Preprints.org logo
Preprint
Article

This version is not peer-reviewed.

Treatment Outcomes and Associated Influencing Factors Among Elderly Patients with Rifampicin-Resistant Tuberculosis from 2015 to 2024

Submitted:

30 August 2026

Posted:

31 August 2026

You are already at the latest version

Abstract
Background Drug-resistant tuberculosis remains a public health challenge globally, yet research on elderly RR-TB patients is scarce. This study examines the epidemiological characteristics and treatment outcome factors among elderly RR-TB patients in China (2015–2024) to inform case detection, clinical management, and TB control amid population aging. Methods Data on elderly RR-TB patients registered in 31 provinces of China (excluding Hong Kong, Macao, and Taiwan) from 2015 to 2024 were obtained from the China Disease Control and Prevention Information System. Descriptive epidemiological methods were used to analyze demographic characteristics, and binary logistic regression was employed to identify factors influencing treatment outcomes. Results From 2015 to 2024, a total of 12,574 elderly patients with RR-TB were registered in China. Among them, 9,327 (74.18%) were male and 3,247 (25.82%) were female; 10,845 (86.25%) were Han ethnicity; 9,077 (72.19%) were aged 65-74 years; 9,961 (79.22%) were local residents; 7,619 (60.59%) were farmers; and 6,763 (53.79%) were Multidrug-resistant. Treatment success was achieved in 4,787 cases (47.82%), while unfavorable outcomes occurred in 7,787 cases (52.18%). From 2022 to 2024, the death proportion was higher than in previous years. The proportions of tuberculosis-related deaths were 6.60% (2022), 10.70% (2023), and 7.02% (2024), respectively, and the proportions of non-tuberculosis-related deaths were 19.79% (2022), 41.98% (2023), and 57.24% (2024), respectively.Regression analysis revealed that the following factors were risk factors for unfavorable treatment outcomes: age 75-84 years, age ≥85 years, intra-provincial migrant, MDR, central region, and western region; and the following factors were protective factors: female, non-farmer occupation and new patients. Conclusions Elderly RR-TB patients in China are predominantly male, farmers, and local residents. Those aged ≥85 years are a high-risk group. In the past two years, treatment success rates have declined due to increased non-tuberculosis deaths. Age ≥75 years, central region residence, and MDR-TB increase the risk of unfavorable treatment outcomes. Enhancing active case-finding in elderly and rural populations and standardizing TB care are needed to improve treatment success.
Keywords: 
tuberculosis
;  
elderly patients
;  
treatment outcomes
;  
influencing factors
;  
China
Subject: 
Public Health and Healthcare  -   Other

1. Introduction

Tuberculosis remains a major global public health challenge. According to the World Health Organization (WHO) report, the global incidence of tuberculosis in 2024 reached 131 per 100,000 population, with approximately 10.7 million new cases worldwide. Among these, the estimated number of rifampicin-resistant and multidrug-resistant tuberculosis (RR-TB/MDR) cases was 390,000 (95% uncertainty interval [UI]: 360,000–430,000) [1]. The WHO has set the goal of “ending the global tuberculosis epidemic by 2035,” aiming to reduce tuberculosis incidence and mortality by 90% and 95%, respectively, compared to 2015 levels [2]. However, the extended treatment duration, high costs, and severe adverse effects associated with RR-TB/MDR pose significant challenges to achieving this goal [3,4,5,6].
China is one of the 30 high RR-TB/MDR burden countries, with an estimated 28,000 new RR-TB/MDR cases in 2024, accounting for 7.1% of the global total [1]. According to the Global Burden of Disease study [7], individuals aged 65 and older account for 12.6% of global tuberculosis cases and up to 59.2% of tuberculosis-related deaths. Due to age-related immune decline, malnutrition and comorbidities, the elderly are more susceptible to tuberculosis [8,9,10]. The elderly often experience poorer treatment outcomes. Previous studies indicate that the treatment success rate for elderly RR-TB patients ranges from only 37.2% to 65.89% [11,12,13]. However, there remains a lack of systematic analysis regarding treatment outcomes and influencing factors for RR-TB in the elderly population.
Therefore, this study systematically analyzes the epidemiological characteristics and factors influencing treatment outcomes among elderly RR-TB patients in China. The findings aim to enhance active case detection, improve diagnosis and treatment effectiveness, and provide scientific evidence and technical support for achieving tuberculosis control objectives.

2. Materials and Methods

2.1. Data Source

Data on elderly patients with RR-TB registered between 1 January 2015, and 31 December 2024, across 31 provinces in mainland China (excluding Hong Kong, Macao Special Administrative Regions, and Taiwan) were extracted from the Detection and Report Management System of the China Disease Control and Prevention Information System. Collected information included demographic characteristics (gender, ethnicity, age, household registration, occupation, region) and treatment management status (registration classification, treatment history, initial regimen, and treatment outcomes).
Eligible cases met predefined inclusion and exclusion criteria for elderly RR-TB patients. Inclusion criteria comprised tuberculosis cases aged ≥65 years. Exclusion criteria were: Cases diagnosed with non-tuberculous mycobacterial disease; comprehensive drug susceptibility testing results indicating non-tuberculous mycobacteria, sensitivity to both isoniazid and rifampicin, or isoniazid monoresistance (without rifampicin resistance); absence of anti-tuberculosis treatment; or cases with a revised clinical diagnosis. Patients with unregistered information were not included in this study.

