Systematic review: agreement between the latent ...kjim.org/upload/kjim-2016-222.pdf · Food and Drug Administration (FDA)-approved Quan-tiFERON-TB Gold In Tube (QFT-GIT; ELISA, Cellestis

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ORIGINAL ARTICLE

Korean J Intern Med 2018;33:1241-1251https://doi.org/10.3904/kjim.2016.222

1WHO Collaborating Centre for Pharmaceutical Policy and Regulation, Department of Pharmaceutical Science, Utrecht University, Utrecht, the Netherlands; 2Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea

Received : July 7, 2016Revised : November 12, 2016Accepted : November 16, 2016

Correspondence toYoon-Kyoung Sung, M.D.Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, 222-1 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea Tel: +82-2-2290-9207 Fax: +82-2-2298-8231E-mail: [email protected]

Background/Aims: To estimate the level of agreement and positivity rates of la-tent tuberculosis infection (LTBI) tests prior to the use of tumor necrosis factor (TNF) inhibitors in relation to underlying rheumatic diseases and endemic tu-berculosis levels. Methods: The Ovid-Medline, Embase, and Cochrane Libraries were searched for articles before October 2013 involving LTBI screening in rheumatic patients, in-cluding rheumatoid arthritis (RA), ankylosing spondylitis (AS), juvenile idiopath-ic arthritis (JIA), and psoriatic arthritis.Results: In pooled analyses, 5,224 rheumatic patients had undergone both a tu-berculin skin test (TST) and an interferon-gamma release assay (IGRA) before TNF inhibitors use. The positivity of TST, QuantiFERON-TB Gold In Tube (QFT-GIT), and T-SPOT.TB (T-SPOT) tests were estimated to be 29%, 17%, and 18%, respectively. The agreement percentage between the TST and QFT-GIT, and between the TST and T-SPOT were 73% and 75%. Populations from low-to-mod-erate endemic TB presented with slightly less agreement (71% between TST and QFT-GIT, and 74% between TST and T-SPOT) than patients from high endemic countries (73% between TST and QFT-GIT, and 81% between TST and T-SPOT). By underlying disease stratification, a lower level of agreement between TST and QFT-GIT was found among AS (64%) than among JIA (77%) and RA patients (73%). Conclusions: We reaffirm the current evidence for accuracy of LTBI test done by TST and IGRA among rheumatic patients is inconsistent. Our stratified analy-sis suggests different screening strategies might be needed in clinical settings considering the endemic status in the patient’s country of origin and the precise nature of underlying diseases.

Keywords: Latent tuberculosis; Rheumatic diseases; Interferon-gamma release tests; Tuberculin test; Tumor necrosis factor-alpha

Systematic review: agreement between the latent tuberculosis screening tests among patients with rheumatic diseasesJunhee Pyo1, Soo-Kyung Cho2, Dam Kim2, and Yoon-Kyoung Sung2

INTRODUCTION

Tuberculosis (TB) remains a major concern and is ex-tremely prevalent in patients with rheumatic diseases due to their immune dysregulation and the immuno-

suppressive agents used in their treatment [1]. Subse-quent to the introduction of biologic agents, the reacti-vation of latent tuberculosis infection (LTBI) and new TB infections both increase. Therefore, it is recommend-ed that all patients who are candidates for treatment

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The Korean Journal of Internal Medicine Vol. 33, No. 6, November 2018

with tumor necrosis factor (TNF) inhibitors should be screened for Mycobacterium tuberculosis infection before treatment is initiated [2,3]. Recently, in 2012, the Amer-ican College of Rheumatology (ACR) recommended the use of a tuberculin skin test (TST) or an interferon-gam-ma release assay (IGRA) to identify LTBI in rheumatoid arthritis (RA) patients who are being considered for bio-logic agent therapy [4].

Screening tests such as the TST and IGRA for LTBI, are commercially available; these would include the U.S. Food and Drug Administration (FDA)-approved Quan-tiFERON-TB Gold In Tube (QFT-GIT; ELISA, Cellestis Ltd., Carnegie, Australia) or the T-SPOT.TB (T-SPOT; Elispot, Oxford Immunotec Inc., Oxford, UK). They have been tested for accuracy, but the agreement levels vary across all studies [5-24]. Although several studies have evaluated diagnostic accuracy and agreement across LTBI screening tests implemented before starting TNF inhibitors with patients with rheumatic diseases, there has been controversy between the individual studies and between countries.

In this study, we conducted a meta-analysis of the lev-el of agreement and positivity rates of LTBI screening tests prior to the use of TNF inhibitors according to the underlying rheumatic disease and the endemic TB sta-tus of each country. We then calculated the proportion of patients with rheumatic diseases targeted for treat-ment for LTBI before starting biologic agents according to each screening strategy and according to the endemic TB status of their countries of origin.

METHODS

Literature search strategyA computerized search of the Ovid-Medline, Embase, and Cochrane databases was conducted to find rele-vant studies published prior to October, 2013. We did not restrict the start date. The following search terms were used: (latent tuberculosis) AND [(rheumatoid AND arthritis) OR (ankylosing AND spondylitis) OR (juve-nile AND idiopathic AND arthritis) OR (psoriatic AND arthritis)]. Our search was restricted to human subjects and to articles written in English. We also screened the bibliographies of selected papers to find other eligible articles.

Inclusion criteriaStudies were eligible for inclusion if patients with rheu-matic diseases were screened for the detection of LTBI prior to the use of TNF inhibitors. Studies that satisfied all of the following criteria were included (1) population: patients with rheumatic diseases such as RA, psoriatic arthritis (PsA), ankylosing spondylitis (AS), and juvenile idiopathic arthritis (JIA) were included. All patients en-rolled in the studies met the ACR criteria for the clas-sification of rheumatic diseases; (2) intervention: LTBI screenings using either TST or one IGRA (QFT-GIT or T-SPOT) had been conducted, mostly before using TNF inhibitors (more than 90% of the population should not have previously used TNF inhibitors); (3) study designs: all observational studies (retrospective or prospective) and clinical trials; and (4) outcomes: results reported in sufficient detail to obtain a positive rate of LTBI and an agreement percentage between TST and one IGRA.

Exclusion criteriaThe exclusion criteria were as follows: (1) case reports, case series, review articles, editorials, letters, comments, and conference abstracts; (2) studies with insufficient data to calculate a positive rate or agreement percentage between TST and one IGRA; (3) studies that used a non-FDA approved LTBI screening test; (4) studies includ-ing more than 10% of patients on current or previous TNF inhibitors. However, if the studies included a mi-nor proportion of patients who were currently using or had previously used TNF inhibitors, which was less than 10% of the total population, these studies were included; (5) studies out of the field of interest; and (6) studies that overlapped with other studies due to patient overlap. Two reviewers independently reviewed the literature us-ing a standardized protocol, and disagreements were re-solved by a meeting where a consensus was established.

Data extractionWe extracted the data available for a meta-analysis from the studies included as follows: (1) study characteris-tics (authors, year of publication, location and period of study, population size, and study design); (2) demo-graphics and clinical characteristics of the patients (age, sex, disease duration of rheumatic disease, concomitant medications, Bacille Calmette-Guerin [BCG] vaccina-tion status, specific rheumatic disease type, and coun-

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Pyo J, et al. Agreement between LTBI tests

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try setting); and (3) Outcome characteristics: number of positive cases and number of total cases collected to calculate the positive rates of LTBI as measured by TST and IGRA. A number of pairs of TST results and IGRA results, including TST+/IGRA+, TST+/IGRA–, TST–/IGRA+, and TST–/IGRA– were extracted to estimate the agreement percentages between the two screening tests. Two reviewers (J.P. and Y.K.S.) extracted the data from the studies by consensus.

