Longitudinal Model-Based Biomarker Analysis of Exposure-Response Relationships in Adults with Pulmonary Tuberculosis.

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 mycobacterial 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 (Studies 29 and 29X), 662 participants had sputum collected over 6 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 bacillus 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. (The studies discussed in this paper have been registered at ClinicalTrials.gov under identifiers NCT00694629 and NCT01043575.).

Bacterial Factors That Predict Relapse after Tuberculosis Therapy.

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 µg per milliliter for isoniazid and 1.0 µg 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 µg per milliliter in the relapse group and 0.0286±0.0092 µg 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 µg 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.).

Optimising pyrazinamide for the treatment of tuberculosis.

Pyrazinamide is a potent sterilising agent that shortens the treatment duration needed to cure tuberculosis. It is synergistic with novel and existing drugs for tuberculosis. The dose of pyrazinamide that optimises efficacy while remaining safe is uncertain, as is its potential role in shortening treatment duration further.Pharmacokinetic data, sputum culture, and safety laboratory results were compiled from Tuberculosis Trials Consortium (TBTC) studies 27 and 28 and Pan-African Consortium for the Evaluation of Antituberculosis Antibiotics (PanACEA) multi-arm multi-stage tuberculosis (MAMS-TB), multi-centre phase 2 trials in which participants received rifampicin (range 10-35 mg·kg-1), pyrazinamide (range 20-30 mg·kg-1), plus two companion drugs. Pyrazinamide pharmacokinetic-pharmacodynamic (PK-PD) and pharmacokinetic-toxicity analyses were performed.In TBTC studies (n=77), higher pyrazinamide maximum concentration (Cmax) was associated with shorter time to culture conversion (TTCC) and higher probability of 2-month culture conversion (p-value<0.001). Parametric survival analyses showed that relationships varied geographically, with steeper PK-PD relationships seen among non-African than African participants. In PanACEA MAMS-TB (n=363), TTCC decreased as pyrazinamide Cmax increased and varied by rifampicin area under the curve (p-value<0.01). Modelling and simulation suggested that very high doses of pyrazinamide (>4500 mg) or increasing both pyrazinamide and rifampicin would be required to reach targets associated with treatment shortening. Combining all trials, liver toxicity was rare (3.9% with grade 3 or higher liver function tests (LFT)), and no relationship was seen between pyrazinamide Cmax and LFT levels.Pyrazinamide's microbiological efficacy increases with increasing drug concentrations. Optimising pyrazinamide alone, though, is unlikely to be sufficient to allow tuberculosis treatment shortening; rather, rifampicin dose would need to be increased in parallel.

Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020-March 2021.

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.

Hydroxychloroquine and Chloroquine Prescribing Patterns by Provider Specialty Following Initial Reports of Potential Benefit for COVID-19 Treatment - United States, January-June 2020.

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.

Characteristics of Hospitalized COVID-19 Patients Discharged and Experiencing Same-Hospital Readmission - United States, March-August 2020.

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.

Elevated Plasma Moxifloxacin Concentrations and SLCO1B1 g.-11187G>A Polymorphism in Adults with Pulmonary Tuberculosis.

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 States 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 by analysis of covariance (ANCOVA) on moxifloxacin exposure and the peak (maximum) concentration (Cmax). The moxifloxacin area under the concentration-time curve from 0 to 24 h (AUC0-24) and Cmax were significantly increased by the drug milligram-per-kilogram dosage and the genotype of variant g.-11187G>A in the SLCO1B1 gene (rs4149015) but not by geographic region. The median moxifloxacin AUC0-24 was 46% higher and the median Cmax was 30% higher in 4 (8%) participants who had the SLCO1B1 g.-11187 AG genotype than in 45 participants who had the wild-type GG genotype (median AUC0-24 from the model, 34.4 versus 23.6 µg · h/ml [P = 0.005, ANCOVA]; median Cmax from the model, 3.5 versus 2.7 µg/ml [P = 0.009, 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 the risk associated with the SLCO1B1 g.-11187G>A variant. (This study has been registered at ClinicalTrials.gov under identifier NCT00164463.).

Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments.

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.

An Assessment of Information Exchange Practices, Challenges, and Opportunities to Support US Disease Surveillance in 3 States.

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.

Population Pharmacokinetics of Pyrazinamide in Patients with Tuberculosis.

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 the TB treatment duration, if treatment is optimized. The goals of this study were (i) to develop a population pharmacokinetic (PK) model for PZA among patients enrolled in PK substudies of Tuberculosis Trial Consortium (TBTC) trials 27 and 28 and (ii) to determine covariates that affect PZA PK. (iii) We also performed simulations and target attainment analysis using the proposed targets of a maximum plasma concentration (Cmax) of >35 µg/ml or an area under the concentration-versus-time curve (AUC) of >363 µg · h/ml to see if higher weight-based dosing could improve PZA efficacy. Seventy-two patients participated in the substudies. The mean (standard deviation [SD]) Cmax was 30.8 (7.4) µg/ml, and the mean (SD) AUC from time zero to 24 h (AUC0-24) was 307 (83) µg · h/ml. A one-compartment open model best described PZA PK. Only body weight was a significant covariate for PZA clearance. Women had a lower volume of distribution (V/F) than men, and both clearance (CL/F) and V/F increased with body weight. Our simulations show that higher doses of PZA (>50 mg/kg of body weight) are needed to achieve the therapeutic target of an AUC/MIC of >11.3 in >80% of patients, while doses of >80 mg/kg are needed for target attainment in 90% of patients, given specific assumptions about MIC determinations. For the therapeutic targets of a Cmax of >35 µg/ml and/or an AUC of >363 µg · h/ml, doses in the range of 30 to 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 of PZA.

