Digital CXR with computer aided diagnosis versus symptom screen to define presumptive tuberculosis among household contacts and impact on tuberculosis diagnosis

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

Background

In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.

Methods

We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage.

Results

In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries.

Conclusions

Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44263-024-00081-2.

Using a Knowledge and Awareness Survey to Engage and Inform a Community-Based Tuberculosis Intervention among Nomads in Adamawa State, Nigeria

BACKGROUND

Nomadic populations are frequently isolated and vulnerable to diseases including tuberculosis (TB) and human immunodeficiency virus (HIV) due to limited access to health-related information and services, poverty, and social exclusion. We designed and implemented community-driven and -based outreach for TB and HIV based on the results of a TB knowledge, attitude, and practices (KAP) survey in Adamawa, Nigeria.

METHODS

We conducted a cross-sectional study on KAP among nomads using an adapted WHO survey. A TB and HIV community-level active case-finding intervention among nomadic populations was planned and delivered based on the KAP survey results.

RESULTS

Among 81 respondents, 26 (32.1%) knew what caused TB. More than 60% reported no health facilities in their community. Radio and healthcare workers were primary sources of information on health. Using community input, we developed and broadcasted radio jingles to sensitize people to TB services. Outreach initiatives led to the verbal screening of 61,891 individuals and 306 were diagnosed with TB. Additionally, 4489 people underwent HIV testing, and 69 were HIV-positive, all of whom were linked to treatment.

CONCLUSIONS

The results of KAP surveys can inform the design of evidence-based TB and HIV community-driven and -based case-finding interventions in rural Nigeria among nomadic populations.

Benchmarking the diagnostic test accuracy of certified AI products for screening pulmonary tuberculosis in digital chest radiographs: Preliminary evidence from a rapid review and meta-analysis

BACKGROUND AND OBJECTIVE

The global market for AI systems used in lung tuberculosis (TB) detection has expanded significantly in recent years. Verifying their performance across diverse settings is crucial before medical organisations can invest in them and pursue safe, wide-scale deployment. The goal of this research was to synthesise the clinical evidence for the diagnostic accuracy of certified AI products designed for screening TB in chest X-rays (CXRs) compared to a microbiological reference standard.

METHODS

Four databases were searched between June to September 2022. Data concerning study methodology, system characteristics, and diagnostic accuracy metrics was extracted and summarised. Study bias was evaluated using QUADAS-2 and by examining sources of funding. Forest plots for diagnostic odds ratio (DOR) and summary receiver operating characteristic (SROC) curves were constructed for the AI products individually and collectively.

RESULTS

10 out of 3642 studies satisfied the review criteria however only 8 were subject to meta-analysis following bias assessment. Three AI products were evaluated with a 95 % confidence interval producing the following pooled estimates for accuracy rankings: qXR v2 (sensitivity of 0.944 [0.887-0.973], specificity of 0.692 [0.549-0.805], DOR of 3.63 [3.17-4.09], Lunit INSIGHT CXR v3.1 (sensitivity of 0.853 [0.787-0.901], specificity of 0.646 [0.627-0.665], DOR of 2.37 [1.96-2.78]), and CAD4TB v3.07 (sensitivity of 0.917 [0.848-0.956], specificity of 0.371 [0.336-0.408], DOR of 1.91 [1.4-2.47]). Overall, the products had a sensitivity of 0.903 (0.859-0.934), specificity of 0.526 (0.409-0.641), and DOR of 2.31 (1.78-2.84).

CONCLUSION

Current publicly available evidence indicates considerable variability in the diagnostic accuracy of available AI products although overall they have high sensitivity and modest specificity which is improving with time. These preliminary results are limited by the small number of studies and poor coverage for low TB burden settings. More research is needed to expand the clinical evidence base for the performance of AI products.

The yield of chest X-ray based versus symptom-based screening among patients with diabetes mellitus in public health facilities in Addis Ababa, Ethiopia

Background

Patients with diabetes mellitus (DM) are at increased risk of developing TB, but the best screening algorithm for early detection and treatment of TB remains unknown. Our objective was to determine if combining routine chest X-ray screening could have a better yield compared with symptom-based screening alone.

Methods

We conducted this cross-sectional study between September 2020 and September 2021 in 26 public health facilities in Addis Ababa, Ethiopia. All DM patients attending the clinics during the study period were offered chest X-ray and symptom screening simultaneously followed by confirmatory Xpert testing. We analyzed the number and proportion of patients with TB by the diagnostic algorithm category and performed binary logistic regression analysis to identify predictors of TB diagnosis.

