Limited role of culture conversion for decision-making in individual patient care and for advancing novel regimens to confirmatory clinical trials

A pharmacometric multistate model for predicting long-term treatment outcomes of patients with pulmonary TB

BACKGROUND

Studying long-term treatment outcomes of TB is time-consuming and impractical. Early and reliable biomarkers reflecting treatment response and capable of predicting long-term outcomes are urgently needed.

OBJECTIVES

To develop a pharmacometric multistate model to evaluate the link between potential predictors and long-term outcomes.

METHODS

Data were obtained from two Phase II clinical trials (TMC207-C208 and TMC207-C209) with bedaquiline on top of a multidrug background regimen. Patients were typically followed throughout a 24 week investigational treatment period plus a 96 week follow-up period. A five-state multistate model (active TB, converted, recurrent TB, dropout, and death) was developed to describe observed transitions. Evaluated predictors included patient characteristics, baseline TB disease severity and on-treatment biomarkers.

RESULTS

A fast bacterial clearance in the first 2 weeks and low TB bacterial burden at baseline increased probability to achieve conversion, whereas patients with XDR-TB were less likely to reach conversion. Higher estimated mycobacterial load at the end of 24 week treatment increased the probability of recurrence. At 120 weeks, the model predicted 55% (95% prediction interval, 50%-60%), 6.5% (4.2%-9.0%) and 7.5% (5.2%-10%) of patients in converted, recurrent TB and death states, respectively. Simulations predicted a substantial increase of recurrence after 24 weeks in patients with slow bacterial clearance regardless of baseline bacterial burden.

CONCLUSIONS

The developed multistate model successfully described TB treatment outcomes. The multistate modelling framework enables prediction of several outcomes simultaneously, and allows mechanistically sound investigation of novel promising predictors. This may help support future biomarker evaluation, clinical trial design and analysis.

Developing biomarker assays to accelerate tuberculosis drug development: defining target product profiles

Drug development for tuberculosis is hindered by the methodological limitations in the definitions of patient outcomes, particularly the slow organism growth and difficulty in obtaining suitable and representative samples throughout the treatment. We developed target product profiles for biomarker assays suitable for early-phase and late-phase clinical drug trials by consulting subject-matter experts on the desirable performance and operational characteristics of such assays for monitoring of tuberculosis treatment in drug trials. Minimal and optimal criteria were defined for scope, intended use, pricing, performance, and operational characteristics of the biomarkers. Early-stage trial assays should accurately quantify the number of viable bacilli, whereas late-stage trial assays should match the number, predict relapse-free cure, and replace culture conversion endpoints. The operational criteria reflect the infrastructure and resources available for drug trials. The effective tools should define the sterilising activity of the drug and lower the probability of treatment failure or relapse in people with tuberculosis. The target product profiles outlined in this Review should guide and de-risk the development of biomarker-based assays suitable for phase 2 and 3 clinical drug trials.

A Systematic Review of Potential Biomarkers for Bacterial Burden and Treatment Efficacy Assessment in Tuberculosis Platform-Based Clinical Trials

Adaptive platform trials can be more efficient than classic trials for developing new treatments. Moving from culture-based to simpler- or faster-to-measure biomarkers as efficacy surrogates may enhance this advantage. We performed a systematic review of treatment efficacy biomarkers in adults with tuberculosis. Platform trials can span different development phases. We grouped biomarkers as: α, bacterial load estimates used in phase 2a trials; β, early and end-of treatment end points, phase 2b-c trials; γ, posttreatment or trial-level estimates, phase 2c-3 trials. We considered as analysis unit (biomarker entry) each combination of biomarker, predicted outcome, and their respective measurement times or intervals. Performance metrics included: sensitivity, specificity, area under the receiver-operator curve (AUC), and correlation measures, and classified as poor, promising, or good. Eighty-six studies included 22 864 participants. From 1356 biomarker entries, 318 were reported with the performance metrics of interest, with 103 promising and 41 good predictors. Group results were: α, mycobacterial RNA and lipoarabinomannan (LAM) in sputum, and host metabolites in urine; β, mycobacterial RNA and host transcriptomic or cytokine signatures for early treatment response; and γ, host transcriptomics for recurrence. A combination of biomarkers from different categories could help in designing more efficient platform trials. Efforts to develop efficacy surrogates should be better coordinated.

Therapeutic developments for tuberculosis and nontuberculous mycobacterial lung disease

Tuberculosis (TB) drug discovery and development has undergone nothing short of a revolution over the past 20 years. Successful public-private partnerships and sustained funding have delivered a much-improved understanding of mycobacterial disease biology and pharmacology and a healthy pipeline that can tolerate inevitable attrition. Preclinical and clinical development has evolved from decade-old concepts to adaptive designs that permit rapid evaluation of regimens that might greatly shorten treatment duration over the next decade. But the past 20 years also saw the rise of a fatal and difficult-to-cure lung disease caused by nontuberculous mycobacteria (NTM), for which the drug development pipeline is nearly empty. Here, we discuss the similarities and differences between TB and NTM lung diseases, compare the preclinical and clinical advances, and identify major knowledge gaps and areas of cross-fertilization. We argue that applying paradigms and networks that have proved successful for TB, from basic research to clinical trials, will help to populate the pipeline and accelerate curative regimen development for NTM disease.

Does PET-CT Have a Role in the Evaluation of Tuberculosis Treatment in Phase 2 Clinical Trials?