Quantification of rifapentine, a potent antituberculosis drug, from dried blood spot samples using liquid chromatographic-tandem mass spectrometric analysis.

The quantification of antituberculosis drug concentrations in multinational trials currently requires the collection of modest blood volumes, centrifugation, aliquoting of plasma, freezing, and keeping samples frozen during shipping. We prospectively enrolled healthy individuals into the Tuberculosis Trials Consortium Study 29B, a phase I dose escalation study of rifapentine, a rifamycin under evaluation in tuberculosis treatment trials. We developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying rifapentine in whole blood on dried blood spots (DBS) to facilitate pharmacokinetic/pharmacodynamic analyses in clinical trials. Paired plasma and whole-blood samples were collected by venipuncture, and whole blood was spotted on Whatman protein saver 903 cards. The methods were optimized for plasma and then validated for DBS. The analytical measuring range for quantification of rifapentine and its metabolite was 50 to 80,000 ng/ml in whole-blood DBS. The analyte was stable on the cards for 11 weeks with a desiccant at room temperature and protected from light. The method concordance for paired plasma and whole-blood DBS samples was determined after correcting for participant hematocrit or population-based estimates of bias from Bland-Altman plots. The application of either correction factor resulted in acceptable correlation between plasma and whole-blood DBS (Passing-Bablok regression corrected for hematocrit; y = 0.98x + 356). Concentrations of rifapentine may be determined from whole-blood DBS collected via venipuncture after normalization in order to account for the dilutional effects of red blood cells. Additional studies are focused on the application of this methodology to capillary blood collected by finger stick. The simplicity of processing, storage, shipping, and low blood volume makes whole-blood DBS attractive for rifapentine pharmacokinetic evaluations, especially in international and pediatric trials.

Protein binding of rifapentine and its 25-desacetyl metabolite in patients with pulmonary tuberculosis.

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 a lower total rifapentine concentration but significantly higher free rifapentine levels 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.

Pharmacokinetic interaction of rifapentine and raltegravir in healthy volunteers.

OBJECTIVES: Latent tuberculosis infection and tuberculosis disease are prevalent worldwide. However, antimycobacterial rifamycins have drug interactions with many antiretroviral drugs. We evaluated the effect of rifapentine on the pharmacokinetic properties of raltegravir. METHODS: In this open-label, fixed-sequence, three-period study, 21 healthy volunteers were given: raltegravir alone (400 mg every 12 h for 4 days) on days 1-4 of Period 1; rifapentine (900 mg once weekly for 3 weeks) on days 1, 8 and 15 of Period 2 and raltegravir (400 mg every 12 h for 4 days) on days 12-15 of Period 2; and rifapentine (600 mg once daily for 10 scheduled doses) on days 1, 4-8 and 11-14 of Period 3 and raltegravir (400 mg every 12 h for 4 days) on days 11-14 of Period 3. Plasma raltegravir concentrations were measured. ClinicalTrials.gov database: NCT00809718. RESULTS: In 16 subjects who completed the study, coadministration of raltegravir with rifapentine (900 mg once weekly; Period 2) compared with raltegravir alone resulted in the geometric mean of the raltegravir AUC from 0 to 12 h (AUC0-12) being increased by 71%; the peak concentration increased by 89% and the trough concentration decreased by 12%. Coadministration of raltegravir with rifapentine in Period 3 did not change the geometric mean of the raltegravir AUC0-12 or the peak concentration, but it decreased the trough concentration by 41%. Raltegravir coadministered with rifapentine was generally well tolerated. CONCLUSIONS: The increased raltegravir exposure observed with once-weekly rifapentine was safe and tolerable. Once-weekly rifapentine can be used with raltegravir to treat latent tuberculosis infection in patients who are infected with HIV.

Association between tuberculin skin test result and clinical presentation of tuberculosis 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.

Seasonality of tuberculosis in the United States, 1993-2008.

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.

Population pharmacokinetics and pharmacodynamics of ofloxacin in South African patients with multidrug-resistant tuberculosis.

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.

CDC/NIH Workshop. Tuberculosis biomarker and surrogate endpoint research roadmap.

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 ofa specimen repository to support biomarker testing. This article summarizes these recommendations and provides a roadmap for their implementation.

Unexpected decline in tuberculosis cases coincident with economic recession - United States, 2009.

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.

Risk of Clinical Severity by Age and Race/Ethnicity Among Adults Hospitalized for COVID-19-United States, March-September 2020.

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.

Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children.

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.