The identification of sensitive, specific and reliable biomarkers that can be quantified in the early phases of tuberculosis treatment and predictive of long-term outcome is key for the development of an effective short-course treatment regimen. Time-to-positivity (TTP), a biomarker of treatment outcome against Mycobacterium tuberculosis, measures longitudinal bacterial growth in Mycobacteria Growth Indicator Tube broth culture and may be predictive of standard time-to-stable-culture-conversion (TSCC). In two randomized phase 2b trials investigating dose-ranging rifapentine (Study 29 and 29x), 662 participants had sputum collected over six months where TTP, TSCC and time-to-culture-conversion were quantified. The goals of this post hoc study were to characterize longitudinal TTP profiles and to identify individual patient characteristics associated with delayed time to culture conversion. In order to do so, a nonlinear mixed-effects model describing longitudinal TTP was built. Independent variables associated with increased bacterial clearance (increased TTP), assessed by subject-specific and population-level trajectories, were higher rifapentine exposure, lower baseline grade of sputum acid-fast bacilli smear, absence of productive cough, and lower extent of lung infiltrates on radiographs. Importantly, sensitivity analysis revealed that major learning milestones in phase 2b trials, such as significant exposure-response and covariate relationships, could be detected using truncated TTP data as early as 6 weeks from start of treatment, suggesting alternative phase 2B study designs. The TTP model built depicts a novel phase 2B surrogate endpoint that can inform early assessment of experimental treatment efficacy and treatment failure or relapse in patients treated with shorter and novel TB treatment regimens, improving efficiency of phase 2 clinical trials.

INTRODUCTION: Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness. METHODS: We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions. RESULTS: Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions). CONCLUSION: Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

IMPORTANCE: Information on underlying conditions and severe COVID-19 illness among children is limited. OBJECTIVE: To examine the risk of severe COVID-19 illness among children associated with underlying medical conditions and medical complexity. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included patients aged 18 years and younger with International Statistical Classification of Diseases, Tenth Revision, Clinical Modification code U07.1 (COVID-19) or B97.29 (other coronavirus) during an emergency department or inpatient encounter from March 2020 through January 2021. Data were collected from the Premier Healthcare Database Special COVID-19 Release, which included data from more than 800 US hospitals. Multivariable generalized linear models, controlling for patient and hospital characteristics, were used to estimate adjusted risk of severe COVID-19 illness associated with underlying medical conditions and medical complexity. EXPOSURES: Underlying medical conditions and medical complexity (ie, presence of complex or noncomplex chronic disease). MAIN OUTCOMES AND MEASURES: Hospitalization and severe illness when hospitalized (ie, combined outcome of intensive care unit admission, invasive mechanical ventilation, or death). RESULTS: Among 43 465 patients with COVID-19 aged 18 years or younger, the median (interquartile range) age was 12 (4-16) years, 22 943 (52.8%) were female patients, and 12 491 (28.7%) had underlying medical conditions. The most common diagnosed conditions were asthma (4416 [10.2%]), neurodevelopmental disorders (1690 [3.9%]), anxiety and fear-related disorders (1374 [3.2%]), depressive disorders (1209 [2.8%]), and obesity (1071 [2.5%]). The strongest risk factors for hospitalization were type 1 diabetes (adjusted risk ratio [aRR], 4.60; 95% CI, 3.91-5.42) and obesity (aRR, 3.07; 95% CI, 2.66-3.54), and the strongest risk factors for severe COVID-19 illness were type 1 diabetes (aRR, 2.38; 95% CI, 2.06-2.76) and cardiac and circulatory congenital anomalies (aRR, 1.72; 95% CI, 1.48-1.99). Prematurity was a risk factor for severe COVID-19 illness among children younger than 2 years (aRR, 1.83; 95% CI, 1.47-2.29). Chronic and complex chronic disease were risk factors for hospitalization, with aRRs of 2.91 (95% CI, 2.63-3.23) and 7.86 (95% CI, 6.91-8.95), respectively, as well as for severe COVID-19 illness, with aRRs of 1.95 (95% CI, 1.69-2.26) and 2.86 (95% CI, 2.47-3.32), respectively. CONCLUSIONS AND RELEVANCE: This cross-sectional study found a higher risk of severe COVID-19 illness among children with medical complexity and certain underlying conditions, such as type 1 diabetes, cardiac and circulatory congenital anomalies, and obesity. Health care practitioners could consider the potential need for close observation and cautious clinical management of children with these conditions and COVID-19.

