Drug tolerance in replicating mycobacteria mediated by a macrophage-induced efflux mechanism.

Treatment of tuberculosis, a complex granulomatous disease, requires long-term multidrug therapy to overcome tolerance, an epigenetic drug resistance that is widely attributed to nonreplicating bacterial subpopulations. Here, we deploy Mycobacterium marinum-infected zebrafish larvae for in vivo characterization of antitubercular drug activity and tolerance. We describe the existence of multidrug-tolerant organisms that arise within days of infection, are enriched in the replicating intracellular population, and are amplified and disseminated by the tuberculous granuloma. Bacterial efflux pumps that are required for intracellular growth mediate this macrophage-induced tolerance. This tolerant population also develops when Mycobacterium tuberculosis infects cultured macrophages, suggesting that it contributes to the burden of drug tolerance in human tuberculosis. Efflux pump inhibitors like verapamil reduce this tolerance. Thus, the addition of this currently approved drug or more specific efflux pump inhibitors to standard antitubercular therapy should shorten the duration of curative treatment.

Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas.

BACKGROUND: Reductions in tuberculosis (TB) transmission have been instrumental in lowering TB incidence in the United States. Sustaining and augmenting these reductions are key public health priorities. METHODS: We fit mechanistic transmission models to distributions of genotype clusters of TB cases reported to the Centers for Disease Control and Prevention during 2012-2016 in the United States and separately in California, Florida, New York, and Texas. We estimated the mean number of secondary cases generated per infectious case (R0) and individual-level heterogeneity in R0 at state and national levels and assessed how different definitions of clustering affected these estimates. RESULTS: In clusters of genotypically linked TB cases that occurred within a state over a 5-year period (reference scenario), the estimated R0 was 0.29 (95% confidence interval [CI], .28-.31) in the United States. Transmission was highly heterogeneous; 0.24% of simulated cases with individual R0 >10 generated 19% of all recent secondary transmissions. R0 estimate was 0.16 (95% CI, .15-.17) when a cluster was defined as cases occurring within the same county over a 3-year period. Transmission varied across states: estimated R0s were 0.34 (95% CI, .3-.4) in California, 0.28 (95% CI, .24-.36) in Florida, 0.19 (95% CI, .15-.27) in New York, and 0.38 (95% CI, .33-.46) in Texas. CONCLUSIONS: TB transmission in the United States is characterized by pronounced heterogeneity at the individual and state levels. Improving detection of transmission clusters through incorporation of whole-genome sequencing and identifying the drivers of this heterogeneity will be essential to reducing TB transmission.

Decrease in Tuberculosis Cases during COVID-19 Pandemic as Reflected by Outpatient Pharmacy Data, United States, 2020.

We analyzed a pharmacy dataset to assess the 20% decline in tuberculosis (TB) cases reported to the US National Tuberculosis Surveillance System (NTSS) during the coronavirus disease pandemic in 2020 compared with the 2016-2019 average. We examined the correlation between TB medication dispensing data to TB case counts in NTSS and used a seasonal autoregressive integrated moving average model to predict expected 2020 counts. Trends in the TB medication data were correlated with trends in NTSS data during 2006-2019. There were fewer prescriptions and cases in 2020 than would be expected on the basis of previous trends. This decrease was particularly large during April-May 2020. These data are consistent with NTSS data, suggesting that underreporting is not occurring but not ruling out underdiagnosis or actual decline. Understanding the mechanisms behind the 2020 decline in reported TB cases will help TB programs better prepare for postpandemic cases.

Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters.

