[ Original Research ]

The Risk of TB in Patients With Type 2 Diabetes Initiating vs Treatment

Sheng-Wei Pan, MD; Yung-Feng Yen, MD, PhD; Yu Ru Kou, PhD; Pei-Hung Chuang, PhD; Vincent Yi-Fong Su, MD; Jia-Yih Feng, MD; Yu-Jiun Chan, MD, PhD; and Wei-Juin Su, MD, MPH

BACKGROUND: Metformin and the are common initial antidiabetic agents; the former has demonstrated anti-TB action in in vitro and animal studies. The comparative effect of metformin vs the sulfonylureas on TB risk in patients with type 2 diabetes mellitus (T2DM) remains unclear. METHODS: In this retrospective cohort study, patients without chronic kidney disease who received a T2DM diagnosis during 2003 to 2013 were identified from the Taiwan National Health Insurance Research Database. Participants with $ 2 years of follow-up were reviewed and observed for TB until December 2013. Patients receiving metformin $ 60 cumulative defined daily dose (cDDD) and sulfonylureas < 15 cDDD in the initial 2 years were defined as metformin majors; it was the inverse for sulfonylurea majors. The two groups were matched 1:1 by propensity score and compared for TB risk by multivariate Cox regression analysis. RESULTS: Among 40,179 patients with T2DM, 263 acquired TB (0.65%) over a mean follow- up of 6.1 years. In multivariate analysis, the initial 2-year dosage of metformin, but not that of the sulfonylureas, was an independent predictor of TB (60-cDDD increase (adjusted hazard ratio [HR], 0.931; 95% CI, 0.877-0.990) after adjustment by cofactors, including adapted diabetes complication severity index. Metformin majors had a significantly lower TB risk than that of sulfonylurea majors before and after matching (HR, 0.477; 95% CI, 0.268-0.850 and HR, 0.337; 95% CI, 0.169-0.673; matched pairs, n ¼ 3,161). Compared with the reference group (initial 2-year metformin < 60 cDDD), metformin treatment showed a dose- dependent association with TB risk (60-219 cDDD; HR, 0.860; 95% CI, 0.637-1.161; 220- 479 cDDD, HR, 0.706; 95% CI, 0.485-1.028; $ 480 cDDD, HR, 0.319; 95% CI, 0.118-0.863). CONCLUSIONS: Metformin use in the initial 2 years was associated with a decreased risk of TB, and metformin users had a reduced risk compared with their sulfonylurea comparators. CHEST 2017; -(-):---

KEY WORDS: diabetes mellitus; metformin; prevention; sulfonylureas; TB

ABBREVIATIONS: aDCSI = adapted diabetes complication severity AFFILIATIONS: From the Institute of Public Health (Drs Pan, Yen, index; AMPK = adenosine monophosphate-activated protein kinase; and Chan), the Faculty of Medicine (Drs Pan, Yen, V. Y.-F. Su, Feng, cDDD = cumulative defined daily dose; CKD = chronic kidney disease; and W.-J. Su), the Institute of Physiology (Dr Kou), the Institute of DM = diabetes mellitus; ICD-9-CM = International Classification of Emergency and Critical Care Medicine (Dr Kou), and the Department Diseases; 9th Revision = Clinical Modification; LHID = Longitudinal of Biotechnology and Laboratory Science in Medicine (Dr Chan), Health Insurance Database; LTBI = latent TB infection; NHRID = National Yang-Ming University; Department of Health Care Man- National Health Insurance Research Database; T2DM = type 2 diabetes agement (Dr Yen), National Taipei University of Nursing and Health mellitus Sciences, Taipei, Taiwan; the Department of Chest Medicine

chestjournal.org 1 TB is a global infectious disease caused by glycemic control are similar, although metformin is Mycobacterium tuberculosis and remains one of the top preferred because of the lower hypoglycemia rate and 10 causes of death worldwide.1 Latent TB infection additional cardiovascular benefits.12-15 In addition, (LTBI) may progress to active disease, especially in metformin has been considered as a potential candidate high-risk populations with immunosuppression.2 drug against TB in in vitro and animal studies.9 Diabetes mellitus (DM), an immune dysfunction Recently, a case-control study reported that metformin metabolic disease affecting 8.5% of the world treatment was associated with a lower chance of active population, carries a threefold increased risk for TB in TB in patients with DM, although the underlying these patients over patients without DM.1,3,4 Among mechanisms and interaction with glycemic control patients diagnosed with TB, DM is a prevalent remain unclear.16 However, even though metformin and comorbidity and increases the risk of poor outcomes, sulfonylureas are both widely used as initial antidiabetic including treatment failure, relapse, and death.5,6 Most agents in patients with T2DM without advanced chronic previous studies aimed to improve outcomes in kidney disease (CKD),17 the beneficial effects and patients with DM acquiring active TB by extending the superiority of these two drugs in reducing TB risk duration of anti-TB treatment, ensuring adherence, among patients with T2DM remain unknown. and discovering potential therapies.7-9 However, for To this end, it is worthwhile to compare the impact of this high-risk population, information on reducing TB metformin and the sulfonylureas on the risk of TB using development is limited.1,10 a large-scale cohort study. The findings could allow Patients with DM and poor glycemic control have a physicians to make better choices for TB prevention in higher risk of TB developing than do those with better high-risk patients with T2DM. Thus, we conducted a control.11 For type 2 DM (T2DM), metformin and the population-based cohort study to investigate the effect of sulfonylureas are two of the most commonly used initial metformin vs sulfonylureas on TB risk in patients with antidiabetic agents worldwide, and their effects on T2DM.