BACKGROUND: Late sequelae of COVID-19 have been reported; however, few studies have investigated the time-course or incidence of late new COVID-19-related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed the type, association, and timing of post-COVID conditions following COVID-19 diagnosis. METHODS: Using the Premier Healthcare Database Special COVID-19 Release (PHD-SR) (release date, October 20, 2020) data, during March-June 2020, 27,589 inpatients and 46,857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted odds ratios were calculated to assess for late conditions that were more common in case-patients compared with control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31-120 days following a COVID-19 encounter. RESULTS: During 31-120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced at least one of five post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced at least one of ten post-COVID conditions. During 31-60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and were also more likely to experience a range of conditions affecting multiple body systems (e.g. nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal system symptoms) than outpatient control-patients. Children with COVID-19 were not more likely to experience late conditions than children without COVID-19. CONCLUSIONS: These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform health care practice and resource planning for follow-up COVID-19 care.

BACKGROUND: Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. METHODS: Using data from the Premier Healthcare Database on 181( )813 hospitalized adults diagnosed with COVID-19 during March-September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. RESULTS: Overall, 84( )497 (47%) patients were admitted to the ICU, 29( )078 (16%) received IMV, and 27( )864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92-0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09-1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09-1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06-1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. CONCLUSIONS: These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.

Coronavirus disease 2019 (COVID-19) is a complex clinical illness with potential complications that might require ongoing clinical care (1-3). Few studies have investigated discharge patterns and hospital readmissions among large groups of patients after an initial COVID-19 hospitalization (4-7). Using electronic health record and administrative data from the Premier Healthcare Database,* CDC assessed patterns of hospital discharge, readmission, and demographic and clinical characteristics associated with hospital readmission after a patient's initial COVID-19 hospitalization (index hospitalization). Among 126,137 unique patients with an index COVID-19 admission during March-July 2020, 15% died during the index hospitalization. Among the 106,543 (85%) surviving patients, 9% (9,504) were readmitted to the same hospital within 2 months of discharge through August 2020. More than a single readmission occurred among 1.6% of patients discharged after the index hospitalization. Readmissions occurred more often among patients discharged to a skilled nursing facility (SNF) (15%) or those needing home health care (12%) than among patients discharged to home or self-care (7%). The odds of hospital readmission increased with age among persons aged ≥65 years, presence of certain chronic conditions, hospitalization within the 3 months preceding the index hospitalization, and if discharge from the index hospitalization was to a SNF or to home with health care assistance. These results support recent analyses that found chronic conditions to be significantly associated with hospital readmission (6,7) and could be explained by the complications of underlying conditions in the presence of COVID-19 (8), COVID-19 sequelae (3), or indirect effects of the COVID-19 pandemic (9). Understanding the frequency of, and risk factors for, readmission can inform clinical practice, discharge disposition decisions, and public health priorities such as health care planning to ensure availability of resources needed for acute and follow-up care of COVID-19 patients. With the recent increases in cases nationwide, hospital planning can account for these increasing numbers along with the potential for at least 9% of patients to be readmitted, requiring additional beds and resources.

Hydroxychloroquine and chloroquine, primarily used to treat autoimmune diseases and to prevent and treat malaria, received national attention in early March 2020, as potential treatment and prophylaxis for coronavirus disease 2019 (COVID-19) (1). On March 20, the Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for chloroquine phosphate and hydroxychloroquine sulfate in the Strategic National Stockpile to be used by licensed health care providers to treat patients hospitalized with COVID-19 when the providers determine the potential benefit outweighs the potential risk to the patient.* Following reports of cardiac and other adverse events in patients receiving hydroxychloroquine for COVID-19 (2), on April 24, 2020, FDA issued a caution against its use(†) and on June 15, rescinded its EUA for hydroxychloroquine from the Strategic National Stockpile.(§) Following the FDA's issuance of caution and EUA rescindment, on May 12 and June 16, the federal COVID-19 Treatment Guidelines Panel issued recommendations against the use of hydroxychloroquine or chloroquine to treat COVID-19; the panel also noted that at that time no medication could be recommended for COVID-19 pre- or postexposure prophylaxis outside the setting of a clinical trial (3). However, public discussion concerning the effectiveness of these drugs on outcomes of COVID-19 (4,5), and clinical trials of hydroxychloroquine for prophylaxis of COVID-19 continue.(¶) In response to recent reports of notable increases in prescriptions for hydroxychloroquine or chloroquine (6), CDC analyzed outpatient retail pharmacy transaction data to identify potential differences in prescriptions dispensed by provider type during January-June 2020 compared with the same period in 2019. Before 2020, primary care providers and specialists who routinely prescribed hydroxychloroquine, such as rheumatologists and dermatologists, accounted for approximately 97% of new prescriptions. New prescriptions by specialists who did not typically prescribe these medications (defined as specialties accounting for ≤2% of new prescriptions before 2020) increased from 1,143 prescriptions in February 2020 to 75,569 in March 2020, an 80-fold increase from March 2019. Although dispensing trends are returning to prepandemic levels, continued adherence to current clinical guidelines for the indicated use of these medications will ensure their availability and benefit to patients for whom their use is indicated (3,4), because current data on treatment and pre- or postexposure prophylaxis for COVID-19 indicate that the potential benefits of these drugs do not appear to outweigh their risks.