The early identification of clusters of persons with tuberculosis (TB) that will grow to become outbreaks creates an opportunity for intervention in preventing future TB cases. We used surveillance data (2009-2018) from the United States, statistically derived definitions of unexpected growth, and machine-learning techniques to predict which clusters of genotype-matched TB cases are most likely to continue accumulating cases above expected growth within a 1-year follow-up period. We developed a model to predict which clusters are likely to grow on a training and testing data set that was generalizable to a validation data set. Our model showed that characteristics of clusters were more important than the social, demographic, and clinical characteristics of the patients in those clusters. For instance, the time between cases before unexpected growth was identified as the most important of our predictors. A faster accumulation of cases increased the probability of excess growth being predicted during the follow-up period. We have demonstrated that combining the characteristics of clusters and cases with machine learning can add to existing tools to help prioritize which clusters may benefit most from public health interventions. For example, consideration of an entire cluster, not only an individual patient, may assist in interrupting ongoing transmission.

A Cluster-based Method to Quantify Individual Heterogeneity in Tuberculosis Transmission.

BACKGROUND: Recent evidence suggests transmission of Mycobacterium tuberculosis (Mtb) may be characterized by extreme individual heterogeneity in secondary cases (i.e., few cases account for the majority of transmission). Such heterogeneity implies outbreaks are rarer but more extensive and has profound implications in infectious disease control. However, discrete person-to-person transmission events in tuberculosis (TB) are often unobserved, precluding our ability to directly quantify individual heterogeneity in TB epidemiology. METHODS: We used a modified negative binomial branching process model to quantify the extent of individual heterogeneity using only observed transmission cluster size distribution data (i.e., the simple sum of all cases in a transmission chain) without knowledge of individual-level transmission events. The negative binomial parameter k quantifies the extent of individual heterogeneity (generally, indicates extensive heterogeneity, and as transmission becomes more homogenous). We validated the robustness of the inference procedure considering common limitations affecting cluster size data. Finally, we demonstrate the epidemiologic utility of this method by applying it to aggregate US molecular surveillance data from the US Centers for Disease Control and Prevention. RESULTS: The cluster-based method reliably inferred k using TB transmission cluster data despite a high degree of bias introduced into the model. We found that the TB transmission in the United States was characterized by a high propensity for extensive outbreaks (; 95% confidence interval = 0.09, 0.10). CONCLUSIONS: The proposed method can accurately quantify critical parameters that govern TB transmission using simple, more easily obtainable cluster data to improve our understanding of TB epidemiology.

Effect of Routine Gastric Residual Aspiration on the Preterm Infant Fecal Microbiome.

OBJECTIVE: Enteral feeding tubes are used in neonatal intensive care units (NICUs) to assess feeding tolerance by utilizing preprandial gastric residual aspiration. This study evaluates the effect of gastric residual aspiration on the preterm infant fecal microbiome and gastrointestinal inflammation. STUDY DESIGN: Fifty-one very low birth weight (VLBW) infants (≤32 weeks' gestational age and ≤1,250 g) enrolled in a larger single-center randomized controlled trial evaluating the effects of routine and nonroutine gastric residual aspiration were selected for further analysis. Of those infants, 30 had microbiome analysis performed on stools collected at 6 weeks by sequencing the bacterial V1 to V3 variable regions of the genes encoding for 16S rRNA. In an additional 21 infants, stool samples collected at 3 and 6 weeks were analyzed for intestinal inflammation using a cytokine multiplex panel. RESULTS: Microbial communities between groups were not distinct from each other and there was no difference in intestinal inflammation between groups. Analyses using gene expression packages DESeq2 and edgeR produced statistically significant differences in several taxa, possibly indicating a more commensal intestinal microbiome in infants not undergoing gastric residual aspiration. CONCLUSION: Omission of routine gastric residual aspiration was not associated with intestinal dysbiosis or inflammation, providing additional evidence that monitors preprandial gastric residuals is unnecessary. KEY POINTS: · Omission of routine gastric residual aspiration was not associated with intestinal dysbiosis or inflammation.. · Existing literature indicates preprandial gastric aspiration does not reliably correlate with development of necrotizing enterocolitis but does correlate with delayed enteral nutrition.. · Further study is required but this data that suggest monitoring preprandial gastric residuals are unnecessary..

