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Discordance between Tuberculin Skin Test and Interferon Gamma Release Assay is Associated with Previous Latent Tuberculosis Infection Treatment

Divya Reddy1*, Max R O’Donnell2,3, Allan M Welter-Frost4, Alison Coe6 and C Robert Horsburgh5,6

1Albert Einstein College of Medicine/Division of Pulmonary Medicine, Bronx, NY, USA

2Columbia University Medical Center/Division of Pulmonary, Allergy and Critical Care Medicine, New York, NY, USA

3Columbia University Mailman School of Public Health/Department of Epidemiology, New York, NY, USA

4University of Iowa Hospitals and Clinics/Department of Internal Medicine, Iowa City, IA, USA

5Boston University School of Public Health/Department of Epidemiology, Boston MA, USA

6Boston University School of Medicine/Department of Medicine, Infectious diseases, Boston, MA, USA

*Corresponding Author:
Reddy D
Albert Einstein College of Medicine/Division of Pulmonary Medicine
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Price Rm 350, Bronx
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E-mail: [email protected]

Received date: August 17, 2016; Accepted date: October 27, 2016; Published date: October 31, 2016

Citation: Reddy D, O’Donnell MR, Welter-Frost AM, Coe A, Horsburgh CR (2016) Discordance between Tuberculin Skin Test and Interferon Gamma Release Assay is Associated with Previous Latent Tuberculosis Infection Treatment. Mycobact Dis 6:227. doi: 10.4172/2161-1068.1000227

Copyright: © 2016 Reddy D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Background: The performance of Interferon gamma release assays (IGRA) in drug users and the impact of previous latent tuberculosis infection (LTBI) treatment on discordance of IGRA and tuberculin skin test (TST) are unclear.
Objective: To determine the prevalence and incidence of LTBI using TST and Quantiferon Gold In-Tube test (QFT-G-IT) in a cohort of persons with hepatitis C virus (HCV) and drug use history. Design: Eligible participants had baseline TST and QFT-G-IT assay and were retested with QFT-G-IT after 12 months to assess prevalence and incidence of LTBI.
Results: Of 193 HCV-infected persons enrolled, 162 (84%) were HIV infected; 132 (81%) were on anti-retroviral therapy and 131 (81%) had a CD4 count >200. 190 (98%) had a history of drug use; only 19 (10%) were active intravenous drug users. 55 (28.5%) had LTBI based on TST results and 13 (7%) were diagnosed with LTBI based on QFT-G-IT. 46/193 persons (23.8%) had positive TST with negative QFT-G-IT test. History of LTBI treatment was a strong predictor of this discordance (OR=41.5; 95%CI 16.2-106.7; p<0.0001). No QFT-G-IT conversions were detected among the 101 initially QFT-G-IT negative patients retested at one year (95% CI: 0-3.6%).
Conclusions: Intravenous drug users who are not actively using drugs have a low prevalence and incidence of LTBI by IGRA. Previous LTBI treatment is associated with a positive TST and a concurrent negative QFT-G-IT.


Latent Tuberculosis; Tuberculin skin testing; Interferon gamma release assay; High-risk groups


A third of the world’s population is infected with Latent Tuberculosis (LTBI) [1]. In the United States, the prevalence of LTBI in the general population is 4.2%, with higher percentages found in foreign-born persons, homeless individuals, prisoners, HIV patients, close contacts of persons with active tuberculosis and injection drug users [2,3]. About 10% of persons with LTBI develop reactivation TB over a lifetime; this reservoir is the most important factor in the continued occurrence of TB in the US [4].

Tuberculin skin testing (TST) has been the standard method for diagnosing LTBI for over 100 years. The TST measures the cellmediated delayed hypersensitivity response to purified protein derivative (PPD) derived from M. tuberculosis . Major disadvantages of the TST include the need for trained personnel to read the TST and a second visit by the patient for test interpretation [5]. In the past decade, Interferon gamma release assays (IGRAs) have been introduced as an alternative method for detecting LTBI. Two types of IGRAs are currently used in practice to diagnose LTBI, Quantiferon TB Gold In-Tube (QFT-G-IT; Cellestis, Victoria, Australia) and the TSPOT.TB (Oxford Immunotec, Oxford, United Kingdom). Both of these tests use M. tuberculosis specific antigens, encoded by genes located in the region of difference 1 (RDI1). The former test is an enzyme-linked immunosorbent assay to measure antigen-specific interferon-γ produced by circulating T-cells in blood and the latter uses an elispot technique to measure peripheral mononuclear cells that produce interferon-γ [5]. Studies have demonstrated moderate agreement (60–80%) between TST and IGRAs with TST being more sensitive and IGRAs being more specific for LTBI [6].