Positron emission tomography-computed tomography (PET-CT) has the potential to revolutionize research in infectious diseases, as it has done with cancer. There is growing interest in it as a biomarker in the setting of early-phase tuberculosis clinical trials, particularly given the limitations of current biomarkers as adequate predictors of sterilizing cure for tuberculosis. PET-CT is a real-time tool that provides a 3-dimensional view of the spatial distribution of tuberculosis within the lung parenchyma and the nature of lesions with uptake (ie, whether nodular, consolidative, or cavitary). Its ability to provide functional data on changes in metabolism, drug penetration, and immune control of tuberculous lesions has the potential to facilitate drug development and regimen selection for advancement to phase 3 trials in tuberculosis. In this narrative review, we discuss the role that PET-CT may have in evaluating responses to drug therapy in active tuberculosis treatment and the challenges in taking PET-CT forward as predictive biomarker of relapse-free cure in the setting of phase 2 clinical trials.

Association of indicators of extensive disease and rifampin-resistant tuberculosis treatment outcomes: an individual participant data meta-analysis

BACKGROUND

Indicators of extensive disease-acid fast bacilli (AFB) smear positivity and lung cavitation-have been inconsistently associated with clinical rifampin-resistant/multidrug-resistant tuberculosis (RR/MDR-TB) outcomes. We evaluated the association of these indicators with end-of-treatment outcomes.

METHODS

We did an individual participant data meta-analysis of people treated for RR/MDR-TB with longer regimens with documented AFB smear and chest radiography findings. We compared people AFB smear-negative without cavities to people: (1) smear-negative with lung cavities; (2) smear-positive without lung cavities and (3) AFB smear-positive with lung cavities. Using multivariable logistic regression accounting for demographic, treatment and clinical factors, we calculated adjusted ORs (aOR) for any unfavourable outcome (death, lost to follow-up, failure/recurrence), and mortality and treatment failure/recurrence alone.

RESULTS

We included 5596 participants; included participants significantly differed from excluded participants. Overall, 774 (13.8%) were AFB smear-negative without cavities, 647 (11.6%) only had cavities, 1424 (25.4%) were AFB smear-positive alone and 2751 (49.2%) were AFB smear-positive with cavities. The median age was 37 years (IQR: 28-47), 3580 (64%) were male and 686 (12.5%) had HIV. Compared with participants AFB smear-negative without cavities, aOR (95% CI) for any unfavourable outcome was 1.0 (0.8 to 1.4) for participants smear-negative with lung cavities, 1.2 (0.9 to 1.5) if smear-positive without cavities and 1.6 (1.3 to 2.0) if AFB smear-positive with lung cavities. Odds were only significantly increased for mortality (1.5, 95% CI 1.1 to 2.1) and failure/recurrence (2.2, 95% CI 1.5 to 3.3) among participants AFB smear-positive with lung cavities.

CONCLUSION

Only the combination of AFB smear-positivity and lung cavitation was associated with unfavourable outcomes, suggesting they may benefit from stronger regimens.

Monitoring Live Mycobacteria in Real-Time Using a Microfluidic Acoustic-Raman Platform

Tuberculosis (TB) is the most common cause of death from an infectious disease. Although treatment has been available for more than 70 years, it still takes too long and many patients default risking relapse and the emergence of resistance. It is known that lipid-rich, phenotypically antibiotic-tolerant, bacteria are more resistant to antibiotics and may be responsible for relapse necessitating extended therapy. Using a microfluidic system that acoustically traps live mycobacteria, M. smegmatis, a model organism for M. tuberculosis we can perform optical analysis in the form of wavelength-modulated Raman spectroscopy (WMRS) on the trapped organisms. This system can allow observations of the mycobacteria for up to 8 h. By adding antibiotics, it is possible to study the effect of antibiotics in real-time by comparing the Raman fingerprints in comparison to the unstressed condition. This microfluidic platform may be used to study any microorganism and to dynamically monitor its response to many conditions including antibiotic stress, and changes in the growth media. This opens the possibility of understanding better the stimuli that trigger the lipid-rich downregulated and phenotypically antibiotic-resistant cell state.

Early Microbiologic Markers of Pulmonary Tuberculosis Treatment Outcomes

Rationale: Earlier biomarkers of pulmonary tuberculosis (PTB) treatment outcomes are critical to monitor shortened anti-TB treatment (ATT). Objectives: To identify early microbiologic markers of unfavorable TB treatment outcomes. Methods: We performed a subanalysis of 2 prospective TB cohort studies conducted from 2013 to 2019 in India. We included participants aged ⩾18 years who initiated 6-month ATT for clinically or microbiologically diagnosed drug-sensitive PTB and completed at least one follow-up visit. Sputum specimens were subjected to a baseline Xpert Mycobacterium tuberculosis/rifampin (MTB/RIF) assay, acid-fast bacilli (AFB) microscopy and liquid and solid cultures, and serial AFB microscopy and liquid and solid cultures at weeks 2, 4, and 8. Poisson regression was used to assess the impact of available microbiologic markers (test positivity, smear grade, time to detection, and time to conversion) on a composite outcome of failure, recurrence, or death by 18 months after the end of treatment. Models were adjusted for age, sex, nutritional status, diabetes, smoking, alcohol consumption, and regimen type. Results: Among 1,098 eligible cases, there were 251 (22%) adverse TB treatment outcomes: 127 (51%) treatment failures, 73 (29%) recurrences, and 51 (20%) deaths. The primary outcome was independently associated with the Xpert MTB/RIF assay (medium-positive adjusted incidence rate ratio [aIRR], 1.91; 95% confidence interval [CI], 1.07-3.40; high-positive aIRR, 2.51; 95% CI, 1.41-4.46), positive AFB smear (aIRR, 1.48; 95% CI, 1.06-2.06), and positive liquid culture (aIRR, 1.98; 95% CI, 1.21-3.23) at baseline; Week 2 positive liquid culture (aIRR, 1.47; 95% CI, 1.04-2.09); and Week 8 positive AFB smear (aIRR, 1.63; 95% CI, 1.06-2.50) and positive liquid culture (aIRR, 1.54; 95% CI, 1.07-2.22). There was no evidence of Mycobacterium tuberculosis growth in the Mycobacterium Growth Indicator Tube at Week 4 conferring a higher risk of adverse outcomes (aIRR, 1.25; 95% CI, 0.89-1.75). Conclusions: Our analysis identifies Week 2 respiratory mycobacterial culture as the earliest microbiologic marker of unfavorable PTB treatment outcomes.

