Diagnosis of Childhood TuberculosisToyin Togun, McGill University, Montreal, QC, CanadaBeate Kampmann, Medical Research Council Unit The Gambia (MRCG), Banjul, The Gambia; Imperial College London, London,United KingdomMadhukar Pai, McGill University, Montreal, QC, Canada; Manipal University, Manipal, India

ã 2017 Elsevier Inc. All rights reserved.

Introduction 1Pathogenesis of TB in Children 2Pediatric Immune Response to M.tb and Differences to Responses in Adults 2Diagnostic Challenges in Childhood TB 2Clinical Diagnostic Approaches 3Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children 4Diagnostic Tests for TB and Their Application in Childhood TB Diagnosis 5Smear Microscopy and Cultures 5Xpert MTB/RIF 5Other Molecular Methods (TB-LAMP, LPAs) 6Urine LAM Detection Assay 6Host Response Tests: Tuberculin Skin Test or Interferon-gamma Release Assay 6Tuberculin skin test (TST) 7Interferon (IFN)-g release assays (IGRAs) 7Diagnostic Algorithm 7Future Prospects 7Diagnostic biomarkers 7Conclusion 10Acknowledgments 11References 11

Introduction

The World Health Organisation (WHO) reported an estimated 10.4 million incident cases of tuberculosis (TB) globally in 2015

including at least a million cases in children below 15 years of age, while an estimated 210,000 children died of TB (WHO, 2016a).

About 75% of all childhood TB cases occur every year in the 22 high-burden countries, most of which are in subSaharan Africa

(Nelson and Wells, 2004). However, routine data on childhood TB is likely to underestimate the true magnitude of the problem,

principally because of the challenges in the diagnosis of TB in children; additionally, a low priority is traditionally given to

childhood TB by most national TB control programs because children are not considered a substantial contributor to the

transmission of Mycobacterium tuberculosis (M.tb) (Newton et al., 2008; Ahmed et al., 2008).

Until recently, pediatric TB disease estimates were derived from the proportions of smear-positive cases by age, resulting in a

significant risk of underestimating the true burden in children given that most pulmonary TB disease in children is smear negative

(Nelson andWells, 2004; Corbett et al., 2003). In support of this assertion, a recently published mathematical model predicted that

the annual incidence of pediatric TB in the 22 high TB-burden countries is greater than 650,000 cases, which is in fact much higher

than the number of notifications in those countries (Dodd et al., 2014). Childhood TB is estimated to constitute approximately 5%

of the TB caseload in low TB burden countries compared with high-burden countries where high transmission rates and large

proportion of population under the age of 15 years mean children account for an estimated 10%–25% of the total TB case load

(Nelson and Wells, 2004; Marais et al., 2006a).

Although the effect of the HIV epidemic on the burden of childhood TB is less well characterized than for adults (Newton et al.,

2008), there is an HIV-related shift in TB disease burden to younger adults who are often parents of young children, putting

children at particularly high risk of exposure and subsequent disease (Graham et al., 2001). The relative importance of TB as a

preventable and treatable cause of childhood disease and death has been highlighted by the recent reductions in morbidity and

mortality from vaccine-preventable infections such as measles, pneumococcus, and Haemophilus influenzae type b (Graham et al.,

2014). Pediatric tuberculosis has since emerged as a leading cause of childhood morbidity and mortality. The 2012 World TB Day

was dedicated to childhood TB, while the Stop TB partnership made a commitment to work towards zero deaths from TB in

children worldwide (WHO, 2014a).

Reference Module in Biomedical Sciences http://dx.doi.org/10.1016/B978-0-12-801238-3.64157-0 1

2 Diagnosis of Childhood Tuberculosis

Pathogenesis of TB in Children

Children are most often exposed to infection from an adult with smear-positive pulmonary TB, with a high risk of infection,

progression to active disease or extra pulmonary dissemination and death following exposure, particularly in infants and children

less than two years of age (Guwatudde et al., 2003; Marais et al., 2004). Route of infection in children is similar to that in adults,

and usually results from inhalation of aerosolized M.tb in infected droplets, usually from adults with cavitary disease (Mendez-

Samperio, 2008). If the pathogen is successful in overcoming the initial barriers, it settles in the terminal alveoli where there is

proliferation of single or multiple foci (primary focus) with a spread via the draining lymphatics to the hilar lymph nodes (primary

complex). The infection can be contained at this stage and the primary complex might be discovered accidentally on routine chest

radiograph (Marais et al., 2004). The only indication of M.tb infection in such patients could be established is by serial tuberculin

skin test (TST) reactivity indicating delayed- type hypersensitization to M.tb proteins.

However, the infection could progress to primary disease in about 20%–40% of the children with hilar glandular enlargement

and involvement of the bronchial tree and/or the pleural cavity. The typical cavitating lung disease is usually only seen in older

children, primarily from early adolescent years onwards (Marais et al., 2005). There can also be haematogenous dissemination of

the organism especially in infants and young children with a spread throughout the body resulting in acute disseminated (i.e.,

miliary) TB, affecting the bones, brain, and abdomen. The mechanisms that determine the differential outcomes following

infection in children are not clearly understood but include age, nutritional status, underlying immunity, vaccination status,

genetic susceptibility, microbial virulence, and comorbidities (Newton et al., 2008). The risk of disease progression is highest in the

first 2 years of life when it is estimated to be 40%–50% while majority of children will develop disease within 2–12 months of the

initial infection; pulmonary TB accounts for 60%–80% of all cases in the absence of prior BCG vaccination or prophylactic

medication (Marais et al., 2004; Cruz and Starke, 2007).

Pediatric Immune Response to M.tb and Differences to Responses in Adults

Newton et al. suggested that the immaturity of the immune response could largely account for the high rate of disease progression

seen in young children following initial infection withM.tb (Newton et al., 2008). The initial immune response toM.tb is similar to

that seen in adults with an early initiation of innate immunity required to limit the growth of the organism through a cascade of

events leading to the recruitment of additional immune cells to the site of infection (Jones et al., 2011). The dendritic cells are the

major antigen presenting cells, which process the M.tb antigens and migrate to regional draining lymph nodes where they present

the processed antigens to naı̈ve CD4+ T-cells via surface MHC-class II molecules (Giacomini et al., 2001). The major components

involved in both the innate and adaptive immune responses to M.tb are as illustrated in Fig. 1.

However, a number of studies have reported an age-related functional impairment of both innate and adaptive immune

responses in children (Holt, 1995; Sepulveda et al., 1997; Filias et al., 2011; Gold et al., 2007; Upham et al., 2006; White et al.,

2002). Specifically, it has been reported that the alveolar macrophages in children show diminished phagocytosis, cell recruitment,

and microbial killing when compared to adults, which could promote delayed initiation of antigen specific T-cell responses and

disease progression (Holt, 1995; Sepulveda et al., 1997; Smith et al., 1997). Similarly, neonates and infants have fewer circulating

dendritic cells with a reduced ability to synthesize IL-12 and to present antigens to naive CD4+ T-cells (Upham et al., 2006; Smith

et al., 1997). Neonatal CD4+ T-cells also have a diminished capacity to express Th 1-type effector function partly due to

hypermethylation of the proximal promoter of the IFN-g gene resulting in restriction of IFN-g responses to variety of stimuli

(White et al., 2002; Kampmann et al., 2006). There is also presentation of antigens to naive CD8+ T-cells via the major

histocompatibility complex (MHC) class I molecules resulting in their activation and proliferation into effector CD8+ cytolytic

T lymphocytes by the less clearly understood phenomenon of cross presentation and/or cross priming (Schaible et al., 2003; van

der Wel et al., 2007; Winau et al., 2006). Further studies are needed to define the role and importance of CD8+ T-cells in immune

responses to M.tb in children and adults.

