OpiniãoEffective and efficient TB diagnostic algorithms are key components of a diagnostic cascade that is designed to ensure that people with TB disease or TB infection are diagnosed accurately and rapidly, and promptly placed on appropriate therapy. In turn, that therapy should improve patient outcomes, reduce transmission and avoid development of drug resistance. This section presents a set of four model algorithms that incorporate the goals of the End TB Strategy and the most recent WHO recommendations for the diagnosis and treatment of TB, DR-TB and TB infection. The model algorithms should be adapted to the local situation.
When adapting a diagnostic algorithm to local settings, it is important to consider the characteristics of the population being served. The four algorithms are as follows:
- Algorithm 1 is the general algorithm that relies on WRDs, such as low- or moderate-complexity NAATs, as the initial diagnostic tests and is appropriate for all settings, although the choice of which mWRD to use may differ in a setting with a high prevalence of MDR/RR-TB (e.g. a test that detects MTBC and RIF with or without INH resistance may be needed), HIV (e.g. a more sensitive test may be needed) or Hr-TB (e.g. a test that detects MTBC, RIF and INH resistance simultaneously will be needed). The algorithm considers the new recommendations on concurrent testing (including use of LF-LAM) for specified risk groups as the first step before results interpretation and management.
- Algorithm 2 and Algorithm 3 are for follow-up testing, after TB is diagnosed, to detect additional drug resistance:
- Algorithms 2a and 2b are used when the purpose is to detect resistance to second-line drugs in people with RR-TB; the choice depends on the availability of targeted NGS.
- Algorithm 3 is used when the purpose is to detect resistance in individuals with RIFsusceptible TB who are at risk of having DR-TB and those with Hr-TB. Molecular testing is preferred, but any existing WRD may be used. Targeted NGS is a valuable addition for Algorithm 2 and 3 because these tests can detect mutations associated with resistance to many anti-TB medicines; also, these molecular tests are useful for people at high risk of having DR-TB (e.g. people in whom therapy is failing).
- Algorithm 4 is the model algorithm for diagnosing TB infection performed based on the recommendations in the WHO consolidated guidelines for tuberculosis: module 2: screening (81). Testing for TB infection should only be conducted after ruling out TB disease.
Algorithms 2 and 3 are appropriate for all settings; however, the resource requirements for follow-up testing may differ widely between settings with a high or low burden of DR-TB.
Each algorithm is accompanied by explanatory notes and a decision pathway that provides a detailed description of considerations for how test results may be used to guide patient care. In general, the algorithms are not necessarily test-specific; rather, they present classes of tests that share expected result categories (e.g. “TB detected”) and their follow-up actions.
TB screening strategies
The diagnosis of TB begins with a person identified as presumed to have TB disease through assessment of signs and symptoms, or screened using another approach. WHO has released updated recommendations on TB screening, and readers are encouraged to consult the latest guidance (54, 81). People presumed to have TB may not always present with symptoms that match the latest screening recommendations, but they still have an increased probability of TB disease that requires diagnostic testing. The modalities for screening, beyond the four-symptom screen, now include CXR, an mWRD used as a screening tool or C-reactive protein in people living with HIV. The addition of mWRD for screening of selected at-risk populations and settings goes beyond its primary use as an initial diagnostic tool; the different uses should not be confused and are further described elsewhere (54). However, priority should be given to ensuring universal access to mWRDs as a diagnostic test for TB and DR-TB before extending its use to screening. Furthermore, the use of mWRDs as a screening test should be considered carefully because it would have large financial and operational implications (e.g. are there enough tests and testing capacity to use mWRDs for screening, in addition to what is needed to conduct all testing for the initial diagnosis and detection of RIF resistance). The methods for screening for TB are described in detail in the latest operational handbook on screening (54). It is important to consider prevalence and pretest probability when choosing a screening strategy, especially in scenarios where mWRDs are used in a screening context rather than for diagnostic testing.