SYSTEMATIC REVIEW article

Front. Pediatr., 29 May 2019

Sec. Pediatric Infectious Diseases

Volume 7 - 2019 | https://doi.org/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

  • 1. Mycobacterial Research Laboratory, University of Basel Children's Hospital, Basel, Switzerland

  • 2. Faculty of Medicine, University of Basel, Basel, Switzerland

  • 3. School of Health Professions, Zürich University of Applied Sciences, Winterthur, Switzerland

  • 4. Paediatric Infectious Diseases and Vaccinology Unit, University of Basel Children's Hospital, Basel, Switzerland

  • 5. UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

  • 6. Department of Paediatric Infectious Diseases and Immunology, Evelina London Children's Hospital, Guy's and St. Thomas' NHS Foundation Trust, London, United Kingdom

  • 7. Royal Children's Hospital Melbourne, Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia

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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.

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 (35). 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 (1114). 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 (1518).

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 (1820).

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

Flow chart outlining selection of articles included in the review.

Table 1

Study numberAuthorsYear of publicationCountryIGRAParticipants nPositive results nNegative results nIndeterminate results nProportion of ind. %Mean age yearsMedian age yearsAge range yearsYears study performedBCG vaccinated n (%)HIV positive n (%)Other immunodeficiencyOther immunodeficiency (%)
1Connell et al. (23)2006AustraliaQFT Gold10120641716.8%nsns0.4–17.92004–200552.5%nsnsns
2Dogra et al. (24)2007IndiaQFT Gold105119400%ns61–122004–200581.9%nsnsns
3aDomínguez et al. (25)2008SpainQFT-GIT134508400%ns%ns0–182004–200664.2%0%nsns
3bDomínguez et al. (25)2008SpainT-SPOT.TB134518032.2%ns%ns0–182004–200664.2%0%nsns
4Taylor et al. (26)2008UKQFT120610775.8%10%ns0.3–162004–200546.7%nsnsns
5Okada et al. (27)2008CambodiaQFT Gold2043316294.4%ns%ns0–5200580%nsnsns
6Ruhwald et al. (28)2008NigeriaQFT-GIT12048531915.8%ns%ns0–15200585.8%nsnsns
7aMandalakas et al. (29)2008South AfricaQFT Gold1221000%4.4%nsns2005–2006ns100%nsns
7bMandalakas. (29)2008South AfricaT-SPOT.TB23121100%4.4%nsns2005–200691.3%100%nsns
8Ohno et al. (30)2008JapanQFT Gold1701700%ns%ns0–10200635.3%nsnsns
9Soysal et al. (31)2008TurkeyT-SPOT.TB2093117352.4%8.4%ns6–10200690%nsnsns
10Chun et al. (32)2008South KoreaQFT-GIT22716194177.5%ns%3.20–15.72006–200799.6%0%nsns
11aConnell et al. (33)2008AustraliaQFT-GIT96286533.1%8.9%ns0.5–19ns52.1%0%nsns
11bConnell et al. (33)2008AustraliaT-SPOT.TB9625571414.6%8.9%ns0.5–19ns52.1%0%nsns
12Petrucci et al. (34)2008Nepal, BrasilQFT-GIT25911713662.3%8.5%ns0.2–15ns96.5%nsnsns
