Impact of the cost exception policy on long-term treatment interruption among pulmonary tuberculosis patients in South Korea: a nationwide population-based study

Abstract

Background

Political change regarding for exemption of co-payment for tuberculosis (TB) treatment was made in July 2016. We investigated the effect of the co-payment waiver on long-term treatment interruption and clinical outcomes among pulmonary TB patients in South Korea.

Methods

Patients who had newly treated TB in South Korea from 2013–2019 were selected from nationwide data using the entire Korean National Health Insurance Service population. Interrupted time series analysis was used to evaluate the effect of policy implementation on treatment adherence. Moreover, mortality rates were assessed depending on the history of long-term treatment interruption.

Results

A total of 73,116 and 1,673 patients were included in the final study population for each drug-susceptible and drug-resistant pulmonary TB. After implementing the cost exemption policy, the long-term treatment discontinuation rates tended to decrease in the continuation phase in the drug-susceptible TB group (slope change: −0.097, P = 0.011). However, it was increased in the intensive phase in the drug-resistant TB group (slope change: 0.733, P = 0.001). Drug-resistant TB patients were likely to experience long-term discontinuation of TB treatment (adjusted odds ratio, 6.04; 95% confidence interval [CI], 5.43–6.71), and history of long-term treatment interruption was a significant risk factor for both 1-year and overall mortality rates among the study population (adjusted hazard ratios: 2.01, 95% CI, 1.86–2.18 and 1.77, 95% CI, 1.70–1.84, respectively).

Conclusions

Implementing the cost exemption policy effectively reduced the long-term treatment discontinuation rate among pulmonary TB patients. Because long-term treatment interruption is relevant to increasing mortalities, political change for widening the coverage helped improve treatment outcomes in TB patients.

Background

Although the incidence rate of tuberculosis (TB) decreased from 2015 to 2019, TB remains one of the top 10 causes of death worldwide. [1] Although the Korea Centers for Disease Control and Prevention established the TB monitoring system and has been conducting the Public-Private Mix TB control project to reduce incidence rates to levels of advanced countries through systematic TB prevention and control, TB remains a serious public health problem in South Korea. [2] There is also a stigma of having the highest prevalence rate (77 per 100,000 people) and the second highest death rate (5.2 per 100,000 people) among the Organization for Economic Cooperation and Development countries. [3]

Premature discontinuation of TB treatment interferes with TB control efforts. This implies exposure to TB drugs for durations is insufficient for an effective cure. Patients with long-term discontinuation of anti-TB medications (2 consecutive weeks during the intensive phase or 2 consecutive months or more during the continuation phase) are defined as a loss to follow-up (LTFU). [4–7] The proportion of LTFU varies considerably among different countries, types of TB, and other patient populations; it has been studied extensively and was found to be ranging from 2.5 to 44.9%. [8–13] In Korea, the LTFU rate has been reported to be as high as 7.3–33.1%. [14–17] Since it can lead to TB outbreaks and drug resistance, reducing LTFU is essential to improve TB control. [18] Various causes, such as low socioeconomic status, adverse effects of anti-TB medications, alcohol abuse, and marginalization, are related to the discontinuation of anti-TB medicines. [19–21]

To improve the accessibility and provide the motivation for treating 138 rare and intractable disorders, including TB, the National Health Insurance Service (NHIS) of Korea initiated a co-payment reduction of up to 90% in 2007. Furthermore, to remove the individual economic burden and to improve treatment compliance, co-payment for TB treatment was waived after July 2016. [3]

However, there are limited studies evaluating the impact of the political change regarding the total exemption from medical service co-payment among TB patients. Hence, this study aimed to investigate the difference in the long-term treatment interruption rate of TB treatment and survival outcomes before and after the policy implementation.

Methods

Data source and study design

All Korean residents must enroll in the Korean NHIS and receive a unique identification number at birth. Claims are accompanied by data regarding fully adjudicated medical and pharmacy claims in South Korea, including general demographic data, the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) codes, medical institution type, medications prescribed, medical cost, and mortality information. This retrospective cohort study evaluated nationwide data using the entire population of Korean NHIS. We identified all outpatient visitors or hospitalized individuals with pulmonary TB during 2013–2019.  

