Utility of a clinical scoring system in prioritizing TB investigations – a systematic review

ABSTRACT

Introduction: Tuberculosis (TB) is among the 10 most common causes of death worldwide and it is the leading cause of mortality in people with human immunodeficiency virus (HIV). Clinical scoring systems have the potential to improve case finding and to prioritize patients for TB testing.

Areas covered: This systematic review investigated the utility of prediction models to improve pulmonary tuberculosis (pTB) case finding. Studies were searched through PubMed until 15th of August 2018 and 20 studies were eligible according to the inclusion criteria. Data on study population, outcome measurements, predictors, and performance were extracted. Many studies showed promising results but lacked external validation. Furthermore, head-to-head studies are needed to compare the different prediction models. Sensitivities of the prediction models ranged from 26% to 96% and specificities from 18% to 92%, negative likelihood ratios (LR-) from 0.22 to 0.8 and positive likelihood ratios(LR+) 1.07 to 7.32. Composite scores including paraclinical measures added to sensitivity.

Expert opinion: TB case finding is of utmost importance to advance the quest for global TB elimination, and simple measures to identify high-risk populations or persons to undergo further diagnostic evaluation are highly needed. A number of clinical scores are available and could be implemented in practice to improve case finding.

KEYWORDS:

• Clinical prediction model
• clinical prediction rule
• clinical score
• case finding
• pulmonary tuberculosis

Article highlights

• In resource-limited areas, scoring systems are essential to prioritize patients with suspected pTB for diagnostic testing and treatment.

• Ideally, scoring systems both have a high sensitivity and specificity. This will result in a minimal number of missed pTB cases and a minimal number of healthy people who undergo further unnecessary testing.

• Many scoring systems have been developed to estimate the probability of pTB and some systems show promising results. To find the most accurate scoring system, head-to-head studies are needed. Furthermore, external validation studies are needed to ensure that the systems are accurate and feasible in different settings.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

C Wejse and F Rudolf were supported with a grant from the Novo Nordisk Foundation (NNF15OC0018034).