13aRicheldi et al. (35)2008ItalyQFT Gold709511014.3%6.1%nsnsnsnsnsnsns
13bRicheldi et al (35)2008ItalyQFT-GIT818631012.3%6.9%nsnsnsnsnsnsns
14Bianchi et al. (36)2009ItalyQFT-GIT3366027420.6%ns%4.52.6–6.82005–200651.5%nsnsns
15aHesseling et al. (37)2009South AfricaQFT Gold21810314.3%2.9%ns0–52005–2006100%0%nsns
15bHesseling et al. (37)2009South AfricaT-SPOT.TB2825213.6%2.9%ns0–52005–2006100%0%nsns
16Higuchi et al. (38)2009JapanQFT308630020.6%9.2%ns8–122005–200699%nsnsns
17Kobashi et al. (39)2009JapanQFT-2G25202312%ns%ns0–192005–200852%0%Immunosuppressive treatment4%
18aKampmann et al. (40)2009UKQFT-GIT20980115146.7%8%ns0.2–162006–200867.9%nsnsns
18bKampmann et al. (40)2009UKT-SPOT.TB20670118188.7%8%ns0.2–162006–200867.9%nsnsns
19Haustein et al. (16)2009UKQFT Gold237411138335%ns%7.30–182006–200850.6%0.8%Inflammatory disorder, organ transplantation, asplenia, malignancies24.1%
20aruzzese et al. (41)2009ItalyQFT-GIT801631620%12.5%ns2–24ns0%0%Rheumatoid arthritis, liver transplantation, panarteritis100%
20bBruzzese et al. (41)2009ItalyT-SPOT.TB747571013.5%12.5%ns2–24ns0%0%Rheumatoid arthritis, liver transplantation, panarteritis100%
21Lighter et al. (42)2009USAQFT-GIT2073117331.4%9%ns0.1–18ns35.7%nsnsns
22Stavri et al. (43)2009RomaniaQFT361710925%ns%ns12–18ns100%100%nsns
23aBamford et al. (44)2010UKQFT-GIT17010156137.6%8.5ns0.2–162005–2007nsnsnsns
23bBamford et al. (44)2010UKT-SPOT.TB94474700%8.5ns0.2–162005–2007nsnsnsns
24Soborg et al. (45)2010GreenlandQFT Gold21171971898221%11.4ns0–182005–200721.7%nsnsns
25Grare et al. (46)2010FranceQFT-GIT51539713.7%6ns0.3–182007–200841.2%0%nsns
26aLucas et al. (47)2010AustraliaQFT-GIT460453457015.2%nsns0.4–162007–200870%0%Schistosomiasis, Malaria, Hepatitis, Strongyloidesns
26bLucas et al. (47)2010AustraliaT-SPOT.TB4203837481.9%nsns0.4–162007–200870%0%Schistosomiasis, Malaria, Hepatitis, Strongyloidesns
27aStefan et al. (48)2010South AfricaQFT-GIT34326514.7%ns70.2–152007–2008100%0%Cancer100%
27bStefan et al. (48)2010South AfricaT-SPOT.TB27617414.8%ns70.2–152007–2008100%0%Cancer100%
28Tsolia et al. (49)2010GreeceQFT-GIT28612515293.1%nsns0–152007–2008nsnsnsns
29Thomas et al. (20)2010BangladeshQFT-GIT3021071217424.5%13.1ns11–15.3200979.1%nsHelminth infection and malnutrition83.1%
30aAdetifa et al. (50)2010GambiaQFT-GIT2157214120.9%nsns0.5–14ns59.1%1.4%nsns
30bAdetifa et al. (50)2010GambiaT-SPOT.TB2157114400%nsns0.5–14ns59.1%1.4%nsns
31Kabeer et al. (51)2010IndiaQFT-GIT8328100%nsns0–15ns74.7%0%nsns
32Stavri et al. (52)2010RomaniaQFT Gold6027151830%9.44ns1–18ns100%nsnsns
33aAltet-Gómez, et al. (53)2011SpainQFT-GIT1666110500%9.1ns0–152005–200769.9%nsnsns
33bAltet-Gómez et al. (53)2011SpainT-SPOT.TB166649931.8%9.1ns0–152005–200769.9%nsnsns
34Cruz et al. (54)2011USAT-SPOT.TB21570135104.7%8.6ns0.1–182005–200636.3%0%nsns