Results

Of 7394 patients screened, 54.6 % were female, and their median age was 53 years. Type-2 diabetes accounted for 89.6 % of all participants of the patients. Of 172 symptomatic patients, chest X-ray suggested TB in 19, and 11 of these were confirmed to have TB (8 bacterilogicially confirmed and 3 clinically diagnosed). Only 2 of the 152 asymptomatic patients without X-ray findings had TB (both bacteriologically confirmed). X-ray was not done for one patient. On the other hand, 28 of 7222 symptom-negative patients had X-ray findings suggestive of TB, and 7 of these were subsequently confirmed with TB (6 clinically diagnosed). When combined with 8 patients who were on treatment for TB at the time of the screening, the overall point prevalence of TB was 380 per 100,000. The direct cost associated with the X-ray-based screening was 42-times higher.

Conclusion

Chest X-ray led to detection of about a third of TB patients which otherwise would have been missed but the algorithm is more expensive. Its full cost implication needs further economic evaluation.

The Contribution of Chest Radiography to the Clinical Management of Children Exposed to Tuberculosis

Rationale: Although World Health Organization guidelines emphasize contact investigation for tuberculosis (TB)-exposed children, data that support chest radiography as a useful tool are lacking. Objectives: We evaluated the diagnostic and prognostic information of chest radiography in children exposed to TB and measured the efficacy of isoniazid preventive therapy (IPT) in those with relevant radiographic abnormalities. Methods: Between September 2009 and August 2012, we enrolled 4,468 TB-exposed children who were screened by tuberculin skin testing, symptom assessment, and chest radiography. Those negative for TB disease were followed for 1 year for the occurrence of new TB diagnoses. We assessed the protective efficacy of IPT in children with and without abnormal chest radiographs. Measurements and Main Results: Compared with asymptomatic children with normal chest films, asymptomatic children with abnormal radiographs were 25.1-fold more likely to have coprevalent TB (95% confidence interval [CI], 1.02-613.76) and 26.7-fold more likely to be diagnosed with incident TB disease during follow-up (95% CI, 10.44-68.30). Among the 29 symptom-negative and CXR-abnormal child contacts, 20% (3/15) of the isoniazid recipients developed incident TB, compared with 57% (8/14) of those who did not receive IPT (82% IPT efficacy). Conclusions: Our results strongly support the use of chest radiography as a routine screening tool for the evaluation of child TB contacts, which is readily available. Radiographic abnormalities not usually considered suggestive of TB may indicate incipient or subclinical disease, although TB preventive treatment is adequate in most cases.

Evaluating the Effectiveness of a Novel Systematic Screening Approach for Tuberculosis among Individuals Suspected or Recovered from COVID-19: Experiences from Niger and Guinea

Evidence suggests that the COVID-19 pandemic negatively impacts tuberculosis (TB) activities. As TB and COVID-19 have similar symptoms, we assessed the effectiveness of integrated TB/COVID-19 screening in Guinea and Niger. From May to December 2020, TB screening was offered to symptomatic patients after a negative COVID-19 PCR test or after recovery from COVID-19 in Guinea. From December 2020 to March 2021, all presumptive COVID-19 patients with respiratory symptoms were tested simultaneously for COVID-19 and TB in Niger. We assessed the TB detection yield and used micro-costing to estimate the costs associated with both screening algorithms. A total of 863 individuals (758 in Guinea, and 105 in Niger), who were mostly male (60%) and with a median age of 34 (IQR: 26–45), were screened for TB. Reported symptoms were cough ≥2 weeks (49%), fever (45%), and weight loss (30%). Overall, 61 patients (7%) tested positive for COVID-19 (13 in Guinea, 48 in Niger) and 43 (4.9%) were diagnosed with TB disease (35 or 4.6% in Guinea, and 8 or 7.6% in Niger). The cost per person initiating TB treatment was USD $367 in Guinea and $566 in Niger. Overall, the yield of both approaches was high, and the cost was modest. Optimizing integrated COVID-19/TB screening may support maintaining TB detection during the ongoing pandemic.

