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. 2019 May 29;7:208. doi: 10.3389/fped.2019.00208

Risk Factors for Indeterminate Interferon-Gamma Release Assay for the Diagnosis of Tuberculosis in Children—A Systematic Review and Meta-Analysis

Noëmi R Meier 1,2, Thomas Volken 3, Marc Geiger 2, Ulrich Heininger 2,4, Marc Tebruegge 5,6,7, Nicole Ritz 1,2,4,7,*
PMCID: PMC6548884  PMID: 31192175

Abstract

Background: Interferon-gamma release assays (IGRA) are well-established immunodiagnostic tests for tuberculosis (TB) in adults. In children these tests are associated with higher rates of false-negative and indeterminate results. Age is presumed to be one factor influencing cytokine release and therefore test performance. The aim of this study was to systematically review factors associated with indeterminate IGRA results in pediatric patients.

Methods: Systematic literature review guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA) searching PubMed, EMBASE, and Web of Science. Studies reporting results of at least one commercially available IGRA (QuantiFERON-TB, T-SPOT.TB) in pediatric patient groups were included. Random effects meta-analysis was used to assess proportions of indeterminate IGRA results. Heterogeneity was assessed using the I2 value. Risk differences were calculated for studies comparing QuantiFERON-TB and T-SPOT.TB in the same study. Meta-regression was used to further explore the influence of study level variables on heterogeneity.

Results: Of 1,293 articles screened, 133 studies were included in the final analysis. These assessed QuantiFERON-TB only in 77.4% (103/133), QuantiFERON-TB and T-SPOT.TB in 15.8% (21/133), and T-SPOT.TB only in 6.8% (9/133) resulting in 155 datasets including 107,418 participants. Overall 4% of IGRA results were indeterminate, and T-SPOT.TB (0.03, 95% CI 0.02–0.05) and QuantiFERON-TB assays (0.05, 95% CI 0.04–0.06) showed similar proportions of indeterminate results; pooled risk difference was−0.01 (95% CI −0.03 to 0.00). Significant differences with lower proportions of indeterminate assays with T-SPOT.TB compared to QuantiFERON-TB were only seen in subgroup analyses of studies performed in Africa and in non-HIV-infected immunocompromised patients. Meta-regression confirmed lower proportions of indeterminate results for T-SPOT.TB compared to QuantiFERON-TB only among studies that reported results from non-HIV-infected immunocompromised patients (p < 0.001).

Conclusion: On average indeterminate IGRA results occur in 1 in 25 tests performed. Overall, there was no difference in the proportion of indeterminate results between both commercial assays. However, our findings suggest that in patients in Africa and/or patients with immunocompromising conditions other than HIV infection the T-SPOT.TB assay appears to produce fewer indeterminate results.

Keywords: Clinical studies, IGRA, latent, pediatrics, risk difference, QuantiFERON, T-SPOT.TB, T cell response

Introduction

Tuberculosis (TB) remains the leading cause of mortality by a single infectious agent, accounting for an estimated 1.6 million deaths worldwide. According to the latest report by the World Health Organization 10 million people are estimated to have developed TB disease in 2017 (1). However, the majority of individuals infected with Mycobacterium tuberculosis are asymptomatic and remain in a latent stage of infection. Data on infected individuals is not included in the World Health Organization TB report as TB infection is not a notifiable disease. Therefore, only estimates exist with one of the most recent estimates suggesting that in 2014 a total of 1.7 billion individuals, equivalent to 23% of the global population, had latent TB infection (2).

Progression from latent TB infection to active TB disease occurs in approximately one in ten adults. Children, however, progress more frequently to active TB and progression may be particularly rapid in the first 2 years of life (3–5). Early diagnosis and treatment are therefore key to reduce the burden of active TB in children.

Immuno-diagnostic tests are the main tools for the diagnosis of latent TB infection and both the tuberculin skin test (TST) and interferon-gamma release assays (IGRA) are used in the clinical setting (6, 7). The latter have been developed to overcome the limited specificity of the TST (8, 9). In adults the two commercially available IGRA, the QuantiFERON-TB and T-SPOT.TB—both existing in several test generations—have replaced the TST in many settings, primarily in an attempt to improve specificity (10).

In children, there is evidence that IGRA may have limited sensitivity and therefore the TST is still advocated by most experts (11–14). In addition, indeterminate IGRA results—due to either high interferon-γ background concentration in the negative control or low interferon-γ response in the positive control—have been shown to be more frequent in children compared to adults (15–18).

Underlying reasons for higher proportions of indeterminate IGRA results in children are largely speculative, but several contributing factors including age, concomitant infections and malnutrition have been postulated (18–20).

The aim of this study was to summarize the existing data on indeterminate IGRA results in children and determine key influencing variables.

Methods

Study Selection

A systematic literature search of studies reporting IGRA results in children was performed using PubMed, Embase, and Web of Science. Studies published until October 1st, 2018 were considered. The study was done according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement (21) (Supplementary Material 1 PRISMA Checklist). The following search terms were used: (tuberculosis OR TB) AND [(((t-spot.tb) OR t-spot) OR quantiferon-tb) OR quantiferon] AND (children OR pediatric OR pediatric). The following inclusion criteria were used (i) patients in the pediatric age range with a mean or median age <18 years and a maximum upper age range of 24 years, (ii) results of at least one of the commercially available IGRA detailed (including a statement about indeterminate test results), (iii) publication in English, French, or German. Case reports, case series, conference abstracts and studies involving fewer than 10 participants, commentaries and reviews were excluded. The search and selection of included studies was done by MG, NM, and NR. In unclear cases a joint decision for inclusion or exclusion of the study was made.

Data Extraction

Data were extracted using a standard form including the following variables: year of publication, country in which the study was done, number of participants, mean or median age of participants, age range of participants, type of test performed, number of positive, negative and indeterminate results, definition of indeterminate result, Bacillus Calmette-Guérin (BCG) vaccination status, human immunodeficiency virus (HIV) infection status and information on other potential immunocompromising conditions (e.g., rheumatic diseases, cancer) and concomitant infections (e.g., helminth or other parasitic infections).