Diagnostic Challenges in Childhood TB

The challenges associated with the diagnosis of TB in children cannot be overemphasized. The clinical presentation of TB in

children mimics other common childhood diseases such as HIV, pneumonia, viral and bacterial blood infection, and malnutrition

(Edwards, 1987). The constitutional symptoms include failure to thrive, weight loss, and intermittent fever while involvement of

the airway can result in persistent unremitting cough or wheeze; however, all of these symptoms lack specificity (Perez-Velez and

Marais, 2012). Children produce smaller quantities of sputum when compared to adults, which is usually swallowed making it

difficult to obtain good quality sputum samples for pathogen detection tests (Edwards et al., 2007). Facilities and expertise for

sputum induction (with inhalation of nebulized hypertonic 3%–5% saline and subsequent aspiration or expectoration of mucus

from the lower respiratory tract) are mostly unavailable in resource-limited settings while gastric lavage requires hospitalization

with overnight fasting for up to three consecutive days in some cases.

The yield from sputum smear microscopy and M.tb culture is limited in childhood TB given the paucibacillary nature of TB

disease in children, and this constitutes one of the major impediments to accurate diagnosis (Perez-Velez and Marais, 2012). Chest

X-ray changes in pediatric TB cases are often nonspecific with wide intra- and inter-observer variations in interpretation. BCG

vaccination given at birth, endemicity, of nontuberculous mycobacteria (NTM), and altered immune response especially in very

Fig. 1 Mechanism of innate and adaptive immune responses to Mycobacterium tuberculosis (Jones et al., 2011). This figure illustrates the keycomponents of innate and adaptive immune mechanisms in the response to Mycobacterium tuberculosis (M.tb). Innate defense molecules in theairways facilitate the phagocytosis ofM.tb by macrophages and dendritic cells (antigen presenting cells, APCs) and Toll-like receptor (TLR) signaling.M.tb is processed within the APC and presented to CD4 cells in regional lymph nodes on major histocompatability complex (MHC) class II molecules. IL-12is secreted by APCs, which causes CD4 cells to proliferate and produce IFNg. IFNg, produced by CD4 cells, CD8 cells, NK cells, and gd cells activates theAPC to become microbicidal. Other molecules such as perforins and granzymes, produced by CD8 cells, NK cells, and gd cells, also facilitate destructionof M.tb bacilli. T regulatory (Treg) cells, Th17 cells, and B cells act to modulate the immune response to M.tb (Illustration © Hugh Gifford 2010).Reproduced with permission from Pediatric Respiratory Reviews.

Diagnosis of Childhood Tuberculosis 3

young children as a result of functional immaturity of immune cells, among other reasons, make TST of limited diagnostic value on

its own, although a positive TST does suggest recent infection in children and must trigger action. (Newton et al., 2008; Haimi-

Cohen et al., 2001). Although every effort must be made to seek a microbiological confirmation, the diagnosis of pediatric

tuberculosis is often presumptive, based on epidemiological and clinical evidence such as history of exposure to an adult TB case,

nonspecific clinical symptoms and signs, and results of investigations such as TST and Chest X-ray (Schaaf et al., 1995).

Clinical Diagnostic Approaches

The difficulty in microbiologically confirming the diagnosis of TB in children has led to the development of a number of

alternative, symptom-based diagnostic approaches that represent potentially simple, stepwise, rational, and logical tools that aid

health care workers in identifying children who are in need of TB treatment (Edwards et al., 2007). A diagnostic approach was

defined as any published systematic method for diagnosis of childhood TB and includes point scoring systems, diagnostic

classifications, and algorithms (Hesseling et al., 2002; Kabra et al., 2004). A “point scoring”system is a diagnostic approach in

which a numerical value is assigned to each characteristic in the system and examples include the Keith-Edwards and Kenneth Jones

point scoring systems (Edwards, 1987; Stegen et al., 1969). For “diagnostic classifications” the characteristics in the system are

stratified into categories such as suspect, probable, or confirmed TB and examples include the Ghidey and Habte approach that was

developed in Ethiopia (Ghidey and Habte, 1983), as well as a subsequent modification of this approach developed in Uganda

4 Diagnosis of Childhood Tuberculosis

(Migliori et al., 1992). In the “diagnostic algorithms,” a stepwise approach to TB diagnosis was advocated often in diagrammatic

form, such as the IMCI/WHO guidelines on management of the child with serious infection or severe malnutrition and the

Okeahialam diagnostic algorithm developed in Tanzania (WHO, 2000; Okeahialam, 1974).

However, a review of the diagnostic approaches reported that the majority of these scoring systems, algorithms, and classifi-

cations were developed without being validated against a gold standard of diagnosis, that is, bacteriological confirmation of

disease, while the few prospective studies conducted to validate these diagnostic approaches were all carried out in hospital based

settings mostly without the use of control groups (Hesseling et al., 2002). Hatherill et al. reported only slight agreement and high

variability in the number of TB cases diagnosed by nine structured approaches evaluated in a high-TB burden setting, and

concluded that diagnostic approaches need to be tailored to their particular epidemiological context so as to avoid systematic

errors in estimating disease burden or patient management in such setting (Hatherill et al., 2010). While there are general concerns

about the diagnostic value of the symptoms-based diagnostic approaches, the natural history of childhood TB demonstrates that

symptoms may have diagnostic value if appropriate risk stratification is applied, especially in immunocompetent children (Lopez

Avalos, 2012; Marais and Pai, 2007).

Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children

The development of novel diagnostic tools that could give a rapid and reliable diagnosis of TB in children and the optimization of

currently available diagnostics are major research priorities (WHO, 2011a). However, the lack of a perfect reference standard for TB

in children and of standardized case definitions constitute major challenges to the assessment of accuracy of new diagnostic tools,

comparison of findings between diagnostic studies or conduct of metaanalysis, whichmight provide evidence base to inform policy

recommendations (Oliwa et al., 2015; WHO, 2013; Graham et al., 2015). As a result, an updated standardized case definition for

the classification of intrathoracic TB in children when evaluating novel diagnostic tools was recently published by an international

panel of experts (Graham et al., 2015). This revised case definition attempts to present broad symptomatic entry criteria that are

compatible with TB. It could thus particularly address the challenge associated with the classification of TB in the majority of

children who will be diagnosed with TB disease, among whom there will be no bacteriological confirmation of disease.

Table 1 shows the revised case definition and classifications into “confirmed tuberculosis,” “unconfirmed tuberculosis,” and

“unlikely tuberculosis.” However, the consensus of the expert panel was that the revised case definition will support the diagnosis

of TB in symptomatic children with suspected intrathoracic TB, much like in the original consensus (Graham et al., 2012). It may

not be appropriate for studies that incorporate investigation for possible TB disease in children from active case finding, as in

household contact tracing, for example.

Table 1 Revised classification of intrathoracic tuberculosis case definitions for diagnostic evaluation studies in children

Case definition Refine criteriaa

Confirmedtuberculosis

• Bacteriological confirmation obtained

• Requires Mycobacterium tuberculosis to be confirmed (culture or Xpert MTB/RIF assay) from at least 1 respiratoryspecimen

Unconfirmedtuberculosis

• Bacteriological confirmation NOT obtained AND at least 2 of the following:

• Symptoms/signs suggestive of tuberculosis (as defined)

• Chest radiograph consistent with tuberculosis

• Close tuberculosis exposure or immunologic evidence of M.tb infection

• Positive response to tuberculosis treatment (requires documented positive clinical response on tuberculosis treatment—no time duration specified)– With M.tb infection

• Immunological evidence of M.tb infection (TST and/or IGRA positive)– Without M.tb infection

• No immunological evidence of M.tb infectionUnlikely tuberculosis • Bacteriological confirmation NOT obtained AND Criteria for “unconfirmed tuberculosis” NOT met.

– With M.tb infection

• Immunological evidence of M.tb infection (TST and/or IGRA positive)– Without M.tb infection

• No immunological evidence of M.tb infection

Abbreviations: M.tb, Mycobacterium tuberculosis; IGRA, interferon-g release assay; TST, tuberculin skin test.aAll children should have symptoms compatible with tuberculosis as determined by the treating clinician.

Adapted from Graham, S. M., Cuevas, L. E., Jean-Philippe, P., Browning, R., Casenghi, M., Detjen, A.K., et al. (2015). Clinical case definitions for classification of intrathoracic

tuberculosis in children: An update. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America 61Suppl. 3:S179-187.