Methods General Hospital (2015-04-004AC), and informed consent was not fi Data Source and Patients required for this study using deidenti ed secondary data. This retrospective nationwide population-based cohort study was Patients with a diagnosis of T2DM (International Classification of conducted in Taiwan using the Longitudinal Health Insurance Diseases, 9th Revision, Clinical Modification [ICD-9-CM] codes Database (LHID)-2005, a data subset of the National Health 250.x0 and 250.x2) that presented in one inpatient record or four or 19 Insurance Research Database (NHIRD), which included the data of 1 more outpatient records during 2003 to 2013 were identified. The million random samples from all the beneficiaries with registration diagnosis of T2DM was validated by the prescription of oral in 2005. The specifics of NHIRD and the accuracy of the major antidiabetic agents or injection, or both. Exclusion criteria diagnosis codes are described elsewhere.18,19 This study was included the following: age < 20 years, an antecedent history of type approved by the Institutional Review Board of Taipei Veterans 1 DM (ICD-9-CM codes 250.x1 and 250.X3), CKD (ICD-9-CM code 585),20 TB, and a diagnosis of T2DM made before 2003. Because advanced CKD, a risk factor for TB, is a contraindication for the use of metformin and most of the sulfonylureas, patients with underlying CKD were excluded to avoid selection bias.17,21 To assess (Drs Pan, Feng, and W.-J. Su), the Division of Infectious Diseases (Dr the dose effects of target drugs prescribed in the initial 2 years, only Chan), Department of Medicine, and the Division of Microbiology (Dr participants with $ 2 years of follow-up were included. Because Chan), Department of Pathology and Laboratory Medicine, Taipei people with a T2DM diagnosis prior to 2003 may have died before Veterans General Hospital; the Section of Infectious Diseases (Dr Yen), 2005 and had no chance to be randomly sampled into the LHID- and the Department of Internal Medicine (Dr V. Y.-F. Su), Taipei City $ Hospital; and the Taipei Association of Health and Welfare Data 2005, despite having 2 years of follow-up, all subjects with a Science (Dr Chuang), Taipei, Taiwan. T2DM diagnosis prior to 2003 were excluded to avoid unbalanced Drs Pan and Feng contributed equally to this work as co-first authors. selection. Additionally, because statin drugs are associated with a reduced risk of TB, as previously reported,22,23 patients who used Drs Chan and W. J. Su contributed equally as co-corresponding > fi authors. statin drugs ( 15 cumulative de ned daily dose, cDDD) before the FUNDING/SUPPORT: index dates were excluded to minimize confounding factors. The This work was supported by the Taipei Veterans fi General Hospital [Grant V106B-015] and the Ministry of Science and index date was the date of rst-time T2DM diagnosis. The included Technology, Taiwan [MOST 106-2314-B-075-007]. patients with T2DM were observed from the index date to the end CORRESPONDENCE TO: Wei-Juin Su, MD, MPH, Department of Chest points, namely, the occurrence of TB, withdrawal from the national Medicine, Taipei Veterans General Hospital, No. 201, Sec 2, Shih-Pai health insurance system, and December 31, 2013. Rd, Taipei 11217, Taiwan; e-mail: [email protected] Outcomes and Measurement Copyright Ó 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved. The outcome was TB occurrence (codes 010-018 in ICD-9-CM) DOI: https://doi.org/10.1016/j.chest.2017.11.040 validated by the prescription of at least two anti-TB drugs for > 28

2 Original Research [ - # - CHEST - 2017 ] cDDD during 180-day intervals.22 DM severity was assessed by the exposure to $ 60 cDDD of definite . The DDD of adapted diabetes complication severity index (aDCSI) score, which metformin was 2,000 mg. In contrast to metformin, a single drug, ranged from 0 to 13. As previously validated and used in claims data the sulfonylureas in this study consisted of several drugs, including studies, the aDSCI score was calculated by a summation of scores , , , , , from seven complication categories of DM after the exclusion of , , , glibornuride, and . items of laboratory results in the original DSCI.24-27 Complications The sulfonylureas were chosen as the comparator to metformin that presented in one inpatient record or three or more outpatient because both metformin and the sulfonylureas can be used as first- records in the years preceding and following the index date were line therapy for T2DM.12,30 counted for this baseline aDCSI. The comorbidities of interest are listed in Table 1, and their corresponding ICD-9-CM codes are Metformin Majors and the Sulfonylurea Majors 18 described elsewhere. The definitions for TB exposure and other fi 7,18,26 Participants with T2DM were classi ed as metformin majors if they rare conditions are listed in e-Appendix 1. Since urbanization had received $ 60 cDDD of metformin and < 15 cDDD of a levels in Taiwan are divided into seven strata according to NHIRD- sulfonylurea in the initial 2 years; it was the inverse for sulfonylurea 28 fi related publications, urbanization was classi ed into urban (levels majors, who had received $ 60 cDDD of a sulfonylurea and < 15 1-2), suburban (levels 3-4), and rural (levels 5-7) areas in this study. cDDD of metformin (Fig 1). Moreover, metformin majors and Income level, an indicator of socioeconomic status, was categorized fi 18 sulfonylurea majors were strati ed by their index years and then into three levels, as previously described. matched 1:1 by propensity score. Logistic regression was used to fi estimate the probability of metformin exposure; the propensity Using the Anatomical Therapeutic Chemical Classi cation System 29 With Defined Daily Doses scheme of the World Health Organization scores were calculated on the basis of age, sex, and aDCSI. (http://www.whocc.no), the cDDDs of each drug were standardized.29 The cDDDs of metformin, the sulfonylureas, statin Statistical Analysis drugs, and insulin during the initial 2 years (a 720-day period) were The variables are presented as mean SD for continuous variables calculated, and the users of certain drugs were defined by their and as numbers (%) for categorical variables. The independent t test