Statistical Analysis

The primary outcome was the proportion of indeterminate IGRA results, which was calculated as the number of indeterminate test results divided by the total number of valid test results. Stratified meta-analyses for proportions were performed using a random effects model and the DerSimonian and Laird method, with the estimate of heterogeneity taken from the inverse-variance fixed-effect model. Stratification variables comprised type of IGRA used (QuantiFERON-TB and T-SPOT.TB), age groups (0–7 ≥ 8 years), geographical location of the population under study (Africa, Australia, North America, South America, Asia, Europe) and immune status (HIV infection rate groups, and presence of other immunocompromising factors). Heterogeneity was determined using the I2 statistic.

In studies comparing both QuantiFERON-TB and T-SPOT.TB, additional stratified meta-analyses for risk differences were performed. Risk differences were defined as the difference in the proportion of indeterminate results between the two IGRA tests and were calculated according to Newcombe and Altman (22). For comparison of pooled risk difference, we applied the DerSimonian and Laird risk difference method. Study weight was indicated by using random effect models for the individual studies to account for the different study characteristics. For risk difference analysis stratification for age groups were done in two groups (0–7 ≥ 8 years) because of the limited number of available datasets.

To further explore potential sources of heterogeneity, we used meta-regression if I2 was higher than 30%. We considered the following variables as potentially explanatory in a multivariable model: type of IGRA used, age group, geographic location of the population under study, immune status (HIV or other immunocompromising conditions) were considered as explanatory variables in a multivariable model.

We used GraphPad Prism Version 7.02 (GraphPad Software, San Diego, CA, USA) and Stata Version 15.1 (StataCorp, College Station, TX, USA) to generate figures and perform meta-analyses. We reported estimated effect sizes with corresponding 95% confidence intervals (95% CI). A p < 0.05 was considered statistically significant.

Results

Demographical Data of the Studies Included

A total of 1,293 citations were identified, of which 379 publications were eligible for full-text assessment and 133 (5 of which were found through additional sources) were included in the final analysis (Figure 1). As 21 publications included data on both QuantiFERON-TB and T-SPOT.TB and one study included data on two different QuantiFERON-TB tests a total of 155 datasets were generated. Table 1 provides an overview of the studies included and summarizes their key characteristics.

Figure 1.

Figure 1

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Flow chart outlining selection of articles included in the review.

Table 1.

Study results and characteristics of all included papers, sorted by year of publication.

