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已发表论文
中国青少年活动性肺结核早期诊断中淋巴细胞免疫学指标分析
Authors Zhang H , Yang L, Sun Y, Zhang Z, Zhou J
Received 24 June 2025
Accepted for publication 17 December 2025
Published 26 December 2025 Volume 2025:18 Pages 6961—6971
DOI https://doi.org/10.2147/IDR.S549262
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Sandip Patil
Haiying Zhang,1 Li Yang,2 Yang Sun,3 Zhi Zhang,2 Jikun Zhou1,4
1School of Public Health, Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Laboratory Medicine, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China; 3Department of Tuberculosis, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China; 4The Institute of Medical Research, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China
Correspondence: Jikun Zhou, The Institute of Medical Research, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China, Email 13933880581@163.com
Introduction: The aim of this study was to detect lymphocyte subpopulations to discover potential immunologic indicators to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and healthy controls (HC) and to predict the risk of progression of LTBI to ATB.
Methodology: Flow cytometry was used to detect lymphocyte subsets in ATB, LTBI and HC to compare the differences in lymphocyte subpopulation levels between groups, and Logistic regression was used to screen ATB-related immune indices, development of a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI.
Results: Compared to the LTBI group, the ATB group had significantly higher CD3+CD4+T cell percentage, whereas CD3−CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, CD3+CD8+T cell number, and CD3−CD16+CD56+NK cell number were significantly lower (P< 0.05). Compared with the HC group, the ATB group had significantly higher CD3+T cell percentage and CD3+CD4+T cell percentage, whereas CD3−CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, and CD3−CD16+CD56+NK cell number were significantly lower (P< 0.05); logistic regression analysis showed that CD3+CD4+T cell percentage, CD3+T cell number, and CD3+CD8+T cell number were all independent indicators for the diagnosis of ATB (P< 0.05), and based on these three immune indicators, we constructed diagnostic feature to distinguish ATB and LTBI, ATB from HC, and successfully developed a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI.
Conclusion: A combined assay of lymphocyte-associated immune markers serves as a biomarker for early ATB diagnosis in adolescents, and established a predictive model to evaluate the risk of progression of LTBI to ATB.
Keywords: active tuberculosis, latent tuberculosis infection, lymphocyte subsets, mycobacterium tuberculosis, Tuberculosis
1School of Public Health, Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Laboratory Medicine, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China; 3Department of Tuberculosis, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China; 4The Institute of Medical Research, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China
Correspondence: Jikun Zhou, The Institute of Medical Research, The Fifth Hospital of Shijiazhuang, Shijiazhuang, Hebei, People’s Republic of China, Email 13933880581@163.com
Introduction: The aim of this study was to detect lymphocyte subpopulations to discover potential immunologic indicators to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and healthy controls (HC) and to predict the risk of progression of LTBI to ATB.
Methodology: Flow cytometry was used to detect lymphocyte subsets in ATB, LTBI and HC to compare the differences in lymphocyte subpopulation levels between groups, and Logistic regression was used to screen ATB-related immune indices, development of a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI.
Results: Compared to the LTBI group, the ATB group had significantly higher CD3+CD4+T cell percentage, whereas CD3−CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, CD3+CD8+T cell number, and CD3−CD16+CD56+NK cell number were significantly lower (P< 0.05). Compared with the HC group, the ATB group had significantly higher CD3+T cell percentage and CD3+CD4+T cell percentage, whereas CD3−CD16+CD56+NK cell percentage, lymphatic cell, CD3+T cell number, and CD3−CD16+CD56+NK cell number were significantly lower (P< 0.05); logistic regression analysis showed that CD3+CD4+T cell percentage, CD3+T cell number, and CD3+CD8+T cell number were all independent indicators for the diagnosis of ATB (P< 0.05), and based on these three immune indicators, we constructed diagnostic feature to distinguish ATB and LTBI, ATB from HC, and successfully developed a novel nomogram model to predict the risk of progression to ATB in individuals with LTBI.
Conclusion: A combined assay of lymphocyte-associated immune markers serves as a biomarker for early ATB diagnosis in adolescents, and established a predictive model to evaluate the risk of progression of LTBI to ATB.
Keywords: active tuberculosis, latent tuberculosis infection, lymphocyte subsets, mycobacterium tuberculosis, Tuberculosis