Data synthesis and statistical analysisTo explore the discrepancies in the prevalence as mea-sured by the TST and the IGRAs, a pooled positive rate and an agreement percentage across the LTBI screening tests before TNF inhibitor use were adopted as the me-ta-meters of our meta-analysis. The positive rate of a test is the proportion of positive cases to the total number of the population screened. In addition, we pooled the data for the agreement percentage (%), which was ad-opted as an indicator of the agreement level across the diagnostic tests, as the agreement index for this analysis. The agreement percentage (%) is the proportion of the concordance cases to the total number of concordance and discordance cases between the TST and one IGRA.

We obtained the pooled positive rates and the agree-ment percentage calculated from all the studies. We then performed two sets of subgroup analyses stratified by the endemic TB rating of the region and the spe-cific rheumatic disease. First, we stratified the studies and synthesized the outcomes of interest according to the endemic TB regions as based on the country set-tings. This was done to explore the differences across countries with various TB endemic ratings. According to the TB prevalence per 100,000 population from the 2011 World Health Organization (WHO) report, we clas-sified the studies into two categories: studies conduct-ed in low-to-moderate endemic TB regions (less than 20/100,000), and high endemic TB regions (more than 20/100,000). Next, we stratified the studies according to the specific rheumatic diseases (RA, AS, JIA) provided a specific rheumatic disease was reported as a subset with a separate outcome analysis in the article. DerSimoni-an-Laird random-effect models were constructed to synthesize the pooled positive rate and the agreement percentage with 95% confidence intervals (CIs) in or-der to consider potential heterogeneity across studies.

This methodological approach was based on an inverse variance technique to calculate the weights and pooled outcomes with 95% CIs. To investigate the heterogene-ity, we calculated the Cochran's Q test and the I2 statis-tics, which were considered significant if the I2 statistics were greater than 50%, and the p value of the Cochran's Q test was less than 0.10. To assess publication bias, we plotted funnel plots and conducted Begg’s test to fur-ther detect asymmetry.

In addition, we estimated the number and proportion of patients with rheumatic diseases targeted for LTBI treatment according to each screening strategy across the TB endemic regions. First, we constructed a 2 × 2 diagnostic table consisting of patient distribution in the literature included to calculate the number of patients and proportion of positive results among the total pop-ulation across the TST and the IGRAs. We assumed that patients who had positive screening results according to each strategy were all supposed to receive LTBI treat-ment. Four screening strategies were used to determine further prophylactic treatment: TST only positive, IGRA only positive, both TST and IGRA positive, and either TST or IGRA positive were all examined. The R version 3.0.1 (https://www.r-statistics.com/2013/05/r-3-0-1-is-re-leased/) package was used for analysis with the metafor command.

This systematic review was conducted according to the Preferred Reporting Items for Systematic Revise and Meta-Analyses (PRISMA) statement.

RESULTS

Literature searchOur literature search process is illustrated in Fig. 1. Af-ter removing duplicates, 280 articles were screened for eligibility in the Ovid-Medline, Embase, and Cochrane databases. Of these, 253 articles were excluded after a review of the titles and abstracts: 171 were reviews/let-ters/editorials/abstracts; seven were case reports/series; six studies used a non-FDA approved LTBI screening test; three studies included patients on current or pre-vious TNF inhibitors; 10 studies had no comparisons across LTBI screening tests; 10 studies used LTBI tests for non-rheumatic diseases (e.g., other autoimmune diseases, human immunodeficiency virus [HIV]); and

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46 studies were out of the field of interest (e.g., safety/efficacy studies of TB prophylaxis or studies evaluating TB incidence).

The full texts of the remaining 27 articles were re-trieved. The following nine articles were then exclud-ed after a review of the full texts: three studies included patients on current or previous TNF inhibitors; three studies had no comparisons across the LTBI screening tests; one study included insufficient data to yield our meta-meters of interest; one study did not separate the data for patients with rheumatic diseases from that for other autoimmune diseases; and one study was out of the field of interest for our research. On searching the bibliographies of the articles included two additional eligible studies were included [18,19]. Finally, a total of

20 studies were used for the qualitative and quantitative review [1-20].

Study characteristicsThe basic characteristics of the 20 studies are summa-rized in the Supplementary Table 1. The author, pub-lication year, disease population, number of patients, age, female proportion, concomitant medications, pre-vious BCG vaccination, disease duration, country set-ting, comparison groups with cut-off information, and summarized positive rate and agreement level of each study are presented in detail, and stratified according to the TB endemic regions (Supplementary Table 1). Nine studies, with a total of 1,359 patients, were con-ducted in high endemic TB areas (Brazil, China, Peru, Poland, Korea, Taiwan, and Turkey); 10 studies with a total of 1,493 patients were in low-to-moderate TB en-demic settings (Canada, Czech, France, Greece, Ireland, Israel, and Spain); and one study of 2,282 patients was conducted in a global setting across all regions (Asia, North/Latin America, and Europe). In this review, the total population was 5,224, which included 3,026 clear-ly defined RA patients (57.9%), 1,009 AS patients (19.3%), 559 PsA patients (10.7%), 141 JIA patients (2.7%), and 489 others (9.3%), including the unknown disease popu-lation. A TST positive test was conducted among 5,051 patients, QFT-GIT among 4,799 patients, and T-SPOT among 846 patients. The agreement level between TST and QFT-GIT was compared among 4,830 patients and between TST and T-SPOT among 864 patients.

Positive rates for the LTBI screening testsThe pooled positive rates among all the 5,051 patients with rheumatic diseases across the LTBI screening tests

Table 1. Estimated number of patients according to screening strategies for latent tuberculosis infection treatment

Variable Total High endemic Low to moderate endemic

TST only positive 736 (32.8) 502 (34.8) 234 (29.3)

IGRA only positive 507 (22.6) 390 (27.0) 117 (14.7)

TST and IGRA positive 300 (13.4) 243 (16.8) 57 (7.1)

TST or IGRA positive 943 (42.0) 649 (55.0) 294 (36.8)

Total no. of patients across all strategies 2,241 1,443 798

Values are presented as number (%). This table represents the estimated number of patients targeted for latent tuberculosis in-fection treatment according to each screening strategy as a subset of our literature review.TST, tuberculosis skin test; IGRA, interferon-gamma release assay.

Figure 1. Flow diagram for the literature search. FDA, U.S. Food and Drug Administration; LTBI, latent tuberculosis infection.

Records identified through databases searching:176 Ovid-Medline, 270 Embase, 4 Cochrane

253 Records excluded: 171 Reviews /letters/editorials/abstracts 7 Case reports/series 6 Not FDA approved screening test

2 Records included, from reference check (2) 9 Records excluded: Not FDA approved screening test (2) No comparison across LTBI test (3)

280 Abstracts screened

27 Full-text articles assessed for eligibility

20 Studies included in meta-analysis

280 Records after duplicates removed

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before the use of TNF inhibitors are summarized in Fig. 2A. The overall positive rates for TST (> 5 mm), QFT-GIT, and T-SPOT among all the patients included un-der the random-effect modeling were estimated as 29% (95% CI, 24 to 34), 17% (95% CI, 11 to 23), and 18% (95% CI, 11 to 26), respectively. A greater positive diagnosis of LTBI was found on the TST test than on the QFT-GIT

or T-SPOT.In a stratified analysis according to TB endemic re-

gion (Fig. 2A), all patients with rheumatic diseases (n = 1,322) in the low-to-moderate endemic setting present-ed positive rates by TST, QFT-GIT, and T-SPOT of 33% (95% CI, 25 to 41), 10% (95% CI, 6 to 14), and 20% (95% CI, 15 to 25), respectively. Among all patients with rheumatic