Symptom- and chest-radiography screening for active pulmonary tuberculosis in HIV-negative adults and adults with unknown HIV status

BACKGROUND

Systematic screening in high-burden settings is recommended as a strategy for early detection of pulmonary tuberculosis disease, reducing mortality, morbidity and transmission, and improving equity in access to care. Questioning for symptoms and chest radiography (CXR) have historically been the most widely available tools to screen for tuberculosis disease. Their accuracy is important for the design of tuberculosis screening programmes and determines, in combination with the accuracy of confirmatory diagnostic tests, the yield of a screening programme and the burden on individuals and the health service.

OBJECTIVES

To assess the sensitivity and specificity of questioning for the presence of one or more tuberculosis symptoms or symptom combinations, CXR, and combinations of these as screening tools for detecting bacteriologically confirmed pulmonary tuberculosis disease in HIV-negative adults and adults with unknown HIV status who are considered eligible for systematic screening for tuberculosis disease. Second, to investigate sources of heterogeneity, especially in relation to regional, epidemiological, and demographic characteristics of the study populations.

SEARCH METHODS

We searched the MEDLINE, Embase, LILACS, and HTA (Health Technology Assessment) databases using pre-specified search terms and consulted experts for unpublished reports, for the period 1992 to 2018. The search date was 10 December 2018. This search was repeated on 2 July 2021.

SELECTION CRITERIA

Studies were eligible if participants were screened for tuberculosis disease using symptom questions, or abnormalities on CXR, or both, and were offered confirmatory testing with a reference standard. We included studies if diagnostic two-by-two tables could be generated for one or more index tests, even if not all participants were subjected to a microbacteriological reference standard. We excluded studies evaluating self-reporting of symptoms.

DATA COLLECTION AND ANALYSIS

We categorized symptom and CXR index tests according to commonly used definitions. We assessed the methodological quality of included studies using the QUADAS-2 instrument. We examined the forest plots and receiver operating characteristic plots visually for heterogeneity. We estimated summary sensitivities and specificities (and 95% confidence intervals (CI)) for each index test using bivariate random-effects methods. We analyzed potential sources of heterogeneity in a hierarchical mixed-model.

MAIN RESULTS

The electronic database search identified 9473 titles and abstracts. Through expert consultation, we identified 31 reports on national tuberculosis prevalence surveys as eligible (of which eight were already captured in the search of the electronic databases), and we identified 957 potentially relevant articles through reference checking. After removal of duplicates, we assessed 10,415 titles and abstracts, of which we identified 430 (4%) for full text review, whereafter we excluded 364 articles. In total, 66 articles provided data on 59 studies. We assessed the 2 July 2021 search results; seven studies were potentially eligible but would make no material difference to the review findings or grading of the evidence, and were not added in this edition of the review. We judged most studies at high risk of bias in one or more domains, most commonly because of incorporation bias and verification bias. We judged applicability concerns low in more than 80% of studies in all three domains. The three most common symptom index tests, cough for two or more weeks (41 studies), any cough (21 studies), and any tuberculosis symptom (29 studies), showed a summary sensitivity of 42.1% (95% CI 36.6% to 47.7%), 51.3% (95% CI 42.8% to 59.7%), and 70.6% (95% CI 61.7% to 78.2%, all very low-certainty evidence), and a specificity of 94.4% (95% CI 92.6% to 95.8%, high-certainty evidence), 87.6% (95% CI 81.6% to 91.8%, low-certainty evidence), and 65.1% (95% CI 53.3% to 75.4%, low-certainty evidence), respectively. The data on symptom index tests were more heterogenous than those for CXR. The studies on any tuberculosis symptom were the most heterogeneous, but had the lowest number of variables explaining this variation. Symptom index tests also showed regional variation. The summary sensitivity of any CXR abnormality (23 studies) was 94.7% (95% CI 92.2% to 96.4%, very low-certainty evidence) and 84.8% (95% CI 76.7% to 90.4%, low-certainty evidence) for CXR abnormalities suggestive of tuberculosis (19 studies), and specificity was 89.1% (95% CI 85.6% to 91.8%, low-certainty evidence) and 95.6% (95% CI 92.6% to 97.4%, high-certainty evidence), respectively. Sensitivity was more heterogenous than specificity, and could be explained by regional variation. The addition of cough for two or more weeks, whether to any (pulmonary) CXR abnormality or to CXR abnormalities suggestive of tuberculosis, resulted in a summary sensitivity and specificity of 99.2% (95% CI 96.8% to 99.8%) and 84.9% (95% CI 81.2% to 88.1%) (15 studies; certainty of evidence not assessed).