Rosuvastatin adjunctive therapy for rifampicin-susceptible pulmonary tuberculosis: a phase 2b, randomised, open-label, multicentre trial

BACKGROUND

Shorter treatments are needed for drug-susceptible tuberculosis. Adjunctive statins increase bactericidal activity in preclinical tuberculosis models. We investigated the safety and efficacy of adjunctive rosuvastatin in people with tuberculosis. We tested the hypothesis that adjunctive rosuvastatin accelerates sputum culture conversion within the first 8 weeks of treatment of rifampicin-susceptible tuberculosis.

METHODS

This phase 2b, randomised, open-label, multicentre trial conducted in five hospitals or clinics in three countries with high tuberculosis burden (ie, the Philippines, Viet Nam, and Uganda) enrolled adult participants aged 18-75 years with sputum smear or Xpert MTB/RIF positive, rifampicin-susceptible tuberculosis who had received less than 7 days of previous tuberculosis treatment. Participants were randomly assigned via a web-based system to receive either 10 mg rosuvastatin once per day for 8 weeks plus standard tuberculosis therapy (rifampicin, isoniazid, pyrazinamide, and ethambutol; rosuvastatin group) or standard tuberculosis therapy alone (control group). Randomisation was stratified by trial site, history of diabetes, and HIV co-infection. Laboratory staff and central investigators involved in data cleaning and analysis were masked to treatment allocation, but study participants and site investigators were not. Both groups continued standard treatment to week 24. Sputum samples were collected once per week for the first 8 weeks after randomisation, and then at weeks 10, 12, and 24. The primary efficacy outcome was time to culture conversion (TTCC; days) in liquid culture by week 8, assessed in randomised participants who had microbiological confirmation of tuberculosis, took at least one dose of rosuvastatin, and who did not show resistance to rifampicin (modified intention-to-treat population), for which groups were compared with the Cox proportional hazards model. The main safety outcome was grade 3-5 adverse events by week 24, assessed in the intention-to-treat population, for which groups were compared with Fisher's exact test. All participants completed 24 weeks of follow-up. This trial is registered with ClinicalTrials.gov (NCT04504851).

FINDINGS

Between Sept 2, 2020, and Jan 14, 2021, 174 participants were screened and 137 were randomly assigned to the rosuvastatin group (70 participants) or control group (67 participants). In the modified intention-to-treat population of 135 participants, 102 (76%) were men and 33 (24%) were women. Median TTCC in liquid media was 42 days (95% CI 35-49) in the rosuvastatin group (68 participants) and 42 days (36-53) in the control group (67 participants; hazard ratio 1·30 [0·88-1·91], p=0·19). Grade 3-5 adverse events occurred in six (9%) of 70 in the rosuvastatin group (none were considered related to rosuvastatin) and four (6%) of 67 in the control group (p=0·75). There were no serious adverse events that were considered to be related to rosuvastatin.

INTERPRETATION

Adjunctive rosuvastatin at 10 mg once per day was safe but did not produce substantive benefits on culture conversion in the overall study population. Future trials could explore the safety and efficacy of higher doses of adjunctive rosuvastatin.

FUNDING

National Medical Research Council, Singapore.

Building sustainable clinical trial sites in Sub-Saharan Africa through networking, infrastructure improvement, training and conducting clinical studies: The PanACEA approach

INTRODUCTION

The Pan-African Consortium for the Evaluation of Anti-Tuberculosis Antibiotics (PanACEA) was designed to build tuberculosis (TB) trial capacity whilst conducting clinical trials on novel and existing agents to shorten and simplify TB treatment. PanACEA has now established a dynamic network of 11 sub-Saharan clinical trial sites and four European research institutions.

OBJECTIVES

In 2011, a capacity development program, funded by the European & Developing Countries Clinical Trials Partnership (EDCTP), was launched with four objectives, aiming at strengthening collaborating TB research sites to reach the ultimate goal of becoming self-sustainable institutions: networking; training; conducting clinical trials; and infrastructure scaling-up of sites.

METHODS

Assessment in six sub-Saharan TB-endemic countries (Gabon, Kenya, South Africa, Tanzania, Uganda and Zambia) were performed through a structured questionnaire, site visits, discussion with the PanACEA consortium, setting of milestones and identification of priorities and followed-up with evaluations of each site. The results of this needs-based assessment was then translated into capacity development measures.

RESULTS

In the initial phase, over a four-year period (March 2011 - June 2014), the programme scaled-up six sites; conducted a monitoring training program for 11 participants; funded five MSc and four PhD students, fostering gender balance; conducted four epidemiological studies; supported sites to conduct five Phase II studies and formed a sustainable platform for TB research (panacea-tb.net).

CONCLUSION

Our experience of conducting TB clinical trials within the PanACEA programme environment of mentoring, networking and training has provided a sound platform for establishing future sustainable research centres. Our goal of facilitating emergent clinical TB trial sites to better initiate and lead research activities has been mostly successful.