Case identification

Pulmonary TB cases were included only when diagnostic and medication codes were identified more than twice within the study period. Diagnostic codes for pulmonary TB were A15-16 or U88.0-88.1 according to ICD-10. Patients with previous TB history earlier than 2013 or those with an observation period of fewer than 6 months were excluded. Because disease-nature could be distinguishable with pulmonary TB, patients with diagnostic codes for extra-pulmonary TB were also excluded. Anti-TB drug prescription(s) included at least one of the following: isoniazid and rifampicin, ethambutol, pyrazinamide, prothionamide, cycloserine, or para-aminosalicylate. Study subjects were grouped according to the presence of drug resistance for first-line TB drugs (drug-susceptible or drug-resistant TB) and treatment period (pre- or post-exemption). 

Charlson comorbidity index

The Charlson comorbidity index (CCI) is a widely used prognostic model that predicts 1-year mortality risk depending on individual comorbidities. Each comorbidity was scored, and the CCI was calculated by summing the comorbidity scores (Supplementary Table S1). Because of its usefulness for measuring the effect of comorbidities on mortality using the administrative database, including ICD-10 codes, we adopted it as a variable. [22, 23]  

Clinical outcomes 

The primary outcome was the difference in the long-term treatment discontinuation rates among pulmonary TB patients between pre- and post-political change. Secondary outcomes included the 1-year and overall mortality among study groups and risk factors for predicting long-term discontinuation of anti-TB therapy and all-cause mortality.  

Ethical approval

The Institutional Review Board of NHIS Ilsan Hospital approved the study, and the study adhered to the Declaration of Helsinki's tenets (NHIMC 2022-05-015). Because this study was based on anonymous health claims data, the requirement for patient consent was waived.  

Statistical analysis 

The variables of each group were compared using the paired t-test or chi-squared test. To evaluate the longitudinal impact of the introduction of the cost exemption policy, an interrupted time series (ITS) analysis was used. ITS is regarded as one of the most robust quasi-experimental designs to assess the impact of an intervention and has been used in numerous studies. [24, 25] In ITS analysis, data are arranged at evenly spaced time intervals and separated by the intervention into segments. Then, the ITS analysis assesses the short-term impact of the intervention as measured by a change in the level and the over-time effect as measured by a change in the trend (i.e., slope) after the intervention.  [26] Cox proportional hazard models were fit to estimate the all-cause adjusted hazard ratio (aHR) and 95% confidence interval (CI).  [10] Subsequently, multivariate logistic regression analysis was performed to evaluate the association between risk factors and long-term discontinuation of anti-TB treatment. The results are reported as the adjusted odds ratio (aOR) with a 95% CI. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Inc., Cary, NC) at a significance level of 5%.

Results

Study population

During the study period, 73,116 drug-susceptible pulmonary TB and 1,673 drug-resistant pulmonary TB patients were extracted. Among drug-susceptible pulmonary TB patients, 39,540 and 33,576 were newly diagnosed and treated before and after introducing the total cost exemption of medical service copayment. In the case of drug-resistant TB, newly diagnosed patients during pre- and post-cost exemption policy were 950 and 723 for each (Figure 1). As demographic data described in Table 1, male and older patients were frequent in both groups. In the case of drug-susceptible pulmonary TB, the long-term treatment discontinuation rate during the post-policy period was lower than before the policy change (30.1% vs. 25.3%, P < 0.0001). However, the long-term treatment discontinuation rate of anti-TB medications in drug-resistant pulmonary TB showed no difference between the pre-and post-cost exemption period (68.3% vs. 69.8%, P = 0.502). 

Long-term treatment interruption by treatment phase in the pulmonary TB groups

Among the drug-susceptible TB patients, compared to the periods before and after the cost exemption policy, the number of long-term discontinuation cases per 100,000 patients during the intensive phase showed no significant difference (8,841 vs. 8,422, P = 0.074). Furthermore, there was no significant change in the slope of the long-term discontinuation rate (slope change: 0.015, P = 0.747). On the other hand, in the continuation phase, the number of long-term discontinuation cases per 100,000 patients and trend slope significantly decreased after the cost exemption policy (21,940 vs. 17,319, P < 0.0001; slope change: −0.097, P = 0.011) (Figure 2). Regarding the intensive phase of drug-resistant TB patients, although the number of long-term discontinuation cases per 100,000 patients decreased (34,182 vs. 31,784, P = 0.501), the slope showed an increasing tendency after policy change during the intensive phase (slope change: 0.733, P = 0.001). However, there was no significant change during the continuation phase (44,348 vs. 44,962, P = 0.782; slope change: −0.049, P = 0.803) (Figure 3).  

