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Background: Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease., Methods: Close contacts (≥4 hours of exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically confirmed, or clinically diagnosed pulmonary or extrapulmonary TB disease through 24 months of follow-up was symptom triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative polymerase chain reaction. Prognostic performance for incident TB was tested by receiver operating characteristic curve analysis at 6, 9, 12, and 24 months of follow-up., Results: Between June 2015 and June 2019, 1854 close contacts were enrolled. Twenty-five progressed to incident TB, of whom 13 had microbiologically confirmed disease. Baseline transcriptomic signature scores were measured in 1789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile for a prognostic test through 6 months and 3 signatures (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the target product profile threshold through ≥12 months of follow-up., Conclusions: Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts to target preventive therapy administration., Competing Interests: Potential conflicts of interest. A. P.-N. and T. J. S. have 2 patents: WO2016123058A1 WIPO (PCT), “Biomarkers for detection of tuberculosis risk,” and WO2017081618A9 WIPO (PCT), “Biomarkers for prospective determination of risk for development of active tuberculosis.” All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Diagnosis of M. tuberculosis (Mtb) infection in close contacts is critical for TB control. Smoking is a risk factor for Mtb infection and TB disease but its effect on longitudinal interferon-gamma release assay (IGRA) results remains unknown. We conducted a multi-site prospective study in Brazil between 2015-2019, among close contacts of adults with culture-confirmed pulmonary TB. IGRA was performed at baseline, month 6 if negative at baseline, and month 24-30 after enrollment. IGRA results were categorized as IGRA-positive (maintained from baseline to last visit), IGRA-conversion (from negative to positive at any time), IGRA-reversion (from positive to negative at any time), and IGRA-negative (maintained from baseline to last visit). Associations between IGRA results and smoking status at baseline (current/former vs never) in contacts were evaluated using propensity score-adjusted logistic regression models. Estimated propensity score was used as a covariate in models, which regressed the outcome (IGRA-positive, IGRA-conversion, IGRA-reversion) on smoking status. Of 430 close contacts, 89 (21%) were IGRA-positive, 30 (7%) were converters, 30 (7%) were reverters and 22 were indeterminate. Smoking frequency was 26 (29%) among IGRA-positive contacts, 7 (23%) in converters, and 3 (10%) in reverters. Smoking in contacts was associated with lower odds of IGRA-reversion (adjusted odds ratio = 0.16; 95% confidence interval = [0.03-0.70]). We did not detect associations between smoking and IGRA-positive or IGRA-conversion. Our findings highlight the importance of smoking on longitudinal IGRA results. This has implications for clinical care and clinical trials in which IGRA status is monitored or used as an outcome., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates., Methods: We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to evaluate TB-ADR risk., Results: There were 156 TB-ADRs among 102 of the 945 (11%) participants included. Most TB-ADRs were hepatic (n = 82 [53%]), of moderate severity (grade 2; n = 121 [78%]), and occurred in NAT2 slow acetylators (n = 62 [61%]). The main prediction model included CM use, HbA1c, alcohol use, HIV seropositivity, BMI, and age, with robust performance (c-statistic = 0.79 [95% confidence interval {CI}, .74-.83) and fit (optimism-corrected slope and intercept of -0.09 and 0.94, respectively). An alternative model replacing BMI with NAT2 had similar performance. HIV seropositivity (hazard ratio [HR], 2.68 [95% CI, 1.75-4.09]) and CM use (HR, 5.26 [95% CI, 2.63-10.52]) increased TB-ADR risk., Conclusions: The models, with clinical variables and with NAT2, were highly predictive of TB-ADRs., Competing Interests: Potential conflicts of interest. The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The Xpert® MTB/RIF rapid molecular test provides a quantitative measure of Mycobacterium tuberculosis (Mtb) DNA in the form of cycle threshold (Ct) values. This information can be translated into mycobacterial load and used as a potential risk measure of bacterial spread for tuberculosis cases, which can impact infection control. However, the role of Ct values in assessing Mtb transmission to close contacts has not yet been demonstrated., Methods: A prospective study was performed to investigate the association between Xpert® MTB/RIF Ct values and Mtb transmission to close contacts of patients with culture-confirmed pulmonary TB in a multi-center Brazilian cohort. We evaluated clinical and laboratory data, such as age, sex, race, smoking habits, drug use, alcohol use, chest radiograph, Xpert® MTB/RIF results among pulmonary tuberculosis cases, and QuantiFERON(QFT)-Plus results at baseline and after six months for close contacts who had a negative result at baseline., Results: A total of 1,055 close contacts of 382 pulmonary tuberculosis cases were included in the study. The median Ct values from