Study number Authors Year of publication Country IGRA Participants n Positive results n Negative results n Indeterminate results n Proportion of ind. % Mean age years Median age years Age range years Years study performed BCG vaccinated n (%) HIV positive n (%) Other immunodeficiency Other immunodeficiency (%)
1 Connell et al. (23) 2006 Australia QFT Gold 101 20 64 17 16.8% ns ns 0.4–17.9 2004–2005 52.5% ns ns ns
2 Dogra et al. (24) 2007 India QFT Gold 105 11 94 0 0% ns 6 1–12 2004–2005 81.9% ns ns ns
3a Domínguez et al. (25) 2008 Spain QFT-GIT 134 50 84 0 0% ns% ns 0–18 2004–2006 64.2% 0% ns ns
3b Domínguez et al. (25) 2008 Spain T-SPOT.TB 134 51 80 3 2.2% ns% ns 0–18 2004–2006 64.2% 0% ns ns
4 Taylor et al. (26) 2008 UK QFT 120 6 107 7 5.8% 10% ns 0.3–16 2004–2005 46.7% ns ns ns
5 Okada et al. (27) 2008 Cambodia QFT Gold 204 33 162 9 4.4% ns% ns 0–5 2005 80% ns ns ns
6 Ruhwald et al. (28) 2008 Nigeria QFT-GIT 120 48 53 19 15.8% ns% ns 0–15 2005 85.8% ns ns ns
7a Mandalakas et al. (29) 2008 South Africa QFT Gold 12 2 10 0 0% 4.4% ns ns 2005–2006 ns 100% ns ns
7b Mandalakas. (29) 2008 South Africa T-SPOT.TB 23 12 11 0 0% 4.4% ns ns 2005–2006 91.3% 100% ns ns
8 Ohno et al. (30) 2008 Japan QFT Gold 17 0 17 0 0% ns% ns 0–10 2006 35.3% ns ns ns
9 Soysal et al. (31) 2008 Turkey T-SPOT.TB 209 31 173 5 2.4% 8.4% ns 6–10 2006 90% ns ns ns
10 Chun et al. (32) 2008 South Korea QFT-GIT 227 16 194 17 7.5% ns% 3.2 0–15.7 2006–2007 99.6% 0% ns ns
11a Connell et al. (33) 2008 Australia QFT-GIT 96 28 65 3 3.1% 8.9% ns 0.5–19 ns 52.1% 0% ns ns
11b Connell et al. (33) 2008 Australia T-SPOT.TB 96 25 57 14 14.6% 8.9% ns 0.5–19 ns 52.1% 0% ns ns
12 Petrucci et al. (34) 2008 Nepal, Brasil QFT-GIT 259 117 136 6 2.3% 8.5% ns 0.2–15 ns 96.5% ns ns ns
13a Richeldi et al. (35) 2008 Italy QFT Gold 70 9 51 10 14.3% 6.1% ns ns ns ns ns ns ns
13b Richeldi et al (35) 2008 Italy QFT-GIT 81 8 63 10 12.3% 6.9% ns ns ns ns ns ns ns
14 Bianchi et al. (36) 2009 Italy QFT-GIT 336 60 274 2 0.6% ns% 4.5 2.6–6.8 2005–2006 51.5% ns ns ns
15a Hesseling et al. (37) 2009 South Africa QFT Gold 21 8 10 3 14.3% 2.9% ns 0–5 2005–2006 100% 0% ns ns
15b Hesseling et al. (37) 2009 South Africa T-SPOT.TB 28 25 2 1 3.6% 2.9% ns 0–5 2005–2006 100% 0% ns ns
16 Higuchi et al. (38) 2009 Japan QFT 308 6 300 2 0.6% 9.2% ns 8–12 2005–2006 99% ns ns ns
17 Kobashi et al. (39) 2009 Japan QFT-2G 25 20 2 3 12% ns% ns 0–19 2005–2008 52% 0% Immunosuppressive treatment 4%
18a Kampmann et al. (40) 2009 UK QFT-GIT 209 80 115 14 6.7% 8% ns 0.2–16 2006–2008 67.9% ns ns ns
18b Kampmann et al. (40) 2009 UK T-SPOT.TB 206 70 118 18 8.7% 8% ns 0.2–16 2006–2008 67.9% ns ns ns
19 Haustein et al. (16) 2009 UK QFT Gold 237 41 113 83 35% ns% 7.3 0–18 2006–2008 50.6% 0.8% Inflammatory disorder, organ transplantation, asplenia, malignancies 24.1%
20a ruzzese et al. (41) 2009 Italy QFT-GIT 80 1 63 16 20% 12.5% ns 2–24 ns 0% 0% Rheumatoid arthritis, liver transplantation, panarteritis 100%
20b Bruzzese et al. (41) 2009 Italy T-SPOT.TB 74 7 57 10 13.5% 12.5% ns 2–24 ns 0% 0% Rheumatoid arthritis, liver transplantation, panarteritis 100%
21 Lighter et al. (42) 2009 USA QFT-GIT 207 31 173 3 1.4% 9% ns 0.1–18 ns 35.7% ns ns ns
22 Stavri et al. (43) 2009 Romania QFT 36 17 10 9 25% ns% ns 12–18 ns 100% 100% ns ns
23a Bamford et al. (44) 2010 UK QFT-GIT 170 101 56 13 7.6% 8.5 ns 0.2–16 2005–2007 ns ns ns ns
23b Bamford et al. (44) 2010 UK T-SPOT.TB 94 47 47 0 0% 8.5 ns 0.2–16 2005–2007 ns ns ns ns
24 Soborg et al. (45) 2010 Greenland QFT Gold 2117 197 1898 22 1% 11.4 ns 0–18 2005–2007 21.7% ns ns ns
25 Grare et al. (46) 2010 France QFT-GIT 51 5 39 7 13.7% 6 ns 0.3–18 2007–2008 41.2% 0% ns ns
26a Lucas et al. (47) 2010 Australia QFT-GIT 460 45 345 70 15.2% ns ns 0.4–16 2007–2008 70% 0% Schistosomiasis, Malaria, Hepatitis, Strongyloides ns
26b Lucas et al. (47) 2010 Australia T-SPOT.TB 420 38 374 8 1.9% ns ns 0.4–16 2007–2008 70% 0% Schistosomiasis, Malaria, Hepatitis, Strongyloides ns
27a Stefan et al. (48) 2010 South Africa QFT-GIT 34 3 26 5 14.7% ns 7 0.2–15 2007–2008 100% 0% Cancer 100%
27b Stefan et al. (48) 2010 South Africa T-SPOT.TB 27 6 17 4 14.8% ns 7 0.2–15 2007–2008 100% 0% Cancer 100%
28 Tsolia et al. (49) 2010 Greece QFT-GIT 286 125 152 9 3.1% ns ns 0–15 2007–2008 ns ns ns ns
29 Thomas et al. (20) 2010 Bangladesh QFT-GIT 302 107 121 74 24.5% 13.1 ns 11–15.3 2009 79.1% ns Helminth infection and malnutrition 83.1%
30a Adetifa et al. (50) 2010 Gambia QFT-GIT 215 72 141 2 0.9% ns ns 0.5–14 ns 59.1% 1.4% ns ns
30b Adetifa et al. (50) 2010 Gambia T-SPOT.TB 215 71 144 0 0% ns ns 0.5–14 ns 59.1% 1.4% ns ns
31 Kabeer et al. (51) 2010 India QFT-GIT 83 2 81 0 0% ns ns 0–15 ns 74.7% 0% ns ns
32 Stavri et al. (52) 2010 Romania QFT Gold 60 27 15 18 30% 9.44 ns 1–18 ns 100% ns ns ns
33a Altet-Gómez, et al. (53) 2011 Spain QFT-GIT 166 61 105 0 0% 9.1 ns 0–15 2005–2007 69.9% ns ns ns
33b Altet-Gómez et al. (53) 2011 Spain T-SPOT.TB 166 64 99 3 1.8% 9.1 ns 0–15 2005–2007 69.9% ns ns ns
34 Cruz et al. (54) 2011 USA T-SPOT.TB 215 70 135 10 4.7% 8.6 ns 0.1–18 2005–2006 36.3% 0% ns ns
35 Moyo et al. (55) 2011 South Africa QFT-GIT 397 68 308 21 5.3% ns 1.9 0.7–2.9 2005–2008 100% 0.5% ns ns
36 Banach et al. (56) 2011 USA QFT Gold 6629 290 6203 136 2.1% ns ns 0–19 2006–2008 ns ns ns ns
37 Kasambira et al. (57) 2011 South Africa QFT-GIT 270 79 172 19 7% ns 6 0.5–16 2006–2009 95.2% 5.2% ns ns
38 Losi et al. (58) 2011 Italy QFT-GIT 235 80 152 3 1.3% ns ns ns 2006–2008 76.6% ns ns ns
39 Shah et al. (59) 2011 South Africa QFT-GIT 196 62 117 17 8.7% 6 ns 0.5–16 2006–2009 94.9% 3.6% ns ns