Risk factors for long-term TB treatment interruption

Old age (aOR, 1.15; 95% CI, 1.11–1.19), multiple comorbidities (CCI ≥ 3) (aOR, 1.17; 95% CI, 1.13–1.21), and drug resistance for first-line TB drugs (aOR, 6.04; 95% CI, 5.43–6.71) were revealed as risk factors for predicting the long-term discontinuation of anti-TB medications among the total study population (Table 2). They were also identified as significant risk factors in the analysis among drug-susceptible and drug-resistant TB patients (Supplementary Tables S2 and S3). 

Mortalities according to the history of long-term TB treatment interruption

The mean follow-up periods were 47.9 and 63.8 months for drug-susceptible and drug-resistant TB for each. In the case of drug-susceptible pulmonary TB, patients with long-term treatment interruption showed a higher overall mortality rate than those without (32.2% vs. 15.0%, P < 0.0001) (Figure 4). In the case of drug-resistant TB, mortality was also higher in patients with a history of long-term treatment discontinuation (12.1% vs. 8.3%, P = 0.008).  

Risk factors associated with 1-year and overall mortality 

Old age (aHR 5.96; 95% CI, 5.23–6.78 [1-year mortality], aHR, 5.83; 95% CI, 5.49–6.20 [overall mortality]), male sex (aHR 1.47; 95% CI, 1.35–1.60 [1-year mortality], aHR, 1.59; 95% CI, 1.52–1.66 [overall mortality]), high CCI (aHR 2.40; 95% CI, 2.18–2.65 [1-year mortality], aHR, 1.97; 95% CI, 1.88–2.06 [overall mortality]), and history of long-term discontinuation of anti-TB drugs (aHR 2.01; 95% CI, 1.86–2.18 [1-year mortality], aHR, 1.77; 95% CI, 1.70–1.84 [overall mortality]) were revealed as risk factors for both 1-year and overall mortality. However, drug-resistant for first-line TB drugs was a negative risk factor for mortality (aHR, 0.02; 95% CI, 0.01–0.15 [1-year mortality], aHR, 0.57; 95% CI, 0.48–0.68 [overall mortality]) (Table 3).

Discussion

Many countries have implemented or tried to implement universal health coverage to improve drug adherence and treatment outcomes of pulmonary TB.  [27-31] In this context, the government of South Korea waived the medical service co-payment for pulmonary TB after July 2016. When comparing outcomes before and after the policy change, a decreasing trend of the long-term treatment discontinuation rate during the continuation phase in drug-susceptible TB was observed. This suggests that reducing the financial burden could help increase treatment compliance because of the nature of TB treatment which requires long-term treatment for more than 6 months. However, a significant difference in long-term treatment discontinuation rate after the cost exemption was not found among drug-resistant TB. The complex nature of drug-resistant TB treatment, such as the long duration of treatment and high rate of adverse events of second-line TB drugs, contributes to lower compliance than first-line TB treatment.  [32] This suggests that additional alternatives other than financial support are needed to increase treatment compliance. In addition, various individual and psycho-social supports, such as self-motivation, awareness about disease and treatment, counseling support, family support, and nutritional support, were important drivers for successful treatment.  [33-35] Therefore, taking these factors into account and correcting them together are expected to reduce treatment discontinuation and improve treatment outcomes.

Unmodifiable variables, such as old age, multiple comorbidities, and drug-resistant TB, were revealed as risk factors for long-term discontinuation of anti-TB drugs. Notably, patients with drug-resistant TB were 6.04 times more likely to experience long-term treatment discontinuation than patients with drug-susceptible TB. Because long treatment interruption, including LTFU, leads to prolonged infectiousness, relapse, death, acquired drug resistance, and treatment failure, special attention is needed during treatment for patients with risk factors.  [36]

According to a long-term mortality analysis study using nationwide population-based data in South Korea, the 5-year mortality rate for TB infection was 24.7%, and the overall mortality rate was 3.23 times higher than that of the general population.  [37] Because our result suggests that the mortality rate in TB patients undergoing long-term discontinuation was 1.77 times higher than those without, efforts to increase treatment compliance of drug-resistant TB patients are significant and urgent to improve the survival rate.