TSTStudy

Low to moderateendemic Areas

Klein, 2013Mariette, 2012

Martin, 2010Minguez, 2012Ringrose, 2011

Saidenberg-K*, 2012Scrivo, 2012

Shovman, 2009Vassilopoulos, 2008Vassilopoulos, 2011

Pooled Value

High endemic AreasCamlar, 2011Chang, 2011Chen, 2012

De Leon, 2008Hatemi, 2012

Kim, 2012Marques, 2009

Paluch-Oles, 2013Xie, 2011

Pooled Value

Hsia§, 2012Overall Pooled Value





Shovman, 2009Vassilopoulos, 2011

Pooled Value

High endemic AreasChang, 2011Chen, 2012


Kim, 2012Paluch-Oles, 2013

Pooled Value


42 (35-49)35 (30-40)39 (27-50)13 (4-22) 26 (17-35)47 (38-56)12 (6-18) 43 (26-59)39 (27-50)37 (30-45)33 (25-41)

28 (14-42)34 (25-43)31 (25-37)27 (18-35)24 (10-37)32 (29-36)15 (5-25) 29 (20-38)21 (10-31)28 (24-32)

9 (8-11) 29 (24-34)

214392705391

1231193570

1551322

I2 = 89%, p < 0.001†

10748

140724101242399058

1447I2 = 54%, p < 0.037†

22825051

I2 = 92%, p < 0.001†

15 (12-19) 20 (11-29) 21 (10-32) 23 (13-33) 25 (18-32) 20 (15-25)

29 (16-42) 2 (-2-5)

15 (-12-42)

18 (11-26)

392705370

155740

I2 = 50%, p = 0.083†

4858

106I2 = 94%, p < 0.001†

846I2 = 89%, p < 0.001†

4 (1-7) 10 (7-13) 7 (1-13)

17 (7-27) 7 (1-12)

18 (11-25)4 (1-8)

11 (1-22) 21 (14-27)10 (6-14)

34 (25-43)36 (28-44)25 (22-28)45 (35-54)19 (14-24)22 (14-31)29 (21-37)

7 (6-8) 17 (11-23)

177392705391

12311935

1551215

I2 = 84%, p < 0.001†

10714072410124290

1302I2 = 87%, p < 0.001†

22824799

I2 = 97%, p < 0.001†

Forest Plot PR%(95% CI)

N Study Forest Plot PR%(95% CI)


NQFT-GIT TSPOT

0 25 50 75 (%)

0 25 50 (%)

0 25 50 (%)

Low to moderateendemic AreasMariette, 2012

Martin, 2010Minguez, 2012

Vassilopoulos, 2008Vassilopoulos, 2011

Pooled Value

High endemic AreasMarques, 2009

Xie, 2011Pooled Value

Overall Pooled Value

* Saidenberg-Kermanac’h et al’s study †p-value of Q-test.§Hsia et al’s study was a multi-nation study and included low to moderate endemic and high endemic areas.

TSTStudy

RAChang, 2011Chen, 2012

Hatemi, 2012Kim, 2012

De Leon, 2008Marques, 2009Minguez, 2012Shovman, 2009

Pooled value

ASChang, 2011

Kim, 2012Pooled value

JIACamlar, 2011


RAChang, 2011Chen, 2012


Kim, 2012Minguez, 2012Shovman, 2009

Pooled value

ASChang, 2011


JIACamlar, 2011


RAMarques, 2009Minguez, 2012

Pooled value

20 (8-31) 31 (25-37)24 (10-37)28 (24-32)27 (18-35)15 (5-25) 17 (-1-34) 46 (29-62)26 (21-31)

46 (33-58)45 (39-52)46 (39-52)

28 (14-42)17 (3-31) 23 (12-33)

4624238

497101481835

1025 I2 = 61%, p = 0.023*

61198259

I2 = 0%, p = 0.951*

392968

I2 = 16%, p = 0.276*

37 (23-51)19 (14-24)45 (35-54)34 (19-49)30 (26-34)22 (3-41) 11 (1-22) 28 (19-37)

31 (20-43)16 (11-21)26 (14-38)

5 (-2-12) 3 (-3-10) 4 (-1-9)

4624210138

4971835

977 I2 = 87%, p < 0.001*

61198259

I2 = 81%, p = 0.021*

392968

I2 = 0%, p = 0.731*

29 (16-42)22 (3-41) 27 (16-38)

481866

I2 = 0%, p = 0.556*

Forest Plot PR%(95% CI)



NQFT-GIT TSPOT

0 25 50 75 100 (%)

0 25 50 (%)

* p-value of Q-test.

0 25 50 (%)

Figure 2. Pooled analysis of the positive rate (PR%) of latent tuberculosis infection screening tests (A) by tuberculosis endemic area and (B) by disease type. TST, tuberculin skin test; QFT-GIT, QuantiFERON-TB Gold In Tube; CI, confidence interval; TSPOT, T-SPOT.TB test; N, number; RA, rheumatoid arthritis; AS, ankylosing spondylitis; JIA, juvenile idiopathic arthritis.

A

B

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diseases (n = 1,447) from the high endemic settings, the positive rates by TST, QFT-GIT, and T-SPOT were 28% (95% CI, 24 to 32), 29% (95% CI, 21 to 37), and 15% (95% CI, –12 to 42), respectively. In this analysis, substantial het-erogeneity was found, evidenced by an I2 value greater than 50% and a p value < 0.10 for the Q test.

In the subgroup analysis according to the underly-ing rheumatic diseases (Fig. 2B), the RA population (n = 1,025) presented consistent positive rates by TST, QFT-GIT, and T-SPOT of 26% to 28%. Among the AS and JIA patients, the positivity rates were not consistent according to the LTBI screening tests. Positivity mea-sured by TST was significantly larger than that by QFT-GIT among the AS and JIA populations. Heterogeneity across studies seemed to be attenuated when analyzed according to the specific underlying disease type, even though significant heterogeneity still existed among RA populations for both the TST and QFT-GIT positive rates, and among AS populations for the QFT-GIT pos-itive rates (Q test; p = 0.023, p < 0.0001, and p = 0.021, re-spectively). However, we cannot exclude the possibility that the nonheterogeneity was potentially driven by the small number of studies among the subgroups.

No statistically significant publication or reporting bias existed in the pooled positive rates of TST, QFT-GIT, and T-SPOT, as demonstrated by the nonsignifi-cant Begg’s test results (Fig. 3).

Percentage agreement in the LTBI screening testsThe pooled agreement percentage among all the 4,830 patients with rheumatic diseases across the LTBI screen-ing tests is summarized in Fig. 4. The overall agreement percentage between TST (> 5 mm) and QFT-GIT, and between TST (> 5 mm) and T-SPOT among all patients resulted in 73% (95% CI, 68 to 78) and 75% (95% CI, 70 to 80), respectively (Fig. 4A).

Even though the differences in the agreement per-centage by TB endemic stratification were not substan-tial (Fig. 4A), the agreement level in the low to moderate endemic areas appears to be numerically lower (71% for TST vs. QFT-GIT, 74% for TST vs. T-SPOT) than that of the high endemic areas (73% for TST vs. QFT-GIT, 81% for TST vs. T-SPOT). In addition, there were significant heterogeneities across all the stratified analyses.

Subgroup analyses by the underlying diseases RA, AS, and JIA showed that the agreement percentage between

the TST and the QFT-GIT was lower among the AS pa-tients (64%; 95% CI, 58% to 70%) than among the RA pa-tients (73%; 95% CI, 69% to 78%) and the JIA patients (77%; 95% CI, 58% to 96%). The subgroup analysis, mea-suring the agreement level between TST and T-SPOT, was available only for the RA population, which present-ed as 86% (95% CI; 77 to 95). Heterogeneity seems to be attenuated by the subgroup analysis; however, we can-not exclude the possibility that the smaller number of studies resulted in the nonheterogeneity.