40 Maritsi et al (60) 2011 UK QFT-GIT 23 1 20 2 8.7% ns 8.9 1.5–13 2007 21.7% ns Autoimmune disease 100%
41 Thomas et al. (61) 2011 UK QFT-GIT 283 29 236 18 6.4% 5.3 ns 0–16 2007-2009 71.7% ns ns ns
42 Zrinski et al. (62) 2011 Croatia QFT-GIT 2173 485 1678 10 0.5% ns ns 0.1–18 2007–2010 100% ns ns ns
43 Debord et al. (63) 2011 France QFT-GIT 19 15 4 0 0% ns 1.52 0.3–5.4 2008–2010 84.2% 0% ns ns
44 Pavić et al. (64) 2011 Croatia QFT Gold 142 18 123 1 0.7% 2.4 ns 0.1–5 2008–2009 100% ns ns ns
45 Mount et al. (65) 2011 UK QFT Gold 126 92 29 5 4% 6.2 ns 0.2–16.4 2009–2011 99% ns ns ns
46 Borgia et al. (66) 2011 Italy QFT GIT 1340 118 1219 3 0.2% ns ns 0–0.25 2011 ns ns ns ns
47 Yassin et al. (67) 2011 Ethiopia QFT-GIT 737 256 308 173 23.5% ns ns 1–15 Ns 72.5% 7.1% ns ns
48 Buonsenso et al. (68) 2012 Italy QFT Gold 66 64 1 1 1.5% ns ns 0–16 1990–2009 ns 3% ns ns
49 Riazi et al. (69) 2012 USA QFT-GIT 517 27 453 37 7.2% ns ns 0.1–18 2004–2011 68.7% ns ns ns
50 Banfield et al. (70) 2012 Australia QFT Gold, QFT-GIT 573 57 423 93 16.2% ns ns 0–17 2006–2007 ns 0% Helminth infection 40%
51a Basu Roy et al. (71) 2012 Bulgaria, Greece, Italy, Spain, UK QFT-GIT 1093 331 742 20 1.8% 8.2 ns 0–16 2006–2009 61.7% ns ns ns
51b Basu Roy et al. (71) 2012 Bulgaria, Greece, Italy, Spain, UK T-SPOT.TB 382 145 231 6 1.6% 8.2 ns 0–16 2006–2009 61.7% ns ns ns
52 Critselis et al. (72) 2012 Greece QFT-GIT 761 221 517 23 3% 7.84 ns 0–18 2007–2010 45.2% ns ns ns
53 Mendez-Echevarria et al. (73) 2012 Spain QFT-GIT 459 96 343 20 4.4% 4.73 ns 0.1–15 2007–2009 46.4% ns ns ns
54 Pong et al. (74) 2012 USA QFT-GIT 23 22 0 1 4.3% 8.5 ns 0–16 2007–2010 ns ns ns ns
55 Nenadic et al. (75) 2012 Croatia QFT-GIT 59 57 2 0 0% 12 ns 4–18 2008–2009 100% ns ns ns
56 Onur et al. (76) 2012 Turkey QFT-GIT 97 37 54 6 6.2% ns ns 0.2–14 2008–2009 87.6% ns ns ns
57 Rose et al. (77) 2012 Tanzania QFT 211 26 128 57 27% ns ns 0–15 2008–2010 91% 37% ns ns
58 Kabeer et al. (78) 2012 India QFT-GIT 145 32 113 0 0% ns ns 0–17 2008–2009 ns ns ns ns
59 Tuuminen et al. (79) 2012 Finland QFT-GIT 59 2 56 1 1.7% ns 12 11–14 2008 ns ns ns ns
60 Ling et al. (80) 2012 Canada QFT-GIT 399 82 311 6 1.5% ns 13 0–18 2009–2011 82% ns ns ns
61 Nkurunungi et al. (81) 2012 Uganda T-SPOT.TB 907 88 770 49 5.4% 5 ns 5 2009–2011 100% 1.4% Helminth infection 9%
62 Verhagen et al. (82) 2012 Venezuela QFT-GIT 140 48 80 12 8.6% 8.15 ns 1–15 2010–2011 86.4% ns Parasitic infection 97.1%
63 Dayal et al. (83) 2012 India QFT-GIT 150 64 57 29 19.3% ns ns 0–18 ns 52% ns ns ns
64 Rutherford et al. (84) 2012 Indonesia QFT-GIT 371 171 190 10 2.7% ns 5.1 0.2–10 ns 73.3% ns ns ns
65 Blandinières et al. (85) 2013 France QFT-GIT 226 53 150 23 10.2% ns ns 0–15 2007–2011 31.9% ns ns ns
66a Mandalakas et al. (86) 2013 South Africa QFT-GIT 238 57 171 10 4.2% ns 3.25 0.2–14.6 2007-2010 93% 50.8% ns ns
66b Mandalakas et al. (86) 2013 South Africa T-SPOT.TB 228 47 180 1 0.4% ns 3.25 0.2–14.6 2007–2010 93% 50% ns ns
67 Yassin et al. (87) 2013 Ethiopia QFT-GIT 458 158 223 77 16.8% ns ns 1–15 2007–2009 75.8% 5.9% ns ns
68 Chegou et al. (88) 2013 South Africa QFT-GIT 76 41 33 2 2.6% 3.1 ns 0–13 2008 90% 28.9% ns ns
69 Rose et al. (89) 2013 Tanzania QFT-GIT 152 20 93 39 25.7% 4.2 ns 0–15 2008–2010 95.4% 35.5% ns ns
70 Bua et al. (90) 2013 Italy QFT-GIT 105 21 84 0 0% ns ns 0.2–15 2009–2011 1.9% 0% ns ns
71a Carvalho et al. (91) 2013 Italy QFT-GIT 18 0 15 3 16.7% ns 5.5 1–18 2009–2010 ns 0% Cancer 100%
71b Carvalho et al. (91) 2013 Italy T-SPOT.TB 17 2 12 3 17.6% ns 6 1–18 2009-2010 ns 0% Cancer 100%
72 Ling et al. (92) 2013 South Africa T-SPOT.TB 557 175 353 29 5.2% ns 1.9 0–15 2009-2011 80.3% 22.3% ns ns
73 Uluk et al. (93) 2013 Papua New Guinea QFT-GIT 199 68 122 9 4.5% ns ns 0.1–12 2009–2010 75% 12.5% ns ns
74 Wassie et al. (94) 2013 Ethiopia QFT-GIT 245 51 187 7 2.9% 14.8 15 12–20 2009 100% 0% Helminth infection 20%
75 Laniado-Laborin et al. (95) 2013 Mexico QFT-GIT 173 71 101 1 0.6% 7.6 ns 0–16 2011–2013 95.3% ns ns ns
76 Dhanasekaran et al. (96) 2013 India QFT-GIT 210 40 166 4 1.9% ns ns 0–3 ns 100% ns ns ns
77 Lodha et al. (97) 2013 India QFT-GIT 362 297 58 7 1.9% ns 9.6 0.5–15 ns 74% 0% ns ns
78 Cranmer et al. (98) 2014 Kenya T-SPOT.TB 160 14 114 32 20% ns ns 0–0.5 1999–2002 100% 7% ns ns
79 Garazzino et al. (99) 2014 Italy QFT-GIT 823 126 662 35 4.3% 1.1 1.1 0–2 2005–2012 26.5% ns ns ns
80 Hermansen et al. (100) 2014 Denmark QFT-GIT 28 26 1 1 3.6% ns ns 1–14 2005–2010 ns ns ns ns
81 Jenum et al. (101) 2014 India QFT-GIT 691 36 633 22 3.2% 1.2 ns 0.1–2.9 2007–2010 100% ns ns ns
82 Holm et al. (102) 2014 Tanzania QFT-GIT 203 26 124 53 26.1% ns 3 0–15 2008–2010 ns 37.4% ns ns
83 Song et al. (103) 2014 South Korea QFT-GIT 2982 317 2649 16 0.5% 15.1 ns 11–19 2008–2012 61% ns ns ns
84 Vallada et al. (104) 2014 Brasil QFT-GIT 195 10 179 6 3.1% 3.9 ns 0.2–5.9 2008 100% ns ns ns
85 Pérez-Porcuna et al. (105) 2014 Brasil QFT-GIT 135 36 80 19 14.1% ns 3.8 0–6 2009–2010 87.4% ns Helminth infection 22.2%
86a Tieu et al. (106) 2014 Thailand QFT-GIT 157 51 106 0 0% 7.2 ns 0.2–16 2009-2011 97.5% 1.9% ns ns
86b Tieu et al. (106) 2014 Thailand T-SPOT.TB 157 47 110 0 0% 7.2 ns 0.2–16 2009–2011 97.5% 1.9% ns ns
87 Bui et al. (107) 2014 USA QFT-GIT 183 12 115 56 30.6% 11 ns 0–18 2010–2011 ns 15.8% Cancer, autoimmune disease, inflammatory bowel disease 41%
88a Chiappini et al. (108) 2014 Italy QFT-GIT 332 96 236 0 0% ns 5.5 ns 2010–2013 33% ns ns ns
88b Chiappini et al. (108) 2014 Italy T-SPOT.TB 313 70 234 9 2.9% ns 5.5 ns 2010–2013 33% ns ns ns