Clinically encountered growth phenotypes of tuberculosis-causing bacilli and their in vitro study: A review

The clinical manifestations of tuberculosis (TB) vary widely in severity, site of infection, and outcomes of treatment-leading to simultaneous efforts to individualize therapy safely and to search for shorter regimens that can be successfully used across the clinical spectrum. In these endeavors, clinicians and researchers alike employ mycobacterial culture in rich media. However, even within the same patient, individual bacilli among the population can exhibit substantial variability in their culturability. Bacilli in vitro also demonstrate substantial heterogeneity in replication rate and cultivation requirements, as well as susceptibility to killing by antimicrobials. Understanding parallels in clinical, ex vivo and in vitro growth phenotype diversity may be key to identifying those phenotypes responsible for treatment failure, relapse, and the reactivation of bacilli that progresses TB infection to disease. This review briefly summarizes the current role of mycobacterial culture in the care of patients with TB and the ex vivo evidence of variability in TB culturability. We then discuss current advances in in vitro models that study heterogenous subpopulations within a genetically identical bulk culture, with an emphasis on the effect of oxidative stress on bacillary cultivation requirements. The review highlights the complexity that heterogeneity in mycobacterial growth brings to the interpretation of culture in clinical settings and research. It also underscores the intricacies present in the interplay between growth phenotypes and antimicrobial susceptibility. Better understanding of population dynamics and growth requirements over time and space promises to aid both the attempts to individualize TB treatment and to find uniformly effective therapies.

Systematic assessment of clinical and bacteriological markers for tuberculosis reveals discordance and inaccuracy of symptom-based diagnosis for treatment response monitoring

Background

Clinical symptoms are the benchmark of tuberculosis (TB) diagnosis and monitoring of treatment response but are not clear how they relate to TB bacteriology, particularly the novel tuberculosis-molecular bacterial load assay (TB-MBLA).

Methods

Presumptive cases were bacteriologically confirmed for TB and assessed for symptoms and bacteriological resolution using smear microscopy (SM), culture, and TB-MBLA over 6-month treatment course. Kaplan–Meier and Kappa statistics were used to test the relationship between symptoms and bacteriological positivity.

Results

A cohort of 46 bacteriologically confirmed TB cases were analyzed for treatment response over a 6-month treatment course. Pre-treatment symptoms and bacteriological positivity concurred in over 70% of the cases. This agreement was lost in over 50% of cases whose chest pain, night sweat, and loss of appetite had resolved by week 2 of treatment. Cough resolved at a 3.2% rate weekly and was 0.3% slower than the combined bacteriological (average of MGIT and TB-MBLA positivity) resolution rate, 3.5% per week. A decrease in TB-MBLA positivity reflected a fall in bacillary load, 5.7 ± 1.3- at baseline to 0.30 ± 1.0- log10 eCFU/ml at month 6, and closer to cough resolution than other bacteriological measures, accounting for the only one bacteriologically positive case out of seven still coughing at month 6. Low baseline bacillary load patients were more likely to be bacteriologically negative, HR 5.6, p = 0.003 and HR 3.2, p = 0.014 by months 2 and 6 of treatment, respectively.

Conclusion

The probability of clinical symptoms reflecting bacteriological positivity weakens as the patient progresses on anti-TB therapy, making the symptom-based diagnosis a less reliable marker of treatment response.

Design principles to assemble drug combinations for effective tuberculosis therapy using interpretable pairwise drug response measurements

A challenge in tuberculosis treatment regimen design is the necessity to combine three or more antibiotics. We narrow the prohibitively large search space by breaking down high-order drug combinations into drug pair units. Using pairwise in vitro measurements, we train machine learning models to predict higher-order combination treatment outcomes in the relapsing BALB/c mouse model. Classifiers perform well and predict many of the >500 possible combinations among 12 antibiotics to be improved over bedaquiline + pretomanid + linezolid, a treatment-shortening regimen compared with the standard of care in mice. We reformulate classifiers as simple rulesets to reveal guiding principles of constructing combination therapies for both preclinical and clinical outcomes. One example ruleset combines a drug pair that is synergistic in a dormancy model with a pair that is potent in a cholesterol-rich growth environment. These rulesets are predictive, intuitive, and practical, thus enabling rational construction of drug combinations.

•

Evaluate the large drug combination space for potential tuberculosis treatments

•

In vitro 2-drug combination measurements predict 3–4 drug treatment outcomes in vivo

•

Strongly synergistic, antagonistic, or potent drug pairs drive treatment outcome

•

Simple rules articulate drug combination design principles for tuberculosis

Emerging data on rifampicin pharmacokinetics and approaches to optimal dosing in children with tuberculosis

INTRODUCTION

Despite its longstanding role in tuberculosis (TB) treatment, there continues to be emerging rifampicin research that has important implications for pediatric TB treatment and outstanding questions about its pharmacokinetics and optimal dose in children.

AREAS COVERED

This review aims to summarize and discuss emerging data on the use of rifampicin for: 1) routine treatment of drug-susceptible TB; 2) special subpopulations such as children with malnutrition, HIV, or TB meningitis; 3) treatment shortening. We also highlight the implications of these new data for child-friendly rifampicin formulations and identify future research priorities.

EXPERT OPINION

New data consistently show low rifampicin exposures across all pediatric populations with 10-20 mg/kg dosing. Although clinical outcomes in children are generally good, rifampicin dose optimization is needed, especially given a continued push to shorten treatment durations and for specific high-risk populations of children who have worse outcomes. A pooled analysis of existing data using applied pharmacometrics would answer many of the important questions remaining about rifampicin pharmacokinetics needed to optimize doses, especially in special populations. Targeted clinical studies in children with TB meningitis and treatment shortening with high-dose rifampicin are also priorities.

A new blood-based RNA signature (R9), for monitoring effectiveness of tuberculosis treatment in a South Indian longitudinal cohort

Tuberculosis (TB) treatment involves a multidrug regimen for six months, and until two months, it is unclear if treatment is effective. This delay can lead to the evolution of drug resistance, lung damage, disease spread, and transmission. We identify a blood-based 9-gene signature using a computational pipeline that constructs and interrogates a genome-wide transcriptome-integrated protein-interaction network. The identified signature is able to determine treatment response at week 1-2 in three independent public datasets. Signature-based R9-score correctly detected treatment response at individual timepoints (204 samples) from a newly developed South Indian longitudinal cohort involving 32 patients with pulmonary TB. These results are consistent with conventional clinical metrics and can discriminate good from poor treatment responders at week 2 (AUC 0.93(0.81-1.00)). In this work, we provide proof of concept that the R9-score can determine treatment effectiveness, making a case for designing a larger clinical study.