2.2. Definitions

Treatment outcomes were categorized as treatment success or unfavorable outcomes. Treatment success included cure and treatment completion. Unfavorable outcomes comprised treatment failure, death, loss to follow-up and other outcomes [14].
New and initially treated patients were those who have never received anti-tuberculosis drug treatment or have received treatment for less than one month [14].
RR-TB refers to mycobacterium tuberculosis from patients with tuberculosis that is resistant to rifampicin, regardless of resistance to other anti-TB drugs [15].

2.3. Statistical Analysis

Data compilation and organization were performed using Microsoft Excel 2024. Statistical analyses were conducted with R software (version 4.4.3). Descriptive epidemiological methods were employed to summarize the demographic characteristics of the study population. Categorical variables were described using frequencies and percentages.
Univariate analysis of treatment outcomes among elderly patients with RR-TB was performed using the χ2test, with a significance level set at α = 0.05. Based on literature review and clinical expertise, all known factors potentially influencing treatment outcomes in elderly patients with RR-TB were pre-specified. After excluding variables with missing data, the remaining pre-specified variables were directly entered into a multivariable binary logistic regression model to identify factors influencing treatment outcomes in this patient population.

3. Results

3.1. Basic Information of RR-TB Patients

From 2015 to 2024, a total of 12,574 elderly patients with RR-TB were registered nationwide. Among them, 9327 (74.18%) were male and 3247 (25.82%) were female; 10,845 (86.25%) were Han ethnicity; 9077 (72.19%) were aged 65–74 years; 9961 (79.22%) were local residents; 7619 (60.59%) were farmers; 6165 (49.03%) were both new patients and initially treated patients; and 6763 (53.79%) were Multidrug-resistant (Table 1).

3.2. Treatment Outcomes

Among the 12,574 elderly patients with RR-TB, treatment success was achieved in 4787 cases (47.82%), while unfavorable outcomes occurred in 7787 cases (52.18%). From 2022 to 2024, the death proportion was higher than in previous years. The proportions of tuberculosis-related deaths were 6.60% (2022), 10.70% (2023), and 7.02% (2024), respectively, and the proportions of non-tuberculosis-related deaths were 19.79% (2022), 41.98% (2023), and 57.24% (2024), respectively (Table 2).

3.3. Univariate Analysis of Factors Influencing Treatment Outcomes

Univariate analysis revealed that the treatment success rate among elderly patients with RR-TB differed significantly across groups of gender, ethnicity, age, household registration status, occupation, region, registration category, and drug resistance type (χ2 = 7.322, 4.468, 25.801, 479.423, 58.802, 80.236, 23.278, 168.392; all p < 0.05) (Table 3).

3.4. Multivariate Analysis of Factors Influencing Treatment Outcomes

Based on the univariate analysis results, variables with a p-value < 0.01 were included in a binary logistic regression model (Table 4). The multivariate analysis revealed that gender, age, household registration status, occupation, registration category, region and drug resistance type were significant factors influencing treatment outcomes. Female (OR = 0.771, 95% CI: 0.678–0.876), age 75–84 years (OR = 1.467, 95% CI: 0.634–1.158), age ≥ 85 years (OR = 2.149, 95% CI: 1.290–1.668), intra-provincial migrant (OR = 1.567, 95% CI: 1.288–1.905), retirees (OR = 0.831, 95% CI: 0.717–0.963), household duties/unemployed (OR = 0.858, 95% CI: 0.736–1.001), other occupations (OR = 0.749, 95% CI: 0.580–0.968), new patient (OR = 0.718, 95% CI: 0.554–0.930), MDR (OR = 1.192, 95% CI: 1.056–1.345), central region (OR = 1.553, 95% CI: 1.359–1.775), and western region (OR = 1.259, 95% CI: 1.085–1.462) (Table 5).