Diagnosis of Childhood Tuberculosis 5

Diagnostic Tests for TB and Their Application in Childhood TB Diagnosis

Over the last decade, a number of new, rapid, and sensitive diagnostic tools for TB have been developed. These include tests based

on molecular methods such as the Xpert MTB/RIF ([“Xpert”] Cepheid, Sunnyvale, USA), the loop-mediated isothermal amplifi-

cation test (TB-LAMP, Eiken Chemical, Tokyo, Japan), and the line probe assays (LPAs). These tests could either replace or

complement the existing conventional tests used for diagnosis of TB and/or for detecting drug resistance including sputum

smear microscopy and solid or liquid culture methods. Although the WHO has endorsed several of these tools for diagnosis of

TB, we discuss their applicability to the diagnosis of TB in children.

Smear Microscopy and Cultures

Diagnosis of TB is traditionally confirmed by identification of AFB in stained smears by microscopy and/or the isolation of M.tb

from culture of clinical specimens. In resource-limited settings however, most cases of TB continue to be confirmed by sputum

smear microscopy. Young children are unable to expectorate and facilities and expertise for sputum induction are mostly

unavailable in high-TB burden countries. Even when sputum samples are available either by induction or spontaneous collection

method, TB in children is mostly smear negative because pediatric TB disease is paucibacillary in nature (Newton et al., 2008;

Hesseling et al., 2002; Marais et al., 2006b). In children, the sensitivity of smear microscopy is less than 15% even with advances in

performance of smear microscopy such as concentration of specimens by centrifugation and the use of the relatively newer

fluorescence microscopy with auramine-phenol staining (Nicol and Zar, 2011).

While culture of M.tb in biological samples including sputum is more sensitive than smear microscopy, both liquid and solid

culture facilities are mostly unavailable in the laboratories within the national public health systems in resource-limited settings

because of cost and the inherent technical demands. Where culture is available, the turnaround time for results of 2–3 weeks for

liquid cultures and even longer for solid cultures make it of limited use in guiding early therapeutic decision making. The culture

system is also prone to contamination. As a consequence, bacteriological confirmation of disease by culture of M.tb in children

seldom exceeds 30% even when using gastric aspirates, induced sputum, liquid culture media, and molecular diagnostic tools

(Nelson and Wells, 2004; Edwards et al., 2007; Nelson et al., 2004; Nicol et al., 2005). The yield of these methods increases with

increasing age of the child.

Xpert MTB/RIF

The Xpert is a diagnostic tool recommended by the WHO for the diagnosis of TB disease and multidrug-resistant (MDR) TB in both

adults and children, aimed at reducing the time to bacteriological confirmation and ability to detect MDR cases rapidly (WHO,

2014b). It is based on nucleic acid amplification and detection of M.tb DNA and mutations associated with rifampicin resistance

simultaneously. This is done through the amplification of the 81 base-pair core region of the RNA polymerase rpob gene of M.tb,

using real-time polymerase chain reaction with molecular beacons. Xpert is a closed system that integrates automated sample

processing, nucleic acid amplification, and detection of target sequences and exhibits high sensitivity and specificity for detecting

M.tb DNA in sputum samples (Fig. 2). Estimates of pooled sensitivity and specificity of Xpert in a systematic review and

Fig. 2 A four-module GeneXpert (“Xpert”) MTB/RIF system. The Xpert is a WHO endorsed rapid diagnostic device recommended for the diagnosis ofTB disease and multidrug-resistant (MDR) TB in both adults and children, aimed at reducing the time to bacteriological confirmation and ability to detectMDR cases rapidly. Picture courtesy of Professor Madhukar Pai, McGill University, Montreal, Canada.

6 Diagnosis of Childhood Tuberculosis

metaanalysis of 22 studies that recruited 8998 adult subjects with presumed TB disease are 89% (95% CrI 85%–92%) and 99%

(95% CrI 98%–99%) respectively (Steingart et al., 2014).

A separate metaanalysis of pediatric Xpert studies showed that compared with culture, the pooled sensitivities and specificities

of Xpert for TB detection were 62% (95% credible interval 51–73) and 98% (97–99), respectively, with use of expectorated or

induced sputum samples and 66% (51–81) and 98% (96–99), respectively, with use of samples from gastric lavage. Xpert

sensitivity was 36%–44% higher than the sensitivity for microscopy. Xpert’s pooled sensitivity and specificity to detect rifampicin

resistance was 86% (95% credible interval 53–98) and 98% (94–100), respectively.

Based on the metaanalysis of data from pediatric studies and the limitations of microbiological diagnosis of TB in children, the

Xpert was recommended in a policy statement in 2013 by the World Health Organisation (WHO) as the initial diagnostic tool for

children with suspected HIV-associated TB or MDR-TB (WHO, 2013). More recently, in 2017, WHO endorsed the use of Xpert

MTB/RIF Ultra cartridge, based on the findings from a large multicenter noninferiority diagnostic accuracy study in adults with

signs and symptoms of pulmonary TB (WHO, 2017a). The Ultra assay was designed to have a higher sensitivity, by the

incorporation of two different multicopy amplification targets (IS6110 and IS1081) as well as a relatively larger DNA reaction

chamber, when compared to Xpert MTB/Rif. The study reported that Ultra had a 5% higher sensitivity relative to Xpert MTB/Rif

(95% CI: +2.7, +7.8) but 3.2% lower specificity (95% CI: �2.1, �4.7), with sensitivity increases being highest among smear-

negative culture-positive patients and among HIV-infected patients (FIND, 2017). Data on the performance of Xpert Ultra cartridge

in children is not yet available.

While Xpert is now the front-line test for TB in adults and children, access to this technology continues to be a problem in many

settings, and the technology is still expensive for low-income settings. While the existing GeneXpert platform is not easy to

decentralize, work is ongoing to develop more robust, molecular solutions that could be decentralized. Furthermore, for children,

the requirement for a sputum sample poses additional challenges, since sputum induction or gastric aspiration is not easy to

implement in many settings. Thus, there is a need for nonsputum based TB tests and target product profiles for such tests have been

published (Denkinger et al., 2015).

Other Molecular Methods (TB-LAMP, LPAs)

The TB-LAMP in a commercial molecular assay that requires minimal laboratory infrastructure and biosafety requirement, has been

evaluated as a replacement to sputum smear microscopy in resource-limited settings. It is a manual assay that provides an

isothermal amplification of M.tb DNA from sputum samples and results could be available in less than one hour (Gray et al.,

2016). Thus, it is potentially applicable as a rapid point of care test at peripheral health care facilities where microscopy is often

performed. However, studies to evaluate the performance of TB-LAMP either as a replacement for smear microscopy or compar-

ision to Xpert MTB/RIF, have all been carried out in adult populations.

In a metaanalysis of 7 studies with 1810 adult patients suspected of having TB, the pooled sensitivity of TB-LAMP was 15%

higher than smear microscopy (78% [95%CI: 71%–83%] vs. 63% [95%CI: 56%–69%]), while a separate metaanalysis of 4 studies

with 1075 patients reported that the pooled sensitivity of TB-LAMP (78% [95% CI: 66.6%–86.4%]) is lower than the pooled

sensitivity of Xpert MTB/Rif (89% [95% CI: 85%–92%]), but the specificity of all three tests is similar (WHO, 2016b). Based on

these metaanalyses from the adult studies, the WHO gave a conditional policy recommendation that TB-LAMP may be used as a

replacement test for sputum smear microscopy for the diagnosis of pulmonary TB in adults and extrapolated the recommendation

to the use of TB-LAMP assay in children by generalization of the data in adults (WHO, 2016b).

LPAs is a high throughput genotypic technology that provides opportunity for rapid detection, programmatic management, and

surveillance of drug-resistant TB. It has been endorsed by the WHO for the detection of resistance to both first-line (i.e., INH and

rifampicin), and second-line anti-TB drugs (i.e., fluoroquinolones and second-line injectable drugs) (WHO, 2016c). However,

LPAs require smear-positive samples or culture isolates. This makes it challenging to apply it in pediatric populations.