AUTHORS' CONCLUSIONS

The summary estimates of the symptom and CXR index tests may inform the choice of screening and diagnostic algorithms in any given setting or country where screening for tuberculosis is being implemented. The high sensitivity of CXR index tests, with or without symptom questions in parallel, suggests a high yield of persons with tuberculosis disease. However, additional considerations will determine the design of screening and diagnostic algorithms, such as the availability and accessibility of CXR facilities or the resources to fund them, and the need for more or fewer diagnostic tests to confirm the diagnosis (depending on screening test specificity), which also has resource implications. These review findings should be interpreted with caution due to methodological limitations in the included studies and regional variation in sensitivity and specificity. The sensitivity and specificity of an index test in a specific setting cannot be predicted with great precision due to heterogeneity. This should be borne in mind when planning for and implementing tuberculosis screening programmes.

Knowledge, attitudes and practices on childhood TB among healthcare workers

BACKGROUND: Increasing childhood TB case detection requires the deployment of diagnostic services at peripheral healthcare level. Capacity and readiness of healthcare workers (HCWs) are key to the delivery of innovative approaches.METHODS: In 2019, HCWs from five district hospitals (DHs) and 20 primary healthcare centres (PHCs) in Cambodia, Cameroon, Cote d´Ivoire, Sierra Leone and Uganda completed a self-administered knowledge-attitudes-practices (KAP) questionnaire on childhood TB. We computed knowledge and attitudes as scores and identified HCW characteristics associated with knowledge scores using linear regression.RESULT: Of 636 eligible HCWs, 497 (78%) participated. Median knowledge scores per country ranged between 7.4 and 12.1 (/18). Median attitude scores ranged between 2.8 and 3.3 (/4). Between 13.3% and 34.4% of HCWs reported diagnosing childhood with (presumptive) TB few times a week. Practising at PHC level, being female, being involved in indirect TB care, having a non-permanent position, having no previous research experience and working in Cambodia, Cameroon, Cote d´Ivoire and Sierra Leone as compared to Uganda were associated with a lower knowledge score.CONCLUSION: HCWs had overall limited knowledge, favourable attitudes and little practice of childhood TB diagnosis. Increasing HCW awareness, capacity and skills, and improving access to effective diagnosis are urgently needed.

Impact of intensified tuberculosis case finding at health facilities on case notifications in Cameroon: A controlled interrupted time series analysis

There is a large gap between the number of people who develop tuberculosis (TB) and those who are diagnosed, treated and notified, with only an estimated 71% of people with TB notified globally in 2019. Implementing better TB case finding strategies is necessary to close this gap. In Cameroon, 1,597 healthcare workers at 725 health facilities were trained and engaged to intensively screen and test people for TB, then follow-up to link people to appropriate care. Primary care centers were linked to TB testing through a locally-tailored specimen referral network. This intervention was implemented across 6 regions of the country, with a population of 16 million people, while the remaining 4 regions in the country, with 7.3 million people, served as a control area. Controlled interrupted time series analyses were used to compare routinely-collected programmatic TB case notification rates in the intervention versus control area for 12 quarters prior to (2016-2018) and for 8 quarters after the start of the intervention (2019-2020). In 2019-2020, a total of 167,508 people were tested for TB at intervention sites, including 52,980 people attending primary care facilities that did not previously provide organized TB services. The number of people tested for TB increased by 45% during the intervention as compared to prior to the intervention. The controlled interrupted time series analyses showed that after two years of the intervention, the all-forms TB case notification rate in the intervention population increased by 9% (ratio of case notification rate ratios = 1.09, 95% CI 1.06 to 1.12), as compared with the counterfactual estimated from pre-intervention trends. This increase was observed even during a negative national impact on case finding from the COVID-19 pandemic. These results support the use of this health-facility based intervention to improve access to TB testing and care in this setting.