Absence of the boosting phenomenon with repeated testing, nonsubjective interpretation and the requirement of only one patient visit make the test a practical alternative to TST [5,6]. Compared to TST, IGRAs are more useful in diagnosing LTBI in individuals with a history of BCG vaccination [7], however like TST; IGRA sensitivity is reduced in HIV infection and in children [8,9]. The utility of IGRAs in serial testing of populations such as health care workers, prison inmates and staff is unclear [10]. Injection and non-injection illicit drug users have been identified by the Centers for Disease Control and Prevention (CDC) as a high-risk group for TB infection and disease. The prevalence of LTBI in this group varies between 10–67% depending upon the study site, duration of drug use, HIV prevalence, and median age of the cohort [11]. Unstable lifestyle, low motivation for testing and low probability of a return office visit for TST interpretation makes IGRA an attractive test for diagnosing LTBI in this group [12]. However, the performance of IGRAs in drug users has not been clearly defined. The utility of IGRAs in detecting incident latent TB infection in drug users who undergo serial testing is also unknown [11].

The goal of the present study is to define the prevalence and incidence of LTBI in a Hepatitis C infected drug user cohort with TST and QFT-G-IT. In addition, we sought to elucidate risk factors for discordant test results, particularly when TST was positive but QFT-GIT was negative.

Materials and Methods

Study population

Patients were recruited for this study from the Hepatitis C, HIV and Related Morbidity (CHARM) cohort at Boston University Medical Center (BUMC). Detailed description of this study cohort has been previously provided [13]. Briefly, the CHARM cohort was initiated in the year 2000 to prospectively evaluate the natural history of HCV infection and HIV/HCV co-infection in an inner city, predominantly drug-using population. Study participation was offered to HCVinfected persons (both male and female), 18 years of age or older, who received their primary care at BUMC, its affiliated Neighborhood Health Centers, or the Boston Veterans Administration (VA) Medical Center. Patients were excluded if they had a previous clinical liver event, if their HCV or HIV sero-status was unknown or if they did not wish to be tested. Between 2008 and 2009, CHARM patients were approached for enrollment into the proposed LTBI-related sub-study. The institutional review board at BUMC approved the study protocol, and all participants provided written informed consent.

Study data

As part of the CHARM study, participants completed a detailed baseline questionnaire and returned for follow-up interviews every 6 months. Baseline and follow-up questionnaires collected information on demographic and socioeconomic factors, tobacco, alcohol and drug use, HIV and Hepatitis C related risk factors and treatment history for the purpose of this study, birth in Puerto Rico was considered birth outside of the United States. Race/Ethnicity questions were combined and patients were asked to classify themselves in White, African American, Hispanic and Other categories. Homelessness was defined as “living in a shelter” or living “on the street”.

Substance use was assessed using the Addiction Severity Index and Alcohol Use Disorders Identification Test (AUDIT) questionnaire [14,15]. A patient was considered to consume excessive/harmful amounts of alcohol if the AUDIT score was ≥8. Active drug use was defined as use of Marijuana, Cocaine and/or Heroin by any route (intravenous, nasal, oral, smoking or subcutaneous injection) within the past 30 days. Physical exams and chart reviews were obtained at baseline and every 12 months. Patients who agreed to be part of the LTBI sub-study answered a separate questionnaire for information on BCG vaccination, LTBI risk factors, previous tuberculin skin testing (TST) and LTBI treatment. The majorities of patients were receiving health care at BUMC and affiliated neighborhood health centers.

Previously performed TST results were documented only after confirmation from the clinic/hospital where the test was performed. For the remaining patients, a TST was performed as part of the study and results were documented. At the time of enrollment and at the 1- year follow-up visit, blood samples were drawn, incubated in QFT-GIT assay tubes, and sent to the Massachusetts State Laboratory for analysis. Standard guidelines were used in interpreting TST and QFTG- IT.

Statistical analysis

Data were analyzed using SAS Version 9.3 (SAS Foundation, Cary, NC). To identify factors that predict TST-positivity and QFT-G-IT positivity, univariate statistical associations with baseline risk factors were calculated as odds ratios (ORs) and tested for statistical significance by the chi-square and Fisher’s exact test. To identify a set of independent predictors of above-mentioned outcomes, we then used conservative multivariate models to simultaneously control for the effects of the various risk factors examined. Variables with a p-value <0.20 in univariate analyses and potential confounders were considered in the multivariate models, using exact logistic regression to calculate adjusted ORs and associated 95% CI [16]. Kappa statistic was calculated to determine concordance between the two tests.