Prevalence of Latent Tuberculosis Infection Among Non-US-Born Persons by Country of Birth-United States, 2012-2017.

BACKGROUND: Most tuberculosis (TB) disease in the United States (US) is attributed to reactivation of remotely acquired latent TB infection (LTBI) in non-US-born persons who were likely infected with Mycobacterium tuberculosis in their countries of birth. Information on LTBI prevalence by country of birth could help guide local providers and health departments to scale up the LTBI screening and preventive treatment needed to advance progress toward TB elimination. METHODS: A total of 13 805 non-US-born persons at high risk of TB infection or progression to TB disease were screened for LTBI at 16 clinical sites located across the United States with a tuberculin skin test, QuantiFERON Gold In-Tube test, and T-SPOT.TB test. Bayesian latent class analysis was applied to test results to estimate LTBI prevalence and associated credible intervals (CrIs) for each country or world region of birth. RESULTS: Among the study population, the estimated LTBI prevalence was 31% (95% CrI, 26%-35%). Country-of-birth-level LTBI prevalence estimates were highest for persons born in Haiti, Peru, Somalia, Ethiopia, Vietnam, and Bhutan, ranging from 42% to 55%. LTBI prevalence estimates were lowest for persons born in Colombia, Malaysia, and Thailand, ranging from 8% to 13%. CONCLUSIONS: LTBI prevalence in persons born outside the US varies widely by country. These estimates can help target community outreach efforts to the highest-risk groups.

Timing of Community Mitigation and Changes in Reported COVID-19 and Community Mobility - Four U.S. Metropolitan Areas, February 26-April 1, 2020.

Community mitigation activities (also referred to as nonpharmaceutical interventions) are actions that persons and communities can take to slow the spread of infectious diseases. Mitigation strategies include personal protective measures (e.g., handwashing, cough etiquette, and face coverings) that persons can use at home or while in community settings; social distancing (e.g., maintaining physical distance between persons in community settings and staying at home); and environmental surface cleaning at home and in community settings, such as schools or workplaces. Actions such as social distancing are especially critical when medical countermeasures such as vaccines or therapeutics are not available. Although voluntary adoption of social distancing by the public and community organizations is possible, public policy can enhance implementation. The CDC Community Mitigation Framework (1) recommends a phased approach to implementation at the community level, as evidence of community spread of disease increases or begins to decrease and according to severity. This report presents initial data from the metropolitan areas of San Francisco, California; Seattle, Washington; New Orleans, Louisiana; and New York City, New York* to describe the relationship between timing of public policy measures, community mobility (a proxy measure for social distancing), and temporal trends in reported coronavirus disease 2019 (COVID-19) cases. Community mobility in all four locations declined from February 26, 2020 to April 1, 2020, decreasing with each policy issued and as case counts increased. This report suggests that public policy measures are an important tool to support social distancing and provides some very early indications that these measures might help slow the spread of COVID-19.

COVID-19 Among American Indian and Alaska Native Persons - 23 States, January 31-July 3, 2020.

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22†-July 3, 2020 were analyzed. The analysis was limited to 23 states§ with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.

Microbiota-Derived Metabolic Factors Reduce Campylobacteriosis in Mice.