Urine LAM Detection Assay

The lateral flow urine lipoarabinomannan (LAM) assay is based on the detection of LAM, which is a key lipopolysaccharide present

in mycobacterial cell wall, in urine samples. This urine-based test would have been advantageous particularly in children given that

it is a nonsputum based test that uses urine, which is a biological sample relatively easy to collect. However, several studies have

found that the urine LAM assay has a low sensitivity for diagnosis of TB, except in HIV-infected patients with advanced disease who

have very low CD4 T-cell counts (Hanifa et al., 2016; Shah et al., 2016). Accordingly, WHO strongly recommended the use of urine

LAM assay for diagnosis of TB only in HIV-infected persons with low CD4 counts or who are seriously ill (WHO, 2015a).

Host Response Tests: Tuberculin Skin Test or Interferon-gamma Release Assay

The WHO guidelines on latent TB testing endorse the use of both TST and IGRA as tests for latent TB infection (LTBI) (WHO,

2015b). For active TB, neither test is optimal, but can be helpful as one of several tests in an algorithm or case definition.

Diagnosis of Childhood Tuberculosis 7

Tuberculin skin test (TST)The TST is the most widely used test based on host response rather than detection of causative organism and can detect evidence of

prior exposure and sensitization to M.tb. It is based on detection of delayed-type hypersensitivity reaction to intradermal injection

of purified protein derivative (PPD), which is a heterogeneous mixture of antigens present in M.tb, BCG-strain of M.bovis, and

several NTMs (Lalvani and Millington, 2007). The TST can establish if the individual has previously been sensitized by mycobac-

teria, as it measures the immune response, but it cannot confirm the presence or absence of M.tb. As such it cannot distinguish

between TB disease and LTBI. Its utility is also hampered by technical and logistical problems including potential for false-positive

and false-negative results (Lopez Avalos, 2012). False-positive reactions could be attributed to prior BCG vaccination or asymp-

tomatic NTM infection while false-negative reactions could occur in young children aged less than 2 years because of functional

immaturity in cell-mediated immune responses, and in immunosuppressive illnesses, malnutrition, or recent measles infection or

simply because the test was done too early following exposure (Dogra et al., 2007). It is also known that around 10% of any given

population have immune anergy and will not respond to the intradermally applied mycobacterial or control antigens.

Interferon (IFN)-g release assays (IGRAs)IGRAs are an alternative test of the host immune response as a measure of prior exposure and sensitization to M.tb. IGRAs are

known to be at least as sensitive—but more specific—than TST for the detection of M.tb infection (Pai et al., 2004), and are based

on measurement of IFN-g production by antigen-specific T-cells following in vitro stimulation of whole blood or peripheral blood

mononuclear cells by M.tb-specific antigens such as ESAT-6, CFP-10, and/or TB 7.7 (Walzl et al., 2011). These antigens are known

to be highly immunogenic and much more specific forM.tb than PPD because they are not present in the BCG vaccine strain ofM.

bovis or most NTM (Dogra et al., 2007). There are currently two commercial IGRA kits that are available; these include the

Quantiferon-TB Gold In-Tube (QFT-GIT; Cellestis, Australia) and the T_SPOT.TB assay (Oxford Immunotec, UK).

Both TST and IGRAs detect evidence of immunological sensitization to M.tb, but neither of the two is able to distinguish

between active TB and LTBI or directly measure the presence of mycobacteria (Pollock et al., 2013; Kampmann et al., 2009).

Neither TST nor IGRAs are able to adequately resolve the “spectrum of TB” as depicted in Fig. 3, where TB can be viewed as a

dynamic continuum from M.tb infection to active TB disease (Pai et al., 2016). Therefore, while IGRAs are designed to be more

specific than TST for diagnosis of LTBI in BCG vaccinated populations and/or in those infected with NTM, neither TST nor IGRA has

been demonstrated to be superior in the diagnosis of LTBI in children. IGRAs do not have sufficient sensitivity or specificity to

confirm or exclude the diagnosis of active TB. Both TST and IGRAs are known to have low predictive value (for progression from

latent to active TB) and their availability in resource-limited settings remains limited (Pollock et al., 2013). In this context, there

have been some promising developments in trying to predict TB using novel biosignatures (Zak et al., 2016), and use of IGRA

conversions to identify those that are likely to progress in the near future that is, detect incipient TB disease (Andrews et al., 2017).

Diagnostic Algorithm

The current preferred algorithm for universal patient access to rapid testing to detect MTB and rifampicin resistance is shown in

Fig. 4. In this algorithm, Xpert MTB/RIF test is used as the initial diagnostic test for all adults and children (regardless of HIV status)

with signs or symptoms of pulmonary TB or with a chest X-ray with abnormalities suggestive of TB.

Future Prospects

Diagnostic biomarkersThe International Roadmap for TB Research published in 2011 by the WHO highlighted the investigation and development of new

diagnostics suitable for children as a research priority (WHO, 2011a). Being able to accurately distinguish between children with

latent TB infection, who have respiratory symptoms due to another pathogen, and children with active TB disease represent the

most pressing issue in the management of children presenting with symptoms consistent with but not specific for TB. Research into

host TB biomarkers has gained more prominence due to the lack of suitable tests based on detection of the M.tb or its products in

clinical samples (Walzl et al., 2011). A recently published blueprint for pediatric TB biomarkers listed the characteristics of an

“ideal” biomarker for TB in children to include: (i) measurable in small volumes of readily obtainable samples such as blood,

urine, stool, saliva, etc.; (ii) identify M.tb with high sensitivity and specificity regardless of age, nutritional status, or HIV status;

(iii) distinguish children with active TB disease from latently infected children with other respiratory infections; and (iv) suitable

for incorporation into a diagnostic platform that would provide rapid results at or near the point of care (Nicol et al., 2015).

Studies investigating TB biomarkers involve immunological approaches including the use of antigen stimulated peripheral

blood as well as the relatively more advanced “omics” approaches including transcriptomics, metabolomics, lipidomics, and proteomic

markers. Peripheral blood is currently the most widely used source of biomarkers as genes, transcripts, proteins, and metabolites

can all be measured in blood, although biomarkers from urine, sputum, saliva, and breath have all been shown to have clinical

diagnostic potential (Parida and Kaufmann, 2010). Immunological markers are based on antigen-specific T-cell responses, notably

the releases of cytokines that are currently considered relevant for protection against M.tb such as IFN-g, IL-2, and TNF-a as well as

the release of cytolytic molecules such as granulysin, granzyme, and perforin (Kaufmann and Parida, 2008). Several studies have

reported that different combinations of TNF-a, IL-12p40, IL-17, sCD40L, EGF, VEGF, IL-1a, IP-10, MCP-1, and IL-15 could

Fig. 3 The spectrum of TB: from Mycobacterium tuberculosis infection to active (pulmonary) TB disease (Pai et al., 2016). Although tuberculosis(TB) disease can be viewed as a dynamic continuum from Mycobacterium tuberculosis infection to active infectious disease, patients are categorized ashaving either latent TB infection (LTBI) or active TB disease for simplicity in clinical and public health settings. Individuals can advance or reversepositions, depending on changes in host immunity and comorbidities. Exposure to M. tuberculosis can result in the elimination of the pathogen, eitherbecause of innate immune responses or because of acquired T cell immunity. Individuals who have eliminated the infection via innate immune responsesor acquired immune response without T cell priming or memory (denoted by �) can have negative tuberculin skin test (TST) or interferon-g release assay(IGRA) results. Some individuals will eliminate the pathogen, but retain a strong memory T cell response and will be positive on the TST or the IGRA.These individuals will not benefit from LTBI treatment. If the pathogen is not eliminated, bacteria persist in a quiescent or latent state that can be detectedas positive TST or IGRA results; these tests elicit T cell responses against M. tuberculosis antigens. These patients would benefit by receiving one of therecommended LTBI preventive therapy regimens (mostly 6–9 months of isoniazid). Patients with subclinical TB might not report symptoms, but will beculture-positive (but generally smear-negative because of the low bacillary load). Patients with active TB disease experience symptoms such as cough,fever, and weight loss, and the diagnosis can usually be confirmed with sputum smear, culture, and molecular tests. Patients with active TB diseasemight sometimes be negative on the TST or the IGRA because of anergy that is induced by the disease itself or immune suppression caused by comorbidconditions, such as HIV infection or malnutrition. Individuals with subclinical or active TB disease should receive one of the recommended treatmentregimens for active TB disease, which consist of an intensive phase with four drugs, followed by a longer continuation phase with two drugs.Reproduced with permission from Nature Reviews Disease Primers.