89 Rose et al. (109) 2014 Canada QFT-GIT 81 15 65 1 1.2% 12.5 ns 0-18 2010–2011 32.1% 100% ns ns
90 Verhagen et al. (110) 2014 Venezuela QFT-GIT 151 63 77 11 7.3% 7.7 ns 0-16 2010–2011 86.8% 0% ns ns
91 Tebruegge et al. (15) 2014 UK QFT-GIT 263 ns ns 24 9.1% ns ns 0-18 2011–2013 ns ns Immunosuppressive therapy 3.1%
92 Al Mekaini et al. (111) 2014 Abu Dhabi QFT-GIT 666 4 660 2 0.3% ns 8.7 1–19 2013 71.6% ns ns ns
93a de Souza-Galvao et al. (112) 2014 Spain QFT-GIT 37 23 14 0 0% 9.2 ns ns ns 67.6% 0% ns ns
93b de Souza-Galvao et al. (112) 2014 Spain T-SPOT.TB 37 21 16 0 0% 9.2 ns ns ns 67.6% 0% ns ns
94 Calzada-Hernandez et al. (113) 2015 Spain QFT-GIT 75 3 66 6 8% ns ns 0–18 2004–2013 ns ns Autoimmune disease 100%
95 Caliman-Sturdza et al. (114) 2015 Romania QFT-GIT 125 52 64 9 7.2% 10.45 ns 0.7–17 2006–2010 64.8% 12.8% Diabetes, leukemia 2.4%
96 Sali et al. (115) 2015 Italy QFT-GIT 621 59 536 26 4.2% 4.1 ns 0–14 2007–2010 ns 0.2% Leukemia, juvenile arthritis, Evan's syndrome 1%
97a Mandalakas et al. (116) 2015 South Africa QFT-GIT 1295 520 741 34 2.6% ns 4.9 0.2–15 2008–2012 86.7% 22% ns ns
97b Mandalakas et al. (116) 2015 South Africa T-SPOT.TB 1243 302 939 2 0.2% ns 4.9 0.2–15 2008–2012 86.7% 21.4% ns ns
98 Spicer et al. (117) 2015 USA T-SPOT.TB 107 5 91 11 10.3% 3.3 1.9 0.3–16 2008–2011 73.8% 0% ns ns
99 Bao et al. (118) 2015 China QFT-GIT 57 28 28 1 1.8% 4.3 ns 0–16 2010–2011 ns 0% Patients on glucocorticoid therapy 21.1%
100 Howley et al. (119) 2015 USA QFT-GIT 2520 142 2365 13 0.5% ns ns 2–14 2010–2011 ns ns ns ns
101 Pavic et al. (120) 2015 Croatia QFT-GIT 171 26 143 2 1.2% 2.4 ns 0.1–5 2010–2012 98.8% ns ns ns
102 Tebruegge et al. (121) 2015 Australia QFT-GIT 142 22 103 2 1.4% ns 8.3 0–18 2010–2011 47.2% ns ns ns
103 Lebina et al. (122) 2015 South Africa QFT-GIT 2105 351 1744 10 0.5% ns ns 5–7 2011 ns ns ns ns
104 Petrone et al. (123) 2015 Uganda QFT-GIT 105 17 81 7 6.7% ns ns 0–16 2011–2012 ns 29.5% ns ns
105 Sun et al. (124) 2015 China T-SPOT.TB 579 119 411 49 8.5% ns ns 0–5 2011–2014 91% 0% ns ns
106a Li et al. (125) 2015 China QFT-GIT 57 28 28 1 1.8% ns ns ns ns 100% 0% ns ns
106b Li et al. (125) 2015 China T-SPOT.TB 96 46 50 0 0% ns ns ns ns 100% 0% ns ns
107 Cruz et al. (126) 2015 Botswana QFT Gold 100 1 96 3 3% ns 10.2 0.8–17 ns 92% 100% ns ns
108 Grinsdale et al. (127) 2016 USA QFT-GIT, QFT Gold 1092 72 943 77 7.1% ns 8.7 0–15 2005–2008 ns ns ns ns
109 Santiago-Garcia et al. (128) 2016 Spain QFT-GIT 81 64 11 6 7.4% ns ns 0–18 2005–2013 ns ns ns ns
110 Perez-Porcuna et al. (129) 2016 Brasil QFT 121 34 71 16 13.2% ns ns 0–6 2009–2010 100% ns ns ns
111 Atikan et al. (130) 2016 Turkey QFT-GIT 71 5 65 1 1.4% 8 ns 3.5–18 2010–2013 97.2% ns Rheumatic disease 100%
112 Boddu et al. (131) 2016 India QFT-GIT 89 21 62 6 6.7% ns ns 1–15 2010–2011 98.9% ns ns ns
113a Nozawa et al. (132) 2016 Japan QFT-GIT 81 4 69 8 9.9% 10.5 ns 1.1–19.2 2010–2014 95.1% ns Rheumatic disease 100%
113b Nozawa et al. (132) 2016 Japan T-SPOT.TB 27 0 27 0 0% 10.15 ns 3.3–19.8 2010–2014 96.3% ns Rheumatic disease 100%
114 El Azbaoui et al. (133) 2016 Morocco QFT-GIT 109 40 49 20 18.3% 7.8 ns 0.4–17 2011–2015 100% 0% ns ns
115 Yun et al. (134) 2016 South Korea QFT-GIT 106 15 88 3 2.8% ns 9 0–18 2011–2015 99% ns ns ns
116 Beshir et al. (135) 2016 Egypt QFT-GIT 150 5 142 3 2% 1.4 0.75 0–12 2014–2015 82% ns ns ns
117 Wong et al. (136) 2017 Taiwan QFT-GIT 47 8 36 3 6.4% 10.2 ns 0.2–18 2008–2014 100% ns Leukemia 12.8%
118 Gabriele et al. (137) 2017 Greece QFT-GIT 79 3 74 2 2.5% ns 12 ns 2011–2012 30.4% ns Juvenile arthritis, lupus 100%
119 Mensah et al. (138) 2017 Ghana QFT-GIT 32 20 10 2 6.3% ns ns 0–15 2012–2014 78.1% ns ns ns
120 Li et al. (139) 2017 China QFT-GIT 2831 71 2698 62 2.2% 9.6 ns 5–15 2013 64.2% 0% ns ns
121 Petrucci et al. (140) 2017 Italy QFT-GIT 517 79 418 20 3.9% 5.4 ns 0–14 Ns 9.7% ns ns ns
122 Silveira et al. (141) 2018 Brasil T-SPOT.TB 86 21 52 13 15.1% ns 9.8 0–19 2007–2011 83.7% 16.3% Autoimmune disease, neoplasia, other immunodeficiencies 36.1%
123 Bielecka et al. (142) 2018 Poland QFT-GIT 146 17 126 3 2.1% ns 7.8 0–17 2009–2012 99% 0% Juvenile arthritis, ulcerative colitis 1.4%
124 Chiappini et al. (143) 2018 Italy QFT-GIT 762 32 730 0 0% ns 3.6 0–18 2009–2015 53.9% 0.1% Parasitic infection 53.7%
125 Mastrolia et al. (144) 2018 Italy QFT-GIT 1779 86 1689 4 0.2% ns 5.8 0–18 2009–2017 75.8% 0% ns ns
126 Mandalakas et al. (145) 2018 USA, Puerto Rico T-SPOT.TB 43196 2189 40753 254 0.6% ns 12.5 0–17 2010–2015 ns ns ns ns
127 Gaensbauer et al. (146) 2018 USA QFT 6336 450 5852 34 0.5% ns ns 2–18 2011–2014 ns ns ns ns
128 Hormi et al. (147) 2018 France QFT 63 8 51 4 6.3% ns 11.6 0.4–18 2011–2015 92.1% 100% ns ns
129a Starshinova et al. (148) 2018 Russia QFT-GIT 312 201 111 0 0% ns ns 1–19 2011–2016 100% 0% ns ns
129b Starshinova et al. (148) 2018 Russia T-SPOT.TB 236 32 204 0 0% ns ns 1–19 2011–2016 100% 0% ns ns
130 Sayyahfar et al. (149) 2018 Iran QFT 31 0 31 0 0% 8.79 ns 3–15 2013–2014 100% ns Renal dysfunction 100%
131 Said et al. (150) 2018 Tanzania QFT Gold 301 39 244 18 6% ns 2.2 0.5–4.9 2015–2016 100% 1.3% Helminth infection 22.3%
132 Sali et al. (151) 2018 Italy QFT 550 64 477 9 1.6% 5.8 ns 0–14 ns 43.5% ns ns ns
133 Vortia et al. (152) 2018 USA QFT-GIT 93 2 90 1 1.1% ns 16 5–19 ns ns ns Inflammatory bowel disease 100%
Total 107‘418 2555 0–24 1999–2018
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QFT, QuantiFERON-TB, assay generation not specified; QFT-GIT, QuantiFERON-TB Gold in tube; ns, not specified.