BACKGROUND: Approximately 5% of patients with drug-susceptible tuberculosis have a relapse after 6 months of first-line therapy, as do approximately 20% of patients after 4 months of short-course therapy. We postulated that by analyzing pretreatment isolates of Mycobacterium tuberculosis obtained from patients who subsequently had a relapse or were cured, we could determine any correlations between the minimum inhibitory concentration (MIC) of a drug below the standard resistance breakpoint and the relapse risk after treatment. METHODS: Using data from the Tuberculosis Trials Consortium Study 22 (development cohort), we assessed relapse and cure isolates to determine the MIC values of isoniazid and rifampin that were below the standard resistance breakpoint (0.1 mug per milliliter for isoniazid and 1.0 mug per milliliter for rifampin). We combined this analysis with clinical, radiologic, and laboratory data to generate predictive relapse models, which we validated by analyzing data from the DMID 01-009 study (validation cohort). RESULTS: In the development cohort, the mean (+/-SD) MIC of isoniazid below the breakpoint was 0.0334+/-0.0085 mug per milliliter in the relapse group and 0.0286+/-0.0092 mug per milliliter in the cure group, which represented a higher value in the relapse group by a factor of 1.17 (P=0.02). The corresponding MIC values of rifampin were 0.0695+/-0.0276 and 0.0453+/-0.0223 mug per milliliter, respectively, which represented a higher value in the relapse group by a factor of 1.53 (P<0.001). Higher MIC values remained associated with relapse in a multivariable analysis that included other significant between-group differences. In an analysis of receiver-operating-characteristic curves of relapse based on these MIC values, the area under the curve (AUC) was 0.779. In the development cohort, the AUC in a multivariable model that included MIC values was 0.875. In the validation cohort, the MIC values either alone or combined with other patient characteristics were also predictive of relapse, with AUC values of 0.964 and 0.929, respectively. The use of a model score for the MIC values of isoniazid and rifampin to achieve 75.0% sensitivity in cross-validation analysis predicted relapse with a specificity of 76.5% in the development cohort and a sensitivity of 70.0% and a specificity of 100% in the validation cohort. CONCLUSIONS: In pretreatment isolates of M. tuberculosis with decrements of MIC values of isoniazid or rifampin below standard resistance breakpoints, higher MIC values were associated with a greater risk of relapse than lower MIC values. (Funded by the National Institute of Allergy and Infectious Diseases.).

Moxifloxacin exhibits concentration-dependent prolongation of human QTc intervals and bactericidal activity against Mycobacterium tuberculosis However, moxifloxacin plasma concentrations are variable between patients. We evaluated whether human gene polymorphisms affect moxifloxacin plasma concentrations in tuberculosis patients from two geographic regions. We enrolled a convenience sample of 49 adults with drug-sensitive pulmonary tuberculosis from Africa and the United State s enrolled in two treatment trials of moxifloxacin as part of multidrug therapy. Pharmacokinetic parameters were evaluated by noncompartmental techniques. Human single-nucleotide polymorphisms of transporter genes were evaluated with analysis of covariance on moxifloxacin exposure and peak concentration (Cmax). Moxifloxacin area under the concentration-time curve from 0 to 24 h (AUC0-24) and Cmax were significantly increased by drug mg/kg dosage and genotype of variant g.-11187G>A in the SLCO1B1 gene (rs4149015), but not by geographic region. Median moxifloxacin AUC0-24 was 46% higher and Cmax 30% higher in 4 (8% of) participants who had the SLCO1B1 g.-11187 AG genotype compared with 45 participants who had the wild type GG genotype (median from model, AUC0-24 34.4 vs. 23.6 mug*h/mL, P =.005; Cmax 3.5 vs. 2.7 mug/mL, P =.009, ANCOVA). Because moxifloxacin exhibits concentration-dependent prolongation of human QTc intervals, and prolonged QTc intervals are associated with cardiac arrhythmia, further study is needed to evaluate risk associated with the SLCO1B1 g.-11187G>A variant.