TABLE 1 ] Characteristics in Patients With T2DM Stratified by aDSCI Score

T2DM, All aDCSI Score, 0 aDCSI Score, 1-2 aDCSI Score $ 3 Variable (N ¼ 40,179) (n ¼ 26,976) (n ¼ 11,065) (n ¼ 2,138) Age, y 57.3 13.2 55.0 12.5 61.0 13.1 67.5 13.4 Male sex 21,384 (53) 14,361 (53) 5,810 (53) 1,213 (57) Level of income High income 7,383 (18) 5,335 (20) 1,783 (16) 265 (12) Intermediate 16,050 (40) 11,072 (41) 4,213 (38) 765 (36) Low income 16,746 (41) 10,569 (39) 5,069 (46) 1,108 (52) Urbanization Urban area 23,526 (59) 16,109 (60) 6,308 (57) 1,109 (52) Suburban area 12,316 (31) 8,150 (30) 3,452 (31) 714 (33) Rural area 4,337 (10) 2,717 (10) 1,305 (12) 315 (15) Metformin dose, 60-cDDD/initial 2 y 2.1 2.7 2.0 2.6 2.1 2.8 2.1 3.0 Sulfonylurea dose, 60-cDDD/initial 2 y 4.7 7.4 4.7 7.2 4.9 7.7 4.4 7.5 Statin drug dose, 60-cDDD/initial 2 y 0.9 1.9 0.8 1.8 1.0 2.1 1.0 2.2 Insulin use 3,791 (9) 2,094 (8) 1,258 (11) 439 (21) Comorbidities Coronary artery disease 3,407 (8) 13 (0.05) 2,710 (24) 684 (32) Cerebrovascular disease 2,392 (6) 156 (1) 1,287 (12) 949 (44) Malignancy 1,258 (3) 848 (3) 331 (3) 79 (4) COPD 1,529 (4) 653 (2) 618 (6) 258 (12) Asthma 1,115 (3) 594 (2) 397 (4) 124 (6) Liver cirrhosis 456 (1) 296 (1) 126 (1) 34 (2) Rheumatoid arthritis 225 (1) 122 (0.5) 81 (1) 22 (1) Follow-up y 6.1 2.6 6.1 2.6 6.1 2.6 5.7 2.6 TB development 263 (1) 158 (1) 86 (1) 19 (1) TB per 100,000 person-years 106.9 95.3 126.4 155.0

Continuous data expressed as mean SD and categorical data expressed as No. (%). aDSCI ¼ adapted diabetes complication severity index; cDDD ¼ cumulative defined daily dose, T2DM ¼ type 2 diabetes mellitus.

chestjournal.org 3 96,069 subjects with a diagnosis of T2DM during 2003-2013

460 younger than 20 y 607 missing data 3,317 with type 1 DM diagnosis 11,136 with CKD diagnosis 570 with an antecedent history of TB 57,918 new T2DM, non-CKD 22,061 with T2DM diagnosis prior to 2003

12,959 follow-up <2 y (include 271 TB) 4,780 statin ≥15 cDDD before T2DM

40,179 T2DM enrolled classified by metformin (MFM) & sulfonylurea (SFU) cDDD in the initial 2 y (cDDDin2Y)

19,647 MFM cDDDin2Y ≥60 4,771 MFM cDDDin2Y 15-59 15,761 MFM cDDDin2Y <15

14,623 SFU cDDDin2Y ≥15 11,310, SFU cDDDin2Y <60

5,024 SFU cDDDin2Y <15 4,451 SFU cDDDin2Y ≥60 (MFM major) (SFU major)

Figure 1 – Flowchart of the study. cDDD ¼ cumulative defined daily dose; CKD ¼ chronic kidney disease; DM ¼ diabetes mellitus; T2DM ¼ type 2 diabetes mellitus.

(continuous variables), c2 test statistics (frequency measures), hazard ratios (HRs) with 95% CIs were calculated. The data Kaplan-Meier method, and log-rank test were used to examine the extraction from LHID-2005 was performed using SAS, version 9.4 differences between groups. Cox proportional hazard regression (SAS Institute), and data were analyzed in SPSS, version 20.0 models were used to identify risk factors for TB development, and (SPSS Inc).