No statistically significant publication or reporting bias existed for the pooled agreement percentage be-tween the TST and QFT-GIT, or between the TST and T-SPOT, a result which was derived from all the studies included, as demonstrated by the nonsignificant Begg’s test results (Fig. 5).

Estimated number and proportion of patients for LTBI treatment In high endemic regions, 34.8% of patients are targeted for treatment for LTBI according to a TST-only posi-tive strategy, 27.0% of patients per a IGRA-only positive strategy, 16.8% of patients per a both TST and IGRA positive strategy, while 55.5% of patients were targeted per an either TST or IGRA positive strategy as needing LTBI treatment (Table 1). In low to moderate endemic regions, 29.3%, 14.7%, 7.1%, and 36.8% of patients need-ed LTBI treatment according to the screening strategies described above The screening strategy that resulted in the largest proportion of patients requiring LTBI pro-phylaxis was the either TST or IGRA positive, followed by the TST-only positive, the IGRA-only positive, and last the both TST and IGRA positive outcome.

DISCUSSION

We reaffirm that the current evidence for the accuracy of the LTBI screening test as done by the TST and IGRA among patients with rheumatic diseases is inconsistent. We also found that among all patients with rheumat-ic diseases there were more positive diagnoses by TST than were obtained by screenings done with either of the IGRA tests. However, in this meta-analysis, we de-tected a numerical indication that populations originat-ing from low-to-moderate endemic TB regions present-

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ed with slightly more disagreement in accuracy, mainly due to the lower positive rates from TST being closer to the rates obtained by IGRAs, than in patients from the high endemic TB regions. When stratified according to underlying disease, a lower level of agreement between TST and IGRAs was found among the AS patients than among the RA and JIA patients. However, we have to interpret this with caution since it was not statistically significant.

The lack of a gold standard for diagnosing LTBI makes an assessment of the diagnostic performance of TST and the IGRAs contentious [25]. The TST is a long-es-tablished method widely used to identify LTBI due to its simplicity and efficiency, although it has several inherent drawbacks, such as a cross-reaction with the BCG vaccination and other environmental mycobacte-ria infections resulting in variability in interpreting the results [26,27]. Testing for LTBI using risk factors and

TST has been shown to reduce the incidence of reacti-vation of tuberculosis in patients taking TNF inhibitors. IGRAs have shown excellent results for screening after exposure to tuberculosis. However, their ability to de-tect LTBI in patients with rheumatic diseases is not yet proven.

Recommendations for screening for LTBI in current guidelines vary on the subject of replacing TST with IG-RAs or of utilizing both tests [28]. In general, the cur-rent international guidelines recommend TST first and IGRA in cases of suspected false-negative TST in pa-tients at risk for M. tuberculosis exposure, or if a history of previous BCG vaccination is present, but in Switzer-land, TST is no longer recommended, and IGRA is the only test advised [29]. In addition, it has been shown that serial TST together with IGRA may be useful to iden-tify a false-negative response in cases of LTBI and new TB infections during long-term TNF inhibitor use, es-

0.084

0.10

0.063

0.042

0.021

0

0.20 0.30 0.40 0.50 0.60 0.70

Positive rate

Begg’s test(p = 0.230)

TST

Stan

dard

err

or

0.066

0.100

0.049

0.033

0.016

0

0.200.150.05 0.25 0.30 0.35

Positive rate


TSPOT

Stan

dard

err

or

0.077

0.100

0.058

0.038

0.019

0

0.20 0.30 0.40 0.50

Positive rate


QFT-GIT

Stan

dard

err

or

A B

C

Figure 3. Assessment of publication bias through funnel plots for positive rates. (A) Tuberculin skin test (TST), (B) QuantiFERON TB-Gold In-Tube test (QFT-GIT, Cellestis Ltd.), and (C) T-SPOT.TB (TSPOT, Oxford Immunotec Inc.).

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pecially in areas with an intermediate TB burden, such as Korea. It has also been shown that the risk of TST conversion increases significantly over 3 years of therapy [30]. Some differences in recommendations due to en-demic prevalence might be reasonable, but its effective-ness has yet to be proven. In our study, 55.5% of patients were targeted to treat LTBI according to the either TST

or QFT positive strategy in the high endemic regions. LTBI treatment for more than half of patients before starting with biologic agents has the distinct possibility of increasing the occurrence of adverse events such as liver function abnormalities and decreasing compliance related to polypharmacy [31].

Our study suggested that the results of both tests differ

TST vs. QFT-GITStudy





Shovman, 2009Vassilopoulos, 2011

Pooled Value

High endemic AreasChang, 2011

Camlar, 2011Chen, 2012

De Leon, 2008Kim, 2012

Hatemi, 2012Paluch-Oles, 2013

Pooled Value


Forest Plot AR%(95% CI)

N Study Forest Plot AR%(95% CI)

NTST vs. T-SPOT

25 50 75 100 (%)

25 50 75 100 (%)

* Saidenberg-Kermanac’h et al’s study †p-value of Q-test.§Hsia et al’s study was a multi-nation study and included low to moderate endemic and high endemic areas.

66 (58-73)67 (62-72)81 (75-88)84 (73-94)76 (67-85)57 (48-66)86 (79-93)56 (37-75)64 (56-71)71 (64-78)

67 (58-76)67 (52-81)80 (75-85)70 (61-79)70 (67-74)67 (51-82)82 (73-90)73 (68-78)

9 (08-11)73 (68-78)

1523921434991

1239825

1551228

I2 = 86%, p < 0.001†

10039

2331017243687

1320I2 = 66%, p = 0.007†

22824830

I2 = 90%, p < 0.001†

81 (75-88)80 (70-91)69 (65-80)71 (64-78)73 (62-83)74 (69-80)

81 (71-91)

75 (70-80)

14351

38715570

806 I2 = 60%, p = 0.020†

81

864I2 = 58%, p = 0.026†


Martin, 2010Minguez, 2012Mariette, 2012

Vassilopoulos, 2011Vassilopoulos, 2008

Pooled Value

High endemic AreasXie, 2011

Overall Pooled Value

TST vs. QFT-GITStudy

RAChang, 2011

Chen, 2012De Leon, 2008Hatemi, 2012

Kim, 2012Shovman, 2009

Pooled Value

ASChang, 2011

Kim, 2012Pooled Value

JIACamlar, 2011

Kim, 2012Pooled Value

Forest Plot AR%(95% CI)

N Study Forest Plot AR%(95% CI)

NTST vs. T-SPOT

25 50 75 100 (%)

50 75 100 (%)

* p-value of Q-test.

76 (63-89)80 (75-85)70 (61-79)67 (51-82)72 (68-76)63 (43-82)73 (69-78)

60 (48-73)65 (58-71)64 (58-70)

67 (52-81)86 (74-99)77 (58-96)

4223310136

49724

933 I2 = 50%, p = 0.078*

58198256

I2 = 0%, p = 0.554*

392968

I2 = 74%, p = 0.048*

90 (81-98)80 (70-91)86 (77-95)

485199

I2 = 40%, p = 0.195*

RAMarques, 2009Minguez, 2012

Pooled Value

A

B

Figure 4. Pooled analysis of the agreement percentage between the TST and interferon-gamma release assay (IGRA) tests (A) by tuberculosis endemic area and (B) by disease type. TST, tuberculin skin test; QFT-GIT, QuantiFERON-TB Gold In Tube; TSPOT, T-SPOT.TB test; AR, agreement rate; CI, confidence interval; N, number; RA, rheumatoid arthritis; AS, ankylosing spondylitis; JIA, juvenile idiopathic arthritis.

www.kjim.org

1249



according to the underlying rheumatic disease and the endemic TB origins of the patient. Therefore, an opti-mal screening strategy for LTBI is needed that considers both tuberculosis risk and patient disease. Considering the different false positivity of screening methods and the adverse drug reactions due to unnecessary prophy-lactic medications, the selection of a screening strategy requires circumspection. Thus, balancing cost, efficacy, and safety should be considered in choosing a screening strategy to determine the prophylactic treatments to be employed.