Study population

The demographic characteristics of the 193 patients with known TST and QFT-G-IT results enrolled in the study are shown in Table 1. Overall, 55/193 (28.5%, 95% CI 20.2%-39.5%) were found to have a positive tuberculin skin test and 138/193 had a negative test at baseline.

Characteristics N (%)
Median age in years (range) 46 (25-63)
Gender, Male 119 (62)
White, non-Hispanic 43 (22)
Black, non-Hispanic 87 (45)
Hispanic 57 (30)
Other 6 (3)
Education, Less than high school 89 (46)
Unemployment (n=190) 158 (83)
Family income < $10800/year (n=192) 143 (74)
Place of birth
United States 148 (77)
Puerto Rico 42 (22)
Other 3 (1)
Married or with partner 39 (20)
Homelessness (n=73) 21 (29)
Ever incarcerated 142 (74)
Received BCG vaccination n=(186) 49 (26)
History of receiving INH prophylaxis 43 (22)
History of cigarette smoking 175 (91)
Current harmful alcohol use 20 (10)
Illicit drug use history
Active intravenous drug users 19 (10)
Active non-intravenous drug users 59 (31)
History (current and past) of intravenous drug use 165 (85)
History (current and past) of non-intravenous drug use 190 (98)
Total current drug (ivdu and non-ivdu) users 69 (36)
Total with past history of drug (ivdu and non-ivdu) use 173 (90)
HIV infected 162 (84)
Receiving/received ART (n=162) 132 (81)
History of opportunistic infections (n=148) 19 (13)
CD4 count at the time of QFT-TB test (n=161)
CD4 count <200 30 (19)
CD4 count 200-350 45 (28)
CD4 count >350 86 (53)
Median HIV viral copies/ml (range) (n=162) 75 (50-500000)
<75 copies/ml 90 (56)
>75 copies/ml 72 (44)
TB=Tuberculosis, HIV=Human Immunodeficiency virus, HCV=Hepatitis C virus, BCG=BacilleCalmette Guerin, ART=Anti-retroviral treatment, INH=Isoniazid
*Data not available in all subjects for all recorded characteristics.

Table 1: Demographic, TB risk factors, and HIV related characteristics of cohort (n=193)* .

Only 13/193 (6.7%, 95% CI 2.8% - 14.1%) were found to have a positive baseline QFT-G-IT test; 1 (1.1%) had an indeterminate result. 43/193 (22%) persons reported previous INH treatment for LTBI. Concordance between the two tests was poor with a kappa statistic of 0.17 (95% CI=0.05-0.3, p<0.0008). 9 persons tested positive and 133 persons tested negative with both tests. 46 persons had a positive TST with a negative QFT-G-IT test. Of 101 initially negative QFT-G-IT persons retested after 1 year, 100 were QFT-G-IT-negative and one had an indeterminate test result. The rate of QFT-G-IT conversions was therefore 0% (95% CI 0-3.6%).

Predictors of TST and QFT-G-IT Positivity

Predictors of TST positivity are shown in Table 2. Univariate analysis demonstrated that patients older than 50 years had roughly a two-fold increased risk of having a positive TST (OR=2.0; 95%CI 1.0-4.1; p=0.04) and patients who did not complete high school (OR 0.5; 95%CI 0.3-1.0; p=0.06) had a decreased risk of a positive TST.

Risk factors TST positive n/total (%) Unadjusted OR (95%CI) p-value Adjusted OR( 95% CI), p-value
Age,> 50 yrs 22/55 (40) 2.0 (1.0-4.1)* 0.04 2.3 (1.0-5.0), 0.04
Gender, Male 38/119 (32) 1.6 (0.8-3.3) 0.24  
White, non-Hispanic 11/43 (26) 0.8 (0.3-1.9) 0.78  
Black, non-Hispanic 27/87 (31) 1.3 (0.6-2.5) 0.58  
Hispanic 12/57 (21) 0.6 (0.3-1.3)* 0.19 0.6 (0.2-1.3), 0.18
Education, Less than high school 19/89 (21) 0.5 (0.3-1.0)* 0.06 0.5 (0.2-1.0), 0.049
Unemployment 45/158 (29) 0.9 (0.4-2.2) 0.9  
Family income, <$10800/yr 46/143 (32) 2.1 (0.9-5.3)* 0.09 3.4 (1.4-9.6), 0.006
Place of birth, Outside US 12/45 (27) 0.9 (0.4-2.0) 0.91  
Married or with partner 11/39 (28) 1.0 (0.4-2.3) 1  
Homelessness 5/21 (24) 0.8 (0.2-2.3) 0.83  
Ever incarcerated 42/142 (30) 1.2 (0.6-2.8) 0.71  
Received BCG vaccination 18/56 (32) 1.3 (0.6-2.8) 0.53  
History of cigarette smoking 50/175 (29) 1.0 (0.3-3.9) 1  
Current harmful alcohol use 3/20 (15) 0.4 (0.1-1.5) 0.24  
Illicit drug use history        
Active intravenous drug user 4/19 (21) 0.6 (0.1-2.2) 0.64  
Active non-intravenous drug user 17/59 (29) 1.0 (0.5-2.1) 1  
History (current and past) of intravenous drug use 47/165 (28) 1.0 (0.4-2.8) 1  
History (current and past) of non-intravenous drug use 53/190 (28) 0.2 (0.003-3.8)* 0.39 0.2 (0.0-3.9), 0.39
HIV infected 49/162 (30) 1.8 (0.7-5.7)* 0.31 2.0 (0.7-6.6), 0.24
OR=Odds Ratios, US =United States, BCG=BacilleCalmette Guerin, HIV=Human Immunodeficiency virus
*Variables included in a multivariate model.