Results and $ 3 (crude HR, 1.326; 95% CI, 1.020-1.724 and Characteristics of Participants 95% CI, 1.680 1.044-2.704). We identified 96,096 patients with a DM diagnosis Independent Risk Factors for TB in T2DM during 2003 to 2013 and finally included 40,179 subjects with newly diagnosed T2DM without underlying CKD The characteristics of patients with T2DM with and and with > 2 years of follow-up, as presented in without TB development are presented in Table 2.In Figure 1. In particular, 271 cases with coprevalent TB multivariate Cox regression analysis, the independent that occurred in the initial 2 years were also excluded. risk factors for TB in patients with T2DM were older The characteristics of patients are shown in Table 1. age (adjusted HR, 1.040; 95% CI, 1.030-1.051), male Over a mean follow-up of 6.1 years, 263 patients with sex (adjusted HR, 2.973; 95% CI, 2.251-3.927), low T2DM (0.65%) acquired TB after the initial 2 years, with income (adjusted HR, 1.710; 95% CI, 1.147-2.548), corresponding TB incidences of 107 per 100,000 person- and metformin and statin drug doses in the initial 2 years. According to DM severity, indicated by aDCSI, years (720 days) (60-cDDD increase, adjusted HR, 26,976, 11,065 and 2,138 patients were classified into 0.931; 95% CI, 0.877-0.990 and adjusted HR, 0.900; groups by aDCSI scores of 0, 1-2, and $ 3; these groups 95% CI, 0.811-0.999) after adjustment for had corresponding TB incidences of 95, 126, and 155 per confounding factors, including aDCSI score. The dose 100,000 person-years, respectively. Compared with the of sulfonylureas in the initial 2 years is not an group with an aDSCI score of 0, the risk of TB independent risk factor for TB development in development increased for the groups with scores of 1-2 patients with T2DM.

4 Original Research [ - # - CHEST - 2017 ] chestjournal.org

TABLE 2 ] Analysis of Risk Factors for TB Development in T2DM Cohort (N ¼ 40,179)

TB Development Univariate Analysis Multivariate Analysis Variable Yes (n ¼ 263) No (n ¼ 39,916) Crude HR (95% CI) P Value Adjusted HR (95% CI) P Value Age, y 63.2 13.3 57.3 13.2 1.042 (1.032-1.052) < .001 1.040 (1.030-1.051) < .001 Male sex 194 (74) 21,190 (53) 2.572 (1.954-3.386) < .001 2.973 (2.251-3.927) < .000 aDCSI score 0.8 1.1 0.5 1.0 1.207 (1.089-1.337) < .001 1.054 (0.924-1.202) .435 Level of income High income 30 (11) 7,353 (18) 1 (reference) 1 (reference) Intermediate 70 (27) 15,980 (40) 1.260 (0.821-1.934) .290 1.300 (0.845-2.002) .233 Low income 163 (62) 16,583 (42) 2.012 (1.363-2.971) < .001 1.710 (1.147-2.548) .008 Urbanization Urban area 137 (52) 23,389 (59) 1 (reference) 1 (reference) Suburban area 82 (31) 12,234 (30) 1.178 (0.896-1.549) .241 1.051 (0.798-1.384) .723 Rural area 44 (17) 4,293 (11) 1.786 (1.271-2.508) .001 1.392 (0.985-1.968) .061 Metformin dose, 60-cDDD/initial 2 y 1.4 2.1 2.1 2.7 0.900 (0.851-0.951) < .001 0.931 (0.877-0.990) .022 Sulfonylurea dose, 60-cDDD/initial 2 y 4.3 6.7 4.7 7.4 0.980 (0.962-0.998) .029 0.995 (0.976-1.015) .631 Statin drug dose, 60-cDDD/initial 2 y 0.4 1.1 0.9 1.9 0.848 (0.761-0.944) .003 0.900 (0.811-0.999) .047 Insulin use 33 (13) 3,758 (9) 1.136 (0.789-1.638) .493 1.189 (0.817-1.731) .367 Comorbidity Coronary artery disease 23 (9) 3,384 (8) 1.047 (0.683-1.606) .834 0.677 (0.427-1.071) .095 Cerebrovascular disease 26 (10) 2,366 (6) 1.907 (1.272-2.859) .002 1.114 (0.693-1.793) .656 Malignancy 7 (3) 1,251 (3) 0.993 (0.469-2.104) .985 0.740 (0.347-1.577) .436 COPD 18 (7) 1,511 (4) 2.040 (1.264-3.292) .004 0.921 (0.549-1.547) .757 Asthma 15 (6) 1,100 (3) 2.248 (1.335-3.786) .002 1.749 (1.007-3.038) .047 Liver cirrhosis 7 (3) 449 (1) 3.023 (1.426-6.406) .004 2.388 (1.117-5.105) .025 Rheumatoid arthritis 4 (2) 221 (1) 2.741 (1.021-7.358) .045 2.478 (0.920-6.673) .073