4. Discussion

The study results indicate that elderly patients with RR-TB in China are predominantly male, a gender distribution consistent with the findings of the multicenter retrospective cohort studies by Liu Huicong et al. and Zou Liping et al. [16,17]. A possible explanation is that men are more likely to work as migrant workers, increasing their opportunities for exposure to sources of infection. Additionally, many have a history of smoking, which further elevates the risk of infection and disease development [18].
In terms of age distribution, patients aged 65–74 years account for a relatively high proportion of RR-TB cases, primarily due to the larger population base in this age group. According to data from the seventh national census, the population aged 65–74 years constitutes 8.77% of the total population, which is significantly higher than the proportions of 3.67% and 1.10% observed in the other two older age groups [19].
Regarding household registration and occupational distribution, the majority of elderly RR-TB patients are locally registered residents and farmers. These individuals are predominantly local farmers who developed acquired drug resistance during the last century due to limited primary healthcare resources and inadequate treatment supervision, leading to reactivation of latent drug-resistant strains [20,21].
In terms of registration classification, the majority are new patients, which aligns with the findings of Zou Liping et al. [17]. Currently, most elderly RR-TB patients in China were infected during their younger years, either having received non-standardized treatment or never having been diagnosed as latently infected individuals. The disease manifests as endogenous reactivation due to declining immunity in old age. Although they harbor drug-resistant strains, this represents their first registration; as elderly patients are predominantly identified through passive case finding and diagnosed at their initial healthcare visit, they have no prior treatment history despite the presence of drug resistance. Consequently, they are registered as new patients receiving initial treatment [20,21,22].
Our study reveals that the treatment success rate among elderly patients with RR-TB registered for treatment in China between 2015 and 2024 was only 47.82%. This rate is substantially lower than the recent global average of 71.36% and the national average of 68.33% reported by the World Health Organization [1], likely attributable to the combined effect of multiple risk factors. Malnutrition is prevalent in the elderly population, not only directly impairing drug absorption and therapeutic efficacy but also exerting a negative synergistic effect with declining immune function [23,24]. Moreover, the high prevalence of comorbidities such as diabetes mellitus and chronic obstructive pulmonary disease not only increases the risk of latent infection reactivation but also complicates treatment regimens through drug–drug interactions that exacerbate hepatorenal burden [25,26,27]. Age-related immunosenescence further compromises the host’s innate capacity to eliminate pathogens, while the high incidence of adverse drug reactions associated with drug-resistant regimens poses particular challenges in elderly patients with limited organ reserve, often necessitating dose reduction, drug substitution, or even treatment discontinuation due to intolerance [28,29]. In addition, persistent socioeconomic barriers—including financial hardship, limited access to healthcare services, and inadequate family-based treatment supervision—undermine long-term treatment adherence and contribute to persistently high rates of loss to follow-up [29,30,31].
Among elderly RR-TB patients registered for treatment in China, treatment success rates increased from 2015 to 2021 but declined from 2022 onward. Notably, treatment success rates fell to extremely low levels of 14.54% in 2023 and 8.77% in 2024. This decline was primarily driven by a sharp increase in deaths during these two years, particularly non-tuberculosis-related deaths, the proportion of which rose from 19.79% in 2022 to 41.98% in 2023 and 57.24% in 2024. A likely explanation is that following the major adjustment of China’s COVID-19 policy at the end of 2022, widespread SARS-CoV-2 infection triggered severe inflammatory responses and immune dysregulation in elderly RR-TB patients with multiple comorbidities (e.g., diabetes, cardiovascular disease), leading to rapid deterioration of their underlying conditions. Furthermore, the accumulated health “debt” from the preceding three years—including delayed chronic disease management and interrupted follow-up care—came to a head during this period. As a result, many patients died from pre-existing comorbidities induced or exacerbated by COVID-19 rather than from tuberculosis itself, driving the alarming increase in non-tuberculosis-related deaths in 2023–2024 [32,33,34,35].
Multivariable analysis revealed that gender, age, household registration, occupation, registration classification, region, and drug resistance type were predictors of treatment outcomes. Female sex was associated with a 0.771-fold lower risk of unfavorable outcomes compared to male sex. Male sex was identified as an independent risk factor for treatment outcomes in MDR-PTB, likely due to poorer adherence, higher rates of smoking and alcohol use, and greater occupational exposure, which together contribute to significantly increased risks of treatment failure and death [36,37].
In this study, RR-TB patients aged ≥75 years had a higher risk of unfavorable outcomes than those aged 65–74 years, with the risk reaching 2.149 times in those aged ≥85 years. In elderly patients, reduced liver/kidney function and bone marrow hematopoietic capacity lead to impaired drug clearance, toxicity accumulation, and immunosenescence-related pathogen elimination failure. Comorbidities limit drug selection, while polypharmacy increases drug interactions and adverse reactions, reducing tolerance and adherence. With physiological reserve at a critical level (immunosenescence + chronic inflammation), susceptibility to infection, treatment failure, and mortality rise. Polypharmacy risks involve both drug-drug and drug-aging organism interactions. Coupled with declines in self-care, balance, cognition, and lack of social support, these factors ultimately hinder completion of 18–24 months of chemotherapy [38,39,40,41].
Patients with intra-provincial mobility exhibited a lower risk of unfavorable outcomes compared to those with local household registration. A possible explanation is that elderly individuals capable of maintaining intra-provincial mobility at an advanced age possess better social adaptability and health management awareness than their locally registered counterparts of the same age. National surveys have confirmed that social participation among elderly migrants is significantly positively correlated with exposure to tuberculosis health education; such patients are more adept at acquiring disease-related knowledge and more proactively cooperate with treatment follow-up, resulting in better treatment adherence [42].
Compared with patients who failed initial treatment, new patients had a lower risk of unfavorable outcomes. New patients, having no prior exposure to anti-tuberculosis drugs, present with primary drug resistance, which typically has a limited resistance spectrum [43]. Farmers were identified as a high-risk group for unfavorable outcomes, consistent with Wei et al. [44]). This may be due to their generally lower education level and rural residence. Poor disease/treatment understanding (related to low education) and limited access to medical care (related to rural residence) both lead to treatment interruption or irregular medication, thereby increasing the risk of drug resistance and treatment failure.
The findings revealed that, relative to the eastern region, both the central and western regions were associated with a higher risk of unfavorable RR-TB treatment outcomes, with the central region demonstrating the most statistically pronounced risk. This phenomenon can be primarily attributed to the central region’s higher proportion of rural residents-rural residence having been previously identified as an independent risk factor for resistance accumulation, conferring a 2.60-fold increased risk [45]. Furthermore, the limited capacity of primary healthcare services in this region provides a breeding ground for acquired drug resistance and the community transmission of resistant strains. When combined with additional risk factors, including heavy economic burden and poor treatment adherence, these elements collectively explain the underlying reasons for the elevated risk of treatment failure and death observed among elderly patients in the central region [46]. MDR-TB patients had a higher risk of unfavorable outcomes than those with rifampicin-monoresistant TB, likely because MDR-TB requires longer regimens and more second-line drugs. This increases treatment burden and adverse drug reactions, reducing adherence and further raising the risk of poor outcomes [47]. Therefore, individualized regimens incorporating new drugs like bedaquiline, tailored to regional and resistance profiles, can enhance efficacy and reduce toxicity, thereby improving treatment success and outcomes in elderly RR-PTB patients.
This study has certain limitations. Factors that may influence treatment outcomes, such as medication dosage, underlying diseases, and comorbidities, were not included in the analysis. This is likely because the aforementioned information was not classified as mandatory fields during data collection, resulting in missing data for some patients. This study was limited to routinely collected surveillance data and could not include additional clinical or socioeconomic variables. Nevertheless, the data were sourced from a surveillance reporting management system, offering a large sample size that is both authentic and reliable. Therefore, the findings retain a certain significance for understanding the factors influencing treatment outcomes in elderly patients with RR-TB.