35Moyo et al. (55)2011South AfricaQFT-GIT39768308215.3%ns1.90.7–2.92005–2008100%0.5%nsns
36Banach et al. (56)2011USAQFT Gold662929062031362.1%nsns0–192006–2008nsnsnsns
37Kasambira et al. (57)2011South AfricaQFT-GIT27079172197%ns60.5–162006–200995.2%5.2%nsns
38Losi et al. (58)2011ItalyQFT-GIT2358015231.3%nsnsns2006–200876.6%nsnsns
39Shah et al. (59)2011South AfricaQFT-GIT19662117178.7%6ns0.5–162006–200994.9%3.6%nsns
40Maritsi et al (60)2011UKQFT-GIT2312028.7%ns8.91.5–13200721.7%nsAutoimmune disease100%
41Thomas et al. (61)2011UKQFT-GIT28329236186.4%5.3ns0–162007-200971.7%nsnsns
42Zrinski et al. (62)2011CroatiaQFT-GIT21734851678100.5%nsns0.1–182007–2010100%nsnsns
43Debord et al. (63)2011FranceQFT-GIT1915400%ns1.520.3–5.42008–201084.2%0%nsns
44Pavić et al. (64)2011CroatiaQFT Gold1421812310.7%2.4ns0.1–52008–2009100%nsnsns
45Mount et al. (65)2011UKQFT Gold126922954%6.2ns0.2–16.42009–201199%nsnsns
46Borgia et al. (66)2011ItalyQFT GIT1340118121930.2%nsns0–0.252011nsnsnsns
47Yassin et al. (67)2011EthiopiaQFT-GIT73725630817323.5%nsns1–15Ns72.5%7.1%nsns
48Buonsenso et al. (68)2012ItalyQFT Gold6664111.5%nsns0–161990–2009ns3%nsns
49Riazi et al. (69)2012USAQFT-GIT51727453377.2%nsns0.1–182004–201168.7%nsnsns
50Banfield et al. (70)2012AustraliaQFT Gold, QFT-GIT573574239316.2%nsns0–172006–2007ns0%Helminth infection40%
51aBasu Roy et al. (71)2012Bulgaria, Greece, Italy, Spain, UKQFT-GIT1093331742201.8%8.2ns0–162006–200961.7%nsnsns
51bBasu Roy et al. (71)2012Bulgaria, Greece, Italy, Spain, UKT-SPOT.TB38214523161.6%8.2ns0–162006–200961.7%nsnsns
52Critselis et al. (72)2012GreeceQFT-GIT761221517233%7.84ns0–182007–201045.2%nsnsns
53Mendez-Echevarria et al. (73)2012SpainQFT-GIT45996343204.4%4.73ns0.1–152007–200946.4%nsnsns
54Pong et al. (74)2012USAQFT-GIT2322014.3%8.5ns0–162007–2010nsnsnsns
55Nenadic et al. (75)2012CroatiaQFT-GIT5957200%12ns4–182008–2009100%nsnsns
56Onur et al. (76)2012TurkeyQFT-GIT97375466.2%nsns0.2–142008–200987.6%nsnsns
57Rose et al. (77)2012TanzaniaQFT211261285727%nsns0–152008–201091%37%nsns
58Kabeer et al. (78)2012IndiaQFT-GIT1453211300%nsns0–172008–2009nsnsnsns
59Tuuminen et al. (79)2012FinlandQFT-GIT5925611.7%ns1211–142008nsnsnsns
60Ling et al. (80)2012CanadaQFT-GIT3998231161.5%ns130–182009–201182%nsnsns
61Nkurunungi et al. (81)2012UgandaT-SPOT.TB90788770495.4%5ns52009–2011100%1.4%Helminth infection9%
62Verhagen et al. (82)2012VenezuelaQFT-GIT1404880128.6%8.15ns1–152010–201186.4%nsParasitic infection97.1%
63Dayal et al. (83)2012IndiaQFT-GIT15064572919.3%nsns0–18ns52%nsnsns
64Rutherford et al. (84)2012IndonesiaQFT-GIT371171190102.7%ns5.10.2–10ns73.3%nsnsns
65Blandinières et al. (85)2013FranceQFT-GIT226531502310.2%nsns0–152007–201131.9%nsnsns
66aMandalakas et al. (86)2013South AfricaQFT-GIT23857171104.2%ns3.250.2–14.62007-201093%50.8%nsns
66bMandalakas et al. (86)2013South AfricaT-SPOT.TB2284718010.4%ns3.250.2–14.62007–201093%50%nsns
