How To Test For Latent Tuberculosis







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IGRAs: What do they tell and what

don’t they tell us?



European Advanced Clinical Tuberculosis Course

Monday 22


September 2014

Amsterdam, Netherlands

Ibrahim Abubakar

Professor of Infectious Disease Epidemiology


IGRAs: What do they tell and what don’t

they tell us?

The answer is 42

0 50 100 150 200 250 2007 2008 2009 2010 2011 2012 2013 2014


1. I am the chair, NICE TB Guideline Development Group

and was a member, WHO LTBI Guideline Development

Group. Views expressed here are mine and not that of the


2. I am CI on a number of studies utilising IGRAs and TST

including the 10,000 participant UK PREDICT TB study.

These studies are fully funded by the UK Government and

National Health Service.


Conflict of Interest



1. What are IGRAs?

2. Latent Tuberculosis

3. Active Tuberculosis

4. Where next?


1. What are IGRAs: Basis of IGRA

Region of Difference (RD) 1

Deleted in M. bovis BCG and absent in most NTMs

Except M. kansasii, M. szulgai, M. marinum or M.flavecens

Rv3875 – Early Secretory Antigenic Target (ESAT) 6 Rv3874 – Culture Filtrate Protein (CFP) 10


1. What are IGRAs: The Assays


Plasma PBMCs

Red Blood Cells

> = 0.35 iu/ml Secondary antibody












Red Blood Cells

Incubation of whole blood with antigens (CFP10, ESAT6, TB7.7)

Cytokine Plasma

Quantiferon Gold in tube

> = 6 spots Antigens (CFP10, ESAT6)










Secondary antibody PBMCs separated T cell Cytokine Antibody IFN gamma TBSPOT TB ..and Xtend


• 2006 NICE Clinical Guidance on

Tuberculosis recommended IGRA use as

part of a 2 step strategy.

• IGRA update in 2011; we are currently

revising these gain

• Plethora of guidelines globally

1. What are IGRAs: Guidelines


1. What are IGRAs: What is latent TB?


2. Latent TB: Predictive Value

• PPV values constrained by life time disease risk

and factors that affect susceptibility.

• PREDICT Value Studies and Systematic Reviews

– There are several with varying conclusions

– Inclusion/exclusion criteria


Progression rates in contacts in migrant communities variable

2. Latent TB: Progression Rates in Migrants

PPV 5/178=2.8% (95% CI; 1.0-4.6) for QFTGIT and 6/181=3.3%

(95% CI; 1.3-5.3) for T-SPOT.TB.

Kik et al ERJ 2010

14 of 112 untreated QFT+ adults developed TB (2-year rate (95% CI)=13·4% (7.7 to 21.1)).

Haldar et al Thorax 2013

7/387 (1.8%) non German contacts developed TB Diel et al AJRCCM 2011


2. Latent TB: Variability


2. Latent TB: Reversion and Conversions

HIV infected: IGRA conversions occurred in 9% (n = 63 of 718), whereas IGRA reversions were seen in 33% (n = 25 of 76) of individuals

Aichelburg et al JID 2014

Contact study in India: QFT conversion rates 11.8%-21.2% and 6.4% had QFT reversions.


2. Latent TB: Serial testing in Health Care


Two systematic reviews

• Zwerling et al Thorax 2012 • Ringhausen et al JOMT 2012


2. Latent TB: Serial testing in Health Care



Boosting by prior TST occurs but not a major issue

Van Zyl Smit PlosOne 2009

1. The use of IGRAs for serial testing is limited by lack of data on best cut-offs and unclear interpretation and prognosis of conversions and reversions.

2. Further longitudinal research required to inform guidelines on serial testing • In low to moderate incidence countries, IGRA positivity less prevalent than TST • Higher false conversions with IGRA than TST


Hinks et al Infect Immun 2009

compared the frequencies of IFN-gamma-secreting T cells specific for 5 RD1-encoded antigens and one DosR-encoded antigen in 205 individuals

Recently acquired (<6 months) versus remotely acquired (>6 months) latent infection did not differ in numbers of peptide pools recognized, proportions recognizing any individual antigen or peptide pool, or antigen-specific T-cell frequencies (P >or= 0.11).