Continuous data expressed as mean SD and categorical data expressed as No. (%). HR, hazard ratio. See Table 1 legend for expansion of other abbreviations. 5 Characteristics in Metformin Majors and metformin major and sulfonylurea major groups were Sulfonylurea Majors 55 and 158 per 100,000 person-years, respectively. As shown in Figure 1, by exposure to $ 60 cDDD of one major drug but < 15 of the other in the initial 2 years, TB Risk in Metformin Majors and Sulfonylurea Comparators 5,024 patients with T2DM were classified as metformin majors and 4,451 as sulfonylurea majors. Using 1:1 As presented in Table 4, for unmatched metformin propensity score matching after stratification by index majors and sulfonylurea comparators, a multivariate year, 3,161 patients in each of the two groups were model showed that metformin majors had a significant selected for further analysis. As shown in Table 3, before reduction of TB risk compared with sulfonylurea majors matching, the number of metformin majors increased as (adjusted HR, 0.477; 95% CI, 0.268-0.850). For matched the index years passed and that of sulfonylurea majors metformin majors and sulfonylurea majors, the decreased over time. After matching, the age, sex, aDCSI multivariate analysis confirmed that the risk of TB scores, and index year were not statistically different remained significantly lower in metformin majors than between the two matched groups. Specifically, a history in sulfonylurea comparators (adjusted HR, 0.337; of TB exposure, AIDS, and renal disease other than CKD 95% CI, 0.169-0.673). Figure 2 shows a subgroup were roughly equal in both groups, as shown in analysis of the risk of TB on metformin majors e-Table 1. The incidence rates of TB in the matched compared with matched sulfonylurea majors. Notably,

TABLE 3 ] Characteristics in Metformin Majors and Sulfonylurea Majors Before and After Propensity Score Matching

Before Matching After Matching Metformin Majors Sulfonylurea Majors Metformin Majors Sulfonylurea Majors (n ¼ 5,024) (n ¼ 4,451) P Value (n ¼ 3,161) (n ¼ 3,161) P Value Age, y 57.3 13.1 59.1 12.5 < .001 58.5 12.5 58.6 12.3 .943 Male sex 2,482 (49) 2,357 (53) .001 1,609 (51) 1,628 (52) .651 aDCSI score 0.5 1.0 0.5 1.0 .821 0.5 0.9 0.6 1.0 .347 Index year 2003-2004 691 (14) 1,490 (33) < .001 662 (21) 662 (21) 1.000 2005-2006 860 (17) 1,142 (26) < .001 769 (24) 769 (24) 1.000 2007-2008 1,110 (22) 927 (21) .139 849 (27) 849 (27) 1.000 2009-2011 2,363 (47) 892 (20) < .001 881 (28) 881 (28) 1.000 Low income 1,773 (35) 2,062 (46) < .001 1,258 (40) 1,315 (42) .152 Rural area 414 (8) 549 (12) < .001 270 (9) 382 (12) < .001 Statin drug dose, 60- 1.2 2.3 0.8 1.8 < .001 1.1 2.2 1.0 2.0 .001 cDDD/initial 2 y Insulin use 294 (6) 389 (9) < .001 199 (6) 246 (8) .024 Comorbidities Coronary artery 455 (9) 398 (9) .857 303 (10) 289 (9) .575 disease Cerebrovascular 316 (6) 247 (6) .139 206 (7) 176 (6) .126 disease Malignancy 156 (3) 119 (3) .220 99 (3) 80 (3) .172 COPD 171 (3) 170 (4) .294 111 (4) 119 (4) .638 Asthma 146 (3) 117 (3) .416 95 (3) 93 (3) .941 Liver cirrhosis 25 (0.5) 54 (1) < .001 19 (1) 35 (1) .039 Rheumatoid 33 (1) 31 (1) .900 17 (1) 23 (1) .428 arthritis Follow-up y 5.5 2.4 7.0 2.5 < .001 6.3 2.5 6.4 2.5 .086 TB development 16 (0.3) 45 (1) < .001 11 (0.3) 32 (1) .002

Continuous data expressed as mean SD and categorical data expressed as No. (%). See Table 1 legend for expansion of abbreviations.

6 Original Research [ - # - CHEST - 2017 ] TABLE 4 ] Analysis of Risk Factors for TB Development in Metformin Majors and Sulfonylurea Majors Before and After Matching

Before Matching After Matching Adjusted HR (95% CI) P Value Adjusted HR (95% CI) P Value Sulfonylurea or metformin use Sulfonylurea majors 1 (reference) 1 (reference) Metformin majors 0.477 (0.268-0.850) .012 0.337 (0.169-0.673) .002 Age, y 1.067 (1.043-1.091) < .001 1.060 (1.031-1.089) < .001 Male sex 2.815 (1.616-4.904) < .001 4.640 (2.209-9.743) < .001 aDCSI score 1.014 (0.765-1.343) .925 0.917 (0.627-1.342) .655 Level of income High income 1 (reference) 1 (reference) Intermediate 1.084 (0.455-2.583) .855 0.764 (0.267-2.188) .616 Low income 1.533 (0.701-3.348) .284 1.603 (0.646-3.979) .309 Urbanization Urban area 1 (reference) 1 (reference) Suburban area 0.803 (0.448-1.440) .462 0.886 (0.449-1.749) .728 Rural area 1.076 (0.510-2.268) .848 1.186 (0.478-2.945) .713 Statin drug dose, 60-cDDD/initial 2 y 0.935 (0.788-1.108) .438 0.873 (0.700-1.090) .231 Insulin use 0.999 (0.426-2.344) .999 0.466 (0.112-1.945) .295 Comorbiditiesa Coronary artery disease 1.152 (0.525-2.530) .724 1.154 (0.436-3.055) .773 Cerebrovascular disease 1.343 (0.521-3.458) .542 1.347 (0.401-4.528) .630 COPD or asthma, or both 0.861 (0.336-2.211) .756 1.299 (0.493-3.423) .597 Other 0.664 (0.161-2.737) .570 1.001 (0.239-4.200) .999