67Yassin et al. (87)2013EthiopiaQFT-GIT4581582237716.8%nsns1–152007–200975.8%5.9%nsns
68Chegou et al. (88)2013South AfricaQFT-GIT76413322.6%3.1ns0–13200890%28.9%nsns
69Rose et al. (89)2013TanzaniaQFT-GIT15220933925.7%4.2ns0–152008–201095.4%35.5%nsns
70Bua et al. (90)2013ItalyQFT-GIT105218400%nsns0.2–152009–20111.9%0%nsns
71aCarvalho et al. (91)2013ItalyQFT-GIT18015316.7%ns5.51–182009–2010ns0%Cancer100%
71bCarvalho et al. (91)2013ItalyT-SPOT.TB17212317.6%ns61–182009-2010ns0%Cancer100%
72Ling et al. (92)2013South AfricaT-SPOT.TB557175353295.2%ns1.90–152009-201180.3%22.3%nsns
73Uluk et al. (93)2013Papua New GuineaQFT-GIT1996812294.5%nsns0.1–122009–201075%12.5%nsns
74Wassie et al. (94)2013EthiopiaQFT-GIT2455118772.9%14.81512–202009100%0%Helminth infection20%
75Laniado-Laborin et al. (95)2013MexicoQFT-GIT1737110110.6%7.6ns0–162011–201395.3%nsnsns
76Dhanasekaran et al. (96)2013IndiaQFT-GIT2104016641.9%nsns0–3ns100%nsnsns
77Lodha et al. (97)2013IndiaQFT-GIT3622975871.9%ns9.60.5–15ns74%0%nsns
78Cranmer et al. (98)2014KenyaT-SPOT.TB160141143220%nsns0–0.51999–2002100%7%nsns
79Garazzino et al. (99)2014ItalyQFT-GIT823126662354.3%1.11.10–22005–201226.5%nsnsns
80Hermansen et al. (100)2014DenmarkQFT-GIT2826113.6%nsns1–142005–2010nsnsnsns
81Jenum et al. (101)2014IndiaQFT-GIT69136633223.2%1.2ns0.1–2.92007–2010100%nsnsns
82Holm et al. (102)2014TanzaniaQFT-GIT203261245326.1%ns30–152008–2010ns37.4%nsns
83Song et al. (103)2014South KoreaQFT-GIT29823172649160.5%15.1ns11–192008–201261%nsnsns
84Vallada et al. (104)2014BrasilQFT-GIT1951017963.1%3.9ns0.2–5.92008100%nsnsns
85Pérez-Porcuna et al. (105)2014BrasilQFT-GIT13536801914.1%ns3.80–62009–201087.4%nsHelminth infection22.2%
86aTieu et al. (106)2014ThailandQFT-GIT1575110600%7.2ns0.2–162009-201197.5%1.9%nsns
86bTieu et al. (106)2014ThailandT-SPOT.TB1574711000%7.2ns0.2–162009–201197.5%1.9%nsns
87Bui et al. (107)2014USAQFT-GIT183121155630.6%11ns0–182010–2011ns15.8%Cancer, autoimmune disease, inflammatory bowel disease41%
88aChiappini et al. (108)2014ItalyQFT-GIT3329623600%ns5.5ns2010–201333%nsnsns
88bChiappini et al. (108)2014ItalyT-SPOT.TB3137023492.9%ns5.5ns2010–201333%nsnsns
89Rose et al. (109)2014CanadaQFT-GIT81156511.2%12.5ns0-182010–201132.1%100%nsns
90Verhagen et al. (110)2014VenezuelaQFT-GIT1516377117.3%7.7ns0-162010–201186.8%0%nsns
91Tebruegge et al. (15)2014UKQFT-GIT263nsns249.1%nsns0-182011–2013nsnsImmunosuppressive therapy3.1%
92Al Mekaini et al. (111)2014Abu DhabiQFT-GIT666466020.3%ns8.71–19201371.6%nsnsns
93ade Souza-Galvao et al. (112)2014SpainQFT-GIT37231400%9.2nsnsns67.6%0%nsns
93bde Souza-Galvao et al. (112)2014SpainT-SPOT.TB37211600%9.2nsnsns67.6%0%nsns
94Calzada-Hernandez et al. (113)2015SpainQFT-GIT7536668%nsns0–182004–2013nsnsAutoimmune disease100%
95Caliman-Sturdza et al. (114)2015RomaniaQFT-GIT125526497.2%10.45ns0.7–172006–201064.8%12.8%Diabetes, leukemia2.4%