5. Conclusions

In summary, elderly RR-TB patients in China are predominantly male, farmers, and local residents. Those aged ≥85 years are a high-risk group. In the past two years, treatment success rates have declined due to increased non-tuberculosis deaths. Age ≥ 75 years, central region residence, and MDR-TB increase the risk of unfavorable treatment outcomes. Therefore, it is necessary to intensify active case finding efforts in key regions and among key populations, particularly in rural areas, central China, and among the very elderly, to facilitate early detection of elderly patients with RR-TB. Meanwhile, for patients aged ≥85 years, a “diagnosis-then-immediate-treatment” mechanism should be implemented, along with individualized low-toxicity regimens prioritizing oral second-line drugs, the establishment of multidisciplinary teams for elderly drug-resistant tuberculosis care, and cross-regional follow-up information sharing for intra-provincially migrated patients. Furthermore, further research on treatment regimens specifically for elderly patients with RR-TB should be conducted to explore more suitable therapeutic strategies, improve treatment success rates, and reduce community transmission, thereby contributing to the goal of ending the tuberculosis epidemic.

Author Contributions

Ge Fangjun contributed to data collation, analysis, and manuscript writing. Li Jinhao and Wen Yaxin contributed to data collation and analysis. Xu Caihong contributed to study supervision and manuscript review. All authors have contributed to, seen, and approved the final, submitted version of the manuscript.

Funding

This work was funded by the National Key Research and Development Program of China (2024YFC2311204, 2024YFC2310905).

Institutional Review Board Statement

This study was conducted in accordance with the ethical standards of the Declaration of Helsinki and was approved by the National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention & Chinese Academy of Preventive Medicine. Given that this research involved the analysis of secondary data, a waiver for informed consent was requested and granted.

Data Availability Statement

The datasets generated and analysed during the present study are not publicly available owing to institutional data privacy and security policies, as the data are the proprietary property of the Chinese Center for Disease Control and Prevention. Reasonable requests for access to the datasets may be directed to the corresponding author, with the prior written permission of the Chinese Center for Disease Control and Prevention.

Acknowledgments

We thank all members who participated in this work. Declaration of generative AI and AI-assisted technologies in the writing process: During the preparation of this work the authors used Deepseek (OpenAI) to enhance sentence structure and improve the clarity of formulations. The scientific content, analysis, and conclusions are entirely the authors’ own. After using this tool/service, the authors reviewed and edited the content as needed and take full responsi- bility for the content of the publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
RR-TB/MDR rifampicin-resistant and multidrug-resistant tuberculosis