8 Diagnosis of Childhood Tuberculosis

differentiate between TB disease and LTBI in adults in TB endemic settings (Sutherland et al., 2010; Chegou et al., 2009; Harari

et al., 2011; Frahm et al., 2011). Given the report that distinct cytokine expression profiles of CD4+ T-cells are associated with

bacterial loads (Caccamo et al., 2010), different cytokine expression profiles could be expected in childhood TB cases which are

paucibacillary when compared to adult TB and represent primary infection rather than reactivation disease. The presence of

antigen-specific T-cells and their respective cytokines can therefore be expected to be lower.

One pediatric study reported that childhood TB was associated with elevated plasma levels of biomarkers at homeostasis

including TGF-b, IL-21, and IL-23 when compared to health controls (Pavan Kumar et al., 2013). Dhanasekaran et al. reported that

the combination of IL-2 and IL-8 in QFT-supernatants of children could differentiate between TB disease and LTBI, while Armand

et al. did not identify any discriminant biomarker between the same groups in another study that used similar methods

(Dhanasekaran et al., 2013; Armand et al., 2014). Tebruegge and colleagues reported that aM.tb-specific biosignature, comprising

the combination of TNF-a, IL-1ra, and IL-10, showed the best discriminatory ability between active TB and LTBI pediatric cases

(Tebruegge et al., 2015). In contrast, Chegou et al. reported that unstimulated levels of IL-1ra and IP-10 and antigen-specific levels

of VEGF in QFT supernatants may be useful for diagnosing TB disease and differentiating between TB disease and M.tb infection

respectively in children investigated in a high HIV/TB prevalence setting (Chegou et al., 2013).

Although serological tests have not been found useful in diagnosis of TB and discouraged by the WHO (WHO, 2011b), Thomas

et al. reported a high diagnostic accuracy for childhood TB of a novel assay called antibodies in lymphocyte supernatant, which was

based on measurement of IgG production by activated plasma cells in BCG-stimulated cultures of PBMCs (Thomas et al., 2011).

Studies using the transcriptomic approach to TB biomarker discovery in children are limited but currently emerging. A TB-specific

whole blood 51-transcript signature with reasonable diagnostic accuracy in distinguishing TB from other diseases with similar

clinical features was identified in HIV-infected and -uninfected Africa children (Anderson et al., 2014), while Verhagen et al.

Fig. 4 Preferred algorithm for universal patient access to rapid testing to detect MTB and rifampicin resistance (reproduced with permission from GLI)(WHO, 2017b). (1). Persons to be evaluated for TB include adults and children with signs or symptoms suggestive of TB or with a chest X-ray withabnormalities suggestive of TB. This algorithm may also be followed for the detection of MTB using CSF, lymph node, and other tissue specimen frompersons being evaluated for extra pulmonary TB. For persons being evaluated for TB who are HIV positive and have CD4 counts �100 cells/mL or areseriously ill, see Algorithm 4. (2). Programs may consider collecting two specimens upfront. The first specimen should be promptly tested using theXpert MTB/RIF test. The second specimen may be used for the additional testing described in this algorithm. For persons being evaluated for pulmonaryTB, sputum is the preferred specimen. (3). Patients at high risk for multidrug-resistant TB (MDR-TB) include previously treated patients including thosewho had been lost to follow-up, relapsed, and failed a treatment regimen; nonconverters (smear-positive at end of intensive phase); MDR-TB contacts;and any other MDR-TB risk groups identified in the country. (4). Patients should be initiated on a first-line regimen according to national guidelines.A sample may be sent for molecular or phenotypic DST for isoniazid if the patient has been previously treated with isoniazid or if there is a highprevalence of isoniazid resistance not associated with rifampicin resistance (i.e., isoniazid mono- or poly-resistance) in this setting or for DST forrifampicin if rifampicin resistance is still suspected. (5). Repeat Xpert MTB/RIF test at the same testing site with a fresh specimen. Interpret the result ofthe repeat test as shown in this algorithm. Use the result of the second Xpert MTB/RIF test for clinical decisions. (6). Further investigations for TB mayinclude chest X-ray, additional clinical assessments, clinical response following treatment with broad-spectrum antimicrobial agents, repeat XpertMTB/RIF testing, or culture. (7). Repeat Xpert MTB/RIF test at the same testing site with a fresh specimen. Use the rifampicin result of the second XpertMTB/RIF test in this algorithm for a decision(s) regarding choice of regimen (first line or second line regimen).

Table 2 Potential biomarker candidates in childhood TB infection and disease

Author, yearStudydesign Methods used Groups Discriminant biomarkers

Thomas et al.(2011)

Case—control

Antibody secreting cells in BCG-stimulatedPBMCs culture supernatants

PTB vs. OD Antibodies in lymphocyte supernatants (ALS)

Verhagen et al.(2013)

Case—control

Microarray analysis of whole blood PTB vs.LTBI

9-gene transcript signature

PTB vs.LTBI vsHC

42-gene transcript signature

Dhanasekaranet al. (2013)

Prospectivestudy

dcRT-MLPA in whole blood PTB vs.LTBI

RAB33A

PTB vs. HC RAB33a, IP-10, SEC14L, FOXP3 & TNFRSF1ALTBI vs. HC IP-10, CD4, SEC14L1, IL4, RAB33A, TGFBR2, BCL2,

TGFB1, TNFRSF1B, RAB13, CD19Multiplex assay in QFT supernatants PTB vs.

LTBIIL-2 & IL-8

PTB vs. HC IL-2, IL-5, IL-8, IL-10LTBI vs. HC IL-2 & IL-13

Chegou et al.(2013)

Case—contact

Multiplex assay in QFT supernatants PTB vs.LTBI

IL-1ra, IP-10 & VEGF

PTB vs. HC IFN-a2, IL-1Ra, sCD40L & VEGFPavan Kumaret al. (2013)

Case—control

Multiplex assay in Plasma PTB vs.EPTB

LPS, LBP and TGF-b

PTB vs. HC MMP/TIMPs, CRP, a2M, Haptoglobin & TGF-bAnderson et al.(2014)

Prospectivestudy

Microarray analysis of whole blood RNAexpression

PTB vs. OD 51-gene transcripts signaturePTB vs.LTBI

42-gene transcripts signature

Armand et al.(2014)

Case—control

Multiplex assay in QFT supernatants LTBI vs. HC IP-10, IL-2, IL-5 & IL-13PTB vs.LTBI

No discriminant marker identified

Tebruegge et al.(2015)

Prospectivestudy

Multiplex assay WBA supernatants PTB vs.LTBI

TNF-a, IL-1ra & IL-10

Zhou et al.(2016)

Case—control

miRNA microarray analysis PTB vs. HC miR-1, miR-155, miR-31, miR-146a, miR-10a,miR-125b, miR-150 & miR-29

dcRT-MLPA : dual-color reverse-transcriptase multiple ligation-dependent probe amplification; QFT : Quantiferon TB gold-intube; RNA: Ribonucleic acid; miRNA: micro ribonucleic

acid; PTB: Pulmonary TB; LTBI: Latent TB infection; EPTB: Extra pulmonary TB; HC: Healthy controls; OD: other diseases; NTM: Nontuberculous mycobacteria.

10 Diagnosis of Childhood Tuberculosis

reported a whole blood 42-transcript signature for TB among Warao Amerindian children in the United States (Verhagen et al.,

2013). Recently, Zhou and colleagues applying a microarray assay of micro RNA (miRNA) reported a combination of eight miRNA

that may be a novel early diagnostic biomarker for childhood TB (Zhou et al., 2016).