Precision-Enhancing Risk Stratification Tools for Selecting Optimal Treatment Durations in Tuberculosis Clinical Trials

Rationale: No evidence-based tools exist to enhance precision in the selection of patient-specific optimal treatment durations to study in tuberculosis clinical trials. Objectives: To develop risk stratification tools that assign patients with tuberculosis into risk groups of unfavorable outcome and inform selection of optimal treatment duration for each patient strata to study in clinical trials. Methods: Publicly available data from four phase 3 trials, each evaluating treatment duration shortening from 6 to 4 months, were used to develop parametric time-to-event models that describe unfavorable outcomes. Regimen, baseline, and on-treatment characteristics were evaluated as predictors of outcomes. Exact regression coefficients of predictors were used to assign risk groups and predict optimal treatment durations. Measurements and Main Results: The parametric model had an area under the receiver operating characteristic curve of 0.72. A six-item risk score (HIV status, smear grade, sex, cavitary disease status, body mass index, and Month 2 culture status) successfully grouped participants into low (1,060/3,791; 28%), moderate (1,740/3,791; 46%), and high (991/3,791; 26%) risk, requiring treatment durations of 4, 6, and greater than 6 months, respectively, to reach a target cure rate of 93% when receiving standard-dose rifamycin-containing regimens. With current one-duration-fits-all approaches, high-risk groups have a 3.7-fold (95% confidence interval, 2.7-5.1) and 2.4-fold (1.9-2.9) higher hazard risk of unfavorable outcomes compared with low- and moderate-risk groups, respectively. Four-month regimens were noninferior to the standard 6-month regimen in the low-risk group. Conclusions: Our model discrimination was modest but consistent with current models of unfavorable outcomes. Our results showed that stratified medicine approaches are feasible and may achieve high cure rates in all patients with tuberculosis. An interactive risk stratification tool is provided to facilitate decision-making in the regimen development pathway.

Recurrent pulmonary tuberculosis after treatment success: a population-based retrospective study in China

OBJECTIVES

Post-treatment recurrence remains a challenge for the global control of tuberculosis (TB). This study investigated longitudinal data on pulmonary TB recurrence rates and its risk factors among successfully treated smear-positive tuberculosis cases in China.

METHODS

From 1 January 2009 to 31 December 2016, we evaluated 33,441 treatment-naïve patients diagnosed with sputum smear-positive, non-multidrug-resistant TB in Hangzhou, China. We included the data of 9,828 patients with TB who were successfully treated.

RESULTS

A total of 4.9% were recurrent cases (479/9,828), identified within a median observation period lasting 1,565 days. Altogether, 51.1% (245/479) of the recurrences occurred within one year. The cumulative 2- and 5-year recurrence rates were 3.90% (95% confidence interval [CI], 3.3%-4.5%) and 5.4% (95% CI, 4.8%-6.0%), respectively. Prolonged treatment (over 7 months) was occurred in 64.7% (6,363/9,828), with median treatment duration of 242 (interquartile range, 195-348) days. Male sex (adjusted hazard ratio [aHR] [95% CI] = 1.61 [1.30-2.00], P<0.001), ≥ 60-years age (aHR [95% CI] = 2.03 [1.70-2.44], P<0.001), pulmonary cavity (aHR [95% CI] = 1.51 [1.25-1.82], P<0.001) and sputum positive at 2 months (aHR [95% CI] =1.39 [1.05-1.81], P=0.02) increased the risk of TB recurrence. Prolonged treatment was associated with reduced TB recurrence (aHR [95% CI] =0.73 [0.61-0.88], P=0.001).

CONCLUSIONS

Recurrence remains a problem for successfully treated patients with sputum smear-positive pulmonary TB, especially those with independent risk factors. Further analysis of prolonged treatment is required.

A systematic review of endpoint definitions in late phase pulmonary tuberculosis therapeutic trials

BACKGROUND

Safe, more efficacious treatments are needed to address the considerable morbidity and mortality associated with pulmonary tuberculosis (TB). However, the current practice in TB therapeutics trials is to use composite binary outcomes, which in the absence of standardization may inflate false positive and negative errors in evaluating regimens. The lack of standardization of outcomes is a barrier to the identification of highly efficacious regimens and the introduction of innovative methodologies METHODS: We conducted a systematic review of trials designed to advance new pulmonary TB drugs or regimens for regulatory approval and inform practice guidelines. Trials were primarily identified from the WHO International Clinical Trial Registry Platform (ICTRP). Only trials that collected post-treatment follow-up data and enrolled at least 100 patients were included. Protocols and Statistical Analysis Plans (SAP) for eligible trials from 1995 to the present were obtained from trial investigators. Details of outcome data, both explicit and implied, were abstracted and organized into three broad categories: favorable, unfavorable, and not assessable. Within these categories, individual trial definitions were recorded and collated, and areas of broad consensus and disagreement were identified and described.

RESULTS

From 2205 trials in any way related to TB, 51 were selected for protocol and SAP review, from which 31 were both eligible and had accessible documentation. Within the three designated categories, we found broad consensus in the definitions of favorable and unfavorable outcomes, although specific details were not always provided, and when explicitly addressed, were heterogeneous. Favorable outcomes were handled the most consistently but were widely variable with respect to specification. In some cases, the same events were defined differently by different protocols, particularly in distinguishing unfavorable from not assessable events. Death was often interpreted as conditional on cause. Patients who did not complete the study because of withdrawal or loss to follow-up presented a particular challenge to consistent interpretation and analytic treatment of outcomes.