References

  1. World Health Organization. Global Tuberculosis Report 2025; World Health Organization: Geneva, Switzerland, 2025. [Google Scholar]
  2. World Health Organization. The END TB Strategy; World Health Organization: Geneva, Switzerland, 2015. [Google Scholar]
  3. Ding, Q.; Zhang, S.K.; Ren, F.; Chen, X.H.; Hu, C.M.; Chen, W.; Ding, Q.; Zhang, S.K.; Ren, F.; Chen, X.H.; Hu, C.M.; et al. Nutritional status and influencing factors in patients with drug-resistant pulmonary tuberculosis: A multicentre, large-sample study. Chin. J. Antituberc. 2023, 45, 826–832. [Google Scholar]
  4. Liang, C.; Tang, S.J.; Lin, M.G. Research progress of comprehensive treatment for tuberculosis. J. Tuberc. Lung Dis. 2024, 5, 70–80. [Google Scholar] [CrossRef]
  5. Tiberi, S.; Utjesanovic, N.; Galvin, J.; Centis, R.; D’AMbrosio, L.; Boom, M.v.D.; Zumla, A.; Migliori, G.B. Drug resistant TB—Latest developments in epidemiology, diagnostics and management. Int. J. Infect. Dis. 2022, 124, S20–S25. [Google Scholar] [CrossRef] [PubMed]
  6. Diriba, G.; Alemu, A.; Yenew, B.; Tola, H.H.; Gamtesa, D.F.; Mollalign, H.; Eshetu, K.; Moga, S.; Abdella, S.; Tollera, G.; et al. Epidemiology of extensively drug-resistant tuberculosis among patients with multidrug-resistant tuberculosis: A systematic review and meta-analysis. Int. J. Infect. Dis. 2023, 132, 50–63. [Google Scholar] [CrossRef] [PubMed]
  7. Global Health Data Exchange. Global Burden of Disease. 2026. Available online: https://vizhub.healthdata.org/gbd-results/.
  8. Donald, P.R.; Marais, B.J.; E Barry, C. Age and the epidemiology and pathogenesis of tuberculosis. Lancet 2010, 375, 1852–1854. [Google Scholar] [CrossRef] [PubMed]
  9. Pratt, R.H.; Winston, C.A.; Kammerer, J.S.; Armstrong, L.R. Tuberculosis in Older Adults in the United States, 1993–2008. J. Am. Geriatr. Soc. 2011, 59, 851–857. [Google Scholar] [CrossRef] [PubMed]
  10. Rajagopalan, S. Tuberculosis in Older Adults. Clin. Geriatr. Med. 2016, 32, 479–491. [Google Scholar] [CrossRef] [PubMed]
  11. Liu, H.; Zou, L.; Yu, J.; Zhu, Q.; Yang, S.; Kang, W.; Ma, J.; Chen, Q.; Shi, Z.; Tang, X.; et al. Treatment outcomes and associated influencing factors among elderly patients with rifampicin-resistant tuberculosis: A multicenter, retrospective, cohort study in China. BMC Infect. Dis. 2025, 25, 1–12. [Google Scholar] [CrossRef] [PubMed]
  12. Li, H.; Mei, J.; Su, W. Analysis of the treatment outcomes and influencing factors of rifampicin-resistant pulmonary tuberculosis patients aged 65 and above in China from 2015 to 2021. Chin. J. Tuberc. 2025, 47, 408–415. [Google Scholar]
  13. Ye, Z.; Ren, F.; Wang, H. Treatment outcomes and influencing factors in elderly patients with multidrug/rifampicin-resistant pulmonary tuberculosis: A National multicenter, retrospective cohort study. Chin. J. Tuberc. 2024, 46, 1023–1029. [Google Scholar]
  14. National Health Commission of the People’s Republic of China. Technical Guidelines for Tuberculosis Prevention and Control in China (2020 Edition) [A/OL]. (2020-04-02). Available online: http://tb.chinacdc.cn/ggl/202004/P020200414515703939844.pdf (accessed on 20 January 2026).
  15. Zhang, J.; Li, J.; Huang, Y.; et al. Epidemiological characteristics, diagnosis and treatment outcomes of rifampicin-resistant pulmonary tuberculosis (RR-PTB) in Guizhou province. BMC Infect. Dis. 2024, 24, 1058. [Google Scholar] [CrossRef] [PubMed]
  16. Liu, H.; Zou, L.; Yu, J.; Zhu, Q.; Yang, S.; Kang, W.; Ma, J.; Chen, Q.; Shi, Z.; Tang, X.; et al. Treatment outcomes and associated influencing factors among elderly patients with rifampicin-resistant tuberculosis: A multicenter, retrospective, cohort study in China. BMC Infect. Dis. 2025, 25, 1–12. [Google Scholar] [CrossRef] [PubMed]
  17. Zou, L.; Kang, W.; Guo, C.; Du, J.; Chen, Q.; Shi, Z.; Tang, X.; Liang, L.; Tang, P.; Pan, Q.; et al. Treatment Outcomes and Associated Influencing Factors Among Patients with Rifampicin-Resistant Tuberculosis: A Multicenter, Retrospective, Cohort Study in China. Infect. Drug Resist. 2024, 17, 3737–3749. [Google Scholar] [CrossRef] [PubMed]