BACKGROUND & AIMS: Campylobacter jejuni, a prevalent foodborne bacterial pathogen, exploits the host innate response to induce colitis. Little is known about the roles of microbiota in C jejuni-induced intestinal inflammation. We investigated interactions between microbiota and intestinal cells during C jejuni infection of mice. METHODS: Germ-free C57BL/6 Il10-/- mice were colonized with conventional microbiota and infected with a single dose of C jejuni (109 colony-forming units/mouse) via gavage. Conventional microbiota were cultured under aerobic, microaerobic, or anaerobic conditions and orally transplanted into germ-free Il10-/- mice. Colon tissues were collected from mice and analyzed by histology, real-time polymerase chain reaction, and immunoblotting. Fecal microbiota and bile acids were analyzed with 16S sequencing and high-performance liquid chromatography with mass spectrometry, respectively. RESULTS: Introduction of conventional microbiota reduced C jejuni-induced colitis in previously germ-free Il10-/- mice, independent of fecal load of C jejuni, accompanied by reduced activation of mammalian target of rapamycin. Microbiota transplantation and 16S ribosomal DNA sequencing experiments showed that Clostridium XI, Bifidobacterium, and Lactobacillus were enriched in fecal samples from mice colonized with microbiota cultured in anaerobic conditions (which reduce colitis) compared with mice fed microbiota cultured under aerobic conditions (susceptible to colitis). Oral administration to mice of microbiota-derived secondary bile acid sodium deoxycholate, but not ursodeoxycholic acid or lithocholic acid, reduced C jejuni-induced colitis. Depletion of secondary bile acid-producing bacteria with antibiotics that kill anaerobic bacteria (clindamycin) promoted C jejuni-induced colitis in specific pathogen-free Il10-/- mice compared with the nonspecific antibiotic nalidixic acid; colitis induction by antibiotics was associated with reduced level of luminal deoxycholate. CONCLUSIONS: We identified a mechanism by which the microbiota controls susceptibility to C jejuni infection in mice, via bacteria-derived secondary bile acids.

Intestinal microbiota enhances pancreatic carcinogenesis in preclinical models.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the United States yet data are scant regarding host factors influencing pancreatic carcinogenesis. Increasing evidence support the role of the host microbiota in carcinogenesis but its role in PDAC is not well established. Herein, we report that antibiotic-mediated microbial depletion of KrasG12D/PTENlox/+ mice showed a decreased proportion of poorly differentiated tumors compared to microbiota-intact KrasG12D/PTENlox/+ mice. Subsequent 16S rRNA PCR showed that ~50% of KrasG12D/PTENlox/+ mice with PDAC harbored intrapancreatic bacteria. To determine if a similar observation in humans correlates with presence of PDAC, benign and malignant human pancreatic surgical specimens demonstrated a microbiota by 16S bacterial sequencing and culture confirmation. However, the microbial composition did not differentiate PDAC from non-PDAC tissue. Furthermore, murine pancreas did not naturally acquire a pancreatic microbiota, as germ-free mice transferred to specific pathogen-free housing failed to acquire intrapancreatic bacteria over time, which was not augmented by a murine model of colitis. Finally, antibiotic-mediated microbial depletion of Nod-SCID mice, compared to microbiota-intact, showed increased time to PDAC xenograft formation, smaller tumors, and attenuated growth. Interestingly, both xenograft cohorts were devoid of intratumoral bacteria by 16S rRNA PCR, suggesting that intrapancreatic/intratumoral microbiota is not the sole driver of PDAC acceleration. Xenografts from microbiota-intact mice demonstrated innate immune suppression by immunohistochemistry and differential regulation of oncogenic pathways as determined by RNA sequencing. Our work supports a long-distance role of the intestinal microbiota on PDAC progression and opens new research avenues regarding pancreatic carcinogenesis.

Bacterial subversion of cAMP signalling inhibits cathelicidin expression, which is required for innate resistance to Mycobacterium tuberculosis.