Our study had several limitations. The most import-ant limitation might be the wide heterogeneity of the summarized results. Diagnostic results came from pa-tients with all rheumatic diseases, of various statuses relating to BCG vaccination and corticosteroid use; they included a minor population of TNF inhibitor use, and different country settings, all of which could contribute to the inconsistencies. Furthermore, a thorough sub-group analysis by underlying disease was impossible since many articles report their diagnostic results only for aggregated patients with rheumatic diseases, rather than separately for each type of disease.

In conclusion, a lower level of agreement between the TST and IGRAs was found in the low-to-moderate en-demic countries than in the high endemic countries, and in AS populations as compared to the other rheu-matic disease populations. Thus, differing strategies may be needed for patients with rheumatic diseases

when detecting LTBI in clinical settings so that endem-ic origins and underlying diseases are also taken into consideration.

Conflict of interestNo potential conflict of interest relevant to this article was reported.

REFERENCES

1. Bouza E, Moya JG, Munoz P. Infections in systemic lupus erythematosus and rheumatoid arthritis. Infect Dis Clin North Am 2001;15:335-361.

Figure 5. Assessment of publication bias through funnel plots for the agreement percentage. (A) Tuberculin skin test (TST) vs. QuantiFERON TB-Gold In-Tube test (QFT-GIT, Cellestis Ltd.) and (B) TST vs. T-SPOT.TB (TSPOT, Oxford Immunotec Inc.).

0.099

0.074

0.050

0.025

0

0.50 0.60 0.70 0.80 0.90

Agreement rate


TST vs. QFT-GIT

Stan

dard

err

or

0.056

0.042

0.028

0.014

0

0.65 0.70 0.800.75 0.85

Agreement rate


TST vs. TSPOT

Stan

dard

err

or

KEY MESSAGE

1. The latent tuberculosis infection (LTBI) screen-ing test results by tuberculin skin test and in-terferon-gamma release assay among rheumatic patients were inconsistent, which were also modified by endemic status of origin country and underlying disease.

2. Our study suggest a different clinical strategy may be required to detect LTBI by considering patient’s origin of country and precise nature of underlying disease.

www.kjim.org



2. Ledingham J, Wilkinson C, Deighton C. British Tho-racic Society (BTS) recommendations for assessing risk and managing tuberculosis in patients due to start anti-TNF-{alpha} treatments. Rheumatology (Oxford) 2005;44:1205-1206.

3. Mariette X, Salmon D. French guidelines for diagnosis and treating latent and active tuberculosis in patients with RA treated with TNF blockers. Ann Rheum Dis 2003;62:791.

4. Singh JA, Furst DE, Bharat A, et al. 2012 Update of the 2008 American College of Rheumatology recommen-dations for the use of disease-modifying antirheumatic drugs and biologic agents in the treatment of rheuma-toid arthritis. Arthritis Care Res (Hoboken) 2012;64:625-639.

5. Camlar SA, Makay B, Appak O, et al. Performance of tu-berculin skin test and interferon gamma assay for the diagnosis of latent tuberculosis infection in juvenile id-iopathic arthritis. Clin Rheumatol 2011;30:1189-1193.

6. Chang B, Park HY, Jeon K, et al. Interferon-γ release assay in the diagnosis of latent tuberculosis infection in arthri-tis patients treated with tumor necrosis factor antago-nists in Korea. Clin Rheumatol 2011;30:1535-1541.

7. Chen DY, Shen GH, Chen YM, Chen HH, Hsieh CW, Lan JL. Biphasic emergence of active tuberculosis in rheuma-toid arthritis patients receiving TNFα inhibitors: the util-ity of IFNγ assay. Ann Rheum Dis 2012;71:231-237.

8. Ponce de Leon D, Acevedo-Vasquez E, Alvizuri S, et al. Comparison of an interferon-gamma assay with tu-berculin skin testing for detection of tuberculosis (TB) infection in patients with rheumatoid arthritis in a TB-endemic population. J Rheumatol 2008;35:776-781.

9. Hatemi G, Melikoglu M, Ozbakir F, Tascilar K, Yazici H. QuantiFERON-TB Gold in tube assay for the screening of tuberculosis before and during treatment with tumor necrosis factor alpha antagonists. Arthritis Res Ther 2012;14:R147.

10. Hsia EC, Schluger N, Cush JJ, et al. Interferon-γ release assay versus tuberculin skin test prior to treatment with golimumab, a human anti-tumor necrosis factor anti-body, in patients with rheumatoid arthritis, psoriatic arthritis, or ankylosing spondylitis. Arthritis Rheum 2012;64:2068-2077.

11. Klein M, Jarosova K, Forejtova S, et al. QuantiFERON TB Gold and tuberculin skin tests for the detection of latent tuberculosis infection in patients treated with tumour

necrosis factor alpha blocking agents. Clin Exp Rheuma-tol 2013;31:111-117.

12. Kim JH, Cho SK, Han M, et al. Factors influencing dis-crepancies between the QuantiFERON-TB gold in tube test and the tuberculin skin test in Korean patients with rheumatic diseases. Semin Arthritis Rheum 2013;42:424-432.

13. Marques CD, Duarte AL, de Lorena VM, et al. Evaluation of an interferon gamma assay in the diagnosis of latent tuberculosis infection in patients with rheumatoid ar-thritis. Rheumatol Int 2009;30:57-62.

14. Mariette X, Baron G, Tubach F, et al. Influence of replac-ing tuberculin skin test with ex vivo interferon γ release assays on decision to administer prophylactic antituber-culosis antibiotics before anti-TNF therapy. Ann Rheum Dis 2012;71:1783-1790.

15. Martin J, Walsh C, Gibbs A, et al. Comparison of inter-feron {gamma} release assays and conventional screening tests before tumour necrosis factor {alpha} blockade in patients with inflammatory arthritis. Ann Rheum Dis 2010;69:181-185.

16. Minguez S, Latorre I, Mateo L, et al. Interferon-gamma release assays in the detection of latent tuberculosis in-fection in patients with inflammatory arthritis scheduled for anti-tumour necrosis factor treatment. Clin Rheuma-tol 2012;31:785-794.

17. Paluch-Oles J, Magrys A, Koziol-Montewka M, Koszarny A, Majdan M. Identification of latent tuberculosis infection in rheumatic patients under consideration for treatment with anti-TNF-α agents. Arch Med Sci 2013;9:112-117.

18. Ringrose JS, Sanche SE, Taylor-Gjevre RM. Detecting latent tuberculosis infection during anti-tumor necrosis factor therapy. Clin Exp Rheumatol 2011;29:790-794.

19. Saidenberg-Kermanac’h N, Semerano L, Naccache JM, et al. Screening for latent tuberculosis in anti-TNF-α candi-date patients in a high tuberculosis incidence setting. Int J Tuberc Lung Dis 2012;16:1307-1314.

20. Scrivo R, Sauzullo I, Mengoni F, et al. Serial interferon-γ release assays for screening and monitoring of tuberculo-sis infection during treatment with biologic agents. Clin Rheumatol 2012;31:1567-1575.

21. Shovman O, Anouk M, Vinnitsky N, et al. QuantiFER-ON-TB Gold in the identification of latent tuberculosis infection in rheumatoid arthritis: a pilot study. Int J Tu-berc Lung Dis 2009;13:1427-1432.