CONCLUSIONS

In a review of 31 clinical trials, we found that outcome definitions were heterogeneous, highlighting the need to establish clearer specification and a move towards universal standardization of outcomes across pulmonary TB trials. The ICH E9 (R1) addendum provides guidelines for undertaking and achieving this goal.

PROSPERO REGISTRATION

PROSPERO CRD42020197993 . Registration 11 August 2020.

Exploring a combined biomarker for tuberculosis treatment response: protocol for a prospective observational cohort study

INTRODUCTION

An improved understanding of factors explaining tuberculosis (TB) treatment response is urgently needed to help clinicians optimise and personalise treatment and assist scientists undertaking novel treatment regimen trials. Promising outcome proxy measures, including sputum bacillary load and host immune response, are widely reported with variable results. However, they have not been studied together in combination with antibiotic exposure. The aim of this observational cohort study is to investigate which antibiotic exposures correlate with sputum bacillary load and which with the host immune response. Subsequently, we will explore if these correlations can be used to inform a candidate combined biomarker predicting cure.

METHODS AND ANALYSIS

All patients aged ≥ 18, diagnosed with drug-sensitive pulmonary TB (culture or molecular test), eligible for standard anti-TB treatment, at selected London, UK TB Services, will be invited to participate in this observational cohort study (target sample size=210). Patients will be asked to give blood for host transcriptomics and antibiotic plasma exposure, in addition to standard of care sputum samples for bacillary load. Antibiotic plasma concentrations will be quantified using a validated liquid chromatograph triple quadrupole mass spectrometer (LC-MS/MS) assay and sputum bacillary load by mycobacterial growth incubator tube time to positivity. Expression from a total of 35 prespecified host blood genes will be quantified using NanoString®. Antibiotic exposure, sputum bacillary load and host blood transcriptomic time series data will be analysed using nonlinear mixed-effects models. Correlations between combinations of longitudinal biomarkers and microbiological cure at the end of treatment and remaining relapse free for 1 year thereafter will be analysed using logistic regression and Cox proportional hazard models.

ETHICS AND DISSEMINATION

The observational cohort study has been approved by the UK's HRA REC (20/SW/0007). Written informed consent will be obtained. Results will be disseminated via publication, presentation and through engagement with institutes/companies developing novel anti-TB treatment combinations.

Pre-Treatment Neutrophil Count as a Predictor of Antituberculosis Therapy Outcomes: A Multicenter Prospective Cohort Study

Background

Neutrophils have been associated with lung tissue damage in many diseases, including tuberculosis (TB). Whether neutrophil count can serve as a predictor of adverse treatment outcomes is unknown.

Methods

We prospectively assessed 936 patients (172 HIV-seropositive) with culture-confirmed pulmonary TB, enrolled in a multicenter prospective cohort study from different regions in Brazil, from June 2015 to June 2019, and were followed up to two years. TB patients had a baseline visit before treatment (month 0) and visits at month 2 and 6 (or at the end of TB treatment). Smear microscopy, and culture for Mycobacterium tuberculosis (MTB) were performed at TB diagnosis and during follow-up. Complete blood counts were measured at baseline. Treatment outcome was defined as either unfavorable (death, treatment failure or TB recurrence) or favorable (cure or treatment completion). We performed multivariable logistic regression, with propensity score regression adjustment, to estimate the association between neutrophil count with MTB culture result at month 2 and unfavorable treatment outcome. We used a propensity score adjustment instead of a fully adjusted regression model due to the relatively low number of outcomes.

Results

Among 682 patients who had MTB culture results at month 2, 40 (5.9%) had a positive result. After regression with propensity score adjustment, no significant association between baseline neutrophil count (10³/mm³) and positive MTB culture at month 2 was found among either HIV-seronegative (OR = 1.06, 95% CI = [0.95;1.19] or HIV-seropositive patients (OR = 0.77, 95% CI = [0.51; 1.20]). Of 691 TB patients followed up for at least 18 months and up to 24 months, 635 (91.9%) were either cured or completed treatment, and 56 (8.1%) had an unfavorable treatment outcome. A multivariable regression with propensity score adjustment found an association between higher neutrophil count (10³/mm³) at baseline and unfavorable outcome among HIV-seronegative patients [OR= 1.17 (95% CI= [1.06;1.30]). In addition, adjusted Cox regression found that higher baseline neutrophil count (10³/mm³) was associated with unfavorable treatment outcomes overall and among HIV-seronegative patients (HR= 1.16 (95% CI = [1.05;1.27]).

Conclusion

Increased neutrophil count prior to anti-TB treatment initiation was associated with unfavorable treatment outcomes, particularly among HIV-seronegative patients. Further prospective studies evaluating neutrophil count in response to drug treatment and association with TB treatment outcomes are warranted.

Nonlinear mixed-effects modeling of longitudinal count data: Bayesian inference about median counts based on the marginal zero-inflated discrete Weibull distribution

This article proposes a Bayesian regression model for nonlinear zero-inflated longitudinal count data that models the median count as an alternative to the mean count. The nonlinear model generalizes a recently introduced linear mixed-effects model based on the zero-inflated discrete Weibull (ZIDW) distribution. The ZIDW distribution is more robust to severe skewness in the data than conventional zero-inflated count distributions such as the zero-inflated negative binomial (ZINB) distribution. Moreover, the ZIDW distribution is attractive because of its convenience to model the median counts given its closed-form quantile function. The median is a more robust measure of central tendency than the mean when the data, for instance, zero-inflated counts, are right-skewed. In an application of the model we consider a biphasic mixed-effects model consisting of an intercept term and two slope terms. Conventionally, the ZIDW model separately specifies the predictors for the zero-inflation probability and the counting process's median count. In our application, the two latent class interpretations are not clinically plausible. Therefore, we propose a marginal ZIDW model that directly models the biphasic median counts marginally. We also consider the marginal ZINB model to make inferences about the nonlinear mean counts over time. Our simulation study shows that the models have good properties in terms of accuracy and confidence interval coverage.

