| Literature DB >> 35339423 |
Ruvandhi R Nathavitharana1, Alberto L Garcia-Basteiro2, Morten Ruhwald3, Frank Cobelens4, Grant Theron5.
Abstract
Rapid, accurate, sputum-free tests for tuberculosis (TB) triage and confirmation are urgently needed to close the widening diagnostic gap. We summarise key technologies and review programmatic, systems, and resource issues that could affect the impact of diagnostics. Mid-to-early-stage technologies like artificial intelligence-based automated digital chest X-radiography and capillary blood point-of-care assays are particularly promising. Pitfalls in the diagnostic pipeline, included a lack of community-based tools. We outline how these technologies may complement one another within the context of the TB care cascade, help overturn current paradigms (eg, reducing syndromic triage reliance, permitting subclinical TB to be diagnosed), and expand options for extra-pulmonary TB. We review challenges such as the difficulty of detecting paucibacillary TB and the limitations of current reference standards, and discuss how researchers and developers can better design and evaluate assays to optimise programmatic uptake. Finally, we outline how leveraging the urgency and innovation applied to COVID-19 is critical to improving TB patients' diagnostic quality-of-care.Entities:
Keywords: Active disease; Diagnosis; Non-sputum; Point-of-care; Tuberculosis
Mesh:
Substances:
Year: 2022 PMID: 35339423 PMCID: PMC9043971 DOI: 10.1016/j.ebiom.2022.103939
Source DB: PubMed Journal: EBioMedicine ISSN: 2352-3964 Impact factor: 11.205
Figure 1Approaches to diagnosing TB. (a) An overview of a typical facility-based TB diagnostic algorithm. People in a community (without risk factors for TB, white; with symptoms or risk factors for TB, grey; with TB, red) attend a health facility. After screening, all at-risk individuals are ideally identified and receive a triage test (note in some very high burden settings, all clinical attendees may be considered at risk; the definition of at-risk is setting-specific), which is done to exclude unnecessary confirmatory testing. Patients who triage positive then receive typically expensive (yet critical) confirmatory testing, which is used to inform treatment. Importantly, screening (and potentially testing) could occur in the community, however, this is not shown as most new technologies need to first demonstrate potential in facilities. (b) Some of the novel materials under investigation for triage or confirmation are shown (some applicable to both use cases), and (c) a selection of products and technologies that use these materials, their developmental stage (if known to be under commercialisation), and potential health system-level of deployment. Notably, there are insufficient late-stage and design-locked triage tests, as well as early and design-locked confirmatory tests useful for facility-based point-of-care testing (this deficit is even more serious for community-based testing, which is diagnostically and operationally more challenging). Abbreviations: AI: artificial intelligence, dCXR: digital chest X-ray.
Current and upcoming non-invasive specimen-based technologies for the rapid non-sputum-based diagnosis of TB. Technologies are listed by specimen and biomarker type (least to most invasive). Examples with best available sensitivity and specificity estimates (as well as the likely WHO target product profiles tests use case) are listed, together with known limitations. Strengths and challenges for POC deployment in high burden settings as well as open questions and considerations for researchers and implementers are discussed. Rankings of the technological level of maturity and level of confidence of available performance estimates are given.
| Specimen | Biomarker | Principle and mechanism | Likely TPP for active TB | Select studies and assays≥5 years away from potential implementation, 2-5 years, ≤2 years, unclear | Level of confidence, and accuracy estimatesLow, medium, high, unclear | Strengths and challenges of technology class | Open questions and key considerations |
|---|---|---|---|---|---|---|---|
| Bacterial or human metabolites or antigens | Compounds like volatile organics or | Triage | Aeonose (eNose) | - Sufficient data exists to generate pooled sensitivity (92%) and specificity (93%) estimates | - Potentially implementable at scale by non-technical personnel | - Lack of independent validation data, which would be facilitated by large public data sets for discovery and training of electronic nose algorithms | |
| TB Breathalyser (Rapid Biosensor Systems) | |||||||
| Transmission occurs when | Confirmatory | Face masks with filters or absorbent materials capture bacteria. This is a collection method and different assays could be applied. | - Promising but too early to tell | - Sampling over long periods possible to improve yield | |||
| Tongue papillae filter and concentrate biomass from respiratory secretions, permitting formation of | Triage | Collection method and not a test itself | - Studies are few and heterogenous, no pooled performance estimates exist | - FLOQSwabs (Copan Italia) preferred | - Performance of novel assays (e.g., next-generation LAM and NAATs unknown) may overcome sensitivity limitations associated | ||
| Host transcriptome | mRNA blood signatures associated with the immune system's response to | Triage | Xpert Host Response (Cepheid) | - A multicentre study showed 90% sensitivity and 86% specificity | - Limited data with small numbers of cases, however, multicentre studies are emerging | - Signatures (including Sweeney3 in Xpert HR) measured using ultra-sensitive methods (sequencing, Nanostring) | |
| RISK6 signature (QuantumDx) | - No product-specific data, but signature performance measured by real-time PCR is 91% sensitivity and 56% specificity (increasing to 75% in patients without previous TB) | ||||||