Table 2: Prevalence and association of baseline risk factors with Latent Tuberculosis (LTBI) diagnosed by Tuberculin skin test (TST).

After adjusting for sex, Hispanic race, homelessness, HIV infection and history of alcohol and non-injection drug use in a multiple logistic regression model, being older than 50 years (aOR 2.2; 95%CI 1.1-4.6; p=0.02) continued to be significantly association with a positive TST result.

The multivariate model also showed that persons with an income < $10800/year had an increased risk (aOR 3.4; 95%CI 1.4-9.6; p=0.006) and persons not completing high school had a decreased risk (aOR 0.5; 95%CI 0.2-1.0; p=0.049) of a positive TST result compared to those with higher incomes.

Univariate analyses to assess for predictors of a positive QFT-G-IT result were limited by the small number of outcomes. However, we did find that patients with HIV infection were significantly less likely to have a positive QFT-G-IT result (OR 0.3; 95%CI 0.1-0.8; p=0.01) compared to HIV-uninfected individuals.

Patients with a history of homelessness in the past 6 months (OR 3.5; 95%CI 1.02-12.2; p=0.06) were more likely to have a positive QFTG- IT result. HIV infection (OR 0.3; 95%CI 0.09-0.9); p=0.02) was found to have the strongest association for a positive QFT-G-IT result in a multivariate model after adjusting for homelessness and income.

Predictors of positive TST with negative QFT-G-IT

Overall, 46 patients had a positive TST and a negative QFT-G-IT while only 4 had a negative TST and a positive QFT-G-IT. The relationship between demographic factors and a positive TST with negative QFT-G-IT discordant result is shown in (Table 3).

Risk factors Patients with positive TST and negative QFT-G-IT test
n/total (%) Unadjusted OR (95%CI) p-value Adjusted OR(95% CI); p-value
Age,>50 years 18/55 (33) 1.8(0.9 -3.7)* 0.09  
Gender, Male 32/115 (28) 1.6(0.8-3.3)* 0.18  
White, non-Hispanic 10/42 (24) 1.0(0.4-2.1) 0.91  
Black, non-Hispanic 22/85 (26) 1.1(0.6-2.2) 0.68  
Hispanic 11/55 (20) 0.7(0.3-1.5) 0.36  
Education, Less than high school 14/85 (16) 0.4(0.2-0.9)* 0.02  
Unemployment 37/154 (24) 0.8(0.3-1.8) 0.56  
Family income, <$10800/year 38/138 (28) 1.9(0.8-4.5)* 0.12  
Place of birth, Outside US 11/44 (25) 1.0(0.5-2.3) 0.93  
Married or with partner 10/38 (26) 1.1(0.5-2.6) 0.77  
Homelessness 3/20 (15) 0.5(0.1-1.8) 0.41  
Ever Incarcerated 35/138 (25) 1.2(0.6-2.6) 0.64  
History of BCG vaccination 15/46 (33) 1.7(0.8-3.6)* 0.18  
History of receiving INH 34/43 (79) 41.5(16.2-106.7) <0.0001 41.5(15.0-114.8); <0.0001
History of cigarette smoking 41/170 (24) 0.8(0.3-2.5) 0.7  
Current harmful alcohol use 3/20 (15) 0.5(0.1-1.8) 0.41  
Illicit drug use history        
Active intravenous drug user 4/19 (21) 0.8(0.3-2.6) 0.71  
Active non-intravenous drug user 16/57 (28) 1.3(0.6-2.7) 0.45  
History (current and past) of intravenous drug use 41/160 (26) 1.6(0.6-4.4) 0.38  
History (current and past) of non-intravenous drug use 44/185 (24) 0.16(0.01-1.8))* 0.15  
HIV infected 43/159 (27) 3.2(0.9-11.2)* 0.06  
OR=Odds Ratios, US =United States, BCG=BacilleCalmette Guerin, INH=Isoniazid, HIV=Human Immunodeficiency virus
*Variables adjusted for in a multivariate model.

