Introduction In 2006, 72% of active TB cases in the UK occurred in people born overseas (HPA 2008). 48% of new entrants with TB were diagnosed within 5 years of entering the UK and 19% within 2 years (HPA 2008). It is a priority therefore, to identify and appropriately treat those infected with latent TB infection through TB screening programmes (DH 2004). NICE (2006) TB new entrant screening guidelines allow certain groups of new entrants to be screened solely via chest x-ray (CXR), omitting a Tuberculin Skin Test (TST). This potentially under-diagnoses latent TB Infection (LTBI). The aim of this study was to determine whether NICE (2006) criteria are adequate in detecting latent TB.
Method A retrospective case-note analysis of new entrants over a 44-month period (2006–2009). All patients were screened using a locally developed ‘Dorset’ algorithm that combined CXR and TST unless contraindicated (see Abstract P54 Figure 1). Each case was then re-evaluated using the NICE algorithm. This allowed direct comparison of each algorithm to detect LTBI.
Results 547 new entrants were referred locally for TB screening (2006–2009). 397 attended. 41 (10.3%) patients (all HIV−ve) were diagnosed with LTBI, based on the following outcomes:
Abnormal CXR and strongly positive TST=14 (34%).
Normal CXR but strongly positive TST=18 (44%).
Abnormal CXR but normal TST=9 (22%).
Comparison of the two algorithms showed that while all 41 cases were detected using the Dorset algorithm, only 27 cases (65.8 %) were detected using the NICE algorithm. This represents a 34.1% shortfall in LTBI detection using NICE (95% CI 19.63% to 48.67%, 99% CI 15.04% to 53.26%).
Discussion This study demonstrated that through the omission of TST, the NICE algorithm missed 14 (34.1%) cases of LTBI compared with the Dorset algorithm. While alternative screening methods such as IGRA are increasing in recognition, these continue to be an expensive option if not provided locally. Therefore TB services without routine access to IGRA can significantly improve their detection of latent TB by simply combining their existing screening tools.
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