See Table 1 and 2 legends for expansion of abbreviations. aBecause the case numbers of certain comorbidities were too small to analyze their effect on TB risk, COPD and asthma were grouped as 1 item, whereas malignancy, liver cirrhosis, and rheumatoid arthritis were grouped and named as “other.”

TB risk for matched metformin majors Decreased Risk Increased Risk compared with sulfonylurea majors aHRa(95% Cl) All matched patients (n = 6,322) 0.335 (0.168-0.669) Age ≥ 60 y (n = 2,725) 0.356 (0.156-0.810) Age < 60 y (n = 3,597) 0.299 (0.082-1.090) Male sex (n = 3,237) 0.298 (0.134-0.662) Female gender (n = 3,085) 0.239 (0.106-1.747) aDSCI score ≥ 1 (n = 2,045) 0.186 (0.053-0.647) aDSCI score = 0 (n = 4,277) 0.483 (0.207-1.129) Index year 2003-2006 (n = 2,862) 0.353 (0.164-0.760) Index year 2007-2011 (n = 3,460) 0.269 (0.053-1.380) Low income level (n = 2,573) 0.411 (0.180-0.940) Not low income (n = 3,749) 0.271 (0.075-0.980) Patients with comorbidity (n = 1,373) 0.133 (0.030-0.598) Without listed comorbidity (n = 4,949) 0.479 (0.215-1.066)

0.0 0.3 0.5 0.8 1.0 1.3 1.5

Figure 2 – Subgroup analysis of the risk of TB for metformin majors compared with the matched sulfonylurea comparators. aDCSI ¼ adapted diabetes complication severity index; aHR ¼ adjusted hazard ratio.aMultivariate analysis including age, sex, aDCSI score, income level, urbanization, statin drug dosage, insulin use, and comorbidities.

chestjournal.org 7 metformin majors had a lower risk of TB in different sulfonylurea dosage, was independently associated with subgroups stratified by age, sex, aDCSI score, index year, a decreased risk of TB in patients with T2DM without income level, and comorbidities. CKD after adjustment. Moreover, this study indicated that metformin majors exposed to metformin of $ 60 Dose-Response Relationship Between Metformin < Use and TB Risk cDDD and sulfonylureas of 15 cDDD in their initial 2 years had a 66% reduced risk of TB development The risks of TB were assessed in all patients with T2DM compared with the propensity score matched exposed to different dosage ranges of metformin in the sulfonylurea majors. Thus, this large-scale cohort study initial 2 years. In Figure 3, the Kaplan-Meier curves provides the first clinical evidence that patients with < show that the reference group using 60 cDDD of T2DM initiating metformin treatment may have a metformin had the highest cumulative incidence rate of significantly lower risk for TB development than the TB, followed in descending order by ascending sulfonylurea comparators. dosage ranges (log-rank test for trend, P ¼ .001). In multivariate analysis, compared with the reference group Patients with DM are susceptible to TB because of an (n ¼ 20,532), a higher dose of metformin in the initial 2 impaired innate response to initial M tuberculosis years was associated with a decreased risk of TB infection with a subsequently delayed adaptive immune 1,3 development during follow-up (60-219 cDDD, effector response, and poorly controlled 11,31 n ¼ 10,564; adjusted HR, 0.860; 95% CI, 0.637-1.161; hyperglycemia may exacerbate the susceptibility. 220-479 cDDD, n ¼ 7,399; adjusted HR, 0.706; 95% CI, Our study included 40,719 patients with T2DM without 0.485-1.028); $ 480 cDDD, n ¼ 1,864; adjusted HR, CKD and showed that patients with escalating levels of 0.319; 95% CI, 0.118-0.863) after adjustment by age, sex, aDCSI, a marker of DM severity at baseline, had an aDCSI, income levels, urbanization, statin drug dose, increased incidence of TB during follow-up, which is insulin use, and comorbidities. Even using patients who consistent with another prospective study assessing the received 15-59 cDDD of metformin as the reference relationship between DM-related complications and TB 27 group (n ¼ 4,771), the dose-response association risk. remained evident (60-219 cDDD, adjusted HR, 0.842; More importantly, our finding is that metformin dosage 95% CI, 0.556-1.274; 220-479 cDDD, adjusted HR, in the initial 2 years leads to a significantly decreased $ 0.682; 95% CI, 0.425-1.093; 480 cDDD, adjusted HR, risk of TB development after adjustment for aDCSI 0.308; 95% CI, 0.109-0.869) after adjustment. scores and other confounders. This result may be robust, because the statistical association with TB was preserved Discussion for metformin but not its comparator the sulfonylureas. This population-based cohort study found that Moreover, our analysis demonstrated that the metformin dosage in the initial 2 years, but not cumulative TB incidence was significantly lower in