Visualizing the dynamics of tuberculosis pathology using molecular imaging

Nearly 140 years after Robert Koch discovered Mycobacterium tuberculosis, tuberculosis (TB) remains a global threat and a deadly human pathogen. M. tuberculosis is notable for complex host-pathogen interactions that lead to poorly understood disease states ranging from latent infection to active disease. Additionally, multiple pathologies with a distinct local milieu (bacterial burden, antibiotic exposure, and host response) can coexist simultaneously within the same subject and change independently over time. Current tools cannot optimally measure these distinct pathologies or the spatiotemporal changes. Next-generation molecular imaging affords unparalleled opportunities to visualize infection by providing holistic, 3D spatial characterization and noninvasive, temporal monitoring within the same subject. This rapidly evolving technology could powerfully augment TB research by advancing fundamental knowledge and accelerating the development of novel diagnostics, biomarkers, and therapeutics.

An Exposure-Response Perspective on the Clinical Dose of Pretomanid

Pretomanid was approved by the U.S. FDA, via the limited population pathway for antibacterial and antifungal drugs, as part of a three-drug regimen with bedaquiline and linezolid for the treatment of extensively drug-resistant and treatment-intolerant or nonresponsive multidrug-resistant tuberculosis. The recommended dose of pretomanid is 200 mg once daily with food. The objective of this work was to retrospectively evaluate this recommended dose by means of exposure-response (E-R) modeling applied to outcomes of both efficacy and safety. Cox proportional-hazards modeling was used, with the steady-state average pretomanid concentration as the exposure metric. The efficacy outcome was time to sputum culture conversion (TSCC) to negative. The safety outcomes were times to the first occurrence of adverse events in classes selected from either pretomanid's investigator brochure or the new drug application (NDA) submission as recognized safety signals for pretomanid based on preclinical as well as clinical experience. Significant E-R relationships were found for TSCC and two adverse-event classes, vomiting (a single preferred term) and gastrointestinal (GI) symptoms (a collection of related terms). No significant E-R relationships were found for the single preferred terms nausea, alanine aminotransferase (ALT) increased, aspartate aminotransferase (AST) increased, and headache and for the collections hepatic disorders, transaminases increased, skin and subcutaneous tissue disorders, and headache. The results suggest that the recommended dose of pretomanid, 200 mg given in the fed state, is appropriate over the range of pharmacokinetic exposures.

Predicting TB treatment outcomes using baseline risk and treatment response markers: developing the PredictTB early treatment completion criteria

Standard treatment of drug-sensitive pulmonary tuberculosis requires six months of treatment. Several randomized clinical trials have attempted to shorten treatment to four months using various strategies but thus far all have failed. The PredictTB trial is an ongoing international randomized clinical trial testing a treatment shortening strategy whereby only drug-sensitive pulmonary TB patients who meet the study early treatment completion criteria are randomized to four vs. six months of treatment. The PredictTB early treatment completion criteria were developed based on a cohort of 92 pulmonary tuberculosis patients treated programmatically through the local tuberculosis treatment program in Cape Town, South Africa, with FDG-PET/CT scans also performed at baseline and week 4 of treatment. Patients were followed for one year after the end of therapy for programmatic treatment outcomes. This methodology paper describes how the PET/CT scans and GeneXpert cycle threshold data of this cohort were analyzed to develop the early treatment completion algorithm currently being used in the PredictTB trial.

Evaluation of pharmacokinetic-pharmacodynamic relationships and selection of drug combinations for tuberculosis

AIMS

Despite evidence of the efficacy of anti-tubercular drug regimens in clinical practice, the rationale underpinning the selection of doses and companion drugs for combination therapy remains empirical. Novel methods are needed to optimise the antibacterial activity in combination therapies. A drug-disease modelling framework for rational selection of dose and drug combinations in tuberculosis is presented here.

METHODS

A model-based meta-analysis was performed to assess the antibacterial activity of different combinations in infected mice. Data retrieved from the published literature were analysed using a two-state bacterial growth dynamics model, including fast- and slow-growing bacterial populations. The contribution of each drug to the overall antibacterial activity of the combination was parameterised as relative change to the potency of the backbone drug (EC₅₀ -F and/or EC₅₀ -S). Rifampicin and bedaquiline were selected as paradigm drugs to evaluate the predictive performance of the modelling approach.

RESULTS

Pyrazinamide increased the potency (EC₅₀ -F and EC₅₀ -S) of rifampicin (RZ) and bedaquiline (BZ) by almost two-fold. By contrast, pretomanid and isoniazid were found to worsen the antibacterial activity of BZ and RZ, respectively. Following extrapolation of in vivo pharmacokinetic-pharmacodynamic relationships, the dose of rifampicin showing maximum bactericidal effect in tuberculosis patients was predicted to be 70 mg·kg^-1 when given in combination with pyrazinamide.

CONCLUSIONS

The use of a drug-disease modelling framework may provide a more robust rationale for extrapolation and selection of dose and companion drugs in humans. Our analysis demonstrates that RZ and BZ should be considered as a backbone therapy in prospective novel combination regimens against tuberculosis.

Longitudinal Pharmacokinetic-Pharmacodynamic Biomarkers Correlate With Treatment Outcome in Drug-Sensitive Pulmonary Tuberculosis: A Population Pharmacokinetic-Pharmacodynamic Analysis

Background

This study aims to explore relationships between baseline demographic covariates, plasma antibiotic exposure, sputum bacillary load, and clinical outcome data to help improve future tuberculosis (TB) treatment response predictions.