22. Vassilopoulos D, Stamoulis N, Hadziyannis E, Archiman-

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dritis AJ. Usefulness of enzyme-linked immunospot assay (Elispot) compared to tuberculin skin testing for latent tu-berculosis screening in rheumatic patients scheduled for anti-tumor necrosis factor treatment. J Rheumatol 2008; 35:1271-1276.

23. Vassilopoulos D, Tsikrika S, Hatzara C, et al. Comparison of two gamma interferon release assays and tuberculin skin testing for tuberculosis screening in a cohort of patients with rheumatic diseases starting anti-tumor ne-crosis factor therapy. Clin Vaccine Immunol 2011;18:2102-2108.

24. Xie X, Chen JW, Li F, Tian J, Gao JS, Zhang D. A T-cell-based enzyme-linked immunospot assay for tuberculosis screening in Chinese patients with rheumatic diseases receiving infliximab therapy. Clin Exp Med 2011;11:155-161.

25. Ruan Q, Zhang S, Ai J, Shao L, Zhang W. Screening of la-tent tuberculosis infection by interferon-γ release assays in rheumatic patients: a systemic review and meta-analy-sis. Clin Rheumatol 2016;35:417-425.

26. Pouchot J, Grasland A, Collet C, Coste J, Esdaile JM, Vin-ceneux P. Reliability of tuberculin skin test measurement.

Ann Intern Med 1997;126:210-214.27. Menzies D. Interpretation of repeated tuberculin tests:

boosting, conversion, and reversion. Am J Respir Crit Care Med 1999;159:15-21.

28. Iannone F, Cantini F, Lapadula G. Diagnosis of latent tuberculosis and prevention of reactivation in rheumatic patients receiving biologic therapy: international recom-mendations. J Rheumatol Suppl 2014;91:41-46.

29. Beglinger C, Dudler J, Mottet C, et al. Screening for tuber-culosis infection before the initiation of an anti-TNF-al-pha therapy. Swiss Med Wkly 2007;137:620-622.

30. Park JH, Seo GY, Lee JS, Kim TH, Yoo DH. Positive conversion of tuberculin skin test and performance of interferon release assay to detect hidden tuberculosis infection during anti-tumor necrosis factor agent trial. J Rheumatol 2009;36:2158-2163.

31. Vanhoof J, Landewe S, Van Wijngaerden E, Geusens P. High incidence of hepatotoxicity of isoniazid treatment for tuberculosis chemoprophylaxis in patients with rheumatoid arthritis treated with methotrexate or sulfas-alazine and anti-tumour necrosis factor inhibitors. Ann Rheum Dis 2003;62:1241-1242.

www.kjim.org

www.kjim.org https://doi.org/10.3904/kjim.2016.222


Supp

lem

enta

ry T

able

1. S

tudy

cha

ract

eris

tics

of t

he in

clud

ed li

tera

ture

Stud

yPo

pula

tion

No.

of

patie

nts,

dise

ase

type

Age,

yr

Fem

ale

sex

Con

com

itant

m

edic

atio

n

BCG

va

ccin

a-tio

n, %

Mea

n di

seas

e du

ratio

n, y

r

Cou

ntry

se

ttin

gC

ompa

riso

nO

utco

me:

(1) p

ositi

vity

, (2)

agre

emen

t

Low

to m

oder

ate

TB

ende

mic

regi

on

Shov

man

et

al. (2

009)

[2

1]

35 R

A pa

tient

s35

RA

pa

tient

s60

23 (6

6)M

TX

: 71%

Pr

edni

sone

: 60%

H

ydro

xych

loro

quin

e:

42%

747.1

Is

rael

Q

FT-G

vs.

TST

(> 5

mm

)

(1) 4

8% in

TST

, 11.

4% in

Q

FT-G

(2) 56

% b

/w T

ST a

nd Q

FT-G

Min

guez

et

al. (2

012)

[16

]

53 P

atie

nts w

ith

rheu

mat

ic d

is-

ease

s (R

A 34

%,

AS 2

4.5%

, PsA

17

%, o

ther

s 24

.5%)

53 A

ll rh

eum

atic

pa

tient

s

49.6

± 13

.0

35 (6

6)Pr

evio

us st

eroi

d us

e:

39.6

%

Prev

ious

DM

ARD

s: 73

.6%

Anak

inra

: 3 p

atie

nts

6 (3

6 un

-kn

own)

8.8

Spai

n Q

FT-G

IT

vs. T

ST

(> 5

mm

), T-

SPO

T v

s. T

ST

(1) 13

.2%

in T

ST, 1

7% in

QFT

-G

IT, 2

0.8%

in T

-SPO

T

(2) 7

7.4%

b/w

TST

and

T-S

POT

an

d Q

FT-G

IT

18 R

A

patie

nts

56.5

± 8.

616

(89)

DM

ARD

s: 11

pat

ient

sSt

eroi

ds: 1

4 pa

tient

sN

R10

.4

Spai

n(1)

16.7%

in T

ST, 2

2.2%

in

QFT

-GIT

, 22.

2% in

T-S

POT

(2) 8

3.3%

b/w

TST

and

T-S

POT,

77

.7% b

/w T

ST a

nd Q

FT-G

IT

Mar

iette

et

al. (2

012)

[14

]

392

Patie

nts (

128

RA,

178

SpA,

91

CD

)

392

All

rheu

mat

ic

patie

nts

45 (3

4–56

)16

2 (4

1)Pr

evio

us co

rtic

oste

roid

: 35

.7%

Prev

ious

cort

icos

tero

id

or im

mun

osup

pres

-sa

nt: 5

9.7%

65.7

NR

Fran

ce

QFT

-GIT

vs

. TST

, T

SPO

T v

s. T

ST (>

5 m

m)

(1) 35

.2%

in T

ST, 9

.9%

in Q

FT-

GIT

, 15.1

% in

T-S

POT

(2) 33

.3% b

/w T

ST a

nd T

-SPO

T,

31.1%

b/w

TST

and

QFT

-GIT

Vass

ilo-

poul

os e

t al

. (201

1) [2

3]

155 P

atie

nts (

74

RA,

35 P

sA, 3

1 AS

, 13 o

ther

Sp

A, 2

oth

er)

155 A

ll rh

eum

atic

pa

tient

s

52 ±

1690

(58)

DM

ARD

s and

/or s

te-

roid

s: 63

%D

MAR

Ds:

52%

Ster

oids

: 43%

76N

RG

reec

eT

ST (>

5 m

m)

vs. T

-SPO

T,

TST

vs.

QFT

-GIT

(1) 37

% in

TST

, 25%

in T

-SPO

T,

21%

in Q

FT-G

IT(2)

71%

b/w

TST

and

T-S

POT,

54

% T

ST a

nd Q

FT-G

IT

Vass

ilo-

poul

os e

t al

. (200

8)

[22]

70 P

atie

nts (

32

RA,

18 A

S, 12

Ps

A, 8

oth

ers)

70 A

ll rh

eum

atic

pa

tient

s

50.9

± 16

.937

(53)

DM

ARD

s: 55

.7%St

eroi

ds: 4

1.4%

40

(37.1

un-

know

n)

NR

Gre

ece

T-SP

OT

vs.

TST

(> 5

mm

)

(1) 38

.6%

in T

ST, 2

2.8%

in

T-SP

OT

(2) 72

.9%

b/w

TST

and

T-S

POT

Said

enbe

rg-

Kerm

an-

ac'h

et a

l. (2

012)

[19]

123 R

heum

atic

pa

tient

s (46

R

A, 53

AS,

15

PsA,

9 o

ther

s)

123 A

ll rh

eum

atic

pa

tient

s

50.4

± 11

.966

(54)

DM

ARD

s: 47

.9%

DM

ARD

s and

cort

ico-

ster

oids

: 28.