The 155 datasets included a total of 107,418 participants with a median number of participants of 166 (range 12–43,196) per dataset. The mean or median age was specified in 69% (107/155) of datasets and reported to be 7.6 and 6 years, respectively. Upper age range was 18 years in 87.2% (116/133), 19 years in 5.3% (7/133), 24 years in 2.3% (3/133), and not specified in 5.3% (7/133) of studies. The studies were done in 45 countries with 36.8% (49/133) in Europe, 21.8% (29/133) in Asia, 20.3% (27/133) in Africa, 11.3% (15/133) in North America, 4.5% (6/133) in Australia, 4.5% (6/133) in South America, and 0.75% (1/133) recruited children in two continents (Asia and South America).

The BCG vaccination rates were reported in 80% (124/155) of datasets and varied from 0 to 100% with a median of 82%. HIV infection rates were reported in 49% (76/155) and varied from 0 to 100% with the median infection rate of 0.05%.

In 33 datasets additional information on immunocompromising or other factors potentially influencing IGRA results was reported: rheumatic or autoimmune diseases in 12.3% (19/155), various forms of cancer in 4.5% (7/155), and parasitic infections in 6.5% (10/155) of datasets. The range of participants included with additional factors varied from 1 to 100% with a median of 83.1% (not specified in 2 datasets).

Definition of Indeterminate Results of Interferon-Gamma Release Assays

A definition for indeterminate results was included in 88% (117/133) of studies with definitions provided for QuantiFERON-TB in 85.7% (108/126) and for T-SPOT.TB in 96.7% (29/30) of datasets. Of those that included a definition for indeterminate results most datasets 49.7% (77/155) simply stated to have used the manufacturers' definition [QuantiFERON-TB 47.6% (60/126) and T-SPOT.TB 56.7% (17/30)]. Further to this for the definition of indeterminate results in the QuantiFERON-TB assay three studies used their own definitions for failed nil controls [nil tube interferon-γ concentration of > 0.7 IU/ml (56) and > 2.0 IU/ml (63, 147), respectively]; five studies stated presence of high background response without reporting specific values (23, 36, 47, 70, 74).