BACKGROUND: State and local public health agencies collect and use surveillance data to identify outbreaks, track cases, investigate causes, and implement measures to protect the public-s health through various surveillance systems and data exchange practices. PURPOSE: The purpose of this assessment was to better understand current practices at state and local public health agencies for collecting, managing, processing, reporting, and exchanging notifiable disease surveillance information. METHODS: Over an 18-month period (January 2014-June 2015), we evaluated the process of data exchange between surveillance systems, reporting burdens, and challenges within 3 states (California, Idaho, and Massachusetts) that were using 3 different reporting systems. RESULTS: All 3 states use a combination of paper-based and electronic information systems for managing and exchanging data on reportable conditions within the state. The flow of data from local jurisdictions to the state health departments varies considerably. When state and local information systems are not interoperable, manual duplicative data entry and other work-arounds are often required. The results of the assessment show the complexity of disease reporting at the state and local levels and the multiple systems, processes, and resources engaged in preparing, processing, and transmitting data that limit interoperability and decrease efficiency. CONCLUSIONS: Through this structured assessment, the Centers for Disease Control and Prevention (CDC) has a better understanding of the complexities for surveillance of using commercial off-the-shelf data systems (California and Massachusetts), and CDC-developed National Electronic Disease Surveillance System Base System. More efficient data exchange and use of data will help facilitate interoperability between National Notifiable Diseases Surveillance Systems.

OBJECTIVE: Evaluating public health surveillance systems is critical to ensuring that conditions of public health importance are appropriately monitored. Our objectives were to qualitatively evaluate 6 state and local health departments that were early adopters of syndromic surveillance in order to (1) understand the characteristics and current uses, (2) identify the most and least useful syndromes to monitor, (3) gauge the utility for early warning and outbreak detection, and (4) assess how syndromic surveillance impacted their daily decision making. DESIGN: We adapted evaluation guidelines from the Centers for Disease Control and Prevention and gathered input from the Centers for Disease Control and Prevention subject matter experts in public health surveillance to develop a questionnaire. PARTICIPANTS: We interviewed staff members from a convenience sample of 6 local and state health departments with syndromic surveillance programs that had been in operation for more than 10 years. RESULTS: Three of the 6 interviewees provided an example of using syndromic surveillance to identify an outbreak (ie, cluster of foodborne illness in 1 jurisdiction) or detect a surge in cases for seasonal conditions (eg, influenza in 2 jurisdictions) prior to traditional, disease-specific systems. Although all interviewees noted that syndromic surveillance has not been routinely useful or efficient for early outbreak detection or case finding in their jurisdictions, all agreed that the information can be used to improve their understanding of dynamic disease control environments and conditions (eg, situational awareness) in their communities. CONCLUSION: In the jurisdictions studied, syndromic surveillance may be useful for monitoring the spread and intensity of large outbreaks of disease, especially influenza; enhancing public health awareness of mass gatherings and natural disasters; and assessing new, otherwise unmonitored conditions when real-time alternatives are unavailable. Future studies should explore opportunities to strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records. Health departments may accelerate the development and use of syndromic surveillance systems, including the improvement of the predictive value and strengthening the early outbreak detection capability of these systems. These efforts support getting the right information to the right people at the right time, which is the overarching goal of CDC's Surveillance Strategy.

Public health surveillance is the foundation of effective public health practice. Public health surveillance is defined as the ongoing systematic collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to the public health practitioners, clinicians, and policy makers responsible for preventing and controlling disease and injury.1 Ideally, surveillance systems should support timely, efficient, flexible, scalable, and interoperable data acquisition, analysis, and dissemination. However, many current systems rely on disease-specific approaches that inhibit efficiency and interoperability (eg, manual data entry and data recoding that place a substantial burden on data partners) and use slow, inefficient, out-of-date technologies that no longer meet user needs for data management, analysis, visualization, and dissemination.2–4 Advances in information technology, data science, analytic methods, and information sharing provide an opportunity to substantially enhance surveillance. As a global leader in public health surveillance, the Centers for Disease Control and Prevention (CDC) is working with public health partners to transform and modernize CDC’s surveillance systems and approaches. Here, we describe recent enhancements in surveillance data analysis and visualization, information sharing, and dissemination at CDC and identify the challenges ahead.