Our study had several strengths. First, it is the first study to analyze the effect of implementing the cost exemption policy on the clinical outcomes of pulmonary TB. In particular, a large-scale study using national health insurance data strengthens the power of the results. Through this study, we found that the political change to widen the coverage helped improve the treatment compliance of pulmonary TB patients. It can also be applied to improve treatment outcomes of other refractory diseases. In addition, the experience of long-term discontinuation of anti-TB drugs, regardless of treatment termination status, negatively affects the long-term survival rate, thus efforts to increase treatment compliance should be highlighted.

However, this study had several limitations. Because pulmonary TB cases were screened and analyzed based on the operational definition using diagnostic code rather than nationwide TB notification data, we could not confirm four treatment outcomes according to guidelines and previous studies.  [38, 39] Especially, information on sputum smear or culture status was unavailable in our data. Hence, we could not capture the detailed treatment outcome, such as treatment failure. In addition, it was challenging to distinguish treatment completion and LTFU, so the long-term treatment discontinuation rate reported herein was likely to be higher than the LTFU rate in the actual central reported data. A recent study analyzing the ratio of LTFU in drug-susceptible TB patients from the Korean National TB Surveillance System reported the LTFU rate as 4.4–12.3%, which supports this theory.  [40] 

Conclusions

In conclusion, implementing the cost exemption policy reduced the long-term treatment discontinuation rate during the continuous phase of drug-susceptible TB patients. And drug-resistant TB was identified as a risk factor for increasing the long-term discontinuation rate of anti-TB drugs, along with old age and multiple comorbidities (CCI ≥ 2). Because the history of long-term treatment discontinuation, regardless of treatment termination status, was a risk factor for increased mortality, efforts to improve patient adherence would be necessary to lead to effective treatment outcomes in TB patients.

Abbreviations

aHR, adjusted hazard ratio

aOR, adjusted odds ratio

CCI, Charlson comorbidity index

CI, confidence interval

ICD-10, International Statistical Classification of Diseases and Related Health Problems

ITS, interrupted time series

LTFU, loss to follow-up

NHIS, National Health Insurance Service

TB, tuberculosis

Declarations

Ethics approval and consent to participate

The Institutional Review Board of NHIS Ilsan Hospital approved the study, and the study adhered to the Declaration of Helsinki's tenets (NHIMC 2022-05-015). Because this study was based on anonymous health claims data, the requirement for patient consent was waived.

Consent for publication

Not applicable

Availability of data and materials

Any data generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

None

Authors’ contributions

SCL takes full responsibility for the content of this manuscript, including the data and analyses. SCL made substantial contributions to the concept and design of the study. SCL and JKL made substantial contributions to the analysis and interpretation of data. JML, SCP, CHH, and SCL drafted the initial manuscript. All authors discussed the results and reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgments

None

References

1. Organization WH. WHO TB burden estimates. In: Geneva; 2020.
2. Im C, Kim Y. Spatial pattern of tuberculosis (TB) and related socio-environmental factors in South Korea, 2008-2016. PLoS One. 2021;16(8):e0255727.
3. Cho KS. Tuberculosis control in the Republic of Korea. Epidemiol Health. 2018;40:e2018036.
4. Viana PVS, Redner P, Ramos JP. Factors associated with loss to follow-up and death in cases of drug-resistant tuberculosis (DR-TB) treated at a reference center in Rio de Janeiro, Brazil. Cad Saude Publica. 2018;34(5):e00048217.
5. Baliashvili D, Magee MJ, Kempker RR, Kuchukhidze G, Aslanikashvili A, Blumberg HM. Contacts of retreatment tuberculosis cases with a prior poor treatment outcome are at increased risk of latent tuberculosis infection. Int J Infect Dis. 2016;43:49-50.
6. Tupasi TE, Garfin AM, Kurbatova EV, Mangan JM, Orillaza-Chi R, Naval LC, et al. Factors Associated with Loss to Follow-up during Treatment for Multidrug-Resistant Tuberculosis, the Philippines, 2012-2014. Emerg Infect Dis. 2016;22(3):491-502.
7. Alene KA, Yi H, Viney K, McBryde ES, Yang K, Bai L, et al. Treatment outcomes of patients with multidrug-resistant and extensively drug resistant tuberculosis in Hunan Province, China. BMC Infect Dis. 2017;17(1):573.
8. Thet Lwin ZM, Sahu SK, Owiti P, Chinnakali P, Majumdar SS. Public-private mix for tuberculosis care and control in Myanmar: a strategy to scale up? Public Health Action. 2017;7(1):15-20.
9. Gadoev J, Asadov D, Tillashaykhov M, Tayler-Smith K, Isaakidis P, Dadu A, et al. Factors Associated with Unfavorable Treatment Outcomes in New and Previously Treated TB Patients in Uzbekistan: A Five Year Countrywide Study. PLoS One. 2015;10(6):e0128907.
10. Wikman-Jorgensen PE, Morales-Cartagena A, Llenas-García J, Pérez-Porcuna TM, Hobbins M, Ehmer J, et al. Implementation challenges of a TB programme in rural northern mozambique: evaluation of 2012-2013 outcomes. Pathog Glob Health. 2015;109(5):221-7.
11. van Lettow M, Bedell R, Maosa S, Phiri K, Chan AK, Mwinjiwa E, et al. Outcomes and Diagnostic Processes in Outpatients with Presumptive Tuberculosis in Zomba District, Malawi. PLoS One. 2015;10(11):e0141414.
12. Wondale B, Medihn G, Teklu T, Mersha W, Tamirat M, Ameni G. A retrospective study on tuberculosis treatment outcomes at Jinka General Hospital, southern Ethiopia. BMC Res Notes. 2017;10(1):680.
13. Conaty SJ, Dart S, Hayward AC, Lipman MC. Reasons for low reported treatment success in notified tuberculosis patients from a London hospital according to new outcome reporting. Commun Dis Public Health. 2004;7(1):73-6.
14. Park YS, Hong SJ, Boo YK, Hwang ES, Kim HJ, Cho SH, et al. The national status of tuberculosis using nationwide medical records survey of patients with tuberculosis in Korea. Tuberc Respir Dis (Seoul). 2012;73(1):48-55.
15. Kim DH, Kim HJ, Park SK, Kong SJ, Kim YS, Kim TH, et al. Treatment outcomes and long-term survival in patients with extensively drug-resistant tuberculosis. Am J Respir Crit Care Med. 2008;178(10):1075-82.
16. Kim DH, Kim HJ, Park SK, Kong SJ, Kim YS, Kim TH, et al. Treatment outcomes and survival based on drug resistance patterns in multidrug-resistant tuberculosis. Am J Respir Crit Care Med. 2010;182(1):113-9.
17. Johnston JC, Shahidi NC, Sadatsafavi M, Fitzgerald JM. Treatment outcomes of multidrug-resistant tuberculosis: a systematic review and meta-analysis. PLoS One. 2009;4(9):e6914.
18. Millett ER, Noel D, Mangtani P, Abubakar I, Kruijshaar ME. Factors associated with being lost to follow-up before completing tuberculosis treatment: analysis of surveillance data. Epidemiol Infect. 2013;141(6):1223-31.
19. Choi H, Chung H, Muntaner C, Lee M, Kim Y, Barry CE, et al. The impact of social conditions on patient adherence to pulmonary tuberculosis treatment. Int J Tuberc Lung Dis. 2016;20(7):948-54.
20. Akkerman O, Tiberi S. The importance of knowing why TB patients stop anti-TB treatment. International Journal of Tuberculosis and Lung Disease. 2020;24(10):989-90.
21. Kim H, Min J, Shin A, Koo H, Lim S, Park M, et al. Reasons why patients with tuberculosis in South Korea stop anti-TB treatment: a cross-sectional study. The International Journal of Tuberculosis and Lung Disease. 2020;24(10):1016-23.
22. Bannay A, Chaignot C, Blotière P-O, Basson M, Weill A, Ricordeau P, et al. The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality. Medical Care. 2016;54(2):188-94.
