Wang Xinyue, Shang Anquan, Chen Haowei, Li Jing, Jiang Yuan, Wang Lili, Qiu Shuai, Sun Fenyong, Yue Chaoyan
Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, PR China.
Department of Laboratory Medicine, The Second People's Hospital of Lianyungang, Clinical College of Xuzhou Medical University, Lianyungang 222006, PR China.
Drug Resist Updat. 2025 Sep;82:101265. doi: 10.1016/j.drup.2025.101265. Epub 2025 Jun 2.
Utilizing Global Burden of Disease Study (GBD 2021) data, this study aims to illustrate trends and spatiotemporal patterns of multidrug-resistant tuberculosis (MDR-TB) burden from 1990 to 2021, and explore their potential mechanisms.
This research extracted core indicators including incidence, mortality, prevalence, and disability-adjusted life years (DALYs), with their age-standardized rate (ASR). Joinpoint regression, age-period-cohort analysis, inequality analysis, and frontier analysis were applied to describe the temporal and spatial trends of the disease burden. Decomposition analysis and risk factor analysis were performed to explore factors associated with MDR-TB burden fluctuation. Bayesian Age-Period-Cohort (BAPC) model was used to project the disease burden till 2050.
Global MDR-TB cases and ASRs of all indicators rose from 1990 to 2021, with heavier burden in older populations and lower socioeconomic regions. Cross-country inequality widened over time. Frontier analysis identified countries including India and Russia with considerable potential for improvement in disease control. Decomposition analysis uncovered epidemiological changes as the main driver of the growing burden globally. Risk factors of MDR-TB in different regions and age groups were heterogeneous. The numbers and ASRs of all indicators are predicted to increase by 2050.
This study revealed that the global disease burden of MDR-TB increased from 1990 to 2021 and is predicted to grow till 2050. Disparities among different social-demographic regions were remarkable and extended over time. Epidemiological changes contributed most to the escalated disease burden. Targeted public health strategies should be adopted for patients in specific regions and age groups.
利用全球疾病负担研究(GBD 2021)数据,本研究旨在阐明1990年至2021年耐多药结核病(MDR-TB)负担的趋势和时空模式,并探索其潜在机制。
本研究提取了包括发病率、死亡率、患病率和伤残调整生命年(DALYs)及其年龄标准化率(ASR)在内的核心指标。采用Joinpoint回归、年龄-时期-队列分析、不平等分析和前沿分析来描述疾病负担的时间和空间趋势。进行分解分析和风险因素分析以探索与耐多药结核病负担波动相关的因素。使用贝叶斯年龄-时期-队列(BAPC)模型预测到2050年的疾病负担。
1990年至2021年,全球耐多药结核病病例数及所有指标的年龄标准化率均有所上升,老年人群和社会经济水平较低地区的负担更重。随着时间的推移,国家间的不平等加剧。前沿分析确定印度和俄罗斯等国家在疾病控制方面有很大的改善潜力。分解分析发现流行病学变化是全球负担增加的主要驱动因素。不同地区和年龄组的耐多药结核病风险因素存在异质性。预计到2050年,所有指标的数量和年龄标准化率都会增加。
本研究表明,1990年至2021年全球耐多药结核病疾病负担增加,预计到2050年还会增长。不同社会人口统计学区域之间的差距显著且随时间扩大。流行病学变化对疾病负担的加剧贡献最大。应针对特定地区和年龄组的患者采取有针对性的公共卫生策略。