The current treatment used for tuberculosis (TB) is lengthy and needs to be shortened and improved. Pyrazinamide (PZA) has potent sterilizing activity and has the potential to shorten TB treatment duration, if optimized. The goals of this study were (a) to develop a population pharmacokinetic (PK) model for PZA among patients enrolled in PK sub-studies of Tuberculosis Trial Consortium (TBTC) trials 27 and 28, and (b) to determine covariates that affect PZA PK. We also (c) performed simulations and target attainment analysis using the proposed targets of Cmax >35 mcg/ml or AUC >363 mcg*hr/ml to see if higher weight-based dosing could improve PZA efficacy. Seventy-two patients participated in the sub-studies. The mean (standard deviation, SD) maximum plasma concentration (Cmax) was 30.8 (7.4) mcg/ml, and the area under the concentration-versus-time curve (AUC0-24) was 307 mcg*hr/ml (83). A one-compartment open model best described PZA PK. Only body weight was a significant covariate for PZA clearance. Women had a lower V/F compared to men, and both Cl/F and V/F increased with body weight. Our simulations show that higher doses for PZA (>50mg/kg) are needed to achieve the therapeutic target of AUC/MIC >11.3 in >80% of patients, while doses >80mg/kg are needed for 90% target attainment, given specific assumptions about MIC determinations. For the therapeutic targets of Cmax >35 mcg/ml and/or AUC >363 mcg*hr/ml, doses in the range of 30-40 mg/kg are needed to achieve the therapeutic target in >90 % of the patients. Further clinical trials are needed to evaluate the safety and efficacy of higher doses for PZA.Reference in this manuscript to any specific commercial product, process, service, manufacturer, or company does not constitute endorsement or recommendation by the U.S. Government or CDC. The findings and conclusions are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

Rifapentine is a highly active antituberculosis antibiotic with treatment-shortening potential; however, exposure-response relations and the dose needed for maximal bactericidal activity have not been established. We used pharmacokinetic/pharmacodynamic data from 657 adults with pulmonary tuberculosis participating in treatment trials to compare rifapentine (n = 405) with rifampin (n = 252) as part of intensive-phase therapy. Population pharmacokinetic/pharmacodynamic analyses were performed with nonlinear mixed-effects modeling. Time to stable culture conversion of sputum to negative was determined in cultures obtained over 4 months of therapy. Rifapentine exposures were lower in participants who were coinfected with human immunodeficiency virus, black, male, or fasting when taking drug. Rifapentine exposure, large lung cavity size, and geographic region were independently associated with time to culture conversion in liquid media. Maximal treatment efficacy is likely achieved with rifapentine at 1200 mg daily. Patients with large lung cavities appear less responsive to treatment, even at high rifapentine doses.

BACKGROUND: In a phase 3, randomized clinical trial (PREVENT TB) of 8053 people with latent tuberculosis infection, 12 once-weekly doses of rifapentine and isoniazid had good efficacy and tolerability. Children received higher rifapentine milligram per kilogram doses than adults. In the present pharmacokinetic study (a component of the PREVENT TB trial), rifapentine exposure was compared between children and adults. METHODS: Rifapentine doses in children ranged from 300 to 900 mg, and adults received 900 mg. Children who could not swallow tablets received crushed tablets. Sparse pharmacokinetic sampling was performed with 1 rifapentine concentration at 24 hours after drug administration (C24). Rifapentine area under concentrationtime curve (AUC) was estimated from a nonlinear, mixed effects regression model (NLME). RESULTS: There were 80 children (age: median, 4.5 years; range, 2-11 years) and 77 adults (age: median, 40 years; all >18 years) in the study. The geometric mean rifapentine milligram per kilogram dose was greater in children than in adults (children, 23 mg/kg; adults, 11 mg/kg). Rifapentine geometric mean AUC and C24 were 1.3-fold greater in children (all children combined) than in adults. Children who swallowed whole tablets had 1.3-fold higher geometric mean AUC than children who received crushed tablets, and children who swallowed whole tablets had a 1.6-fold higher geometric mean AUC than adults. The higher rifapentine doses in children were well tolerated. To obtain rifapentine exposures comparable in children to adults, dosing algorithms modeled by NLME were developed. CONCLUSIONS: A 2-fold greater rifapentine dose for all children resulted in a 1.3-fold higher AUC compared to adults administered a standard dose. Use of higher weight-adjusted rifapentine doses for young children are warranted to achieve systemic exposures that are associated with successful treatment of latent tuberculosis infection in adults.

