DOI: 10.4103/ijmy.ijmy_105_26 ISSN: 2212-5531
Primary Drug Resistance Analysis of Mycobacterium tuberculosis in Liupanshui, China
Shunfu Yu, Ting Xu, Guangyou Yan, Hong Xiao, Shengxu Deng, Shaojing Fu, Honglin Liu
Background:
Drug-resistant tuberculosis (DR-TB) remains a major global public health challenge, while local drug resistance data in southwestern China are still incomplete. The drug resistance characteristics of
Mycobacterium tuberculosis
(MTB) in the Liupanshui area have not been systematically reported, and the clinical application value of the high-resolution melting (HRM) method for drug resistance detection in this region also lacks evaluation evidence.
Methods:
From February 2023 to September 2025, 1200 TB patients who attended designated TB treatment facilities in Liupanshui City were enrolled. The HRM method was used to detect resistance to isoniazid (INH), rifampicin (RFP), ethambutol (EMB), and fluoroquinolones (FQs). Meanwhile, among the culture-positive isolates (
n
= 506), phenotypic drug susceptibility testing using the proportion method was performed for INH, RFP, EMB, levofloxacin (LVFX), and moxifloxacin (MOX). Univariate Chi-square tests and Cramer’s V coefficient were employed to assess associations between clinical variables and drug resistance, and multivariate logistic regression was used to identify independent influencing factors for resistance. All effect estimates were supplemented with 95% confidence intervals (CIs). The Bonferroni method was applied for multiple testing correction, with three independent multiple comparison scenarios established in this study, and the corrected significance levels (α’) were set at 0.0125, 0.01, and 0.0167, respectively.
Results:
Among the 1200 patients, 67.6% were male, and 86.1% were newly treated. The HRM method detected resistance rates of 12.8% (95% CI: 11.1%–14.8%) for INH, 13.1% (95% CI: 11.3%–15.1%) for RFP, 5.4% (95% CI: 4.3%–6.8%) for EMB, and 2.4% (95% CI: 1.7%–3.4%) for FQs. For the proportion method (
n
= 506), the resistance rates were 15.6% (95% CI: 12.9%–19.2%) for INH, 17.2% (95% CI: 13.3%–19.7%) for RFP, 9.9% (95% CI: 7.6%–12.8%) for EMB, 3.4% (95% CI: 2.1%–5.3%) for LVFX, and 1.8% (95% CI: 0.9%–3.3%) for MOX. The overall prevalence of multidrugresistant TB (MDR-TB) in the study population was 8.0% (95% CI: 6.6%–9.7%), with 7.3% (95% CI: 5.8%–9.0%) in newly treated patients and 12.6% (95% CI: 8.4%–18.5%) in retreated patients. Agreement between the HRM method and the proportion method was excellent for INH and RFP (Kappa: 0.93 [95% CI: 0.89–0.97] and 0.95 [95% CI: 0.92–0.98], respectively), moderate for EMB (Kappa: 0.62 [95% CI: 0.54–0.70]), and good for FQs (Kappa: 0.82 [95% CI: 0.74–0.90]). The positive predictive values of the HRM method for INH and RFP were 97.3% and 93.1%, respectively, and the negative predictive values were 98.4% and 99.8%, indicating excellent diagnostic performance. Regularity of treatment was strongly correlated with genetic resistance to all four drugs (
P
< 0.001, Cramer’s V coefficient: 0.115–0.632), and retreatment was significantly associated with RFP genetic resistance (
P
< 0.001, Cramer’s V coefficient: 0.133). Multivariate logistic regression analysis showed that irregular treatment was an independent risk factor for RFP resistance (odds ratio = 59.94, 95% CI: 34.78–103.26,
P
< 0.001).
Conclusion:
The burden of DR-TB in Liupanshui area is substantial. The RFP resistance rate among newly treated patients (11.2%) exceeded the national baseline level for new cases. The prevalence of MDR-TB was relatively high, and retreated patients had a significantly elevated risk of resistance. The HRM method can serve as a rapid screening tool but should be complemented with phenotypic drug susceptibility testing for confirmation. Management of treatment adherence is a key element in controlling drug resistance. The findings of this study provide evidence-based support for the formulation of precise prevention and control strategies for TB in the Liupanshui area.