5%C

ortic

oste

roid

s: 38

.2%

56.1

NR

Fran

ce

TST

( ≥ 6

mm

) vs

. QFT

-G

IT

(1) 4

7.2%

in T

ST, 1

7.9%

in Q

FT-

GIT

(2) 57

% b

/w T

ST a

nd Q

FT-G

IT

www.kjim.org



Mar

tin

et

al. (2

010)

[15

]

150

Patie

nts (

87

RA,

37 P

sA,

22 A

S, 2

JIA,

2

othe

rs)

150

All

rheu

mat

ic

patie

nts

50.1

(17–8

8)91

(61)

DM

ARD

s: 80

.5%82

(9.7

un-

cert

ain)

11.6

Irel

and

QFT

-GIT

vs

. TST

, T-

SPO

T

vs. T

ST (>

5 m

m)

(1) 18

% in

TST

, 9.2

% in

T-

SPO

T, 7.

1% in

QFT

-GIT

(2) 8

1.1%

b/w

TST

and

T-S

POT,

82

.9%

b/w

TST

and

QFT

-G

IT

Scri

vo e

t al.

(201

2) [2

0]11

9 Pa

tient

s (61

R

A, 4

0 Ps

A, 13

AS

, 5 B

ehce

t’s

dise

ase)

119

All

rheu

mat

ic

patie

nts

47 (1

8–80

)82

(69)

DM

ARD

s: 16

%D

MAR

Ds a

nd g

luco

cor-

ticoi

ds: 5

4.6%

G

luco

cort

icoi

ds: 1

0.1%

No

imm

unos

uppr

es-

sant

: 19.

3%

5.8

NR

Ital

yQ

FT-G

IT

vs. T

ST (>

5 m

m)

(1) 11

.7% in

TST

, 4%

in Q

FT-

GIT

(2) 8

5.7%

b/w

TST

and

QFT

-G

IT

Kle

in e

t al.

(201

3) [11

]30

5 Pat

ient

s (11

7 R

A, 11

0 AS

, 6

PsA,

72 JI

A)

161 A

ll rh

eum

atic

pa

tient

s (p

re-t

reat

-m

ent

patie

nts

num

ber

for b

oth

TST

and

Q

FT-G

te

st)

44.18

± 14

.7716

5 (54

)G

luco

cort

icoi

ds: R

A 67

.6%

, AS

11.8

%, P

sA

83.3%

, JIA

45.

8%

MT

X: R

A 63

.2%

, AS

14.5%

, PsA

33.3%

, JIA

58

.3%

Leflu

nom

ide:

RA

14.5%

, AS

1.8%

, PsA

16.6

%,

JIA

12.5%

Su

lfasa

lazi

ne: R

A 5.9

%,

AS 2

5.4%

, PsA

33.3%

, JI

A 12

.5%

No

DM

ARD

s/G

C th

erap

y: R

A 11

.1%, A

S 65

.4%

, PsA

0%

, JIA

18

.1%

NR

NR

Cze

chQ

FT-G

IT

vs. T

ST (>

5 m

m)

(1) 3.

9% in

QFT

-GIT

, 42%

in

TST

(2) 6

6% b

/w T

ST a

nd Q

FT-G

IT

Rin

gros

e et

al

. (201

1) [18

]

91 P

atie

nts

(not

det

aile

d de

mog

raph

ic

info

rmat

ion

prov

ided

for

tota

l pop

ula-

tion)

91 A

ll rh

eum

atic

pa

tient

s

55.7

(31–

81)

for

only

12

posi

tive

popu

la-

tion

7

(58)

fo

r onl

y 12

pos

-iti

ve

popu

-la

tion

NR

5 (3 u

ncer

-ta

in) f

or

only

12

posi

tive

popu

la-

tion

NR

Can

ada

QFT

-GIT

vs.

TST

( ≥ 10

m

m)

(1) 2

6.4%

in T

ST, 6

.6%

in Q

FT-

GIT

(2) κ

Coe

ffici

ent 0

.180

b/w

T

ST a

nd Q

FT-G

IT (i

t was

in

vert

ed to

agr

eem

ent %

in

anal

ysis

)

Supp

lem

enta

ry T

able

1. C

onti

nued

Stud

yPo

pula

tion

No.

of

patie

nts,

dise

ase

type

Age,

yr

Fem

ale

sex

Con

com

itant

m

edic

atio

n

BCG

va

ccin

a-tio

n, %

Mea

n di

seas

e du

ratio

n, y

r

Cou

n-tr

y se

ttin

gC

ompa

riso

nO

utco

me:

(1) p

ositi

vity

, (2) a

gree

-m

ent

www.kjim.org



Hig

h T

B en

dem

ic re

gion

Cha

ng e

t al

. (201

1) [6

] 10

7 Pat

ient

s (61

AS

, 46

RA)

46 R

A

patie

nts

5245

(98)

Glu

coco

rtic

oids

: 67%

MT

X: 8

5%BC

G

scar

s 21

patie

nts

(46)

NR

Kor

ea

QFT

-GIT

vs.

TST

(> 10

m

m)

(1) 2

0% in

TST

, 37%

in Q

FT-

GIT

(2) 76

% b

/w T

ST a

nd Q

FT-G

IT

61 A

S

patie

nts

315 (

8)G

luco

cort

icoi

ds: 1

0%M

TX

: 5%

BC

G

scar

s 42

patie

nts

(69)

NR

Kor

ea(1)

44%

in T

ST, 3

1% in

QFT

-G

IT(2)

60%

b/w

TST

and

QFT

-GIT

Mar

ques

et

al. (2

009)

[13

]

48 R

A Pa

tient

s 48

RA

pa

tient

s49

.71 ±

12.41

43M

TX

: 62.

5%Pr

edni

sone

: 12.

7 ± 6

.7 m

g/da

y (on

ly d

osag

e re

-po

rted

for p

redn

ison

e)

100

10.2

Braz

il T-

SPO

T v

s. T

ST (>

5 m

m

in R

A)

(1) 14

% in

TST

, 25%

in T

-SPO

T

(2) 8

9.6%

b/w

TST

and

T-

SPO

T (c

alcu

late

d fr

om P

PV,

NPV

, sen

sitiv

ity, s

peci

ficity

in

the

pape

r)

Cam

lar e

t al

. (201

1) [5]

39 P

atie

nts w

ith

JIA

39 JI

A

patie

nts

11.1

± 4.

221

(54)

MT

X +

ster

oid:

7.5%

St

eroi

d: 5%

Sulfa

sala

zine

+ st

eroi

d:

7.5%

Sulfa

sala

zine

: 20%

33N

RTu

rkey

QFT

-GIT

, T

ST (>

10

mm

)

(1) 2

8% in

TST

, 5%

in Q

FT-

GIT

(2) 6

6.7%

b/w

TST

and

QFT

-G

IT

Kim

et a

l. (2

013)

[12]

724

Patie

nts (

497

RA,

198

AS, 2

9 JI

A; d

etai

led

dem

ogra

phy

avai

labl

e fo

r ea

ch d

isea

se

grou

p)

497 R

A pa

tient

s 54

425 (

85.5)

MT

X: 6

0.6%

Glu

coco

rtic

oids

: 75.1

%Pr

ior T

NF

inhi

bito

r: 6.

8%

NR

NR

Kor

ea

QFT

-GIT

vs.

TST

(> 5

mm

)(1)

28.

2% in

TST

, 30.

2% in

Q

FT-G

IT

(2) 71

.8%

b/w

TST

and

QFT

-G

IT

198

AS

patie

nts

33.5

57 (2

8.8)

MT

X: 2

3.7%

Glu

coco

rtic

oids

: 47.0

%Pr

ior T

NF

inhi

bito

r: 9.

1%

NR

NR

Kor

ea(1)

45.5

% in

TST

, 16.

