 (1.23–2.36), 2.37 (1.12–5.02), and 3.67 (1.78–7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold.ConclusionsCD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term.BACKGROUNDThere is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term.This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values.METHODSThis study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values.Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold.RESULTSLower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold.CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.CONCLUSIONSCD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
Background There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. Methods This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan-Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. Results Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16-2.15), 1.71 (1.23-2.36), 2.37 (1.12-5.02), and 3.67 (1.78-7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. Conclusions CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management. Keywords: Human papillomavirus, peripheral lymphocyte subsets, HPV infection, HPV clearance, Prediction model
BACKGROUND: There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. METHODS: This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. RESULTS: Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16–2.15), 1.71 (1.23–2.36), 2.37 (1.12–5.02), and 3.67 (1.78–7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. CONCLUSIONS: CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
Abstract Background There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood influence human papillomavirus (HPV) infection and to identify whether peripheral blood lymphocyte (PBL) subsets could be used as biomarkers to predict HPV clearance in the short term. Methods This study involved 716 women undergoing colposcopy from 2019 to 2021. Logistic and Cox regression were used to analyze the association of PBLs with HPV infection and clearance. Using Cox regression, bidirectional stepwise regression and the Akaike information criterion (AIC), lymphocyte prediction models were developed, with the C-index assessing performance. ROC analysis determined optimal cutoff values, and their accuracy for HPV clearance risk stratification was evaluated via Kaplan‒Meier and time-dependent ROC. Bootstrap resampling validated the model and cutoff values. Results Lower CD4 + T cells were associated with a higher risk of HPV, high-risk HPV, HPV18 and HPV52 infections, with corresponding ORs (95% CI) of 1.58 (1.16–2.15), 1.71 (1.23–2.36), 2.37 (1.12–5.02), and 3.67 (1.78–7.54), respectively. PBL subsets mainly affect the natural clearance of HPV, but their impact on postoperative HPV outcomes is not significant (P > 0.05). Lower T-cell and CD8 + T-cell counts, as well as a higher NK cell count, are unfavorable factors for natural HPV clearance (P < 0.05). The optimal cutoff values determined by the PBL prognostic model (T-cell percentage: 67.39%, NK cell percentage: 22.65%, CD8 + T-cell model risk score: 0.95) can effectively divide the population into high-risk and low-risk groups, accurately predicting the natural clearance of HPV. After internal validation with bootstrap resampling, the above conclusions still hold. Conclusions CD4 + T cells were important determinants of HPV infection. T cells, NK cells, and CD8 + T cells can serve as potential biomarkers for predicting natural HPV clearance, which can aid in patient risk stratification, individualized treatment, and follow-up management.
ArticleNumber 80
Audience Academic
Author Chen, Yanlin
Dong, Binhua
Sun, Pengming
Feng, Yebin
Lin, Wenyu
Osafo, Kelvin Stefan
Mao, Xiaodan
Li, Ye
Chen, Ming
Xu, Shuxia
Gao, Hangjing
Kang, Yafang
Huang, Lixiang
Huang, Leyi
Liu, Dabin
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37127618$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords Prediction model
HPV clearance
Human papillomavirus, peripheral lymphocyte subsets, HPV infection
Language English
License 2023. The Author(s).
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Snippet There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in peripheral blood...
Background There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in...
BackgroundThere is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in...
BACKGROUND: There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes in...
Abstract Background There is a close correlation between HPV infection and systemic immune status. The purpose of this study was to determine which lymphocytes...
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SubjectTerms Accuracy
Biomarkers
Blood
Cancer therapies
CD4 antigen
CD4-Positive T-Lymphocytes
CD8 antigen
Cervix
Childrens health
Cohort analysis
cohort studies
Colposcopy
Female
Hepatitis
HPV clearance
Human papillomavirus
Human Papillomavirus Viruses
Human papillomavirus, peripheral lymphocyte subsets, HPV infection
Humans
Identification and classification
Immune clearance
Immune status
Immunology
Infections
Influence
Lymphocytes
Lymphocytes T
Maternal & child health
Natural killer cells
Papillomaviridae
Papillomavirus Infections
patients
Peripheral blood
prediction
Prediction model
Prediction models
Regression analysis
Retrospective Studies
risk
risk assessment
Risk factors
Risk groups
T-lymphocytes
Tumors
Womens health
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Title Peripheral blood lymphocytes influence human papillomavirus infection and clearance: a retrospective cohort study
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