Child Contact Case Management-A Major Policy-Practice Gap in High-Burden Countries

The 2021 Global Tuberculosis (TB) report shows slow progress towards closing the pediatric TB detection gap and improving the TB preventive treatment (TPT) coverage among child and adolescent contacts. This review presents the current knowledge around contact case management (CCM) in low-resource settings, with a focus on child contacts, which represents a key priority population for CCM and TPT. Compelling evidence demonstrates that CCM interventions are a key gateway for both TB case finding and identification of those in need of TPT, and their yield and effectiveness should provide a strong rationale for prioritization by national TB programs. A growing body of evidence is now showing that innovative models of care focused on community-based and patient-centered approaches to household contact investigation can help narrow down the CCM implementation gaps that we are currently facing. The availability of shorter and child-friendly TPT regimens for child contacts provide an additional important opportunity to improve TPT acceptability and adherence. Prioritization of TB CCM implementation and adequate resource mobilization by ministries of health, donors and implementing agencies is needed to timely close the gap.

Triage of Persons With Tuberculosis Symptoms Using Artificial Intelligence-Based Chest Radiograph Interpretation: A Cost-Effectiveness Analysis

BACKGROUND

In settings without access to rapid expert radiographic interpretation, artificial intelligence (AI)-based chest radiograph (CXR) analysis can triage persons presenting with possible tuberculosis (TB) symptoms, to identify those who require additional microbiological testing. However, there is limited evidence of the cost-effectiveness of this technology as a triage tool.

METHODS

A decision analysis model was developed to evaluate the cost-effectiveness of triage strategies with AI-based CXR analysis for patients presenting with symptoms suggestive of pulmonary TB in Karachi, Pakistan. These strategies were compared to the current standard of care using microbiological testing with smear microscopy or GeneXpert, without prior triage. Positive triage CXRs were considered to improve referral success for microbiologic testing, from 91% to 100% for eligible persons. Software diagnostic accuracy was based on a prospective field study in Karachi. Other inputs were obtained from the Pakistan TB Program. The analysis was conducted from the healthcare provider perspective, and costs were expressed in 2020 US dollars.

RESULTS

Compared to upfront smear microscopy for all persons with presumptive TB, triage strategies with AI-based CXR analysis were projected to lower costs by 19%, from $23233 per 1000 persons, and avert 3%-4% disability-adjusted life-years (DALYs), from 372 DALYs. Compared to upfront GeneXpert, AI-based triage strategies lowered projected costs by 37%, from $34346 and averted 4% additional DALYs, from 369 DALYs. Reinforced follow-up for persons with positive triage CXRs but negative microbiologic tests was particularly cost-effective.

CONCLUSIONS

In lower-resource settings, the addition of AI-based CXR triage before microbiologic testing for persons with possible TB symptoms can reduce costs, avert additional DALYs, and improve TB detection.

Provision of Decentralized TB Care Services: A Detect-Treat-Prevent Strategy for Children and Adolescents Affected by TB

In this review, we discuss considerations and successful models for providing decentralized diagnosis, treatment, and prevention services for children and adolescents. Key approaches to building decentralized capacity for childhood TB diagnosis in primary care facilities include provider training and increased access to child-focused diagnostic tools and techniques. Treatment of TB disease should be managed close to where patients live; pediatric formulations of both first- and second-line drugs should be widely available; and any hospitalization should be for as brief a period as medically indicated. TB preventive treatment for child and adolescent contacts must be greatly expanded, which will require home visits to identify contacts, building capacity to rule out TB, and adoption of shorter preventive regimens. Decentralization of TB services should involve the private sector, with collaborations outside the TB program in order to reach children and adolescents where they first enter the health care system. The impact of decentralization will be maximized if programs are family-centered and designed around responding to the needs of children and adolescents affected by TB, as well as their families.

Digital chest radiography enhances screening efficiency for pulmonary tuberculosis in primary health clinics, South Africa

BACKGROUND

Optimized tuberculosis (TB) screening in high burden settings is essential for case finding. We evaluated digital chest x-ray with computer-aided detection (CAD) software (d-CXR) for identifying undiagnosed TB in three primary health clinics in South Africa.

METHODS

The cross-sectional study consented adults who were sequentially screened for TB using the World Health Organization (WHO) four symptom questionnaire and d-CXR. Participants reporting ≥1 TB symptom and/or CAD score ≥60 (suggestive of TB) provided two spot sputum for Xpert MTB/RIF Ultra (Xpert Ultra) and liquid culture testing respectively. TB yield (proportion of screened tested positive) and number needed to test [NNT] (no of tests to identify one TB patient) were calculated. Risk factors for microbiologically confirmed or presumed (on radiological grounds) were determined.