2 Log-rank test for trend, P = .001 Metformin dosage in the initial 2 y <60 cDDD (n = 20,532)

60-219 cDDD (n = 10,564)

1 TB free 220-479 cDDD (n = 7,399) initial 2 y as the baseline TB incidence (%) ≥480 cDDD (n = 1,684) Figure 3 – Kaplan-Meier curves for TB development in metformin sub- groups. The cumulative incidence of TB in T2DM subgroups of different 0 metformin doses (< 60, 60-219, 200- 479, and $ 480 cDDD in the initial 2 0 246810 years) is shown. See Figure 1 legend for expansion of abbreviations. Follow-up y

8 Original Research [ - # - CHEST - 2017 ] metformin majors than in sulfonylurea majors. information regarding the effect of metformin on TB is Furthermore, with the use of index year stratification quite scarce.16,35,36 Notably, studies targeting potential and the propensity score matched method, the benefits of metformin in preventing diseases such as multivariate analysis demonstrated that the metformin cancer have been criticized for several biases in the study major group did have a significantly reduced risk of TB design.30,37 In our study design, we selected sulfonylurea compared with the matched sulfonylurea major group users, but not nonusers of metformin, to compare the after adjustment. Finally, our subgroup analysis TB risk with metformin users as a method to reduce confirmed that the reduced risk of TB in metformin influence from confounding by indication of these majors was present consistently across various drugs. Of note, we also excluded patients with subgroups. Regarding TB prevention, our results may underlying CKD to avoid selection bias. Moreover, in imply that patients with T2DM should proactively assessing future TB risk, the dosage and subgroup consider metformin as a better choice than the classification of metformin and the sulfonylureas were sulfonylureas in their initial years of treatment unless constructed on the basis of data in the initial 2 years, not contraindicated. during the whole follow-up period, to avoid misclassification and time-related bias.30 In addition, Since metformin and the sulfonylureas are known to their effects on TB risk were adjusted by DM severity, have similar efficacy on glycemic control,15 and their indicated by baseline aDCSI, and dosage of statin drugs, confounders, including DM severity and the use of which are frequently prescribed in patients with DM and insulin, were controlled in our study, a specific are reported to have a TB prevention effect in recently mechanism other than glycemic control may influence published studies.22,23 Thus, this research was conducted the risk of TB in patients majorly exposed to the each of logically to prevent bias and make the findings more the two drugs. Metformin is a first-line antidiabetic robust. agent that decreases hepatic glucose production and improves insulin sensitivity, and it is also an adenosine This study of claims data has several limitations. First, monophosphate-activated protein kinase (AMPK) certain potential confounding factors, such as levels of activating compound.32,33 Recently, Singhal et al9 hemoglobin A1c and smoking habit, were not disclosed that metformin could inhibit the growth of available in the NHIRD. However, we used the aDCSI intracellular M tuberculosis in vitro through increased score at baseline as a surrogate marker for hemoglobin phagosome-lysosome fusion and production of A1c and adjusted this variable in multivariate analyses mitochondrial reactive oxygen species through an to minimize bias from different DM severities. To AMPK-dependent pathway. They also disclosed that verify aDCSI as a practical alternative to hemoglobin metformin could enhance the efficacy of conventional A1c, further research is warranted to confirm the anti-TB drugs in a mouse model of M tuberculosis relationship between the diabetic complication score infection, although another animal study reported that and hemoglobin A1c level.38 Second, the reasons for this add-on effect was not significant.34 In contrast, initiating metformin and sulfonylurea treatment may antidiabetic sulfonylureas, which act by increasing have been dissimilar, although they are the two most insulin release, are not reported to have an anti-TB effect frequently used initial drugs for T2DM in Taiwan and in the literature. Although the mechanism remains are contraindicated in advanced CKD.12,14,17 Thus, uncertain, the dose-response association between uncovered bias, such as the prescription pattern of metformin use and decreased risk of TB in our study DM drugs, which may change over time as TB may also suggest the anti-TB effect of metformin. Our incidence continues to decline in Taiwan, may exist in findings may be supported by a case-control study the comparison of TB risk in metformin majors and demonstrating an association of metformin with a lower sulfonylurea majors. However, we used index year chance of active TB in patients with DM (n ¼ 451).16 stratification and propensity score matching to treat Thus, regarding the impact of metformin on TB risk, our the competing groups to reduce potential bias. Third, large-scale longitudinal cohort study may fill the the LTBI status of each patient with T2DM was not knowledge gap between preclinical studies and the few available in our study. Thus, the effect of the initial use human reports of small sample size. of metformin in preventing TB infection from TB Most of the previous TB studies in DM populations exposure, or in preventing active TB disease from focused on the impacts of certain comorbidities and primary progression of LTBI, could not be cardiovascular-protective drugs on TB risk, but the differentiated in the present study. Finally, this study

