A Blueprint to Address Research Gaps in the Development of Biomarkers for Pediatric Tuberculosis

Childhood tuberculosis contributes significantly to the global tuberculosis disease burden but remains challenging to diagnose due to inadequate methods of pathogen detection in paucibacillary pediatric samples and lack of a child-specific host biomarker to identify disease. Accurately diagnosing tuberculosis in children is required to improve case detection, surveillance, healthcare delivery, and effective advocacy. In May 2014, the National Institutes of Health convened a workshop including researchers in the field to delineate priorities to address this research gap. This blueprint describes the consensus from the workshop, identifies critical research steps to advance this field, and aims to catalyze efforts toward harmonization and collaboration in this are

Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis.

Background: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. Methods: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. Findings: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. Interpretation: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. Funding: WHO, US National Institutes of Health

Tuberculosis Caused by Mycobacterium africanum, United States, 2004–2013

Mycobacterium africanum is endemic to West Africa and causes tuberculosis (TB). We reviewed reported cases of TB in the United States during 2004–2013 that had lineage assigned by genotype (spoligotype and mycobacterial interspersed repetitive unit variable number tandem repeats). M. africanum caused 315 (0.4%) of 73,290 TB cases with lineage assigned by genotype. TB caused by M. africanum was associated more with persons from West Africa (adjusted odds ratio [aOR] 253.8, 95% CI 59.9–1,076.1) and US-born black persons (aOR 5.7, 95% CI 1.2–25.9) than with US-born white persons. TB caused by M. africanum did not show differences in clinical characteristics when compared with TB caused by M. tuberculosis. Clustered cases defined as >2 cases in a county with identical 24-locus mycobacterial interspersed repetitive unit genotypes, were less likely for M. africanum (aOR 0.1, 95% CI 0.1–0.4), which suggests that M. africanum is not commonly transmitted in the United States

Association between Mycobacterium tuberculosis complex phylogenetic lineage and acquired drug resistance.

BackgroundDevelopment of resistance to antituberculosis drugs during treatment (i.e., acquired resistance) can lead to emergence of resistant strains and consequent poor clinical outcomes. However, it is unknown whether Mycobacterium tuberculosis complex species and lineage affects the likelihood of acquired resistance.MethodsWe analyzed data from the U.S. National Tuberculosis Surveillance System and National Tuberculosis Genotyping Service for tuberculosis cases during 2004-2011 with assigned species and lineage and both initial and final drug susceptibility test results. We determined univariate associations between species and lineage of Mycobacterium tuberculosis complex bacteria and acquired resistance to isoniazid, rifamycins, fluoroquinolones, and second-line injectables. We used Poisson regression with backward elimination to generate multivariable models for acquired resistance to isoniazid and rifamycins.ResultsM. bovis was independently associated with acquired resistance to isoniazid (adjusted prevalence ratio = 8.46, 95% CI 2.96-24.14) adjusting for HIV status, and with acquired resistance to rifamycins (adjusted prevalence ratio = 4.53, 95% CI 1.29-15.90) adjusting for homelessness, HIV status, initial resistance to isoniazid, site of disease, and administration of therapy. East Asian lineage was associated with acquired resistance to fluoroquinolones (prevalence ratio = 6.10, 95% CI 1.56-23.83).ConclusionsWe found an association between mycobacterial species and lineage and acquired drug resistance using U.S. surveillance data. Prospective clinical studies are needed to determine the clinical significance of these findings, including whether rapid genotyping of isolates at the outset of treatment may benefit patient management

Assessing the impact of antiretroviral therapy on tuberculosis notification rates among people with HIV: a descriptive analysis of 23 countries in sub-Saharan Africa, 2010–2015

Abstract Background HIV is a major driver of the tuberculosis epidemic in sub-Saharan Africa. The population-level impact of antiretroviral therapy (ART) scale-up on tuberculosis rates in this region has not been well studied. We conducted a descriptive analysis to examine evidence of population-level effect of ART on tuberculosis by comparing trends in estimated tuberculosis notification rates, by HIV status, for countries in sub-Saharan Africa. Methods We estimated annual tuberculosis notification rates, stratified by HIV status during 2010–2015 using data from WHO, the Joint United Nations Programme on HIV/AIDS, and the United Nations Population Division. Countries were included in this analysis if they had ≥4 years of HIV prevalence estimates and ≥ 75% of tuberculosis patients with known HIV status. We compared tuberculosis notification rates among people living with HIV (PLHIV) and people without HIV via Wilcoxon rank sum test. Results Among 23 included countries, the median annual average change in tuberculosis notification rates among PLHIV during 2010–2015 was -5.7% (IQR -6.9 to -1.7%), compared to a median change of -2.3% (IQR -4.2 to -0.1%) among people without HIV (p-value = 0.0099). Among 11 countries with higher ART coverage, the median annual average change in TB notification rates among PLHIV was -6.8% (IQR -7.6 to -5.7%) compared to a median change of -2.1% (IQR -6.0 to 0.7%) for PLHIV in 12 countries with lower ART coverage (p = 0.0106). Conclusion Tuberculosis notification rates declined more among PLHIV than people without HIV, and have declined more in countries with higher ART coverage. These results are consistent with a population-level effect of ART on decreasing TB incidence among PLHIV. To further reduce TB incidence among PLHIV, additional scale-up of ART as well as greater use of isoniazid preventive therapy and active case-finding will be necessary

Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases

Tuberculin skin test result and risk of death among persons with active TB.

BACKGROUND: Although the tuberculin skin test (TST) is frequently used to aid in the diagnosis of tuberculosis (TB) disease and to identify persons with latent TB infection, it is an imperfect test and approximately 10-25% of persons with microbiologically confirmed TB disease have a negative TST. Previous studies have suggested that persons with a negative TST are more likely to present with severe TB disease and have an increased rate of TB-related death. METHODS: We analyzed culture-confirmed TB cases captured in US TB surveillance data from 1993 to 2008 and performed multivariate logistic regression analysis to determine the association between TST result and death. RESULTS: Of 284,866 cases of TB reported in the US, 58,180 persons were eligible for inclusion in the analysis and 3,270 of those persons died after initiating TB treatment. Persons with a negative TST accounted for only 14% of the eligible cases but accounted for 42% of the deaths. Persons with a TST≥15 mm had 67% lower odds of death than persons with a negative TST (adjusted odds ratio 0.33, 95% confidence interval 0.30-0.36). CONCLUSIONS: A negative TST is associated with an increased risk of death among persons with culture-confirmed TB disease, even after adjustment for HIV status, site of TB disease, sputum smear AFB status, drug susceptibility, age, sex, and origin of birth. In addition to indicating risk of developing disease, the TST may also be a marker for increased risk of death

Sociodemographic and clinical factors associated with acquired resistance to rifamycins (N = 4,005).

*<p>Regions defined by World Health Organization <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0083006#pone.0083006-World3" target="_blank">[37]</a>.</p><p>Missing values not reported in table.</p><p>Abbreviations: PR = prevalence ratio, CI = confidence interval, DST = drug susceptibility test, AFB = acid-fast bacilli, DOT = directly observed therapy.</p