RESULTS

Among 3041 participants, 45% (1356/3,041) screened positive on either d-CXR or symptoms. TB yield was 2.3% (71/3041) using Xpert Ultra and 2.7% (82/3041) using Xpert Ultra plus culture. Modelled TB yield (identified by Xpert Ultra) by screening approach was: 1.9% (59/3041) for d-CXR alone, 2.0% (62/3041) for symptoms alone and 2.3% (71/3041) for both. The NNT was 9.7 for d-CXR, 17.8 for symptoms and 19.1 for d-CXR and/or symptom. Males, those with previous TB, untreated HIV or unknown HIV status, and acute illness were at higher risk of developing TB.

CONCLUSION

d-CXR screening identified a similar yield of undiagnosed TB compared to symptom-based screening, however required fewer diagnostic tests. Due to its objective nature, d-CXR screening may improve case detection in clinics.

A deep learning system that generates quantitative CT reports for diagnosing pulmonary Tuberculosis

The purpose of this study was to establish and validate a new deep learning system that generates quantitative computed tomography (CT) reports for the diagnosis of pulmonary tuberculosis (PTB) in clinic. 501 CT imaging datasets were collected from 223 patients with active PTB, while another 501 datasets, which served as negative samples, were collected from a healthy population. All the PTB datasets were labeled and classified manually by professional radiologists. Then, four state-of-the-art 3D convolution neural network (CNN) models were trained and evaluated in the inspection of PTB CT images. The best model was selected to annotate the spatial location of lesions and classify them into miliary, infiltrative, caseous, tuberculoma, and cavitary types. The Noisy-Or Bayesian function was used to generate an overall infection probability of this case. The results showed that the recall and precision rates of detection, from the perspective of a single lesion region of PTB, were 85.9% and 89.2%, respectively. The overall recall and precision rates of detection, from the perspective of one PTB case, were 98.7% and 93.7%, respectively. Moreover, the precision rate of type classification of the PTB lesion was 90.9%. Finally, a quantitative diagnostic report of PTB was generated including infection possibility, locations of the lesion, as well as the types. This new method might serve as an effective reference for decision making by clinical doctors.

The impact of chest radiography and Xpert MTB/RIF testing among household contacts in Chennai, India

Tuberculosis prevalence surveys have demonstrated the benefit of screening with chest x-ray (CXR) and sensitive diagnostic tests compared to symptoms and smear microscopy. However, in programmatic practice there is little evidence on the yield of different algorithms. We implemented contact tracing in Chennai, India for adult sputum-positive TB patients registered from January 2015 to March 2016. Patients with symptoms or abnormal X-ray findings further underwent testing using Xpert MTB/RIF (Xpert) and smear microscopy. A retrospective cohort study was done to summarize the key findings. We verbally screened 5553 contacts for symptoms, CXR through private sector collaboration, Xpert, and smear microscopy. Overall, 1312 (23.6%) contacts screened positive. CXR alone identified 531 (40.5%) of them, 679 (51.8%) were symptom-positive only, while 102 (7.8%) were positive on both the symptom and CXR screen. Overall, 35 bacteriologically positive cases were identified (0.7%). A standard approach of symptoms screening followed by microscopy identified only 9 (25.7%) of the total number of bacteriologically positive cases, whereas the combination of a CRX screening followed by microscopy identified 13 (37.1%) of the cases. The algorithm of symptoms screening followed by Xpert testing, detected 20 cases, whereas the combination of symptoms and CXR followed by Xpert increased this number to 35 (75% increase compared to symptoms and Xpert). Optimal use of more sensitive screening tests, better diagnostic tests, and novel private sector engagement can improve diagnostic yield in a programmatic setting.

Active household contact screening for tuberculosis and provision of isoniazid preventive therapy to under-five children in Afghanistan

Objectives

This observational study analyzed the performance of the National TB Control Program (NTP) in Afghanistan in household contact screening from 2011 to 2018 and its use as an entry point for isoniazid preventive therapy (IPT), as well as the IPT completion rates for children under age five.

Methods

From 2011 to 2018, the Afghanistan NTP released guidelines for passive and active contact screening of bacteriologically confirmed TB cases. Health workers were trained in contact screening. Presumptive TB cases gave sputum for AFB smear microscopy; other diagnostics were used if patients could not produce sputum. Children under five (excluding those with active TB) were treated for latent TB infection. We calculated the yield and the number needed to screen and number needed to test to find a case of TB, as well as the rates of IPT initiation and completion.