chestjournal.org 9 investigated the risk of TB development in TB-naive predominantly exposed to metformin in the initial 2 patients with DM; the effect of metformin in treating years, defined as metformin majors, had a significantly active TB disease remains unclear here. Further well- reduced risk of TB compared with matched sulfonylurea designed clinical studies are required to assess the host comparators, defined as sulfonylurea majors. Thus, direct effect of metformin, in combination with regarding the risk of TB development, our findings may standard anti-TB regimens, on TB treatment suggest that metformin is a better initial drug than the outcomes. sulfonylureas for high-risk patients with T2DM if not contraindicated. The additive value of metformin in Conclusions improving treatment outcomes of patients with This population-based cohort study discovered that concomitant DM and active TB also deserves further patients with T2DM but without CKD who were study in the future.

Acknowledgments 4. Jeon CY, Murray MB. Diabetes mellitus pharmacies. J Pharm Policy Pract. increases the risk of active tuberculosis: a 2015;8(1):15. Author contributions: S.-W. P., Y.-F. Y., and systematic review of 13 observational 15. Nathan DM, Buse JB, Davidson MB, W.-J. S. are the guarantors of the paper and studies. PLOS Med. 2008;5(7):e152. take responsibility for the integrity of the et al; American Diabetes Association; work as a whole, from inception to published 5. Yen YF, Chung MS, Hu HY, et al. European Association for Study of Association of pulmonary tuberculosis Diabetes. Medical management of article. S.-W. P., Y.-F. Y., J.-Y. F., Y.-J C., and and ethambutol with incident depressive hyperglycemia in type 2 diabetes: a W.-J. S. conceived the study concept and disorder: a nationwide, population-based consensus algorithm for the initiation design. S.-W. P., Y.-F. Y., and P.-H. C. cohort study. J Clin Psychiatry. 2015;76(4): and adjustment of therapy: a consensus performed the acquisition of data. S.-W. P., e505-e511. statement of the American Diabetes Y.-F. Y., Y. R. K., V. Y.-F. S., P.-H. C., Y.-J. C., Association and the European 6. Baker MA, Harries AD, Jeon CY, et al. J.-Y. F., and W.-J. S. conducted data analysis Association for the Study of Diabetes. The impact of diabetes on tuberculosis and interpretation. S.-W. P., Y. R. K., J.-Y. F., Diabetes Care. 2009;32(1):193-203. and Y.-J. C. contributed to critical revision of treatment outcomes: a systematic review. the manuscript. Y.-J. C. and W.-J. S. were the BMC Med. 2011;9:81. 16. Marupuru S, Senapati P, Pathadka S, Miraj SS, Unnikrishnan MK, Manu MK. supervisors of this study. 7. Wang JY, Lee MC, Shu CC, et al. Optimal Protective effect of metformin against Financial/nonfinancial disclosures: duration of anti-TB treatment in patients tuberculosis infections in diabetic patients: None with diabetes: nine or six months? Chest. declared. an observational study of south Indian 2015;147(2):520-528. tertiary healthcare facility. Braz J Infect Other contributions: The authors thank the 8. Gnanasan S, Ting KN, Wong KT, Mohd Dis. 2017;21(3):312-316. National Health Research Institute of Taiwan Ali S, Muttalif AR, Anderson C. 17. Ioannidis I. Diabetes treatment in patients for providing the National Health Insurance Convergence of tuberculosis and diabetes with renal disease: Is the landscape clear Research Database. The authors thank mellitus: time to individualise enough? World J Diabetes. 2014;5(5): Professor Yu-Chin Lee, MD, Jia-Horng pharmaceutical care. Int J Clin Pharm. 651-658. Wang, MD, and Hsin-Kuo Ko , MD, PhD, 2011;33(1):44-52. for providing administrative support at 18. Pan SW, Yen YF, Feng JY, et al. The 9. Singhal A, Jie L, Kumar P, et al. risk of depressive disorder among Taipei Veterans General Hospital. The Metformin as adjunct antituberculosis authors also thank Professor Mei-Lin Ho, contacts of tuberculosis patients in a TB- therapy. Sci Transl Med. 2014;6(263): endemic area: a population-based cohort PhD, at Soochow University, Taiwan, for 263ra159. providing research facilities. study. Medicine (Baltimore). 2015;94(43): 10. Lee MR, Huang YP, Kuo YT, et al. e1870. Role of sponsors: The sponsor had no role in Diabetes mellitus and latent tuberculosis 19. Lin CC, Lai MS, Syu CY, et al. Accuracy of the design of the study, the collection and infection: a systemic review and meta- diabetes diagnosis in health insurance analysis of the data, or the preparation of the analysis. Clin Infect Dis. 2017;64(6): claims data in Taiwan. J Formos Med manuscript. 719-727. Assoc. 2005;104(3):157-163. Additional information: The e-Appendix 11. Lee PH, Fu H, Lai TC, Chiang CY, 20. Chen YC, Su YC, Li CY, Hung SK. 13-year and e-Table can be found in the Chan CC, Lin HH. 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