Table 2 summarizes studies that investigated potential biomarker candidates in childhood TB infection and disease states. These

reports suggest that available data in children are limited and that there is a marked heterogeneity in the methodology of the studies

often with overlapping or conflicting results. Research into TB biomarkers using the metabolomic and/or proteomic approaches is

still relatively new. To date, proteomic and metabolomic studies that have investigated novel TB biomarker were carried out mostly

in adult populations and rarely involved children. In general, the cost effectiveness and real world applicability of high throughput

“omics” assays in high TB burden countries is still very doubtful, and major translational work will be required to develop simple

and affordable assays that can be used for TB control efforts in resource-limited settings (Togun and Pai, 2017).

Conclusion

The recent WHO End TB Strategy sets ambitious targets for TB control including the achievement of a 90% reduction in TB

incidence rate by the year 2035 compared to the current levels (WHO, 2016d). This strategy provides added opportunity for global

TB control efforts to address childhood TB, which is now increasingly being recognized as an important cause of childhood

morbidity and mortality caused by a preventable and treatable infectious disease. Increased funding and policy support should be

made available for concerted research efforts to improve the diagnosis and treatment of TB infection and disease in this particularly

vulnerable group. This will ultimately contribute towards the global effort to eradicated TB disease, as many cases of adult TB are

likely to arise from undiscovered and untreated primary infection in childhood.

Diagnosis of Childhood Tuberculosis 11

Acknowledgments

TT is a recipient of a Steinberg Postdoctoral Fellowship in Global Health fromMcGill University. His research is also supported by a

Grand Challenges Canada (GCC) grant on diagnosis of childhood TB. BK is a recipient of a UK Medical Research Council (MRC)

Childhood TB Research Programme grant no MR/K01194/1. MP is a recipient of a Canada Research award and a grant from GCC

on childhood TB diagnosis.

Conflicts of interest : TOT and BK have no conflicts to disclose. MP is a consultant to the Bill and Melinda Gates Foundation.

References

Ahmed T, Sobhan F, and Ahmed AMS (2008) Childhood Tuberculosis: A review of Epidemiology Diagnosis and Management. Infectious Diseases Journal of Pakistan 17: 52–60.Anderson ST, Kaforou M, Brent AJ, Wright VJ, Banwell CM, Chagaluka G, et al. (2014) Diagnosis of childhood tuberculosis and host RNA expression in Africa. The New England

Journal of Medicine 370(18): 1712–1723.Andrews JR, Nemes E, Tameris M, Landry BS, Mahomed H, McClain JB, et al. (2017) Serial QuantiFERON testing and tuberculosis disease risk among young children: An

observational cohort study. The Lancet Respiratory Medicine 5(4): 282–290.Armand M, Chhor V, de Lauzanne A, Guerin-El Khourouj V, Pedron B, Jeljeli M, et al. (2014) Cytokine responses to quantiferon peptides in pediatric tuberculosis: A pilot study. The

Journal of Infection 68(1): 62–70.Caccamo N, Guggino G, Joosten SA, Gelsomino G, Di Carlo P, Titone L, et al. (2010) Multifunctional CD4(+) T cells correlate with active Mycobacterium tuberculosis infection.

European Journal of Immunology 40(8): 2211–2220.Chegou NN, Black GF, Kidd M, van Helden PD, and Walzl G (2009) Host markers in QuantiFERON supernatants differentiate active TB from latent TB infection: Preliminary report. BMC

Pulmonary Medicine 9: 21.Chegou NN, Detjen AK, Thiart L, Walters E, Mandalakas AM, Hesseling AC, et al. (2013) Utility of host markers detected in Quantiferon supernatants for the diagnosis of tuberculosis in

children in a high-burden setting. PLoS ONE 8(5) e64226.Corbett EL, Watt CJ, Walker N, Maher D, Williams BG, Raviglione MC, et al. (2003) The growing burden of tuberculosis: global trends and interactions with the HIV epidemic. Archives

of Internal Medicine 163(9): 1009–1021.Cruz AT and Starke JR (2007) Clinical manifestations of tuberculosis in children. Paediatric Respiratory Reviews 8(2): 107–117.Denkinger CM, Kik SV, Cirillo DM, Casenghi M, Shinnick T, Weyer K, et al. (2015) Defining the needs for next generation assays for tuberculosis. The Journal of Infectious Diseases

211(suppl 2): S29–S38.Dhanasekaran S, Jenum S, Stavrum R, Ritz C, Faurholt-Jepsen D, Kenneth J, et al. (2013) Identification of biomarkers for Mycobacterium tuberculosis infection and disease in

BCG-vaccinated young children in Southern India. Genes and Immunity 14(6): 356–364.Dodd PJ, Gardiner E, Coghlan R, and Seddon JA (2014) Burden of childhood tuberculosis in 22 high-burden countries: A mathematical modelling study. The Lancet Global Health 2

(8): e453–e459.Dogra S, Narang P, Mendiratta DK, Chaturvedi P, Reingold AL, Colford JM Jr, et al. (2007) Comparison of a whole blood interferon-gamma assay with tuberculin skin testing for the

detection of tuberculosis infection in hospitalized children in rural India. The Journal of Infection 54(3): 267–276.Edwards K (1987) The diagnosis of childhood tuberculosis. Papua and New Guinea Medical Journal 30(2): 169–178.Edwards DJ, Kitetele F, and Van Rie A (2007) Agreement between clinical scoring systems used for the diagnosis of pediatric tuberculosis in the HIV era. The International Journal of

Tuberculosis and Lung Disease 11(3): 263–269.Filias A, Theodorou GL, Mouzopoulou S, Varvarigou AA, Mantagos S, and Karakantza M (2011) Phagocytic ability of neutrophils and monocytes in neonates. BMC Pediatrics 11: 29.FIND. Report for WHO: A multicentre non-inferiority diagnostic accuracy study of the Ultra assay compared to the Xpert MTB/RIF assay. Geneva, Switzerland; Foundation for Innovative

New Diagnostics 2017. Available from: https://www.finddx.org/wp-content/uploads/2017/03/Ultra-WHO-report_24MAR2017_FINAL.pdf [Accessed 22 April 2017].Frahm M, Goswami ND, Owzar K, Hecker E, Mosher A, Cadogan E, et al. (2011) Discriminating between latent and active tuberculosis with multiple biomarker responses. Tuberculosis

(Edinburgh, Scotland) 91(3): 250–256.Ghidey Y and Habte D (1983) Tuberculosis in childhood: An analysis of 412 cases. Ethiopian Medical Journal 21(3): 161–167.Giacomini E, Iona E, Ferroni L, Miettinen M, Fattorini L, Orefici G, et al. (2001) Infection of human macrophages and dendritic cells with Mycobacterium tuberculosis induces a

differential cytokine gene expression that modulates T cell response. Journal of Immunology 166(12): 7033–7041.Gold MC, Robinson TL, Cook MS, Byrd LK, Ehlinger HD, Lewinsohn DM, et al. (2007) Human neonatal dendritic cells are competent in MHC class I antigen processing and

presentation. PLoS ONE 2(9) e957.Graham SM, Coulter JB, and Gilks CF (2001) Pulmonary disease in HIV-infected African children. The International Journal of Tuberculosis and Lung Disease 5(1): 12–23.Graham SM, Ahmed T, Amanullah F, Browning R, Cardenas V, Casenghi M, et al. (2012) Evaluation of tuberculosis diagnostics in children: 1. Proposed clinical case definitions for

classification of intrathoracic tuberculosis disease. Consensus from an expert panel. The Journal of Infectious Diseases 205(Suppl 2): S199–S208.Graham SM, Sismanidis C, Menzies HJ, Marais BJ, Detjen AK, and Black RE (2014) Importance of tuberculosis control to address child survival. Lancet 383(9928): 1605–1607.Graham SM, Cuevas LE, Jean-Philippe P, Browning R, Casenghi M, Detjen AK, et al. (2015) Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children: An

Update. Clinical Infectious Diseases 61(Suppl 3): S179–S187.Gray CM, Katamba A, Narang P, Giraldo J, Zamudio C, Joloba M, et al. (2016) Feasibility and operational performance of tuberculosis detection by loop-mediated isothermal

amplification platform in decentralized settings: Results from a multicenter study. Journal of Clinical Microbiology 54(8): 1984–1991.Guwatudde D, Nakakeeto M, Jones-Lopez EC, Maganda A, Chiunda A, Mugerwa RD, et al. (2003) Tuberculosis in household contacts of infectious cases in Kampala, Uganda.