Results

From 2011 to 2018, 142,797 bacteriologically confirmed TB cases were diagnosed in Afghanistan. The number of household members eligible for screening was estimated to be 856,782, of whom 586,292 (81%) were screened for TB and 117,643 (20.1%) were found to be presumptive TB cases. Among the cases screened, 10,896 TB cases (all forms) were diagnosed (1.85%, 95% CI 1.82–1.89), 54.4% in females. The number needed to screen to diagnose a single case of TB (all forms) was 53.8; the number needed to test was 10.7. Out of all children under five, 101,084 (85.9%) were initiated on IPT, and 69,273 (68.5%) completed treatment.

Conclusions

Program performance in contact screening in Afghanistan is high, at 81%, and the yield of TB is also high—close to 10 times higher than the national TB incidence rate. IPT initiation and completion rates are also high as compared to those of many other countries but need further improvement, especially for completion.

Use of Digital Technology to Enhance Tuberculosis Control: Scoping Review

Background

Tuberculosis (TB) is the leading cause of death from a single infectious agent, with around 1.5 million deaths reported in 2018, and is a major contributor to suffering worldwide, with an estimated 10 million new cases every year. In the context of the World Health Organization’s End TB strategy and the quest for digital innovations, there is a need to understand what is happening around the world regarding research into the use of digital technology for better TB care and control.

Objective

The purpose of this scoping review was to summarize the state of research on the use of digital technology to enhance TB care and control. This study provides an overview of publications covering this subject and answers 3 main questions: (1) to what extent has the issue been addressed in the scientific literature between January 2016 and March 2019, (2) which countries have been investing in research in this field, and (3) what digital technologies were used?

Methods

A Web-based search was conducted on PubMed and Web of Science. Studies that describe the use of digital technology with specific reference to keywords such as TB, digital health, eHealth, and mHealth were included. Data from selected studies were synthesized into 4 functions using narrative and graphical methods. Such digital health interventions were categorized based on 2 classifications, one by function and the other by targeted user.

Results

A total of 145 relevant studies were identified out of the 1005 published between January 2016 and March 2019. Overall, 72.4% (105/145) of the research focused on patient care and 20.7% (30/145) on surveillance and monitoring. Other programmatic functions 4.8% (7/145) and electronic learning 2.1% (3/145) were less frequently studied. Most digital health technologies used for patient care included primarily diagnostic 59.4% (63/106) and treatment adherence tools 40.6% (43/106). On the basis of the second type of classification, 107 studies targeted health care providers (107/145, 73.8%), 20 studies targeted clients (20/145, 13.8%), 17 dealt with data services (17/145, 11.7%), and 1 study was on the health system or resource management. The first authors’ affiliations were mainly from 3 countries: the United States (30/145 studies, 20.7%), China (20/145 studies, 13.8%), and India (17/145 studies, 11.7%). The researchers from the United States conducted their research both domestically and abroad, whereas researchers from China and India conducted all studies domestically.

Conclusions

The majority of research conducted between January 2016 and March 2019 on digital interventions for TB focused on diagnostic tools and treatment adherence technologies, such as video-observed therapy and SMS. Only a few studies addressed interventions for data services and health system or resource management.

A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis

We undertook a systematic review of the diagnostic accuracy of artificial intelligence-based software for identification of radiologic abnormalities (computer-aided detection, or CAD) compatible with pulmonary tuberculosis on chest x-rays (CXRs). We searched four databases for articles published between January 2005-February 2019. We summarized data on CAD type, study design, and diagnostic accuracy. We assessed risk of bias with QUADAS-2. We included 53 of the 4712 articles reviewed: 40 focused on CAD design methods (“Development” studies) and 13 focused on evaluation of CAD (“Clinical” studies). Meta-analyses were not performed due to methodological differences. Development studies were more likely to use CXR databases with greater potential for bias as compared to Clinical studies. Areas under the receiver operating characteristic curve (median AUC [IQR]) were significantly higher: in Development studies AUC: 0.88 [0.82–0.90]) versus Clinical studies (0.75 [0.66–0.87]; p-value 0.004); and with deep-learning (0.91 [0.88–0.99]) versus machine-learning (0.82 [0.75–0.89]; p = 0.001). We conclude that CAD programs are promising, but the majority of work thus far has been on development rather than clinical evaluation. We provide concrete suggestions on what study design elements should be improved.