Antimicrobial peptides such as cathelicidins are important components of innate immune defence against inhaled microorganisms, and have shown antimicrobial activity against Mycobacterium tuberculosis in in vitro models. Despite this, little is known about the regulation and expression of cathelicidin during tuberculosis in vivo. We sought to determine whether the cathelicidin-related antimicrobial peptide gene (Cramp), the murine functional homologue of the human cathelicidin gene (CAMP or LL-37), is required for regulation of protective immunity during M. tuberculosis infection in vivo. We used Cramp-/- mice in a validated model of pulmonary tuberculosis, and conducted cell-based assays with macrophages from these mice. We evaluated the in vivo susceptibility of Cramp-/- mice to infection, and also dissected various pro-inflammatory immune responses against M. tuberculosis. We observed increased susceptibility of Cramp-/- mice to M. tuberculosis as compared with wild-type mice. Macrophages from Cramp-/- mice were unable to control M. tuberculosis growth in an in vitro infection model, were deficient in intracellular calcium influx, and were defective in stimulating T cells. Additionally, CD4+ and CD8+ T cells from Cramp-/- mice produced less interferon-ß upon stimulation. Furthermore, bacterial-derived cAMP modulated cathelicidin expression in macrophages. Our results demonstrate that cathelicidin is required for innate resistance to M. tuberculosis in a relevant animal model and is a key mediator in regulation of the levels of pro-inflammatory cytokines by calcium and cyclic nucleotides. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Suppressor Cell-Depleting Immunotherapy With Denileukin Diftitox is an Effective Host-Directed Therapy for Tuberculosis.

Host-directed therapies that augment host immune effector mechanisms may serve as important adjunctive therapies for tuberculosis treatment. We evaluated the activity of denileukin diftitox in an acute mouse model of tuberculosis (TB) infection and analyzed the cellular composition and bacterial burden in lungs and spleens. These in vivo studies show that denileukin diftitox potentiates standard TB treatment in the mouse model, an effect which may be due to depletion of T-regulatory and myeloid-derived suppressor cells during TB infection. Our results indicate that denileukin diftitox and other suppressor cell-depleting therapies may be useful adjunctive, host-directed therapies for TB.

Cathepsin K Contributes to Cavitation and Collagen Turnover in Pulmonary Tuberculosis.

Cavitation in tuberculosis enables highly efficient person-to-person aerosol transmission. We performed transcriptomics in the rabbit cavitary tuberculosis model. Among 17 318 transcripts, we identified 22 upregulated proteases. Five type I collagenases were overrepresented: cathepsin K (CTSK), mast cell chymase-1 (CMA1), matrix metalloproteinase 1 (MMP-1), MMP-13, and MMP-14. Studies of collagen turnover markers, specifically, collagen type I C-terminal propeptide (CICP), urinary deoxypyridinoline (DPD), and urinary helical peptide, revealed that cavitation in tuberculosis leads to both type I collagen destruction and synthesis and that proteases other than MMP-1, MMP-13, and MMP-14 are involved, suggesting a key role for CTSK. We confirmed the importance of CTSK upregulation in human lung specimens, using immunohistochemical analysis, which revealed perigranulomatous staining for CTSK, and we showed that CTSK levels were increased in the serum of patients with tuberculosis, compared with those in controls (3.3 vs 0.3 ng/mL; P = .005).

Mycobacterium tuberculosis dysregulates MMP/TIMP balance to drive rapid cavitation and unrestrained bacterial proliferation.

Active tuberculosis (TB) often presents with advanced pulmonary disease, including irreversible lung damage and cavities. Cavitary pathology contributes to antibiotic failure, transmission, morbidity and mortality. Matrix metalloproteinases (MMPs), in particular MMP-1, are implicated in TB pathogenesis. We explored the mechanisms relating MMP/TIMP imbalance to cavity formation in a modified rabbit model of cavitary TB. Our model resulted in consistent progression of consolidation to human-like cavities (100% by day 28), with resultant bacillary burdens (>10(7) CFU/g) far greater than those found in matched granulomatous tissue (10(5) CFU/g). Using a novel, breath-hold computed tomography (CT) scanning and image analysis protocol, we showed that cavities developed rapidly from areas of densely consolidated tissue. Radiological change correlated with a decrease in functional lung tissue, as estimated by changes in lung density during controlled pulmonary expansion (R(2) = 0.6356, p < 0.0001). We demonstrated that the expression of interstitial collagenase (MMP-1) was specifically greater in cavitary compared to granulomatous lesions (p < 0.01), and that TIMP-3 significantly decreased at the cavity surface. Our findings demonstrated that an MMP-1/TIMP imbalance is associated with the progression of consolidated regions to cavities containing very high bacterial burdens. Our model provided mechanistic insight, correlating with human disease at the pathological, microbiological and molecular levels. It also provided a strategy to investigate therapeutics in the context of complex TB pathology. We used these findings to predict a MMP/TIMP balance in active TB and confirmed this in human plasma, revealing the potential of MMP/TIMP levels as key components of a diagnostic matrix aimed at distinguishing active from latent TB (PPV = 92.9%, 95% CI 66.1-99.8%, NPV = 85.6%; 95% CI 77.0-91.9%).