  18. Nondoli, H.G. Tuberculosis in transit: Risk factors in Tanzania’s high-mobility border regions. Pan Afr. Med. J. 2025, 52, 21. [Google Scholar] [CrossRef] [PubMed]
  19. Committee, I.R. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ)-Short and Long Forms. 2005. Available online: http://www.ipaq.ki.se/scoring.pdf.
  20. Chen, Y.; Zhao, Y. Multidrug-resistant tuberculosis in rural China: Lack of public awareness, unaffordable costs and poor clinical management. BMJ Case Rep. 2018, 2018, bcr2018225794. [Google Scholar] [CrossRef] [PubMed]
  21. Teo, A.K.J.; Rahevar, K.; Morishita, F.; Ang, A.; Yoshiyama, T.; Ohkado, A.; Kawatsu, L.; Yamada, N.; Uchimura, K.; Choi, Y.; et al. Tuberculosis in older adults: Case studies from four countries with rapidly ageing populations in the western pacific region. BMC Public Heal. 2023, 23, 1–11. [Google Scholar] [CrossRef] [PubMed]
  22. Zhang, Y.J.; Jiang, Y.; Sun, H.; et al. Analysis of detection and treatment prognosis of 154 elderly pulmonary tuberculosis patients. J. Tuberc. Lung Dis. 2023, 4, 48–53. [Google Scholar]
  23. zen, N.T.; Güneş, K. The vicious cycle of malnutrition and tuberculosis: A narrative review. Cyprus Pharm. Rev. 2024, 46, 444–448. [Google Scholar] [CrossRef] [PubMed]
  24. Liu, Q.-X.; Tang, D.-Y.; Xiang, X.; He, J.-Q. Associations between nutritional and immune status and clinicopathologic factors in patients with tuberculosis: A comprehensive analysis. Front. Cell. Infect. Microbiol. 2022, 12, 1013751. [Google Scholar] [CrossRef] [PubMed]
  25. Verma, A.K.; Singh, A.; Chandra, S.; et al. Drug resistant tuberculosis among elderly: Challenges. Indian J. Tuberc. 2022. [Google Scholar] [CrossRef] [PubMed]
  26. Gao, W.W. Analysis of detection and treatment prognosis of 154 elderly pulmonary tuberculosis patients. Chin. J. Tuberc. Respir. Dis. 2014, 37, 732–733. [Google Scholar]
  27. Chinese Medical Association Tuberculosis Branch. Expert consensus on the diagnosis and treatment of severe pulmonary tuberculosis. Chin. J. Tuberc. Respir. Dis. 2025, 48, 1127–1143. [Google Scholar]
  28. Zou, L.; Kang, W.; Guo, C.; Du, J.; Chen, Q.; Shi, Z.; Tang, X.; Liang, L.; Tang, P.; Pan, Q.; et al. Treatment Outcomes and Associated Influencing Factors Among Patients with Rifampicin-Resistant Tuberculosis: A Multicenter, Retrospective, Cohort Study in China. Infect. Drug Resist. 2024, 17, 3737–3749. [Google Scholar] [CrossRef] [PubMed]
  29. Gu, Y.; Zhao, X.Q.; Wang, Y.G.; et al. Discussion on dual supervision management for pulmonary tuberculosis patients aged over 75 with chronic diseases. J. Xuzhou Med. Univ. 2008, 28, 236–239. [Google Scholar]
  30. Hamida, A.; Wang, S.M.; Zhang, Y. Current status and influencing factors of medication adherence among patients with multidrug-resistant tuberculosis in Tacheng Prefecture. Prim. Med. Forum 2025, 29, 1–5+49. [Google Scholar]
  31. Tao, T.; Zhang, H.F.; Fan, P.F.; et al. Factors influencing treatment outcomes of elderly pulmonary tuberculosis patients in Lishui City. J. Prev. Med. 2025, 37, 892–896+902. [Google Scholar]
  32. Jha, P.; Brown, P.E.; Lam, T.; Morawski, E.; Reid, A. Excess deaths in China during SARS-CoV-2 viral waves in 2022–2023. Prev. Med. Rep. 2024, 41, 102687. [Google Scholar] [CrossRef] [PubMed]
  33. Abodunrin, O.R.; Olagunju, M.T.; Huang, X.; Wang, J.; Hu, Z.; Shen, C. Regional risk factors associated with adverse outcomes of COVID-19 infection among the older adult: A systematic review and meta-analysis. J. Infect. Public Health 2024, 18, 102632. [Google Scholar] [CrossRef] [PubMed]
  34. Ghanbari-Jahromi, M.; Kharazmi, E.; Bastani, P.; Shams, M.; Marzaleh, M.A.; Bahrami, M.A. Factors disrupting the continuity of care for patients with chronic disease during the pandemics: A systematic review. Heal. Sci. Rep. 2024, 7, e1881. [Google Scholar] [CrossRef] [PubMed]
  35. Raphson, L.; Lipsitch, M. Estimated Excess Deaths Due to COVID-19 Among the Urban Population of Mainland China, December 2022 to January 2023. Epidemiology 2024, 35, 372–376. [Google Scholar] [CrossRef] [PubMed]
