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已发表论文
基于 GeneXpert MTB/RIF 检测预测儿童耐药结核病的列线图模型
Authors Wang L, Ma W, Wei N, Guo W, Zhao D, Zhou N, Guo X, Han M, Zhang F, Guo C, Li S
Received 12 June 2025
Accepted for publication 21 January 2026
Published 13 February 2026 Volume 2026:19 542863
DOI https://doi.org/10.2147/IDR.S542863
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Hazrat Bilal
Lingchao Wang,1,* Weiwei Ma,1,* Na Wei,1 Weijie Guo,2 Dean Zhao,1 Nan Zhou,1 Xiaonan Guo,1 Meigui Han,1 Fangmin Zhang,1 Can Guo,2 Shujun Li1
1Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), Weihui, 453100, People’s Republic of China; 2Department of Tuberculosis, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), Weihui, 453100, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shujun Li, Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), No. 88 of Jiankang Road, Weihui, Henan, 453100, People’s Republic of China, Tel +86 13781905766, Fax +86 0373-4402573, Email ruolin2223@126.com Dean Zhao, Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), No. 88 of Jiankang Road, Weihui, Henan, 453100, People’s Republic of China, Tel +86 13781905766, Fax +86 0373-4402573, Email zhaodean6@21cn.com
Objective: To develop and validate a clinical-imaging integrated nomogram predictive model for DR-TB risk in pediatric patients (≤ 18 years), and to evaluate the diagnostic performance of the GeneXpert MTB/RIF assay in this context.
Methods: This retrospective study included 223 patients with TB aged ≤ 18 years hospitalised between 1 July 2018 and 31 December 2023. Drug resistance profiles were analysed, and the clinical/imaging features of DR-TB were compared with those of drug-susceptible TB (DS-TB). Multivariate logistic regression was used to identify DR-TB risk factors.
Results: Of the 223 patients, 73.5% had DS-TB and 26.5% had DR-TB (including 13.5% with multidrug-resistant TB). Resistance rates to first-line drugs were as follows: isoniazid 22.4%, rifampicin 16.1%, streptomycin 8.1% and ethambutol 3.6%. Independent DR-TB risk factors were retreatment (odds ratio [OR] = 5.303, 95% confidence interval [CI]: 1.378– 20.414), smoking history (OR = 4.129, 95% CI: 1.233– 13.825), right middle lobe involvement (OR = 3.004, 95% CI: 1.148– 7.863) and cavity formation (OR = 2.950, 95% CI: 1.325– 6.567) (all P < 0.05). A nomogram model was developed, with an area under the curve of 0.776, showing effective predictive performance and clinical utility. The GeneXpert MTB/RIF assay had 87.5% sensitivity and 90.48% specificity for detecting rifampicin resistance, with good agreement with drug susceptibility testing (kappa 0.751) (P < 0.001). No significant differences in T-lymphocyte subsets were found between the DR-TB and DS-TB groups.
Conclusion: In children and adolescents, TB is more common in older individuals and consists primarily of new cases. The nomogram model has good predictive value for DR-TB risk. Key predictors include retreatment, smoking, right middle lobe involvement and cavity formation. The GeneXpert MTB/RIF assay is a potential early screening tool for DR-TB. Further validation with larger samples is needed.
Keywords: drug-resistant tuberculosis, GeneXpert MTB/RIF, Mycobacterium tuberculosis, nomogram predictive model, paediatric tuberculosis
1Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), Weihui, 453100, People’s Republic of China; 2Department of Tuberculosis, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), Weihui, 453100, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shujun Li, Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), No. 88 of Jiankang Road, Weihui, Henan, 453100, People’s Republic of China, Tel +86 13781905766, Fax +86 0373-4402573, Email ruolin2223@126.com Dean Zhao, Department of Pediatric, The First Affiliated Hospital of Henan Medical University (formerly The First Affiliated Hospital of Xinxiang Medical University), No. 88 of Jiankang Road, Weihui, Henan, 453100, People’s Republic of China, Tel +86 13781905766, Fax +86 0373-4402573, Email zhaodean6@21cn.com
Objective: To develop and validate a clinical-imaging integrated nomogram predictive model for DR-TB risk in pediatric patients (≤ 18 years), and to evaluate the diagnostic performance of the GeneXpert MTB/RIF assay in this context.
Methods: This retrospective study included 223 patients with TB aged ≤ 18 years hospitalised between 1 July 2018 and 31 December 2023. Drug resistance profiles were analysed, and the clinical/imaging features of DR-TB were compared with those of drug-susceptible TB (DS-TB). Multivariate logistic regression was used to identify DR-TB risk factors.
Results: Of the 223 patients, 73.5% had DS-TB and 26.5% had DR-TB (including 13.5% with multidrug-resistant TB). Resistance rates to first-line drugs were as follows: isoniazid 22.4%, rifampicin 16.1%, streptomycin 8.1% and ethambutol 3.6%. Independent DR-TB risk factors were retreatment (odds ratio [OR] = 5.303, 95% confidence interval [CI]: 1.378– 20.414), smoking history (OR = 4.129, 95% CI: 1.233– 13.825), right middle lobe involvement (OR = 3.004, 95% CI: 1.148– 7.863) and cavity formation (OR = 2.950, 95% CI: 1.325– 6.567) (all P < 0.05). A nomogram model was developed, with an area under the curve of 0.776, showing effective predictive performance and clinical utility. The GeneXpert MTB/RIF assay had 87.5% sensitivity and 90.48% specificity for detecting rifampicin resistance, with good agreement with drug susceptibility testing (kappa 0.751) (P < 0.001). No significant differences in T-lymphocyte subsets were found between the DR-TB and DS-TB groups.
Conclusion: In children and adolescents, TB is more common in older individuals and consists primarily of new cases. The nomogram model has good predictive value for DR-TB risk. Key predictors include retreatment, smoking, right middle lobe involvement and cavity formation. The GeneXpert MTB/RIF assay is a potential early screening tool for DR-TB. Further validation with larger samples is needed.
Keywords: drug-resistant tuberculosis, GeneXpert MTB/RIF, Mycobacterium tuberculosis, nomogram predictive model, paediatric tuberculosis