Chapter 6: Discussion of thesis
6.4 Future research
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diagnosed. An important implication of the findings in chapters 2, 3, 4, and 5 is that the entire WHO algorithm and confirmatory testing for all are unable to definitively rule out
tuberculosis.
In all outpatients, the WHO Xpert algorithm and Xpert for all would miss 40% and 33% of tuberculosis cases, respectively. The low yield is because both the W4SS and Xpert have inadequate sensitivities. However, Xpert Ultra may improve yield. For example, in 1 included cohort of outpatients not on ART, Xpert Ultra improved sensitivity compared with Xpert by 16 percentage points (73% vs 57%).173
Similarly, in HIV-positive inpatients, both Xpert and AlereLAM were insufficiently sensitive to identify all tuberculosis cases. In 1 included cohort,20 sputum Xpert combined with either urine Xpert or AlereLAM missed 19% and 39% of tuberculosis cases, respectively. In those with a negative result on both tests, physicians should consider additional diagnostic
approaches that incorporate clinical symptoms and signs, radiological tests (e.g., chest x-ray and abdominal ultrasound), laboratory tests (e.g., haemoglobin concentration), and
tuberculosis confirmatory tests on non-sputum samples (e.g., Xpert Ultra).45,92,121,196,197
Newer technologies might substantially close the diagnostic gap in inpatient populations. For example, sputum Xpert Ultra and FujiLAM have shown increased sensitivity compared with Xpert and AlereLAM, respectively.43,75 In chapter 4, sputum Xpert when combined with FujiLAM diagnosed 92% of tuberculosis cases (versus 61% when combined with AlereLAM). In a recent Cochrane systematic review, sputum Xpert Ultra increased sensitivity over sputum Xpert in PLHIV by 13 percentage points (88% vs 75%).43
Furthermore, a recent study showed that the sensitivity of urine Xpert Ultra was double that of AlereLAM (33% vs 16%).48
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newly developed CRP-based CPMs in chapter 5 also require validation in outpatient PLHIV on ART and in outpatient PLHIV from PCF settings.
Further studies should focus on developing an accurate initial screening tool to guide confirmatory testing in outpatients on ART and HIV-positive inpatients. Possible tools may include biomarkers at different ‘omics’ levels and CPMs. In one study that assessed several candidate transcriptional signatures for tuberculosis among participants with symptoms and signs of tuberculosis, these signatures approximated or met the minimum WHO TPP for a triage test.122 However, only 44 participants were PLHIV. In another study that recruited PLHIV irrespective of tuberculosis symptoms and signs from a community setting, the RISK11 blood transcriptional signature approached the minimum WHO TPP for a triage test.123 The newly developed CPMs in chapter 5 may be used as a benchmark to evaluate emerging biomarkers for tuberculosis screening; CRP may also be combined with other biomarkers to improve predictive performance. Particular attention should be placed on HIV- positive inpatients; in chapter 3, no current screening tool had optimal accuracy in this population, and resource-limited settings might be unable to do systematic confirmatory testing with Xpert in all HIV-positive inpatients.
For confirmatory tests, only 1 study assessed Xpert Ultra. This study enrolled outpatients not on ART irrespective of tuberculosis symptoms and signs, showing that Xpert Ultra improved sensitivity over Xpert by 16 percentage points. No studies assessed Xpert Ultra in outpatients on ART, pregnant PLHIV, and HIV-positive inpatients regardless of tuberculosis symptoms and signs. Since Xpert Ultra improved sensitivity by a substantial margin over Xpert, further studies should assess the accuracy of Xpert Ultra in all PLHIV irrespective of tuberculosis symptoms and signs, including in key subgroups. Other molecular-based tests, such as TB- LAMP and Trunat assays, also require evaluation. In chapter 4, only 2 studies evaluated FujiLAM in 477 HIV-positive inpatients irrespective of tuberculosis symptoms and signs. In these 2 studies, FujiLAM increased sensitivity by 21 percentage points compared with AlereLAM. Another study in outpatient PLHIV not on ART has also showed that FujiLAM increased sensitivity by 23 percentage points compared with AlereLAM.163. Thus, future studies should assess the accuracy of FujiLAM in PLHIV irrespective of tuberculosis symptoms and signs.
The diagnostic accuracy of screening tools and confirmatory tests in different settings also warrants attention. For example, future studies should assess test accuracy in countries
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outside of Africa, in settings with a low tuberculosis prevalence, and in the context of regular screening.
Finally, future diagnostic test accuracy studies – especially those conducted among inpatients – should be appropriately designed. Investigators should select a robust reference standard that includes several samples for culture and Xpert from both pulmonary and extrapulmonary sites. Furthermore, investigators should look to include participants who are unable to
produce sputum for testing.
6.4.2 Further studies to assess utility of certain screening tools and strategies Diagnostic test accuracy studies should be followed by studies that measure the consequences of a test. In other words, further studies are needed to determine the impact of tests or
strategies on health outcomes and costs. In particular, randomised trials are needed to evaluate important health outcomes, such as morbidity, mortality. Other test characteristics (e.g., feasibility, acceptability) also require evaluation.81
Since chapters 3 and 4 show that currently available screening tools to guide Xpert and LF- LAM confirmatory testing have low accuracy in inpatients, the analyses in these chapters are likely sufficient to conclude that Xpert and AlereLAM for all inpatients has clinical value.
However, the clinical utility of screening tools in outpatient PLHIV might need to be determined. Chapter 2, for example, showed that the specificity of CRP was higher than W4SS in outpatients not on ART, and a parallel strategy of W4SS and chest X-ray had higher sensitivity but lower specificity in outpatients on ART. A randomized clinical trial might determine the effect of replacing W4SS with these approaches on several outcomes such as mortality, number of confirmatory tests needed, number of participants placed on IPT/TPT, number of bacteriologically confirmed tuberculosis cases, and time to diagnosis of
tuberculosis. Furthermore, since decision makers need to consider the resource implications of these alternative approaches, health economic analyses (using randomized trial data or decision models) are also needed. These analyses may include cost-effectiveness, cost minimization, and/or budget impact analyses. Finally, future studies should evaluate the acceptability and feasibility of alternative tools and strategies for both the patient and the health system.
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