  36. Luo, Q.N. Influencing Factors Associated with the Treatment Outcome of Multidrug-Resistant Pulmonary Tuberculosis. Master’s Thesis, Hainan Medical University, Haikou, China, 2023. [Google Scholar]
  37. Saliba, M.F.; Karam, Z.Z.; El Khayat, M.; Koka, E.; Halwani, D.A.; Ghanawi, J.; Hneiny, L.; Jurdi, M.; Dhaini, H.R.; Musharrafieh, U.; et al. Risk factors for silicotuberculosis among miners: A scoping review. BMC Public Health 2025, 25, 1–15. [Google Scholar] [CrossRef] [PubMed]
  38. Romero-Rodríguez, D.P.; Díaz-Alvarado, C.A.; Rocha-González, H.I.; Juárez, E. Control of Mycobacterium tuberculosis infection in the elderly: Is there a role for epigenetic reprogramming reversal? BioFactors 2025, 51, e2151. [Google Scholar] [CrossRef] [PubMed]
  39. Headley, C.A.; Gautam, S.; Olmo-Fontanez, A.; Garcia-Vilanova, A.; Dwivedi, V.; Schami, A.; Weintraub, S.; Tsao, P.S.; Torrelles, J.B.; Turner, J. Mitochondrial Transplantation Promotes Protective Effector and Memory CD4 + T Cell Response During Mycobacterium Tuberculosis Infection and Diminishes Exhaustion and Senescence in Elderly CD4 + T cells. Adv. Sci. 2024, 11, e2401077. [Google Scholar] [CrossRef] [PubMed]
  40. Leo, B.; Retnowulan, H. Complicated Case of Multidrug-Resistant Tuberculosis with Multiple Comorbidities, Successfully Treated After Several Treatment Modifications. Clin. Med. Insights Circ. Respir. Pulm. Med. 2022, 16. [Google Scholar] [CrossRef] [PubMed]
  41. Li, H.-J.; Zhou, Y.-Y.; Yu, H.-H.; Jiang, J.; Cai, Y.-W. A Preliminary Screening Tool for High-Risk Frailty in Older Adults Patients with Pulmonary Tuberculosis. Clin. Interv. Aging 2025, 20, 57–68. [Google Scholar] [CrossRef] [PubMed]
  42. Liu, J.; Liu, C.; Cui, Y.; Liu, Z.; Feng, Y.; Wang, Y.; Guan, L.; Liu, W.; Zhang, H.; Liu, X.; et al. Social participation and exposure to tuberculosis education: A cross-sectional study of older (≥60 years) domestic migrants in China. BMC Public Health 2025, 25, 1–11. [Google Scholar] [CrossRef] [PubMed]
  43. Liu, J.Y.; Li, H.F.; Lin, H.Y. Analysis of drug resistance spectrum in 220 pulmonary tuberculosis patients. China Med. Pharm. 2011, 1, 80–93. [Google Scholar]
  44. Wei, S.Y.; Gao, Q.; Cao, Y.X.; Han, L.; Du, J.; Li, L.; Li, X.J. A meta-analysis of risk factors for multidrug-resistant tuberculosis in China. Zhonghua Jie He He Hu Xi Za Zhi 2022, 45, 1221–1230. [Google Scholar] [PubMed]
  45. Wang, F.-L.; Chen, R.; Xu, Q.; Wang, X.-Q.; Tao, F.-X.; Huang, Z.-K.; Zhang, Y.-T.; Chen, S.-Q.; Wu, X.-J.; Cao, H.-Y.; et al. Longitudinal phenotypic and genomic evidence revealing increased risk of drug resistance accumulation in tuberculosis patients in the counties of central China. Microbiol. Spectr. 2025, 13, e0038025. [Google Scholar] [CrossRef] [PubMed]
  46. Zhou, Y.; Wang, X.; et al. Longitudinal phenotypic and genomic evidence revealing increased risk of drug resistance accumulation in tuberculosis patients in the counties of central China. Microbiol. Spectr. 2025, 13, e0038025. [Google Scholar] [CrossRef] [PubMed]
  47. Nahid, P.; Mase, S.R.; Migliori, G.B.; et al. Treatment of Drug-Resistant Tuberculosis: An Official ATS/CDC/ERS/IDSA Clinical Practice Guideline. Am. J. Respir. Crit. Care Med. 2019, 200, e93–e142. [Google Scholar] [CrossRef] [PubMed]
Table 1. Basic characteristics of RR-TB patients in China, 2015–2024 (n = 12,574).
Table 1. Basic characteristics of RR-TB patients in China, 2015–2024 (n = 12,574).
Characteristics Number Proportion Characteristics (%)
Gender
Male 9327 74.18
Female 3247 25.82
Ethnicity
Han 10,845 86.25
Minority 1729 13.75
Age
65–74 years 9077 72.19
75–84 years 3096 24.62
≥85 years 401 3.19
Household Registration
Local 9961 79.22
Intra-city migrant 1734 13.79
Intra-provincial migrant 679 5.4
Inter-provincial migrant 198 1.57
Other 2 0.02
Occupation
Farmer 7619 60.59
Retirees 2182 17.35
Household duties/Unemployed 2258 17.96
Other 515 4.10
Region
Eastern region 3747 29.8
Central region 4888 38.87
Western region 3939 31.33
Registration Category
New patient 6165 49.03
Relapse 4622 36.76
Return after loss to follow-up 150 1.20
Treatment failure after initial regimen 562 4.47
Other 1075 8.56
Drug Resistance Type
Rifampin monoresistance 5394 42.90