Table 3: Association of baseline risk factors with a positive Tuberculin skin test (TST) and negative Quantiferon Gold In-tube (QFT-G-IT) assay.

Univariate and a multivariate model including age, sex, education, income, BCG vaccination history, HIV status, and illicit non-injection drug usage showed that history of LTBI treatment with INH was the only significant predictor of a positive TST and negative QFT-G-IT result.


Users of intravenous and other illicit drugs are at high-risk for acquisition of both TB and HIV [3,11].

Our study found moderate prevalence of LTBI by TST (28.5%), low prevalence by QFT-T-IT (7%) and no incidence by QFT-G-IT in a population of persons with a history of drug use. This is in contrast to two previous studies that examined the prevalence of LTBI in drug using populations using QFT-G-IT. Grimes et al. [17] studied LTBI among 119 crack cocaine drug users in Houston, Texas. Of these subjects, 28% tested positive for LTBI with a TST and 34% tested positive for LTBI with QFT-G-IT. Over 90% of this cohort reported smoking crack 48 hours before LTBI screening [17]. Garfein et al. showed that 67% (621/1020) of an IV drug user cohort in Tijuana, Mexico tested positive for LTBI with QFT-G-IT, but TST was not performed. All study subjects were active IV drug users [18]. In contrast, in our study only 36% of subjects were active drug (injection and non-injection) users. Therefore, we conclude that the differences between our results and those found previously are related to an increased risk for recent TB infection associated with active drug use.

Another difference between our cohort and the previous two studies is the prevalence of HIV infection. In our study, 84% of study subjects were HIV-infected, compared with only 7% in the study of Grimes [17] and 4% in the Garfein study [18]. However, our HIV-infected subjects were largely on effective antiretroviral regimens with low viral loads and near-normal CD4 counts, thus potentially diminishing differences between the populations. Moreover, lack of QFT-G-IT conversions during the 1-year follow up supports the conclusion that they were at low risk for exposure to TB.

We also found that a large number of our study subjects had discordance between TST and QFT-G-IT, nearly all of whom were TST positive/QFT-G-IT negative (46/50, or 92%). This pattern of discordance was strongly associated with previous treatment for LTBI. Neither of the previous two studies [17,18], commented on LTBI treatment history among the participants in their studies. If LTBI treatment successfully eliminates viable tubercle bacilli from the host, this might provide an explanation for the observed discordance. Several studies have documented a decline in IFN-γ levels or reversion to test negativity measured by IGRA in patients during TB disease treatment [19-22]. Two prospective follow-up studies of persons with LTBI treated with isoniazid have been reported; in both, IGRA+ recent convertors or close contacts of TB disease cases were followed for up to two years [23,24]. In both studies modest decreases in IFN-gamma production were observed, but IGRA tests did not generally revert to negative. However, it is possible that IGRA tests might have become negative with longer follow-up.

Our study has a number of limitations. First, the small number of patients with a positive QFT-G-IT limited our ability to perform an analysis of risk factors for a positive test. Second, we did not have accurate information about the timing of or adherence to INH treatment in those who reported receiving it. Nonetheless, the very strong association between Isoniazid treatment history and TST positive/QFT-G-IT negative status is unlikely to have occurred by chance. Third, there were missing data, particularly among covariates such as employment, family income, and history of opportunistic infections. Fourth, our inability to successfully locate and retest 117 of the subjects testing negative with QFT-G-IT at baseline limits the reliability of our estimate of the one-year LTBI incidence rates.


We conclude that the incidence and prevalence of latent tuberculosis infection by QFT-G-IT is low in drug users who are not actively using illicit drugs. Serial screening for LTBI may therefore not be useful or cost-effective in patient populations with demographic characteristics similar to ours. Previous treatment of LTBI with Isoniazid was strongly associated with a positive TST and negative QFT-G-IT, potentially suggesting cure of LTBI.


All those who have contributed to this work have been listed as authors. This work was supported by the National Institute of Drug Abuse (Award Number DA19841). Dr. O’Donnell was supported by National Institute of Allergy and Infectious Diseases (T32 AI52074).


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