96Sali et al. (115)2015ItalyQFT-GIT62159536264.2%4.1ns0–142007–2010ns0.2%Leukemia, juvenile arthritis, Evan's syndrome1%
97aMandalakas et al. (116)2015South AfricaQFT-GIT1295520741342.6%ns4.90.2–152008–201286.7%22%nsns
97bMandalakas et al. (116)2015South AfricaT-SPOT.TB124330293920.2%ns4.90.2–152008–201286.7%21.4%nsns
98Spicer et al. (117)2015USAT-SPOT.TB1075911110.3%3.31.90.3–162008–201173.8%0%nsns
99Bao et al. (118)2015ChinaQFT-GIT57282811.8%4.3ns0–162010–2011ns0%Patients on glucocorticoid therapy21.1%
100Howley et al. (119)2015USAQFT-GIT25201422365130.5%nsns2–142010–2011nsnsnsns
101Pavic et al. (120)2015CroatiaQFT-GIT1712614321.2%2.4ns0.1–52010–201298.8%nsnsns
102Tebruegge et al. (121)2015AustraliaQFT-GIT1422210321.4%ns8.30–182010–201147.2%nsnsns
103Lebina et al. (122)2015South AfricaQFT-GIT21053511744100.5%nsns5–72011nsnsnsns
104Petrone et al. (123)2015UgandaQFT-GIT105178176.7%nsns0–162011–2012ns29.5%nsns
105Sun et al. (124)2015ChinaT-SPOT.TB579119411498.5%nsns0–52011–201491%0%nsns
106aLi et al. (125)2015ChinaQFT-GIT57282811.8%nsnsnsns100%0%nsns
106bLi et al. (125)2015ChinaT-SPOT.TB96465000%nsnsnsns100%0%nsns
107Cruz et al. (126)2015BotswanaQFT Gold10019633%ns10.20.8–17ns92%100%nsns
108Grinsdale et al. (127)2016USAQFT-GIT, QFT Gold109272943777.1%ns8.70–152005–2008nsnsnsns
109Santiago-Garcia et al. (128)2016SpainQFT-GIT81641167.4%nsns0–182005–2013nsnsnsns
110Perez-Porcuna et al. (129)2016BrasilQFT12134711613.2%nsns0–62009–2010100%nsnsns
111Atikan et al. (130)2016TurkeyQFT-GIT7156511.4%8ns3.5–182010–201397.2%nsRheumatic disease100%
112Boddu et al. (131)2016IndiaQFT-GIT89216266.7%nsns1–152010–201198.9%nsnsns
113aNozawa et al. (132)2016JapanQFT-GIT8146989.9%10.5ns1.1–19.22010–201495.1%nsRheumatic disease100%
113bNozawa et al. (132)2016JapanT-SPOT.TB2702700%10.15ns3.3–19.82010–201496.3%nsRheumatic disease100%
114El Azbaoui et al. (133)2016MoroccoQFT-GIT10940492018.3%7.8ns0.4–172011–2015100%0%nsns
115Yun et al. (134)2016South KoreaQFT-GIT106158832.8%ns90–182011–201599%nsnsns
116Beshir et al. (135)2016EgyptQFT-GIT150514232%1.40.750–122014–201582%nsnsns
117Wong et al. (136)2017TaiwanQFT-GIT4783636.4%10.2ns0.2–182008–2014100%nsLeukemia12.8%
118Gabriele et al. (137)2017GreeceQFT-GIT7937422.5%ns12ns2011–201230.4%nsJuvenile arthritis, lupus100%
119Mensah et al. (138)2017GhanaQFT-GIT32201026.3%nsns0–152012–201478.1%nsnsns
120Li et al. (139)2017ChinaQFT-GIT2831712698622.2%9.6ns5–15201364.2%0%nsns
121Petrucci et al. (140)2017ItalyQFT-GIT51779418203.9%5.4ns0–14Ns9.7%nsnsns
122Silveira et al. (141)2018BrasilT-SPOT.TB8621521315.1%ns9.80–192007–201183.7%16.3%Autoimmune disease, neoplasia, other immunodeficiencies36.1%
123Bielecka et al. (142)2018PolandQFT-GIT1461712632.1%ns7.80–172009–201299%0%Juvenile arthritis, ulcerative colitis1.4%