Rifapentine is highly protein bound in blood, but the free, unbound drug is the microbiologically active fraction. In this exploratory study, we characterized the free plasma fraction of rifapentine in 41 patients with tuberculosis. We found lower total rifapentine concentration but significantly higher free rifapentine in African patients of Black race compared to non-Africans. These data support larger pharmacokinetic/pharmacodynamic studies to confirm these findings and assess free rifapentine in relation to microbiological and clinical outcomes.

SETTING: A large randomized controlled trial recently showed that for treating latent tuberculous infection (LTBI) in persons at high risk of progression to tuberculosis (TB) disease, a 12-dose regimen of weekly rifapentine plus isoniazid (3HP) administered as directly observed treatment (DOT) can be as effective as 9 months of daily self-administered isoniazid (9H). OBJECTIVES: To assess the cost-effectiveness of 3HP compared to 9H. DESIGN: A computational model was designed to simulate individuals with LTBI treated with 9H or 3HP. Costs and health outcomes were estimated to determine the incremental costs per active TB case prevented and per quality-adjusted life year (QALY) gained by 3HP compared to 9H. RESULTS: Over a 20-year period, treatment of LTBI with 3HP rather than 9H resulted in 5.2 fewer cases of TB and 25 fewer lost QALYs per 1000 individuals treated. From the health system and societal perspectives, 3HP would cost respectively US21525 and 4294 more per TB case prevented, and respectively 4565 and 911 more per QALY gained. CONCLUSIONS: 3HP may be a cost-effective alternative to 9H, particularly if the cost of rifapentine decreases, the effectiveness of 3HP can be maintained without DOT, and 3HP treatment is limited to those with a high risk of progression to TB disease.

BACKGROUND: The tuberculin skin test (TST) is used to test for latent tuberculosis (TB) infection and support the diagnosis of active TB. However, little is known about the relationship between the TST result and the clinical presentation of TB disease. METHODS: We analyzed US TB surveillance data, 1993--2010, and used multinomial logistic regression to calculate the association between TST result (0--4 mm [negative], 5--9 mm, 10--14 mm, and >= 15 mm) and clinical presentation of disease (miliary, combined pulmonary and extrapulmonary, extrapulmonary only, non-cavitary pulmonary, and cavitary pulmonary). For persons with pulmonary disease, multivariate logistic regression was used to calculate the odds of having acid-fast bacilli (AFB) positive sputum. RESULTS: There were 64,238 persons with culture-confirmed TB included in the analysis, which was stratified by HIV status and birthplace (US- vs. foreign-born). Persons with a TST >= 15 mm were less likely to have miliary or combined pulmonary and extrapulmonary disease, but more likely to have cavitary pulmonary disease than non-cavitary pulmonary disease. Persons with non-cavitary pulmonary disease with a negative TST were significantly more likely to have AFB positive sputum. CONCLUSIONS: Clinical presentation of TB disease differed according to TST result and persons with a negative TST were more likely to have disseminated disease (i.e., miliary or combined pulmonary and extrapulmonary). Further study of the TST result may improve our understanding of the host-pathogen relationship in TB disease.

The ultimate goal of evidence-based drug treatment is to produce a desired pharmacological response in a predictable manner and also to minimise adverse effects. This goal requires not only an increased awareness of the need to provide specific dosing recommendations aimed at specific patient groups, but also the implementation of a consistent integrative approach to recognise all factors contributing to the within- and between-subject variability in drug disposition and response. The assessment of new anti-tuberculosis agents and regimens in children requires a specific programme of investigation, and should be included early in human drug evaluation programmes. Appreciation of this principle is an important step forward towards the full integration of children into the tuberculosis research agenda and control programmes. The development of anti-tuberculosis drug formulations and regimens tailored to the requirements of children needs to consider physiological age-related differences for pharmacokinetics and toxicity between adults and children. Research based on these principles will create an evidence base that will inform the appropriate treatment of children with novel agents and regimens and will also inform future research, including the use of chemoprophylaxis and treatment-shortening strategies in children.