Bradshaw et al PlosOne 2011

2. Latent TB: Remote Infection

Other data support the notion that IGRAs do not distinguish remote from recent infection Ringhausen et al Plos One 2013 - miners Kik et al IJTLD 2009


HIV - Two systematic reviews

• Lower sensitivity than in immunocompetent individuals • TSpotTB might have be more sensitive than TST

• Indeterminates higher in HIV, high burden settings and with low CD4 count

• Limited predictive value data (Aicheburg, Sester)


2. Latent TB: Prior to anti-TNF alpha agents

• High risk of progression to active TB in patients

with infliximab*

• Small number of prospective studies to assess


Keane J NEJM 2001


2. Latent TB: Prior to anti-TNF alpha agents

Study, reference Assay No. patients with IMID

Main findings

Bocchino et al. QFT-IT T-SPOT.TB 66 8/15 patients with IMID and risk factors for TB infection were positive to TST, T-SPOT.TB and QFT-IT. The remaining 7 were negative to TST but positive to either T-SPOT.TB and/or QFT-IT. 35/51 patients with IMID without risk factors for TB infection were negative to TST,


Ponce de Leon et al. QFT-IT 101 Proportion of TST-positive results was significantly less in patients with IMID than in healthy controls (27/101 (26.7%) vs 61/93 (65.6%) P < 0.001) and size TST response significantly less (mean 3.73 vs 11.0 mm P < 0.001) Proportion TST-positive results in patients with IMID was 41% of healthy controls, significantly lower than proportion QFT-IT-positive results in patients with IMIDs was 75% of healthy controls (P = 0.008)

Difference in proportion TST-positive & QFT-IT-positive was significant in patients with IMID (P = 0.013) but not in healthy controls (P = 0.45)

Vassilopoulos et al. [ T-SPOT.TB 70 Agreement between TST and T-SPOT.TB results was moderate (72.8%)

On multivariate analysis BCG was associated with TST-positive ELISpot-negative results (P = 0.01)

Matulis et al. QFT-IT 142 QFT-IT associated more closely with presence risk factors for LTBI than TST (OR 23.8 (95% CI 5.14 to 110 vs OR 2.77 (95% CI 1.22 to 6.27 P = 0.009).

Odds QFT-IT-positive result increased with increasingly relevant markers of LTBI risk factors. QFT-IT associated less closely with BCG than TST (OR 0.47 (95% CI 0.15 to 1.47) vs OR 2.44 (95% CI 0.74 to 8.01) P = 0.025)

Cobanoglu et al. QFT-IT 68 Agreement between TST & QFT-IT results in patients with IMID was poor (agreement 47% & 55% k = 0.18)

Agreement between TST & QFT-IT results in healthy controls (n = 38) was poor (agreement 64% k = − 0.54)

Takahashi et al. QFT-G 14 Agreement between conventional diagnosis for LTBI (TST, chest radiography & medical history) and QFT-G results was moderate (64.3%).

Sellam et al. T-SPOT.TB 7 Agreement between TST and T-SPOT.TB results in patients with IMID with confirmed LTBI based on previous primo-infection, previous TB with inadequate treatment or TB lesions on chest radiograph (independent of TST) was moderate (71%).

Pratt et al. QFT-G 101 7/101 (7%) patients with rheumatoid arthritis were QFT-G-positive. 4/7 were started on anti-TNF treatment. No cases of M. tuberculosis reactivation or de novo infection in 98 patients within 6 to 30 months following initiation anti-TNF treatment.


2. Latent TB: Response to treatment

Wilkinson et al JID 2006

IGRAs are not suitable for monitoring response to LTBI treatment

Chee CBE et al AJRCCM 2007

Elispot response by time Adetifa et al AJRCCM 2013


• 6/7 studies show IGRA is cost effective • But is such comparison valid?


• Multi-centre data on immigrant (≤35 years) screening with single-step


• Determine prevalence of LTBI in immigrants and how it varies by region

of origin

• Assessment of screening at different incidence thresholds – computed:

– Number of immigrants who need to be screened

– LTBI yield and proportion of individuals with LTBI who would not be


• Undertook decision-based economic analysis (with secondary cases)

– (a)Relative costs of screening at different incidence thresholds?

– (b)Which threshold, if any, is the most cost-effective?