Mutation of Rv2887, a marR-like gene, confers Mycobacterium tuberculosis resistance to an imidazopyridine-based agent.

Drug resistance is a major problem in Mycobacterium tuberculosis control, and it is critical to identify novel drug targets and new antimycobacterial compounds. We have previously identified an imidazo[1,2-a]pyridine-4-carbonitrile-based agent, MP-III-71, with strong activity against M. tuberculosis. In this study, we evaluated mechanisms of resistance to MP-III-71. We derived three independent M. tuberculosis mutants resistant to MP-III-71 and conducted whole-genome sequencing of these mutants. Loss-of-function mutations in Rv2887 were common to all three MP-III-71-resistant mutants, and we confirmed the role of Rv2887 as a gene required for MP-III-71 susceptibility using complementation. The Rv2887 protein was previously unannotated, but domain and homology analyses suggested it to be a transcriptional regulator in the MarR (multiple antibiotic resistance repressor) family, a group of proteins first identified in Escherichia coli to negatively regulate efflux pumps and other mechanisms of multidrug resistance. We found that two efflux pump inhibitors, verapamil and chlorpromazine, potentiate the action of MP-III-71 and that mutation of Rv2887 abrogates their activity. We also used transcriptome sequencing (RNA-seq) to identify genes which are differentially expressed in the presence and absence of a functional Rv2887 protein. We found that genes involved in benzoquinone and menaquinone biosynthesis were repressed by functional Rv2887. Thus, inactivating mutations of Rv2887, encoding a putative MarR-like transcriptional regulator, confer resistance to MP-III-71, an effective antimycobacterial compound that shows no cross-resistance to existing antituberculosis drugs. The mechanism of resistance of M. tuberculosis Rv2887 mutants may involve efflux pump upregulation and also drug methylation.

Efflux inhibition with verapamil potentiates bedaquiline in Mycobacterium tuberculosis.

Drug efflux is an important resistance mechanism in Mycobacterium tuberculosis. We found that verapamil, an efflux inhibitor, profoundly decreases the MIC of bedaquiline and clofazimine to M. tuberculosis by 8- to 16-fold. This exquisite susceptibility was noted among drug-susceptible and drug-resistant clinical isolates. Thus, efflux inhibition is an important sensitizer of bedaquiline and clofazimine, and efflux may emerge as a resistance mechanism to these drugs.

Risk of tuberculosis reactivation with tofacitinib (CP-690550).

Individuals with latent tuberculosis infection (LTBI) live with a risk of reactivation, and several treatments for chronic inflammatory conditions are highly associated with such reactivation. A new Janus kinase inhibitor, tofacitinib (CP-690550), has shown promising results for treatment of inflammatory disorders, thus raising concerns of risk of active tuberculosis. Our goal was to characterize the impact of tofacitinib on LTBI using a mouse model of contained tuberculosis. Our data indicate that tofacitinib reduces host containment of Mycobacterium tuberculosis and promotes bacterial replication in the lungs, suggesting tuberculosis reactivation. Tofacitinib may carry a significant risk for LTBI reactivation in humans.

Using Electronic Health Record Data to Measure the Latent Tuberculosis Infection Care Cascade in Safety-Net Primary Care Clinics.

