AUTHOR=Chen Haiyan , Tong Zhaowei , Zhong Jianfeng , Tong Yong , Zeng Qingqiu , Shen Bin , Song Qun , Qian Fuchu , Xiao Xin 

TITLE=Prediction of risk factors associated with the development of multidrug-resistant tuberculosis in patients with tuberculosis

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1588196

DOI=10.3389/fpubh.2025.1588196

ISSN=2296-2565

ABSTRACT=ObjectiveThis study aimed to develop and validate a reliable nomogram based on clinical factors to predict development of multidrug-resistant tuberculosis (MDR-TB) associated with individuals with tuberculosis (TB), so as to reduce the harm and economic burden caused by disease progression.MethodsThe study included 4,251 individuals with TB who received treatment at Huzhou Central Hospital between January 2016 and December 2023, excluding 87 individuals because of infection with non-TB mycobacterium or incomplete information (including missing laboratory or clinical data). A total of 4,164 individuals (2,261 sputum smear-positive and 1,903 sputum smear-negative patients) were ultimately included in the analysis. This analysis incorporated clinical baseline presentations, demographic information, imaging findings, laboratory results, and clinical diagnoses to develop a predictive model for MDR-TB.ResultsThis study demonstrated that sex, age, a history of anti-TB therapy, body mass index (BMI) ≤ 18.5, smoking history, occupation, previously diagnosed TB, pulmonary cavitation, comorbidities, poverty, and C-reactive protein (CRP) ≥ 37.3 mg/L were major risk factors for MDR-TB in patients with TB. The area under the receiver operating characteristic (ROC) curve was 0.902 for the training group and 0.909 for the validation group. Calibration curve analysis revealed that the predicted and actual incidence rates of MDR-TB in the two groups were in good agreement, whereas decision curve analysis (DCA) indicated that the predictive model resulted in better clinical benefit.ConclusionThe nomogram model established in this study included 11 clinical characteristics and demographic features of patients with TB, which may be valuable for predicting MDR-TB.