124Chiappini et al. (143)2018ItalyQFT-GIT7623273000%ns3.60–182009–201553.9%0.1%Parasitic infection53.7%
125Mastrolia et al. (144)2018ItalyQFT-GIT177986168940.2%ns5.80–182009–201775.8%0%nsns
126Mandalakas et al. (145)2018USA, Puerto RicoT-SPOT.TB431962189407532540.6%ns12.50–172010–2015nsnsnsns
127Gaensbauer et al. (146)2018USAQFT63364505852340.5%nsns2–182011–2014nsnsnsns
128Hormi et al. (147)2018FranceQFT6385146.3%ns11.60.4–182011–201592.1%100%nsns
129aStarshinova et al. (148)2018RussiaQFT-GIT31220111100%nsns1–192011–2016100%0%nsns
129bStarshinova et al. (148)2018RussiaT-SPOT.TB2363220400%nsns1–192011–2016100%0%nsns
130Sayyahfar et al. (149)2018IranQFT3103100%8.79ns3–152013–2014100%nsRenal dysfunction100%
131Said et al. (150)2018TanzaniaQFT Gold30139244186%ns2.20.5–4.92015–2016100%1.3%Helminth infection22.3%
132Sali et al. (151)2018ItalyQFT5506447791.6%5.8ns0–14ns43.5%nsnsns
133Vortia et al. (152)2018USAQFT-GIT9329011.1%ns165–19nsnsnsInflammatory bowel disease100%
Total107‘41825550–241999–2018

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

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

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

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

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

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

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

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 (164168). 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.

Statements

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.

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.

Conflict of interest

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.

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

    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)].

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Summary

Keywords

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

Citation

Meier NR, Volken T, Geiger M, Heininger U, Tebruegge M and Ritz N (2019) Risk Factors for Indeterminate Interferon-Gamma Release Assay for the Diagnosis of Tuberculosis in Children—A Systematic Review and Meta-Analysis. Front. Pediatr. 7:208. doi: 10.3389/fped.2019.00208

Received

14 November 2018

Accepted

08 May 2019

Published

29 May 2019

Volume

7 - 2019

Edited by

Dimitri Van der Linden, Cliniques Universitaires Saint-Luc, Belgium

Reviewed by

Delane Shingadia, Great Ormond Street Hospital, United Kingdom; Tea Nieminen, Helsinki Children's Hospital, Finland; Anna Starshinova, Saint Petersburg State University, Russia

Updates

Copyright

*Correspondence: Nicole Ritz

This article was submitted to Pediatric Infectious Diseases, a section of the journal Frontiers in Pediatrics

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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