Introduction: Prevention of tuberculosis disease through diagnosis and treatment of latent tuberculosis infection is critical for achieving tuberculosis elimination in the U.S. Diagnosis and treatment of latent tuberculosis infection in safety-net primary care settings that serve patients at risk for tuberculosis may increase uptake of this prevention effort and accelerate progress toward elimination. Optimizing tuberculosis prevention in these settings requires measuring the latent tuberculosis infection care cascade (testing, diagnosis, and treatment) and identifying gaps to develop solutions to overcome barriers. We used electronic health record data to describe the latent tuberculosis infection care cascade and identify gaps among a network of safety-net primary care clinics. Methods: Electronic health record data for patients seen in the OCHIN Clinical Network, the largest network of safety-net clinics in the U.S., between 2012 and 2019 were extracted. electronic health record data were used to measure the latent tuberculosis infection care cascade: patients who met tuberculosis screening criteria on the basis of current recommendations were tested for tuberculosis infection, diagnosed with latent tuberculosis infection, and prescribed treatment for latent tuberculosis infection. Outcomes were stratified by diagnostic test and treatment regimen. Results: Among 1.9 million patients in the analytic cohort, 43.5% met tuberculosis screening criteria, but only 21.4% were tested for latent tuberculosis infection; less than half (40.4%) were tested using an interferon-gamma release assay. Among those with a valid result, 10.5% were diagnosed with latent tuberculosis infection, 29.1% of those were prescribed latent tuberculosis infection treatment, and only 33.6% were prescribed a recommended rifamycin-based regimen. Conclusions: Electronic health record data can be used to measure the latent tuberculosis infection care cascade. A large proportion of patients in this safety-net clinical network are at high risk for tuberculosis infection. Addressing identified gaps in latent tuberculosis infection testing and treatment may have a direct impact on improving tuberculosis prevention in primary care clinics and accelerate progress toward elimination.

Examining Test Cutoffs to Optimize Diagnosis of Latent Tuberculosis Infection in People Born Outside the United States.

Rationale: Detection of latent tuberculosis infection (LTBI) in persons born in high tuberculosis (TB) incidence countries living in low TB incidence countries is key to TB elimination in low-incidence countries. Optimizing LTBI tests is critical to targeting treatment. Objectives: To compare the sensitivity and specificity of tuberculin skin test (TST) and two interferon-γ release assays at different cutoffs and of a single test versus dual testing. Methods: We examined a subset (N = 14,167) of a prospective cohort of people in the United States tested for LTBI. We included non-U.S.-born, human immunodeficiency virus-seronegative people ages 5 years and older with valid TST, QuantiFERON-TB Gold-in-Tube (QFT), and T-SPOT.TB (TSPOT) results. The sensitivity/specificity of different test cutoffs and test combinations, obtained from a Bayesian latent class model, were used to construct receiver operating characteristic (ROC) curves and assess the area under the curve (AUC) for each test. The sensitivity/specificity of dual testing was calculated. Results: The AUC of the TST ROC curve was 0.81 (95% credible interval (CrI), 0.78-0.86), with sensitivity/specificity at cutoffs of 5, 10, and 15 mm of 86.5%/61.6%, 81.7%/71.3%, and 55.6%/88.0%, respectively. The AUC of the QFT ROC curve was 0.89 (95% CrI, 0.86-0.93), with sensitivity/specificity at cutoffs of 0.35, 0.7, and 1.0 IU/mL of 77.7%/98.3%, 66.9%/99.1%, and 61.5%/99.4%. The AUC of the TSPOT ROC curve was 0.92 (95% CrI, 0.88-0.96) with sensitivity/specificity for five, six, seven, and eight spots of 79.2%/96.7%, 76.8%/97.7%, 74.0%/98.6%, and 71.8%/99.5%. Sensitivity/specificity of TST-QFT, TST-TSPOT, and QFT-TSPOT at standard cutoffs were 73.1%/99.4%, 64.8%/99.8%, and 65.3%/100%. Conclusion: Interferon-γ release assays have a better predictive ability than TST in people at high risk of LTBI.