Definition of indeterminate results for the T-SPOT.TB most commonly referred to low mitogen and/or high nil responses in combination with negative antigen response without stating specific values. Some studies indicated the absolute number of spots as cut-offs, others defined the number of spots in relation to the nil and/or mitogen response. In four studies a nil control of more than 10 spots was considered indeterminate, as opposed to the manufacturer's definition of ≥ 6 spots (92, 98, 112, 145).

Type of Interferon-Gamma Release Assays

Of the 133 studies, 77.4% (103/133) assessed QFT only, 15.8% (21/133) assessed both QuantiFERON-TB and T-SPOT.TB, and 6.8% (9/133) assessed T-SPOT.TB only. The proportions of indeterminate results ranged from 0 to 35% in the included studies. The overall pooled effect size (equivalent to the pooled proportion of indeterminate results) was 0.04 (95% CI 0.03–0.05, I2 = 96.32%) for both IGRAs combined.

QuantiFERON-TB was used in 124 studies including 57,183 participants. The pooled proportion of indeterminate results of QuantiFERON-TB was 0.05 (95% CI 0.04–0.06, I2 = 96.06%) (Figure 2). T-SPOT.TB was analyzed in 30 studies including 50,235 participants. The pooled proportion of indeterminate results of T-SPOT.TB was 0.03 (95% CI 0.02–0.05, I2 = 95.02%).

Figure 2.

Figure 2

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Proportion of indeterminate results with 95% CI by type of IGRA. Studies arranged according to year of publication.

A total of 21 studies assessed QuantiFERON-TB and T-SPOT.TB in the same study which allowed calculation of risk differences for the proportion of indeterminate results. The pooled proportion of indeterminate results was lower for T-SPOT.TB compared to QuantiFERON-TB (risk difference −0.01, 95% CI −0.03 to −0.00, I2 = 87.7%), but did not reach statistical significance (Figure 3).

Figure 3.

Figure 3

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Risk difference (RD) with 95% CI in studies that included a head-to-head comparison of QuantiFERON-TB and T-SPOT.TB assays. Studies arranged according to year of publication.

Indeterminate Results According to Age

The mean or median age was specified in 108 datasets; of those 55 datasets had median or mean ages 0–7 years 52 datasets had median or mean ages ≥8years. The pooled proportions of indeterminate results were 0.04 (95% CI 0.03–0.06, I2 = 94.46%) for the age group 0–7 years and 0.04 (95% CI 0.03–0.05, I2 = 95.19%) for ≥8years. For the 48 datasets in which the mean or median age was not specified the proportions of indeterminate results were 0.05 (95% CI 0.03–0.06, I2 = 97.35%).

Of the 21 studies comparing both QuantiFERON-TB and T-SPOT.TB, 16 studies specified mean or median age. The pooled risk difference (negative values indicating lower risk of indeterminate results in the T-SPOT.TB) for 0–7 years was −0.01 (95% CI −0.03 to −0.01, I2 = 79.6%) and for ≥8 years −0.01 (95% CI −0.04 to −0.02, I2 = 76.7%). For studies which did not specify mean or median age the pooled risk difference was −0.03 (95% CI −0.10 to −0.05, I2 = 98.5%) (Figure 4). Risk differences within age groups for both assays were not statistically significant.

Figure 4.

Figure 4

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Risk differences (RD) with 95% CI in studies that included a head-to-head comparison of QuantiFERON-TB and T-SPOT.TB assays stratified by age. Studies sorted according to year of publication.

Indeterminate Results According to Geographical Location of the Study Population

A stratified analysis according to continents showed the following proportions for indeterminate IGRA results: Europe 0.03 (95% CI 0.02–0.05, I2 = 93.49%), Africa 0.07 (95% CI 0.04–0.10, I2 = 97.02%), Australia 0.08 (95% CI 0.04–0.14, I2 = 94.33%), Asia 0.03 (95% CI 0.01–0.04, I2 = 93.12%), North America 0.03 (95% CI 0.02–0.05, I2 = 97.48%), South America 0.09 (95% CI 0.06–0.14, I2 = 77.03%). One report with study sites in Asia and South America was excluded from this particular analysis, as the data could not be separated according to site of recruitment (34).

When continent of the study was included in the risk differences analysis the proportion of indeterminate results for T-SPOT.TB was significantly lower compared to QuantiFERON-TB in studies performed in Africa only (p < 0.001). The pooled risk difference for African studies was −0.022 (95% CI −0.032 to −0.011, I2 = 15.4%). Risk differences for studies performed on all other continents were not statistically significant (Figures 5, 6).

Figure 5.

Figure 5

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Risk differences (RD) with 95% CI in studies that included a head-to-head comparison of QuantiFERON-TB and T-SPOT.TB assays stratified by continent. Studies arranged according to year of publication.

Figure 6.

Figure 6

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Risk differences (RD) with 95% CI in studies that included a head-to-head comparison of QuantiFERON-TB and T-SPOT.TB assays stratified by African/Non-African origin of the study. Studies arranged according to year of publication.

Indeterminate Results by Immune Status

The pooled proportion of indeterminate IGRA results for the 0% HIV+, 0 < 51% HIV+, 51–100% HIV+, immunocompromised/HIV− and no information were 0.03 (95% CI 0.02–0.05, I2 = 94.45%), 0.07 (95% CI 0.04–0.11, I2 = 97.70%), 0.03 (95% CI 0.01–0.05, I2 = 73.96%), 0.12 (95% CI 0.07–0.18, I2 = 47.12%), 0.03 (95% CI 0.03–0.04, I2 = 94.78%), respectively.

When immune status was included in the risk difference analysis of indeterminate results the T-SPOT.TB was associated with lower proportions of indeterminate results only in studies that included immunocompromised, HIV-uninfected participants: the pooled risk difference was −0.071(95% CI −0.133 to −0.010, I2 = 0.0%) and statistically significant (p = 0.022). The risk differences in the remaining groups were not statistically significant (Figure 7).

Figure 7.

Figure 7

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Risk differences (RD) with 95% CI in studies that included a head-to-head comparison of QuantiFERON-TB and T-SPOT.TB assays stratified by immune status. Studies arranged according to year of publication.