| cfDNA | Extracellular | Confirmatory | No prototypes with public data | - A systematic review and meta-analysis of different cfDNA in-house assays found a sensitivity and specificity of 78% and 97% respectively but large heterogeneity noted | - Technical collection parameters influence performance | - Still at proof-of-concept stage | |
| Host markers | Markers of inflammation made in response to disease may assist in screening and triage. | Triage | CRP (near-POC instruments like the iChroma platform (Boditech)) and other instrument-free rapid diagnostic tests are commercially-available) | - Robust meta-analysis data show sensitivity and specificity of 77% and 74% in PLHIV | - CRP outperforms WHO 4-symptom based screening in PLHIV | - More CRP data needed in HIV-negatives and PLHIV (some studies report large specificity differences by HIV status | |
| Antigens, cytokines, and antibodies | Altered molecular signatures are detectable in blood | Triage | MBT assay | - A LFA five marker prototype had 94% sensitivity and 96% specificity | - High POC potential | - Other than CRP, all tests are prototypes | |
| SeroSelectTB | - A LFA protype had 84% sensitivity and 97% specificity | ||||||
| Simoa array panel | - 86% sensitivity and 69% specificity in a multinational global validation cohort | ||||||
| Triage, confirmatory | NanoDisk-MS (Nanopin) | - 88% sensitivity and 96% specificity in a large Chinese cohort | |||||
| Immune cell profiling | T-cell activation markers can discriminate active disease from other forms | Confirmatory | TAM-TB (Beckman Coulter) | - A prospective study with non-TB infected controls showed 82% sensitivity and 93% specificity, which were unaffected by HIV | - Demonstrated potential in children | - Validations required | |
| Swallowed or disseminated | Confirmatory | Ultra | - A Tanzanian study in presumptive TB patients found sensitivity to range from 63-84% and specificity from 76-93% depending of the type of laboratory | - Evidence to support use in children | - Data in adults (including PLHIV) scarce | ||
| LAM | Urine is easy to collect and will have high diagnostic yield. | Confirmatory | FujiLAM (FujiFILM) | - In a large multicentre head-to-head evaluation in HIV-negative outpatients, sensitivity was 53% and specificity 99% and highly variable between settings | - Utility for EPTB | - Data in important patient groups like HIV-negatives are lacking | |
| FLOW-TB (Salus Discovery) | A second-generation version of the assay had a sensitivity of 86% and specificity 89% in inpatients | ||||||
| TB-LAM (Biopromic) | Unclear (in development) | ||||||
| TB-LAM (Mologic) | Unclear (in development) | ||||||
| cfDNA | No prototypes with public data | A proof-of-concept study with an enrichment step had a sensitivity of 84% and specificity 100% |
Abbreviations: LFA: lateral flow antigen, POC: point of care
Current and upcoming non-invasive non-specimen-based digital and/or AI-based technologies for the rapid non-sputum-based diagnosis of TB. Technologies are listed by specimen and biomarker type (least to most invasive). Examples with best available sensitivity and specificity estimates (as well as the likely WHO target product profiles tests use case) are listed, together with known limitations. Strengths and challenges for POC deployment in high burden settings as well open questions and considerations for researchers and implementers are discussed. Rankings of the technological level of maturity and level of confidence of available performance estimates are given.
| Specimen | Biomarker | Principle and mechanism | Likely TPP for active TB | Select studies and assays≥5 years away from potential implementation, 2-5 years, ≤2 years, unclear | Level of confidence, and accuracy estimatesLow, medium, high, unclear | Strengths and challenges of technology class | Open questions and key considerations |
|---|---|---|---|---|---|---|---|
| Cough sounds | TB disease distorts lung architecture, affecting chest sounds in a way detectable by portable digital signal processing. | Triage | - Only proof-of-concept studies exist | - Promising but too early to tell. | - Able to rapidly screen all facility entrants | - Early-stage technology | |
| Stethoscopes | - Stethee | - Unknown | |||||
| Portable dCXR | CXR highly sensitive and increasingly feasible to be near POC due to advances in low-dose portable instruments and automated image reading. | Triage | Software products include: qXR (QURE.ai Technologies), CAD4TB (Delft Imaging Systems), and Lunit (FujiFILM), CAD4Good (EPCON) (see AI4HLTH for a complete overview) | - In a very large evaluation in Bangladesh, qXR and CAD4-TB have the highest specificities (both 73%) at >90% sensitivity | - Automated reading systems can overcome radiologist shortages and are WHO-endorsed | - Challenges in identifying which settings for prioritisation, including case finding scenarios where pre-symptomatic TB can be detected | |
| POCUS | Improving affordability and portability of ultrasound devices has led to interest in the use of POCUS. | Triage | Many (most standard point-of-care ultrasound machines can be used) | - Systematic review reported sensitivities ranging from 73-100% for subpleural nodules detected and 47-80% for lung consolidation | Potential to expand diagnosis of extrapulmonary TB and increase diagnostic yield in populations such as children or PLHIV | - Limited data, currently majority of studies in adults and for pulmonary TB |
Key challenges that need to be overcome for new diagnostic technologies to have a transformative impact on the TB epidemic. These issues are complex, multifactorial, and interdisciplinary, however, together they create a significant barrier to the adoption of promising new non-invasive TB tests at the point-of-care. When developing and planning to implement a new test, all factors require consideration, otherwise potential impact is undermined.
Colour theme key: Red- technical; orange- programmatic; purple- policy.
Abbreviations: POC: point of care, DST: drug susceptibility testing.