American Journal of Epidemiology 158(9): 887–898.Haimi-Cohen Y, Zeharia A, Mimouni M, Soukhman M, and Amir J (2001) Skin indurations in response to tuberculin testing in patients with nontuberculous mycobacterial

lymphadenitis. Clinical Infectious Diseases 33(10): 1786–1788.Hanifa Y, Fielding KL, Chihota VN, Adonis L, Charalambous S, Karstaedt A, et al. (2016) Diagnostic accuracy of lateral flow urine LAM assay for TB screening of adults with advanced

immunosuppression attending routine HIV care in South Africa. PLoS ONE 11(6) e0156866.Harari A, Rozot V, Bellutti Enders F, Perreau M, Stalder JM, Nicod LP, et al. (2011) Dominant TNF-alpha+Mycobacterium tuberculosis-specific CD4+ T cell responses discriminate

between latent infection and active disease. Nature Medicine 17(3): 372–376.Hatherill M, Hanslo M, Hawkridge T, Little F, Workman L, Mahomed H, et al. (2010) Structured approaches for the screening and diagnosis of childhood tuberculosis in a high

prevalence region of South Africa. Bulletin of the World Health Organization 88(4): 312–320.Hesseling AC, Schaaf HS, Gie RP, Starke JR, and Beyers N (2002) A critical review of diagnostic approaches used in the diagnosis of childhood tuberculosis. The International Journal

of Tuberculosis and Lung Disease 6(12): 1038–1045.Holt PG (1995) Postnatal maturation of immune competence during infancy and childhood. Pediatric Allergy and Immunology 6(2): 59–70.Jones C, Whittaker E, Bamford A, and Kampmann B (2011) Immunology and pathogenesis of childhood TB. Paediatric Respiratory Reviews 12(1): 3–8.

12 Diagnosis of Childhood Tuberculosis

Kabra SK, Lodha R, and Seth V (2004) Some current concepts on childhood tuberculosis. The Indian Journal of Medical Research 120(4): 387–397.Kampmann B, Tena-Coki G, and Anderson S (2006) Blood tests for diagnosis of tuberculosis. Lancet 368(9532): 282. author reply -3.Kampmann B, Whittaker E, Williams A, Walters S, Gordon A, Martinez-Alier N, et al. (2009) Interferon-gamma release assays do not identify more children with active tuberculosis than

the tuberculin skin test. The European Respiratory Journal 33(6): 1374–1382.Kaufmann SH and Parida SK (2008) Tuberculosis in Africa: Learning from pathogenesis for biomarker identification. Cell Host & Microbe 4(3): 219–228.Lalvani A and Millington KA (2007) T cell-based diagnosis of childhood tuberculosis infection. Current Opinion in Infectious Diseases 20(3): 264–271.Lopez Avalos GG (2012) Prado Montes de Oca E Classic and new diagnostic approaches to childhood tuberculosis. Journal of Tropical Medicine 2012: 818219.Marais BJ and Pai M (2007) Recent advances in the diagnosis of childhood tuberculosis. Archives of Disease in Childhood 92(5): 446–452.Marais BJ, Gie RP, Schaaf HS, Hesseling AC, Obihara CC, Nelson LJ, et al. (2004) The clinical epidemiology of childhood pulmonary tuberculosis: A critical review of literature from

the pre-chemotherapy era. The International Journal of Tuberculosis and Lung Disease 8(3): 278–285.Marais BJ, Gie RP, Hesseling AH, and Beyers N (2005) Adult-type pulmonary tuberculosis in children 10-14 years of age. The Pediatric Infectious Disease Journal 24(8): 743–744.Marais BJ, Hesseling AC, Gie RP, Schaaf HS, and Beyers N (2006a) The burden of childhood tuberculosis and the accuracy of community-based surveillance data. The International

Journal of Tuberculosis and Lung Disease 10(3): 259–263.Marais BJ, Hesseling AC, Gie RP, Schaaf HS, Enarson DA, and Beyers N (2006b) The bacteriologic yield in children with intrathoracic tuberculosis. Clinical Infectious Diseases 42(8):

e69–e71.Mendez-Samperio P (2008) Role of antimicrobial peptides in host defense against mycobacterial infections. Peptides 29(10): 1836–1841.Migliori GB, Borghesi A, Rossanigo P, Adriko C, Neri M, Santini S, et al. (1992) Proposal of an improved score method for the diagnosis of pulmonary tuberculosis in childhood in

developing countries. Tubercle and Lung Disease 73(3): 145–149.Nelson LJ and Wells CD (2004) Global epidemiology of childhood tuberculosis. The International Journal of Tuberculosis and Lung Disease 8(5): 636–647.Nelson LJ, Schneider E, Wells CD, and Moore M (2004) Epidemiology of childhood tuberculosis in the United States, 1993-2001: The need for continued vigilance. Pediatrics 114(2):

333–341.Newton SM, Brent AJ, Anderson S, Whittaker E, and Kampmann B (2008) Paediatric tuberculosis. The Lancet Infectious Diseases 8(8): 498–510.Nicol MP and Zar HJ (2011) New specimens and laboratory diagnostics for childhood pulmonary TB: Progress and prospects. Paediatric Respiratory Reviews 12(1): 16–21.Nicol MP, Pienaar D, Wood K, Eley B, Wilkinson RJ, Henderson H, et al. (2005) Enzyme-linked immunospot assay responses to early secretory antigenic target 6, culture filtrate

protein 10, and purified protein derivative among children with tuberculosis: Implications for diagnosis and monitoring of therapy. Clinical Infectious Diseases 40(9): 1301–1308.Nicol MP, Gnanashanmugam D, Browning R, Click ES, Cuevas LE, Detjen A, et al. (2015) A blueprint to address research gaps in the development of biomarkers for pediatric

tuberculosis. Clinical Infectious Diseases 61(Suppl 3): S164–S172.Okeahialam TC (1974) Diagnostic criteria of tuberculosis in malnourished children. East African Medical Journal 51(1): 79–89.Oliwa JN, Karumbi JM, Marais BJ, Madhi SA, and Graham SM (2015) Tuberculosis as a cause or comorbidity of childhood pneumonia in tuberculosis-endemic areas: A systematic

review. The Lancet Respiratory Medicine 3(3): 235–243.Pai M, Riley LW, and Colford JM Jr (2004) Interferon-gamma assays in the immunodiagnosis of tuberculosis: A systematic review. The Lancet Infectious Diseases 4(12): 761–776.Pai M, Behr MA, Dowdy D, Dheda K, Divangahi M, Boehme CC, et al. (2016) Tuberculosis. Nature Reviews Disease Primers 2: 16076.Parida SK and Kaufmann SH (2010) The quest for biomarkers in tuberculosis. Drug Discovery Today 15(3–4): 148–157.Pavan Kumar N, Anuradha R, Andrade BB, Suresh N, Ganesh R, Shankar J, et al. (2013) Circulating biomarkers of pulmonary and extrapulmonary tuberculosis in children. Clinical and

Vaccine Immunology 20(5): 704–711.Perez-Velez CM and Marais BJ (2012) Tuberculosis in children. The New England Journal of Medicine 367(4): 348–361.Pollock L, Basu Roy R, and Kampmann B (2013) How to use: Interferon gamma release assays for tuberculosis. Archives of Disease in Childhood. Education and Practice Edition 98

(3): 99–105.Schaaf HS, Beyers N, Gie RP, Nel ED, Smuts NA, Scott FE, et al. (1995) Respiratory tuberculosis in childhood: The diagnostic value of clinical features and special investigations. The

Pediatric Infectious Disease Journal 14(3): 189–194.Schaible UE, Winau F, Sieling PA, Fischer K, Collins HL, Hagens K, et al. (2003) Apoptosis facilitates antigen presentation to T lymphocytes through MHC-I and CD1 in tuberculosis.