Prevention of tuberculosis in household members: estimates of children eligible for treatment

Objective

To estimate of the number of children younger than 5 years who were household contacts of people with tuberculosis and were eligible for tuberculosis preventive treatment in 2017.

Methods

To estimate the number of eligible children, we obtained national values for the number of notified cases of bacteriologically confirmed pulmonary tuberculosis in 2017, the proportion of the population younger than 5 years in 2017 and average household size from published sources. We obtained global values for the number of active tuberculosis cases per household with an index case and for the prevalence of latent tuberculosis infection among children younger than 5 years who were household contacts of a tuberculosis case through systematic reviews, meta-analysis and Poisson regression models.

Findings

The estimated number of children younger than 5 years eligible for tuberculosis preventive treatment in 2017 globally was 1.27 million (95% uncertainty interval, UI: 1.24–1.31), which corresponded to an estimated global coverage of preventive treatment in children of 23% at best. By country, the estimated number ranged from less than one in the Bahamas, Iceland, Luxembourg and Malta to 350 000 (95% UI: 320 000–380 000) in India. Regionally, the highest estimates were for the World Health Organization (WHO) South-East Asia Region (510 000; 95% UI: 450 000–580 000) and the WHO African Region (470 000; 95% UI: 440 000–490 000).

Conclusion

Tuberculosis preventive treatment in children was underutilized globally in 2017. Treatment should be scaled up to help eliminate the pool of tuberculosis infection and achieve the End TB Strategy targets.

Tuberculosis and HIV-An Update on the "Cursed Duet" in Children

HIV and tuberculosis (TB) often occur together with each exacerbating the other. Improvements in vertical transmission prevention has reduced the number of HIV-infected children being born and early antiretroviral therapy (ART) protects against tuberculosis. However, with delayed HIV diagnosis, HIV-infected infants often present with tuberculosis co-infection. The number of HIV exposed uninfected children has increased and these infants have high exposure to TB and may be more immunologically vulnerable due to HIV exposure in utero. Bacillus Calmette-Guérin (BCG) immunization shortly after birth is essential for preventing severe TB in infancy. With early infant HIV diagnosis and ART, disseminated BCG is no longer an issue. TB prevention therapy should be implemented for contacts of a source case and for all HIV-infected individuals over a year of age. Although infection can be identified through skin tests or interferon gamma release assays, the non-availability of these tests should not preclude prevention therapy, once active TB has been excluded. Therapeutic options have moved from isoniazid only for 6-9 months to shorter regimens. Prevention therapy after exposure to a source case with resistant TB should also be implemented, but should not prevent pivotal prevention trials already under way. A microbiological diagnosis for TB remains the gold standard because of increasing drug resistance. Antiretroviral therapy for rifampicin co-treatment requires adaptation for those on lopinavir-ritonavir, which requires super-boosting with additional ritonavir. For those with drug resistant TB, the main problems are identification and overlapping toxicity between antiretroviral and anti-TB therapy. In spite of renewed focus and improved interventions, infants are still vulnerable to TB.

The performance and yield of tuberculosis testing algorithms using microscopy, chest x-ray, and Xpert MTB/RIF

Setting

The introduction of Xpert MTB/RIF (Xpert) and renewed interest in chest x-ray (CXR) for tuberculosis testing has provided additional choices to the smear-based diagnostic algorithms used by TB programs previously. More programmatic data is needed to better understand the implications of possible approaches.

Objective

We sought to evaluate how different testing algorithms using microscopy, Xpert and CXR impacted the number of people detected with TB in a district hospital in Nepal.

Design

Consecutively recruited patients with TB-related symptoms were offered smear microscopy, CXR and Xpert. We tested six hypothetical algorithms and compared yield, bacteriologically positive (Bac+) cases missed, and tests conducted.

Results

Among 929 patients, Bac+ prevalence was 17.3% (n = 161). Smear microscopy detected 121 (75.2% of Bac+). Depending on the radiologists' interpretation of CXR, Xpert testing could be reduced by (31%-60%). Smear microscopy reduced Xpert cartridge need slightly, but increased the overall diagnostic tests performed.

Conclusion

Xpert detected a large proportion of Bac+ TB cases missed by microscopy. CXR was useful in greatly reducing the number of diagnostic tests needed even among presumptive TB patients. Loose CXR readings should be used to identify more people for TB testing. More analysis of costs and standardized CXR reading should be considered.