Lianpeng Wu,1,2 Xiyue Cai,3 Shuya Xu,4 Xuefeng Lin,5 Tingting Peng,1 Xiangao Jiang2,6 

1Department of Clinical Laboratory Medicine, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Wenzhou, Zhejiang, 325000, People’s Republic of China; 2Key Laboratory of Diagnosis and Treatment of New and Recurrent Infectious Diseases of Wenzhou, Wenzhou Sixth People’s Hospital, Wenzhou, Zhejiang, 325000, People’s Republic of China; 3Medical Management Office, Wenzhou Municipal Public Hospital Management Center, Wenzhou, Zhejiang, 325000, People’s Republic of China; 4Department of Tuberculosis Clinic, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Wenzhou, Zhejiang, 325000, People’s Republic of China; 5Department of Clinical Laboratory Medicine, Yueqing People’s Hospital, Wenzhou, Zhejiang, 325600, People’s Republic of China; 6Department of Infectious Diseases, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Wenzhou, Zhejiang, 325000, People’s Republic of China

Correspondence: Tingting Peng, Department of Clinical Laboratory Medicine, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Wenzhou, Zhejiang, 325000, People’s Republic of China, Email pengttwz@163.com Xiangao Jiang, Department of Infectious Diseases, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Key Laboratory of Diagnosis and Treatment of New and Recurrent Infectious Diseases of Wenzhou, Wenzhou Sixth People’s Hospital, No. 252 Baili East Road, Lucheng District, Wenzhou, Zhejiang, 325000, People’s Republic of China, Email xiangaojiang@wmu.edu.cn

Purpose: This study aimed to elucidate the epidemiological features, drug resistance patterns, and temporal trends among elderly tuberculosis (TB) patients in Wenzhou, China, from 2014 to 2023, providing insights for targeted TB control strategies.
Patients and Methods: Data were extracted from 10,993 TB patients registered in the Laboratory Information System of Wenzhou Central Hospital and the Tuberculosis Information Management System of the Chinese Center for Disease Control and Prevention. Patients were divided into elderly (≥ 60 years, n=2,727) and non-elderly (< 60 years, n=8,266) groups. Sociodemographic, clinical, and phenotypic drug susceptibility testing data were analyzed using chi-square tests. Temporal trends in drug resistance were assessed via Joinpoint regression to estimate annual percentage changes (APC).
Results: The elderly group had higher proportions of males (79.65% vs 69.66%), Han ethnicity (99.63% vs 96.35%), and lesions involving ≥ 3 lung fields (42.35% vs 32.62%), but lower proportions of migrants (20.32% vs 51.20%), urban residents (41.03% vs 53.41%), employed individuals (8.98% vs 32.91%), and pulmonary cavitation (46.75% vs 53.54%). The overall drug-resistant tuberculosis (DR-TB) rate was similar between the elderly and non-elderly groups (20.76% vs 20.30%). However, the elderly group had lower rates of streptomycin (SM) resistance (11.07% vs 12.62%), rifampicin (RFP) resistance (6.20% vs 8.06%), and multidrug-resistant tuberculosis (MDR-TB) (5.39% vs 7.10%). From 2014 to 2023, the overall DR-TB rate among elderly patients decreased from 31.58% to 20.64% (− 34.63%), with a significant decline in MDR-TB (APC of − 9.9%). Resistance to isoniazid (INH) decreased from 2016 to 2023 (APC − 4.0%), and RFP resistance decreased from 2014 to 2021 (APC − 10.7%). Significant decreases were also observed among migrant populations (APC − 10.1%, 2014– 2020), urban residents (APC − 8.7%, 2014– 2021), and unemployed individuals (APC − 4.3%, 2014– 2023).
Conclusion: Our study revealed that drug resistance among elderly TB patients in Wenzhou has decreased over the past decade, particularly for MDR-TB and key first-line drugs. However, the elderly group still exhibited distinct epidemiological and drug resistance profiles compared to younger patients. These findings offer clear suggestions for public health policy-making and clinical practice, which can help further reduce the burden of tuberculosis and drug resistance in the elderly population.

Keywords: tuberculosis, elderly population, drug resistance, epidemiology, joinpoint regression model