2% in

QFT

-G

IT

(2) 6

4.7%

b/w

TST

and

QFT

-G

IT

Supp

lem

enta

ry T

able

1. C

onti

nued

Stud

yPo

pula

tion

No.

of

patie

nts,

dise

ase

type

Age,

yr

Fem

ale

sex

Con

com

itant

m

edic

atio

n

BCG

va

ccin

a-tio

n, %

Mea

n di

seas

e du

ratio

n, y

r

Cou

n-tr

y se

ttin

gC

ompa

riso

nO

utco

me:

(1) p

ositi

vity

, (2)

agre

emen

t

www.kjim.org



29 JI

A

pat

ient

s

15

.920

(69.

0)M

TX

: 72.

4%

Glu

coco

rtic

oids

: 51.7

%Pr

ior T

NF

inhi

bito

r: 34

.5%

NR

NR

Kor

ea(1)

17.2%

in T

ST, 3

.4%

in Q

FT-

GIT

(2)

86.

2% b

/w T

ST an

d Q

FT-G

IT

Ponc

e de

Le

on e

t al.

(200

8) [8

]

101 R

A pa

tient

s10

1 RA

pat

ient

s57

.6 ±

12.6

91 (9

0.1)

Pred

niso

lone

use

: 91.1

%M

TX

: 73.3

%80

.2N

RPe

ru

QFT

-G v

s. T

ST (>

5 m

m)

(1) 2

6.7%

in T

ST, 4

4.6%

in

QFT

-G

(2) 70

.3 %

b/w

TST

and

QFT

-G

Che

n et

al.

(201

2) [7

]24

2 R

A pa

tient

s (d

etai

led

dem

ogra

phy

avai

labl

e fo

r ea

ch p

air o

f tes

t re

sult)

242

RA

pat

ient

s

54.

719

2 (82

.4)

MT

X: 9

7.4%

Sulfa

sala

zine

: 94.

4%D

aily

ster

oid

dose

: 5.5

mg

97.9

9.0

Taiw

an

QFT

-G v

s. T

ST (>

5 m

m)

(1) 31

.0%

in T

ST, 1

8.6%

in

QFT

-G

(2) 8

0.3%

b/w

TST

and

QFT

-G

Palu

ch-

Ole

s et a

l. (2

013)

[17]

90 P

atie

nts

(81 R

A, 9

AS)

90 A

ll r

heum

atic

p

atie

nts

53.1

(19–8

2)67

(74.

4)N

R N

RN

RPo

land

QFT

-GIT

vs.

TST

(> 5

mm

)(1)

28.

9% in

TST

, 22.

2% in

QFT

-G

IT

(2) 8

2% b

/w T

ST a

nd Q

FT-G

IT

Hat

emi e

t al

. (201

2) [9

]40

RA

patie

nts

40 R

A p

atie

nts

52.6

± 13

.529

(72.

5)M

TX

: 31 p

atie

nts

Sulfa

sala

zine

: 7Pr

edni

solo

ne: 3

3

62.5

(BC

G

scar

)N

RTu

rkey

QFT

-G v

s. T

ST (>

5 m

m)

(1) 2

2% in

TST

, 60%

in Q

FT-G

(2) 71

% b

/w T

ST a

nd Q

FT-G

Xie

et a

l. (2

011)

[24]

58 P

atie

nts (

25

AS, 2

4 R

A, 4

un

diffe

ren-

tiate

d Sp

A, 3

PsA,

2 re

activ

e ar

thri

tis)

58 A

ll r

heum

atic

pat

ient

s

35.4

(16–

71)

25 (4

3.1)

DM

ARD

s: 58

pat

ient

sG

luco

cort

icoi

d: 16

89.7

6.6

Chi

naT-

SPO

T v

s. T

ST (>

5 m

m)

(1) 2

0.7%

in T

ST, 2

.3% in

T-

SPO

T (2)

68.

6% b

/w T

ST a

nd T

-SPO

T

Supp

lem

enta

ry T

able

1. C

onti

nued

Stud

yPo

pula

tion

No.

of

patie

nts,

dise

ase

type

Age,

yr

Fem

ale

sex

Con

com

itant

m

edic

atio

n

BCG

va

ccin

a-tio

n, %

Mea

n di

seas

e du

ratio

n, y

r

Cou

n-tr

y se

ttin

gC

ompa

riso

nO

utco

me:

(1) p

ositi

vity

, (2) a

gree

-m

ent

www.kjim.org



Glo

bal r

egio

n

Hsi

a et a

l. (2

012)

[10]

2,28

2 Pa

tient

s be

fore

gol

im-

umab

trea

t-m

ent (

67%

R

A, 17

.6%

Ps

A, 15

.5% A

S;

20.0

% p

atie

nts

used

bio

logi

cs

as p

revi

ous

trea

tmen

t);

pool

ed a

nal-

ysis

from

5 ph

ase I

II c

lini-

cal t

rial

dat

a

2,28

2 Al

l rh

eum

atic

pa

tient

s

4

9.0

1,515

(6

5.8)

MT

X: 1

,269

pat

ient

sD

MAR

Ds:

1,771

Cor

ticos

tero

id: 1

,539

34.2

60.8

%

wer

e m

ore

than

3 ye

ars

Glo

bal

(Asi

a,

Nor

th/

Lati

n Am

eri-

ca, E

u-ro

pe)

IGR

A vs

. TST

(>

5 m

m)

(1) 9

.4%

in T

ST, 7

.0%

in IG

RAs

(2) 8

7.2%

b/w

TST

and

IGR

As

Valu

es a

re p

rese

nted

as

num

ber

(%),

mea

n ±

SD, o

r m

edia

n (r

ange

).B

CG

, Bac

ille

Cal

met

te-G

ueri

n; T

B, t

uber

culo

sis;

RA

, rhe

umat

oid

arth

riti

s; M

TX

, met

hotr

exat

e; Q

FT-G

, Qua

nti-

FER

ON

-TB

Gol

d; T

ST, t

uber

culi

n sk

in t

est;

b/w

, be

twee

n; A

S, a

nkyl

osin

g sp

ondy

litis

; PsA

, pso

riat

ic a

rthr

itis

; DM

AR

Ds,

dis

ease

-mod

ifyi

ng a

ntir

heum

atic

dru

gs; Q

FT-G

IT, Q

uant

iFER

ON

TB

-Gol

d (in

tube

form

at;

Cel

lest

is L

td.,

Car

negi

e, A

ustr

alia

); T-

SPO

T, T

SPO

T. T

B (O

xfor

d Im

mun

otec

, Inc

., O

xfor

d, U

K);

NR

, not

rep

orte

d; S

pA, s

pond

yloa

rthr

opat

hy; C

D, C

rohn

’s di

seas

e;

JIA

, juv

enil

e id

iopa

thic

art

hrit

is; G

C, g

luco

cort

icoi

d; P

PV, p

osit

ive

pred

icti

ve v

alue

; NPV

, neg

ativ

e pr

edic

tive

val

ue; T

NF,

tum

or n

ecro

sis

fact

or; I

GR

A, i

nter

fer-

on-g

amm

a re

leas

e as

says

.

Supp

lem

enta

ry T

able

1. C

onti

nued

Stud

yPo

pula

tion

No.

of

patie

nts,

dise

ase

type

Age,

yr

Fem

ale

sex

Con

com

itant

m

edic

atio

n

BCG

va

ccin

a-tio

n, %

Mea

n di

seas

e du

ratio

n, y

r

Cou

n-tr

y se

ttin

gC

ompa

riso

nO

utco

me:

(1) p

ositi

vity

, (2) a

gree

-m

ent

www.kjim.org

Documents

Systematic review: agreement between the latent ...kjim.org/upload/kjim-2016-222.pdf · Food and Drug Administration (FDA)-approved Quan-tiFERON-TB Gold In Tube (QFT-GIT; ELISA, Cellestis