MDR 6763 53.79
(Pre-XDR)/XDR 417 3.31
Initial Regimen
6 Lfx(Mfx)Bdq Lzd(Cs)Cfz/12Lfx(Mfx)Lzd(Cs)Cfz 318 2.53
6 Lfx(Mfx)Cfz Cs Am(Cm)Z(E,Pto)/14Lfx(Mfx)Cfz Cs Z(E,Pto) 83 0.66
6 Bdq Lzd Cfz Cs/14 Lzd Cfz Cs 14 0.11
4–6 Lfx(Mfx)Bdq(Am) Cfz Z H (High-dose) Pto E/5 Lfx(Mfx) Cfz Z E 24 0.19
Other 12,135 96.51
Table 2. Treatment outcomes of RR-TB patients in China, 2015–2024 (n = 12,574).
Table 2. Treatment outcomes of RR-TB patients in China, 2015–2024 (n = 12,574).
Year Cure Treatment Completion Treatment Failure Lose to Follow-Up Death Other Total Treatment Success Rate (%) Death Proportion
(%)
2015 63 89 66 64 72 36 390 38.97 18.46
2016 85 173 76 98 95 42 569 45.34 16.70
2017 154 284 100 143 152 77 910 48.13 16.70
2018 276 513 146 182 295 137 1549 50.94 19.04
2019 384 825 181 247 468 165 2270 53.26 20.62
2020 417 684 144 212 408 177 2042 53.92 19.98
2021 517 701 162 267 423 164 2234 54.52 18.93
2022 362 340 110 147 376 90 1425 49.26 26.39
2023 67 39 95 93 384 51 729 14.54 52.67
2024 25 15 44 42 293 37 456 8.77 64.25
合计 2350 3663 1124 1495 2966 976 12,574 47.82 23.59
Table 3. Univariate analysis of factors influencing treatment outcomes on RR-TB patients in China, 2015–2024 (n = 12,574).
Table 3. Univariate analysis of factors influencing treatment outcomes on RR-TB patients in China, 2015–2024 (n = 12,574).
Characteristics Treatment Success (n) Treatment Failure (n) Treatment Success Rate (%) χ2 Value p Value
Gender 7.322 0.0068
Male 791 2456 24.36
Female 2055 7272 22.03
Age 25.801 <0.001
65–74 years 2153 6924 23.72
75–84 years 629 2467 20.32
≥85 years 64 337 15.96
Household Registration 479.423 <0.001
Local 1852 8109 18.59
Intra-city migrant 716 1018 41.29
Intra-provincial migrant 214 465 31.52
Inter-provincial migrant 64 134 32.32
Other 0 2 0
Occupation 58.802 <0.001
Farmer 1575 6044 20.67
Retirees 558 1624 25.57
Household duties/Unemployed 546 1712 24.18
Other 167 348 32.43
Region 80.236 <0.001
Eastern region 1039 2708 27.73
Central region 980 3908 20.05
Western region 827 3112 21
Registration Category 23.278 <0.001
New patient 1376 1249 52.42
Relapse 1061 1071 49.77
Return after loss to follow-up 19 42 31.15
Treatment failure after initial regimen 118 156 43.07
Other 89 115 43.63
Drug Resistance Type 168.392 <0.001
Rifampin monoresistance 974 4420 18.06
MDR 1825 4938 26.99
Pre-XDR/XDR 47 370 11.27
Table 4. Binary logistic regression relevant variable assignment table.
Table 4. Binary logistic regression relevant variable assignment table.
Variable Assignment
Dependent Variable
Successful Treatment Yes = 0; No = 1
Independent Variables
Gender Male = 0; Female = 1
Age 65–74 years = 0; 75–84 years = 1; ≥85 years = 2
Household Registration Status Local = 0; Intra-city migrant = 1; Intra-provincial migrant = 2; Inter-provincial migrant = 3
Occupation Farmer = 0; Retirees = 1; Household duties/Unemployed = 2; Other = 3
Registration Category Treatment failure after initial regimen = 0; New patient = 1; Relapse = 2; Return after loss to follow-up = 3
Region Eastern region = 0; Central region = 1; Western region = 2
Drug Resistance Type Rifampin monoresistance = 0; MDR = 1; Pre-XDR/XDR = 2
Table 5. Multivariate analysis of factors influencing treatment outcomes on RR-TB patients in China, 2015–2024 (n = 23,959).
Table 5. Multivariate analysis of factors influencing treatment outcomes on RR-TB patients in China, 2015–2024 (n = 23,959).
Variable β Sx Waldχ2 Value p Value OR Value 95% CI
Female −0.260 0.065 15.822 <0.001 0.771 0.678–0.876
75–84 years 0.383 0.066 34.008 <0.001 1.467 0.634–1.158
≥85 years 0.765 0.170 20.324 <0.001 2.149 1.290–1.668
Intra-provincial migrant 0.449 0.100 20.252 <0.001 1.567 1.288–1.905
Retirees −0.186 0.075 6.062 0.0138 0.831 0.717–0.963
Household duties/Unemployed −0.153 0.078 3.810 0.0509 0.858 0.736–1.001
Other −0.289 0.131 4.883 0.0271 0.749 0.580–0.968
New patient −0.332 0.132 6.300 0.0121 0.718 0.554–0.930
MDR 0.175 0.062 8.071 0.0045 1.192 1.056–1.345
Central region 0.440 0.068 41.591 <0.001 1.553 1.359–1.775
Western region 0.230 0.076 9.183 0.0024 1.259 1.085–1.462
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.