Despite the important role of fluoroquinolones and the predominant use of ofloxacin for treating multidrug-resistant tuberculosis in South Africa, there are limited data on ofloxacin pharmacokinetics in patients with multidrug-resistant tuberculosis, no ofloxacin pharmacokinetic data from South African patients, and no direct assessment of the relationship between ofloxacin pharmacokinetics and the MIC of ofloxacin of patient isolates. Our objectives are to describe ofloxacin pharmacokinetics in South African patients being treated for multidrug-resistant tuberculosis and assess the adequacy of ofloxacin drug exposure with respect to the probability of pharmacodynamic target attainment (area under the time curve/MIC ratio of at least 100). Sixty-five patients with multidrug-resistant tuberculosis were recruited from 2 hospitals in South Africa. We determined the ofloxacin MICs for the Mycobacterium tuberculosis isolates from baseline sputum specimens. Patients received daily doses of 800 mg ofloxacin, in addition to other antitubercular drugs. Patients underwent pharmacokinetic sampling at steady state. NONMEM was used for data analysis. The population pharmacokinetics of ofloxacin in this study has been adequately described. The probability of target attainment expectation in the study population was 0.45. Doubling the dose to 1,600 mg could increase this to only 0.77. The currently recommended ofloxacin dose appeared inadequate for the majority of this study population. Studies to assess the tolerability of higher doses are warranted. Alternatively, ofloxacin should be replaced with more potent fluoroquinolones.

BACKGROUND: Although seasonal variation in tuberculosis incidence has been described in several recent studies, the mechanism underlying this seasonality remains unknown. Seasonality of tuberculosis disease may indicate the presence of season-specific risk factors that could potentially be controlled if they were better understood. We conducted this study to determine whether tuberculosis is seasonal in the United States and to describe patterns of seasonality in specific populations. METHODS: We performed a time series decomposition analysis of tuberculosis cases reported to the Centers for Disease Control and Prevention from 1993 through 2008. Seasonal amplitude of tuberculosis disease (the difference between the months with the highest and lowest mean case counts), was calculated for the population as a whole and for populations with select demographic, clinical, and epidemiologic characteristics. RESULTS: A total of 243,432 laboratory-confirmed tuberculosis cases were reported over a period of 16 years. A mean of 21.4% more cases were diagnosed in March, the peak month, compared with November, the trough month. The magnitude of seasonality did not vary with latitude. The greatest seasonal amplitude was found among children aged <5 years and in cases associated with disease clusters. CONCLUSIONS: Tuberculosis is a seasonal disease in the United States, with a peak in spring and trough in late fall. The latitude independence of seasonality suggests that reduced winter sunlight exposure may not be a strong contributor to tuberculosis risk. Increased seasonality among young children and clustered cases suggests that disease that is the result of recent transmission is more influenced by season than disease resulting from activation of latent infection.

BACKGROUND: Since 1953, through the cooperation of state and local health departments, the U.S. Centers for Disease Control and Prevention (CDC) has collected information on incident cases of tuberculosis (TB) disease in the United States. In 2009, TB case rates declined -11.4%, compared to an average annual -3.8% decline since 2000. The unexpectedly large decline raised concerns that TB cases may have gone unreported. To address the unexpected decline, we examined trends from multiple sources on TB treatment initiation, medication sales, and laboratory and genotyping data on culture-positive TB. METHODS: We analyzed 142,174 incident TB cases reported to the U. S. National Tuberculosis Surveillance System (NTSS) during January 1, 2000-December 31, 2009; TB control program data from 59 public health reporting areas; self-reported data from 50 CDC-funded public health laboratories; monthly electronic prescription claims for new TB therapy prescriptions; and complete genotyping results available for NTSS cases. Accounting for prior trends using regression and time-series analyses, we calculated the deviation between observed and expected TB cases in 2009 according to patient and clinical characteristics, and assessed at what point in time the deviation occurred. RESULTS: The overall deviation in TB cases in 2009 was -7.9%, with -994 fewer cases reported than expected (P <.001). We ruled out evidence of surveillance underreporting since declines were seen in states that used new software for case reporting in 2009 as well as states that did not, and we found no cases unreported to CDC in our examination of over 5400 individual line-listed reports in 11 areas. TB cases decreased substantially among both foreign-born and U.S.-born persons. The unexpected decline began in late 2008 or early 2009, and may have begun to reverse in late 2009. The decline was greater in terms of case counts among foreign-born than U.S.-born persons; among the foreign-born, the declines were greatest in terms of percentage deviation from expected among persons who had been in the United States less than 2 years. Among U.S.-born persons, the declines in percentage deviation from expected were greatest among homeless persons and substance users. Independent information systems (NTSS, TB prescription claims, and public health laboratories) reported similar patterns of declines. Genotyping data did not suggest sudden decreases in recent transmission. CONCLUSIONS: Our assessments show that the decline in reported TB was not an artifact of changes in surveillance methods; rather, similar declines were found through multiple data sources. While the steady decline of TB cases before 2009 suggests ongoing improvement in TB control, we were not able to identify any substantial change in TB control activities or TB transmission that would account for the abrupt decline in 2009. It is possible that other multiple causes coincident with economic recession in the United States, including decreased immigration and delayed access to medical care, could be related to TB declines. Our findings underscore important needs in addressing health disparities as we move towards TB elimination in the United States.