• Data available for 1229 immigrants aged ≤35


2 Latent TB: Health-economic analyses – optimum screening


Screening threshold for immigrants (annual incidence per 100,000)

Cases of active TB (over 20 years) Costs over 20 years (2010 GB pounds) ICER

(GBP per TB case averted) Under 16 16-35 years

None None 95.4 608,370.0 Baseline

40 500 91.9 678,586.5 Extended dominance 40 400 91.8 683,710.0 Strict dominance 40 450 91.7 683,267.9 Extended dominance 40 350 90.8 697,208.7 Extended dominance 40 300 87.1 761,431.6 Extended dominance 40 250 83.4 823,312.8 17,956.0

40 500 +SSA 82.2 850,103.1 Extended dominance 40 200 71.1 1,121,093.2 Extended dominance 40 150 54.2 1,431,928.5 20,818.8

40 100 53.7 1,456,820.1 Extended dominance 40 40 50.9 1,527,478.5 29,403.1

All All 50.9 1,532,256.6 101,938.3


2 Latent TB: cost effectiveness sensitivity analysis -

progression from LTBI to active TB critical parameter

Point Estimate Range explored <16 from >40 16-35 from >250 <16 from >40 16-35 from >150 <16 from >40 16-35 from >40 Screen all <16 Screen all 16-35 Progression to active TB (%;over 20 years) 5% 2.5% 15% 41,823.6 2,049.3 47,494.4 3,040.8 64,498.4 6,013.6 208,178.6 31,133.8


2. Latent TB: Children

• Similar accuracy with TST

• Reduced sensitivity in high burden settings • Reduced sensitivity in HIV



Conflicting and confusing; poor methodology; conflicts of interest not stated

2. Latent TB: What do the guidelines say?

• Contact tracing in adults • Contact tracing in children

• Immunocompromised individuals with HIV • Prior to anti TNF Alpha therapy

• Migrant screening

• Serial testing of health care workers

Quantitative results? Significance for predictive value unclear, may be useful for predicting conversion and reversion.


2. Latent TB: Uncertainties

• Which migrants to screen • Impact of remote infection

New Entrants

• What does reversion mean? • Impact of remote infection • Unable to assess re-infection


• What does reversion mean?

• False Negative rates unknown in high risk groups


3. Active TB

• No correlation between IGRA and bacterial load

• Responses detected may relate to re-infection or

previous infection that has not been cleared.

Ulrichs T, IJTLD, 2000

Vekemans J, Inf & Imm, 2001 Wu-Hsieh BA, CID, 2001 Al-Attiyah R, FEMS I M M, 2003 Ferrand RA, IJTLD, 2005


3. Active TB: Sensitivity and Specificity

• IGRAs can not distinguish active from latent TB

• This view is consistently supported by all


3. Active TB: Treatment Monitoring

Pathan et al J Immu 2001 Carrara et al CID 2003


3. Active TB: Treatment Monitoring

Hang et al J Infect 2014

• QFT-IT showed positive results in 95.6%, 86.2%, and 83.5% at 0, 2, and 7 months, respectively.

• Positive-to-negative conversion of QFT-IT results between 0 and 2 months was significantly associated with earlier recurrence (adjusted hazard ratio, 5.57; 95% CI, 2.28-13.57).

Future longitudinal studies ought to consider other markers and not just interferon gamma

Chiappini et al Clin Ther 2012 - Systematic Review:

• Reversion from positive to negative IGRA values occurs in a minority of treated patients, monitoring IGRA changes over time seems to have only speculative value in adults.


3. Active TB: Children

• Similar accuracy with TST

• Should not be used alone to diagnose active TB i.e. use in a similar manner as TST currently used in children



HIV - Two systematic reviews

IGRAs in their current form have limited utility for diagnosing active and should not be used to rule in or rule out active TB.


3. Active TB: Uncertainties

• False negative in 15-25% of cases

(not a rule out test)


• Increased risk of false negative results

• Unsuitable for treatment monitoring


• Even more paucity of data


• WHO Post 2015 Strategy

• Elimination Plan just launched

• LTBI a central component


WHO guidelines are due to be published soon addressing

issues from the perspective of low –ish incidence

countries (100 per 100,000)

Position in high incidence developing countries is clear:

there is no strong evidence that IGRAs are superior and

TST should be used.


A wide array of new tests in development

• Revisiting immune based tests

– IGRA plus – antigens, cytokines (IP10, IL2) – Lateral flow

• Transcriptomics

• Proteomics

We need a simple point of care test that does not require incubation in

the laboratory to screen followed by a test with the highest possible

positive and negative predictive values


4. IGRAs: What do they tell and what don’t

they tell us?

• The answer is not 42…..IGRAs:

– Should not be used to diagnose active TB

– May be used in those with latent TB at high risk of

progression to active (single or two step)

– Note: context depended


• Sandra Kik, KNCV

• Lele Rangaka, UCL

• Manish Pareek, University of Leicester

• Helen Stagg, UCL

• Charlotte Jackson, UCL

• NIHR and MRC for funding





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