pulmonary tuberculosis cases of QFT-Plus positive (at baseline or six months) close contacts were lower compared with those who were QFT-Plus negative. An adjusted logistic regression demonstrated that reduced Ct values from the index cases were independently associated with QFT-Plus conversion from negative to positive (OR: 1.61, 95% CI: 1.12-2.32) after adjusting for clinical characteristics., Conclusion: Close contacts of pulmonary TB index cases exhibiting low Xpert MTB/RIF Ct values displayed higher rates of TB infection, reflecting Mtb transmission., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Successful tuberculosis (TB) treatment is necessary for disease control. The World Health Organization (WHO) has a target TB treatment success rate of ≥90%. We assessed whether the different types of unfavorable TB treatment outcome had different predictors., Methods: Using data from Regional Prospective Observational Research for Tuberculosis-Brazil, we evaluated biological and behavioral factors associated with each component of unsuccessful TB outcomes, recently updated by WHO (death, loss to follow-up [LTFU], and treatment failure). We included culture-confirmed, drug-susceptible, pulmonary TB participants receiving standard treatment in 2015-2019. Multinomial logistic regression models with inverse probability weighting were used to evaluate the distinct determinants of each unsuccessful outcome., Results: Of 915 participants included, 727 (79%) were successfully treated, 118 (13%) were LTFU, 44 (5%) had treatment failure, and 26 (3%) died. LTFU was associated with current drug-use (adjusted odds ratio [aOR] = 5.3; 95% confidence interval [CI], 3.0-9.4), current tobacco use (aOR = 2.9; 95% CI, 1.7-4.9), and being a person with HIV (PWH) (aOR = 2.0; 95% CI, 1.1-3.5). Treatment failure was associated with PWH (aOR = 2.7; 95% CI, 1.2-6.2) and having diabetes (aOR = 2.2; 95% CI, 1.1-4.4). Death was associated with anemia (aOR = 5.3; 95% CI, 1.4-19.7), diabetes (aOR = 3.1; 95% CI, 1.4-6.7), and PWH (aOR = 3.9; 95% CI, 1.3-11.4). Direct observed therapy was protective for treatment failure (aOR = 0.5; 95% CI, .3-.9) and death (aOR = 0.5; 95% CI, .2-1.0)., Conclusions: The treatment success rate was below the WHO target. Behavioral factors were most associated with LTFU, whereas clinical comorbidities were correlated with treatment failure and death. Because determinants of unsuccessful outcomes are distinct, different intervention strategies may be needed to improve TB outcomes., Competing Interests: Potential conflicts of interest. The authors do not have an association that might pose a conflict of interest. V. C. R. reports grants or contracts outside of the submitted work from TB Alliance for Drug Development (NC-008), Impacto da COVID-19 Nas Manifestações Clínicas, Diagnóstico, Desfecho Do Tratamento e Resposta Imune para Tuberculose Pulmonar (440933/2020-0 to CNPq account (not to self), Associative BRICS Research in COVID-19 and Tuberculosis (ABRICOT) (G-202105-67821 to Fiotec), RePORT International Data Harmonization (R-202108-68053 to Fiotec), Transcriptional Signature of TB in advanced HIV (DAA3-18-64313 to Fiotec), Predictors of Resistance Emergence Evaluation in Multidrug-resistant Tuberculosis patients on Treatment – PREEMPT (R01AI134430), Caribbean, Central, and South America network for HIV Epidemiology (CCASAnet) (U01AI069923 to Fiotec), and immunogenetic predictors of active and incipient TB in HIV-negative and -positive close TB contacts (R01AI147765 to Fiotec); consulting fees paid to self from ONU-OMS Country review for HIV response Myanmar; payment or honoraria paid to self from GLAXOSMITHKLINE BRASIL LTDA, Qiagen (Infecto Rio Conference), and virology education (Infecto Rio Conference); payment directly to the conference for registration for ViiV 18 European AIDS conference; and payment directly to self from NIH Data Safety Monitoring Board., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Despite widespread availability of curative therapy, tuberculosis (TB) treatment outcomes remain suboptimal. Clinical prediction models can inform treatment strategies to improve outcomes. Using baseline clinical data, we developed a prediction model for unsuccessful TB treatment outcome and evaluated the incremental value of human immunodeficiency virus (HIV)-related severity and isoniazid acetylator status., Methods: Data originated from the Regional Prospective Observational Research for Tuberculosis Brazil cohort, which enrolled newly diagnosed TB patients in Brazil from 2015 through 2019. This analysis included participants with culture-confirmed, drug-susceptible pulmonary TB who started first-line anti-TB therapy and had ≥12 months of follow-up. The end point was unsuccessful TB treatment: composite of death, treatment failure, regimen switch, incomplete treatment, or not evaluated. Missing predictors were imputed. Predictors were chosen via bootstrapped backward selection. Discrimination and calibration were evaluated with c-statistics and calibration plots, respectively. Bootstrap internal validation estimated overfitting, and a shrinkage factor was applied to improve out-of-sample prediction. Incremental value was evaluated with likelihood ratio-based measures., Results: Of 944 participants, 191 (20%) had unsuccessful treatment outcomes. The final model included 7 baseline predictors: hemoglobin, HIV infection, drug use, diabetes, age, education, and tobacco use. The model demonstrated good discrimination (c-statistic = 0.77; 95% confidence interval, .73-.80) and was well calibrated (optimism-corrected intercept and slope, -0.12 and 0.89, respectively). HIV-related factors and isoniazid acetylation status did not improve prediction of the final model., Conclusions: Using information readily available at treatment initiation, the prediction model performed well in this population. The findings may guide future work to allocate resources or inform targeted interventions for high-risk patients., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: It is unclear whether diabetes or prediabetes affects unfavorable treatment outcomes and death in people with tuberculosis (PWTB)., Methods: Culture-confirmed, drug-susceptible PWTB, enrolled in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil cohort between 2015 and 2019 (N = 643) were stratified based on glycemic status according to baseline glycated hemoglobin. Unfavorable tuberculosis (TB) outcome was defined as treatment failure or modification, recurrence, or death; favorable outcome was cure or treatment completion. We corroborated the findings using data from PWTB reported to the Brazilian National System of Diseases Notification (SINAN) during 2015-2019 (N = 20 989). Logistic regression models evaluated associations between glycemic status and outcomes., Results: In both cohorts, in univariate analysis, unfavorable outcomes were more frequently associated with smoking, illicit drug use, and human immunodeficiency virus infection. Diabetes, but not prediabetes, was associated with unfavorable outcomes in the RePORT-Brazil (adjusted relative risk [aRR], 2.45; P < .001) and SINAN (aRR, 1.76; P < .001) cohorts. Furthermore, diabetes was associated with high risk of death (during TB treatment) in both RePORT-Brazil (aRR, 2.16; P = .040) and SINAN (aRR, 1.93; P = .001)., Conclusions: Diabetes was associated with an increased risk of unfavorable outcomes and mortality in Brazilian PWTB. Interventions to improve TB treatment outcomes in persons with diabetes are needed., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: It is unknown whether dysglycemia is associated with Mycobacterium tuberculosis transmission., Methods: We assessed epidemiological and clinical characteristics of patients with culture-confirmed pulmonary tuberculosis and their close contacts, enrolled in a multicenter prospective cohort in Brazil. Contacts were investigated at baseline and 6 months after enrollment. QuantiFERON positivity at baseline and conversion (from negative to positive at month 6) were compared between subgroups of contacts according to glycemic status of persons with tuberculosis (PWTB) as diabetes mellitus (DM) or prediabetes. Multivariable mixed-effects logistic regression models were performed to test independent associations with baseline QuantiFERON positive and QuantiFERON conversion., Results: There were 592 PWTB (153 DM, 141 prediabetes, 211 normoglycemic) and 1784 contacts, of whom 658 were QuantiFERON-positive at baseline and 106 converters. Multivariable analyses demonstrated that tuberculosis-prediabetes cases, acid-fast bacilli-positive, pulmonary cavities, and living with someone who smoked were independently associated with QuantiFERON positive in contacts at baseline. DM, persistent cough, acid-fast bacilli-positive, and pulmonary cavities in tuberculosis source cases were associated with QuantiFERON conversion., Conclusions: Contacts of persons with pulmonary tuberculosis and dysglycemia were at increased risk of being QuantiFERON positive at baseline or month 6. Increased focus on such close contacts could improve tuberculosis control., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Weight change may inform tuberculosis treatment response, but its predictive power may be confounded by human immunodeficiency virus (HIV)., Methods: We prospectively followed up adults with culture-confirmed, drug-susceptible, pulmonary tuberculosis receiving standard 4-drug therapy (isoniazid, rifampin, pyrazinamide, and ethambutol) in Brazil. We examined median weight change 2 months after treatment initiation by HIV status, using quantile regression, and unsuccessful tuberculosis treatment outcome (treatment failure, tuberculosis recurrence, or death) by HIV and weight change status, using Cox regression., Results: Among 547 participants, 102 (19%) were HIV positive, and 35 (6%) had an unsuccessful outcome. After adjustment for confounders, persons living with HIV (PLWH) gained a median of 1.3 kg (95% confidence interval [CI], -2.8 to .1) less than HIV-negative individuals during the first 2 months of tuberculosis treatment. PLWH were at increased risk of an unsuccessful outcome (adjusted hazard ratio, 4.8; 95% CI, 2.1-10.9). Weight change was independently associated with outcome, with risk of unsuccessful outcome decreasing by 12% (95% CI, .81%-.95%) per 1-kg increase., Conclusions: PLWH gained less weight during the first 2 months of tuberculosis treatment, and lack of weight gain and HIV independently predicted unsuccessful tuberculosis treatment outcomes. Weight, an easily collected biomarker, may identify patients who would benefit from alternative treatment strategies., (© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)