The Centers for Disease Control and Prevention and National Institutes of Health convened a multidisciplinary meeting to discuss surrogate markers of treatment response in tuberculosis. The goals were to assess recent surrogate marker research and to provide specific recommendations for (1) the qualification and validation of biomarkers of treatment outcome; (2) the standardization of specimen and data collection for future clinical trials, including a minimum set of samples and collection time points; and (3) the creation of a specimen repository to support biomarker testing. This article summarizes these recommendations and provides a roadmap for their implementation.

BACKGROUND: Tuberculosis Trials Consortium Study 28, was a double blind, randomized, placebo-controlled, phase 2 clinical trial examining smear positive pulmonary Mycobacterium tuberculosis. Over the course of intensive phase therapy, patients from African sites had substantially delayed and lower rates of culture conversion to negative in liquid media compared to non-African patients. We explored potential explanations of this finding. METHODS: In TBTC Study 28, protocol-correct patients (n = 328) provided spot sputum specimens for M. tuberculosis culture in liquid media, at baseline and weeks 2, 4, 6 and 8 of study therapy. We compared sputum culture conversion for African and non-African patients stratified by four baseline measures of disease severity: AFB smear quantification, extent of disease on chest radiograph, cavity size and the number of days to detection of M. tuberculosis in liquid media using the Kaplan-Meier product-limit method. We evaluated specimen processing and culture procedures used at 29 study laboratories serving 27 sites. RESULTS: African TB patients had more extensive disease at enrollment than non-African patients. However, African patients with the least disease by the 4 measures of disease severity had conversion rates on liquid media that were substantially lower than conversion rates in non-African patients with the greatest extent of disease. HIV infection, smoking and diabetes did not explain delayed conversion in Africa. Some inter-site variation in laboratory processing and culture procedures within accepted practice for clinical diagnostic laboratories was found. CONCLUSIONS: Compared with patients from non-African sites, African patients being treated for TB had delayed sputum culture conversion and lower sputum conversion rates in liquid media that were not explained by baseline severity of disease, HIV status, age, smoking, diabetes or race. Further investigation is warranted into whether modest variation in laboratory processes substantially influences the efficacy outcomes of phase 2 TB treatment trials or if other factors (e.g., nutrition, host response) are involved. TRIAL REGISTRATION: ClinicalTrials.gov NCT00144417.

A simple serodiagnostic test based on the Mycobacterium leprae-specific phenolic glycolipid, PGL-I, for individuals with leprosy is nearly universally positive in leprosy patients with high bacillary loads, but cannot be used as a stand-alone diagnostic test for the entire spectrum of the disease process. For patients with early infection with no detectable acid fast bacilli in lesions or with low or no antibody titer to PGL-I as in those at the tuberculoid end of the disease spectrum, this diagnostic approach has limited usefulness. To identify additional M. leprae antigens that might enhance the serological detection of these individuals, we have examined the reactivity patterns of patient sera to PGL-I, lipoarabinomannan (LAM) and six recombinant M. leprae proteins (ML1877, ML0841, ML2028, ML2038, ML0380 and ML0050) by Western blot and ELISA. Overall, the responses to ML2028 (Ag85B) and ML2038 (bacterioferritin) were consistently high in both multibacillary and paucibacillary groups and weak or absent in endemic controls, while responses to other antigens showed considerable variability, from strongly positive to completely negative. This analysis has given a clearer understanding of some of the differences in the antibody responses, between individuals at opposite ends of the disease spectrum, as well as illustrating the heterogeneity of antibody responses towards protein, carbohydrate, and glycolipid antigens within a clinical group. Correlating these response patterns with a particular disease state would allow for a more critical assessment of the form of disease within the leprosy spectrum and could lead to better patient management.