Nature Medicine 9(8): 1039–1046.Sepulveda RL, Arredondo S, Rodriguez E, Gonzalez B, Leiva LE, and Sorensen RU (1997) Effect of human newborn BCG immunization on monocyte viability and function at 3 months

of age. The International Journal of Tuberculosis and Lung Disease 1(2): 122–127.Shah M, Hanrahan C, Wang ZY, Dendukuri N, Lawn SD, Denkinger CM, et al. (2016) Lateral flow urine lipoarabinomannan assay for detecting active tuberculosis in HIV-positive

adults. The Cochrane Database of Systematic Reviews 5:CD011420.Smith S, Jacobs RF, and Wilson CB (1997) Immunobiology of childhood tuberculosis: A window on the ontogeny of cellular immunity. The Journal of Pediatrics 131(1): 16–26.Stegen G, Jones K, and Kaplan P (1969) Criteria for guidance in the diagnosis of tuberculosis. Pediatrics 43(2): 260–263.Steingart KR, Schiller I, Horne DJ, Pai M, Boehme CC, and Dendukuri N (2014) Xpert(R) MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults. The Cochrane

Database of Systematic Reviews 1:CD009593.Sutherland JS, de Jong BC, Jeffries DJ, Adetifa IM, and Ota MO (2010) Production of TNF-alpha, IL-12(p40) and IL-17 can discriminate between active TB disease and latent infection

in a West African cohort. PLoS ONE 5(8)e12365.Tebruegge M, Dutta B, Donath S, Ritz N, Forbes B, Camacho-Badilla K, et al. (2015) Mycobacteria-specific cytokine responses detect tuberculosis infection and distinguish latent from

active tuberculosis. American Journal of Respiratory and Critical Care Medicine 192(4): 485–499.Thomas T, Brighenti S, Andersson J, Sack D, and Raqib R (2011) A new potential biomarker for childhood tuberculosis. Thorax 66(8): 727–729.Togun T and Pai M (2017) The uncertain science of predicting tuberculosis. The Lancet Respiratory Medicine 5(4): 239–240.Upham JW, Rate A, Rowe J, Kusel M, Sly PD, and Holt PG (2006) Dendritic cell immaturity during infancy restricts the capacity to express vaccine-specific T-cell memory. Infection

and Immunity 74(2): 1106–1112.van der Wel N, Hava D, Houben D, Fluitsma D, van Zon M, Pierson J, et al. (2007) M. tuberculosis and M. leprae translocate from the phagolysosome to the cytosol in myeloid cells.

Cell 129(7): 1287–1298.Verhagen LM, Zomer A, Maes M, Villalba JA, Del Nogal B, Eleveld M, et al. (2013) A predictive signature gene set for discriminating active from latent tuberculosis in Warao

Amerindian children. BMC Genomics 14: 74.Walzl G, Ronacher K, Hanekom W, Scriba TJ, and Zumla A (2011) Immunological biomarkers of tuberculosis. Nature Reviews Immunology 11(5): 343–354.White GP, Watt PM, Holt BJ, and Holt PG (2002) Differential patterns of methylation of the IFN-gamma promoter at CpG and non-CpG sites underlie differences in IFN-gamma gene

expression between human neonatal and adult CD45RO- T cells. Journal of Immunology 168(6): 2820–2827.WHO (2000) Management of the child with a serious infection or severe malnutrition. Guidelines for care at the first-referral level in developing countries. Geneva: World Health

Organization. WHO/FCH/CAH/00.1.WHO. An International Roadmap for Tuberculosis Research Geneval, Switzerland; World Health Organization, Stop TB Partnership 2011. www.stoptb.org/assets/documents/resources/

. . ./tbresearchroadmap.pdf [Accessed 02 January 2015].WHO. Commercial Serodiagnostic Tests for Diagnosis of Tuberculosis—Policty Statement. Geneva, Switzerland; World Health Organization 2011. Available from: http://apps.who.int/

iris/bitstream/10665/44652/1/9789241502054_eng.pdf [Accessed on 15 March 2014].

Diagnosis of Childhood Tuberculosis 13

WHO. Automated Real-time Nucleic Acid Amplification Technology for Rapid and Simultaneous Detection of Tuberculosis and Rifampicin Resistance: Xpert MTB/RIF assay for thediagnosis of pulmonary and extrapulmonary TB in adults and children. Policy update. Geneva, Switzerland; World Health Organization 2013. Available from: http://apps.who.int/iris/bitstream/10665/112472/1/9789241506335_eng.pdf?ua¼1 (Accessed 03/12/2014).

WHO. Stop TB Partnership. Towards Zero TB Deaths in Children. http://stoptb.org/assets/documents/news/ChildhoodTB_report_singles.pdf (Accessed 02 December 2014).WHO. Roadmap for rolling out Xpert MTB/RIF for rapid diagnosis of TB and MDR-TB. http://www.who.int/tb/laboratory/roadmap_xpert_mtb-rif.pdf (Accessed 04 December 2014)

2010.WHO. The use of lateral flow urine lipoarabinomannan assay (LF-LAM) for the diagnosis and screening of active tuberculosis in people living with HIV Geneval, Switzerland; World

Health Organization 2015a. Available from: http://apps.who.int/iris/bitstream/10665/193633/1/9789241509633_eng.pdf?ua¼1&ua¼1 [Accessed 20 April 2017].WHO. Guidelines on the management of latent tuberculosis infection. Geneval, Switzerland; Wolrd Health Organization 2015b. Available from http://apps.who.int/iris/bitstream/

10665/136471/1/9789241548908_eng.pdf?ua¼1&ua¼1 [Accessed 22 April 2017].WHO, 2016a. Global Tuberculosis Report 2016. Geneva, Switzerland. World Health Organization. 2016 Available from: http://apps.who.int/iris/bitstream/10665/250441/

1/9789241565394-eng.pdf?ua¼1 [Accessed 09 February 2017].WHO. The use of loop-mediated isothermal amplification (TB-LAMP) for the diagnosis of pulmonary tuberculosis. Geneva, Switzerland; World Health Organization 2016b. Available

from: http://apps.who.int/iris/bitstream/10665/249154/1/9789241511186-eng.pdf [Accessed 22 April 2017].WHO. The use of molecular line probe assay for the detection of resistance to second-line anti-tuberculosis drugs—Policy Guidance. Geneva, Switzerland; World Health Organization

2016c. Available from: http://www.who.int/tb/WHOPolicyStatementSLLPA.pdf [Accessed 20 April 2017].WHO. WHO End TB Strategy. Geneva, Switzerland. Available from: http://www.who.int/tb/post2015_TBstrategy.pdf [Accessed 20 December 2016d].WHO. WHO Meeting Report of a Technical Expert Consultation: Non-inferiority analysis of Xpert MTB/RIF Ultra compared to Xpert MTB/RIF. Geneva, Switzerland: World Health

Organization; 2017a. Available from: http://apps.who.int/iris/bitstream/10665/254792/1/WHO-HTM-TB-2017.04-eng.pdf [Accessed 22 April 2017].WHO. GLI model TB diagnostic algorithms. Geneva, Switzerland. Stop TB Partnership—Global Laboratory Initiative 2017b. Available from: http://www.stoptb.org/wg/gli/assets/

documents/GLI_algorithms.pdf [Accessed on 23 April 2017].Winau F, Weber S, Sad S, de Diego J, Hoops SL, Breiden B, et al. (2006) Apoptotic vesicles crossprime CD8 T cells and protect against tuberculosis. Immunity 24(1): 105–117.Zak DE, Penn-Nicholson A, Scriba TJ, Thompson E, Suliman S, Amon LM, et al. (2016) A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet 387

(10035): 2312–2322.Zhou M, Yu G, Yang X, Zhu C, Zhang Z, and Zhan X (2016) Circulating microRNAs as biomarkers for the early diagnosis of childhood tuberculosis infection. Molecular Medicine

Reports 13(6): 4620–4626.