Meta-Regression of Indeterminate Results

Of the four variables in the model (type of IGRA, age group, continent where study was performed, immune status), only studies including non-HIV-infected immunocompromised patients had a statistically significant contribution to the heterogeneity in the multiple regression model (p = 0.0003).

Discussion

Indeterminate IGRA results have been reported shortly after introduction of these tests in routine clinical use. Despite this, analysis of indeterminate IGRA results has commonly been neglected in the literature, with those results either having been excluded from previous systematic literature reviews or only having been included in very limited subgroup analyses (11, 153, 154). To our knowledge, this systematic review is the first to comprehensively analyse the occurrence of indeterminate IGRA results in children and adolescents. We found that 4% of IGRA results are indeterminate, suggesting that 1 in 25 tests will not produce a conclusive result. The main factor associated with indeterminate results identified in this meta-analysis was the presence of an immunocompromising condition other than HIV infection.

In our analysis T-SPOT.TB assays were associated with a similar risk of indeterminate results compared to various generations of QuantiFERON-TB tests. T-SPOT.TB assays require lymphocyte adjustment which may reduce the risk of an indeterminate result particularly in patients with reduced lymphocyte count, such as HIV infection or immunocompromising conditions associated with lymphopenia. This assumption is confirmed by results from a meta-analysis including studies in adult HIV-infected patients showing that low CD4 cell counts increased indeterminate rates of QuantiFERON-TB but not of T-SPOT.TB assays (155). Our results contrast with another earlier meta-analysis by Diel et al that reported fewer indeterminate results for QFT-GIT (2.1%) compared to T-SPOT.TB (3.8%) (154). The authors concluded that the more demanding laboratory work for the T-SPOT.TB was likely the reason for higher indeterminate rates. However, their analysis predominately included studies in adults, did not include random effects models, and only included studies published until 2009.

Immunocompromising conditions, including HIV infection, have been identified in earlier studies as a major contributing factor to indeterminate results (16). A study by Oni et al. showed that HIV infection in adults increased the risk of indeterminate results, either through low positive control responses or high interferon-γ background concentrations in the negative control (156). In another study by Mandalakas et al. indeterminate results were more frequent in children infected with HIV than in HIV-uninfected children (116). The previously reported lower sensitivity of QuantiFERON-TB assays in HIV-infected individuals may be linked to a higher rate of indeterminate results, as the difference between the assays was negligible in a study after exclusion of indeterminate results in one analysis (157). Diel et al. reported in their meta-analysis that the rates of indeterminate results for QuantiFERON-TB and T-SPOT.TB assays were higher in immunocompromised compared to immunocompetent individuals, with 6.1 and 4.4%, respectively (154).

Further factors have been shown to influence IGRA results, particularly chronic rheumatic or auto-inflammatory diseases (158, 159). IGRA performance depends on intact cellular Th1 responses. Helminth infections, which primarily induce Th2 responses, may alter cytokine production and thereby increase the rate of indeterminate results (20, 150, 160, 161).

Importantly, in our analysis younger age was not associated with indeterminate results, reflected in similar proportions of indeterminate IGRA results in all age groups. This conflicts with several studies that have reported a clear correlation between IGRA performance, proportions of indeterminate results and age (15, 16, 18, 27, 33, 158). It is well-established that young children have a maturing immune system that may result in diminished cytokine release (162, 163). The link between age and cytokine concentrations has also been shown in numerous studies in healthy children unrelated to TB diagnostics (162, 163). One potential reason for not detecting a significant association between age and indeterminate IGRA results in this meta-analysis is that aggregate data based on the reported mean/median ages rather than individual patient data were used for this analysis.

There were several factors we were unable to analyse in the datasets that have been reported in some of the included studies, which mainly concern pre-analytical factors. Several studies in children and in adults found a decrease in interferon-γ production and indeterminate IGRA results to be associated with delayed sample incubation, shipping of samples, variation in environmental temperatures, and poor phlebotomy technique (164–168). In addition, co-medication may influence results as a recent ex vivo study showed that both corticosteroids and anti-TNF-alpha agents can cause false-negative IGRA results, and potentially also increase the rate of indeterminate results (169).

One potential limitation of our meta-analysis is the considerable heterogeneity of the included studies. Despite using empirical random effects weighting, excluding studies with < 10 participants, and using only data of the two commercially available IGRAs, heterogeneity remained. Moreover, it is possible that studies with poor IGRA performance and higher proportion of indeterminate results were less likely to be published, leading to publication bias. In addition, details on the type of QuantiFERON-TB assays used were often not reported in the publications, precluding a comparison of different test generations.

Conclusions

In children, indeterminate IGRA results occur in 1 in 25 tests performed on average. Overall, there was no difference in the proportion of indeterminate results between both commercial assays. However, the data of this meta-analysis indicate that in patients in Africa and/or children with immunocompromising conditions other than HIV infection the T-SPOT.TB assay appears to produce fewer indeterminate results than the QuantiFERON-TB assays.

Author Contributions

NR, MT, and UH conceptualized the study. NM and MG designed the search strategy and searched the literature, selected the studies and extracted the data. NR reviewed and approved the search strategy. NM, MG, and TV performed the data analysis. All authors performed the data interpretation. NM, MG, and NR wrote the draft manuscript. All authors reviewed, provided intellectual input into and approved the final manuscript.

Conflict of Interest Statement

MT has received support from Cepheid for conference attendance. MT also received QuantiFERON-TB Gold assays at reduced cost for another research project from the manufacturer (Cellestis/Qiagen). The manufacturer had no influence on the study design, the data interpretation, the writing of the manuscript or the decision to submit the data for publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

NM was supported by the following funding bodies: Bangerter Rhyner Stiftung, Lunge Zürich, Nora van Meeuwen-Häftliger Stiftung, and Schweizerische Lungenstiftung. MT was supported by a grant by the Technology Strategy Board/Innovate UK.

Glossary

Abbreviations

BCG

Bacille Calmette-Guérin

CI

Confidence interval

HIV

Human immunodeficiency virus

IGRA

Interferon-gamma release assay

IFN-γ

Interferon-gamma

ns

not specified

QFT

QuantiFERON-TB

TB

Tuberculosis

TST

Tuberculin skin test. *QFT used representative for the two reported generations of QFT [QFT Gold and QFT-GIT (Gold In-Tube)].

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fped.2019.00208/full#supplementary-material

Click here for additional data file. (52KB, docx)

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