23. Stavem K, Hoel H, Skjaker SA, Haagensen R. Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients. Clinical epidemiology. 2017;9:311-20.
24. Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. Bmj. 2015;350:h2750.
25. Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr. 2013;13(6 Suppl):S38-44.
26. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 2017;46(1):348-55.
27. Health Mo, Taiwan W. Taiwan health and welfare report. Retrived from. 2016.
28. Organization WH. Pharmaceutical pricing and reimbursement systems in eastern Europe and central Asia: report of the Pharmaceutical Pricing and Reimbursement Information network for countries in eastern Europe and central Asia. In: World Health Organization. Regional Office for Europe; 2020.
29. Xin YJ, Xiang L, Jiang JN, Lucas H, Tang SL, Huang F. The impact of increased reimbursement rates under the new cooperative medical scheme on the financial burden of tuberculosis patients. Infect Dis Poverty. 2019;8(1):67.
30. Le QN, Blizzard L, Si L, Giang LT, Neil AL. The evolution of social health insurance in Vietnam and its role towards achieving universal health coverage. Health Policy OPEN. 2020;1:100011.
31. Ikegami N, Yoo BK, Hashimoto H, Matsumoto M, Ogata H, Babazono A, et al. Japanese universal health coverage: evolution, achievements, and challenges. Lancet. 2011;378(9796):1106-15.
32. Wang Y, Chen H, Huang Z, McNeil EB, Lu X, Chongsuvivatwong V. Drug Non-Adherence And Reasons Among Multidrug-Resistant Tuberculosis Patients In Guizhou, China: A Cross-Sectional Study. Patient Prefer Adherence. 2019;13:1641-53.
33. Franke MF, Appleton SC, Bayona J, Arteaga F, Palacios E, Llaro K, et al. Risk factors and mortality associated with default from multidrug-resistant tuberculosis treatment. Clin Infect Dis. 2008;46(12):1844-51.
34. Deshmukh RD, Dhande DJ, Sachdeva KS, Sreenivas AN, Kumar AMV, Parmar M. Social support a key factor for adherence to multidrug-resistant tuberculosis treatment. Indian J Tuberc. 2018;65(1):41-7.
35. Soedarsono S, Mertaniasih NM, Kusmiati T, Permatasari A, Juliasih NN, Hadi C, et al. Determinant factors for loss to follow-up in drug-resistant tuberculosis patients: the importance of psycho-social and economic aspects. BMC Pulm Med. 2021;21(1):360.
36. Volmink J, Garner P. Directly observed therapy for treating tuberculosis. Cochrane Database Syst Rev. 2006; https://doi.org/10.1002/14651858.CD003343.pub2.(2):Cd003343.
37. Park SC, Kang MJ, Han CH, Lee SM, Kim CJ, Lee JM, et al. Long-term mortality of patients with tuberculosis in Korea. Int J Tuberc Lung Dis. 2020;24(5):492-8.
38. Organization WH, Initiative ST. Treatment of tuberculosis: guidelines: World Health Organization; 2010.
39. Holden IK, Andersen PH, Wejse C, Lillebaek T, Johansen IS. Review of tuberculosis treatment outcome reporting system in Denmark, a retrospective study cohort study from 2009 through 2014. BMC Health Serv Res. 2020;20(1):83.
40. Kim HW, Park S, Min J, Sun J, Shin AY, Ha JH, et al. Hidden loss to follow-up among tuberculosis patients managed by public-private mix institutions in South Korea. Sci Rep. 2022;12(1):12362.

Tables

Table 1. Baseline characteristics of the study population

Notes: Data are presented as mean ± standard deviation and numbers (%) 

* Initial 2 months for drug-susceptible pulmonary tuberculosis and 8 months for drug-resistant pulmonary tuberculosis during the intensive phase and at least 4 months for drug-susceptible pulmonary tuberculosis and 12 months for drug-resistant pulmonary tuberculosis during the continuation phase.

TB, tuberculosis; CCI, Charlson comorbidity score; MDR, multi-drug resistant; XDR, extensively drug resistant

Table 2. Risk factors associated with long-term treatment interruption in the total study population

OR, odds ratio; CCI, Charlson comorbidity index; MDR, multi-drug resistant; XDR, extensively drug resistant; TB, tuberculosis

Table 3. Risk factors associated with all-cause mortality in the total study population

* Initial 2 months for drug-susceptible pulmonary tuberculosis and 8 months for drug-resistant pulmonary tuberculosis during the intensive phase and at least 4 months for drug-susceptible pulmonary tuberculosis and 12 months for drug-resistant pulmonary tuberculosis during the continuation phase.

HR, hazard ratio; CCI, Charlson comorbidity index; TB, tuberculosis; MDR, multi-drug resistant; XDR, extensively drug resistant