Methods

Data were available from a longitudinal cohort study in Malawian drug-sensitive TB patients on standard therapy, including steady-state plasma antibiotic exposure (154 patients), sputum bacillary load (102 patients), final outcome (95 patients), and clinical details. Population pharmacokinetic and pharmacokinetic-pharmacodynamic models were developed in the software package NONMEM. Outcome data were analyzed using univariate logistic regression and Cox proportional hazard models in R, a free software for statistical computing.

Results

Higher isoniazid exposure correlated with increased bacillary killing in sputum (P < .01). Bacillary killing in sputum remained fast, with later progression to biphasic decline, in patients with higher rifampicin area under the curve (AUC)_0-24 (P < .01). Serial sputum colony counting negativity at month 2 (P < .05), isoniazid C_MAX (P < .05), isoniazid C_MAX/minimum inhibitory concentration ([MIC] P < .01), and isoniazid AUC_0-24/MIC (P < .01) correlated with treatment success but not with remaining free of TB. Slower bacillary killing (P < .05) and earlier progression to biphasic bacillary decline (P < .01) both correlate with treatment failure. Posttreatment recurrence only correlated with slower bacillary killing (P < .05).

Conclusions

Patterns of early bacillary clearance matter. Static measurements such as month 2 sputum conversion and pharmacokinetic parameters such as C_MAX/MIC and AUC_0-24/MIC were predictive of treatment failure, but modeling of quantitative longitudinal data was required to assess the risk of recurrence. Pooled individual patient data analyses from larger datasets are needed to confirm these findings.

Intracellular Pharmacodynamic Modeling Is Predictive of the Clinical Activity of Fluoroquinolones against Tuberculosis

Clinical studies of new antitubercular drugs are costly and time-consuming. Owing to the extensive tuberculosis (TB) treatment periods, the ability to identify drug candidates based on their predicted clinical efficacy is vital to accelerate the pipeline of new therapies. Recent failures of preclinical models in predicting the activity of fluoroquinolones underline the importance of developing new and more robust predictive tools that will optimize the design of future trials.

Clinical studies of new antitubercular drugs are costly and time-consuming. Owing to the extensive tuberculosis (TB) treatment periods, the ability to identify drug candidates based on their predicted clinical efficacy is vital to accelerate the pipeline of new therapies. Recent failures of preclinical models in predicting the activity of fluoroquinolones underline the importance of developing new and more robust predictive tools that will optimize the design of future trials. Here, we used high-content imaging screening and pharmacodynamic intracellular (PDi) modeling to identify and prioritize fluoroquinolones for TB treatment. In a set of studies designed to validate this approach, we show moxifloxacin to be the most effective fluoroquinolone, and PDi modeling-based Monte Carlo simulations accurately predict negative culture conversion (sputum sterilization) rates compared to eight independent clinical trials. In addition, PDi-based simulations were used to predict the risk of relapse. Our analyses show that the duration of treatment following culture conversion can be used to predict the relapse rate. These data further support that PDi-based modeling offers a much-needed decision-making tool for the TB drug development pipeline.

Shortened treatment regimens versus the standard regimen for drug-sensitive pulmonary tuberculosis

BACKGROUND

Tuberculosis causes more deaths than any other infectious disease worldwide, with pulmonary tuberculosis being the most common form. Standard first-line treatment for drug-sensitive pulmonary tuberculosis for six months comprises isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE) for two months, followed by HRE (in areas of high TB drug resistance) or HR, given over a four-month continuation phase. Many people do not complete this full course. Shortened treatment regimens that are equally effective and safe could improve treatment success.

OBJECTIVES

To evaluate the efficacy and safety of shortened treatment regimens versus the standard six-month treatment regimen for individuals with drug-sensitive pulmonary tuberculosis.

SEARCH METHODS

We searched the following databases up to 10 July 2019: the Cochrane Infectious Diseases Group Specialized Register; the Central Register of Controlled Trials (CENTRAL), in the Cochrane Library; MEDLINE (PubMed); Embase; the Latin American Caribbean Health Sciences Literature (LILACS); Science Citation Index-Expanded; Indian Medlars Center; and the South Asian Database of Controlled Clinical Trials. We also searched the World Health Organization (WHO) International Clinical Trials Registry Platform, ClinicalTrials.gov, the Clinical Trials Unit of the International Union Against Tuberculosis and Lung Disease, the UK Medical Research Council Clinical Trials Unit, and the Clinical Trials Registry India for ongoing trials. We checked the reference lists of identified articles to find additional relevant studies.

SELECTION CRITERIA

We searched for randomized controlled trials (RCTs) or quasi-RCTs that compared shorter-duration regimens (less than six months) versus the standard six-month regimen for people of all ages, irrespective of HIV status, who were newly diagnosed with pulmonary tuberculosis by positive sputum culture or GeneXpert, and with presumed or proven drug-sensitive tuberculosis. The primary outcome of interest was relapse within two years of completion of anti-tuberculosis treatment (ATT).

DATA COLLECTION AND ANALYSIS

Two review authors independently selected trials, extracted data, and assessed risk of bias for the included trials. For dichotomous outcomes, we used risk ratios (RRs) with 95% confidence intervals (CIs). When appropriate, we pooled data from the included trials in meta-analyses. We assessed the certainty of evidence using the GRADE approach.

MAIN RESULTS

We included five randomized trials that compared fluoroquinolone-containing four-month ATT regimens versus standard six-month ATT regimens and recruited 5825 adults with newly diagnosed drug-sensitive pulmonary tuberculosis from 14 countries with high tuberculosis transmission in Asia, Africa, and Latin Ameria. Three were multi-country trials that included a total of 572 HIV-positive people. These trials excluded children, pregnant or lactating women, people with serious comorbid conditions, and those with diabetes mellitus. Four trials had multiple treatment arms. Moxifloxacin replaced ethambutol in standard four-month, daily or thrice-weekly ATT regimens in two trials; moxifloxacin replaced isoniazid in four-month ATT regimens in two trials, was given daily in one trial, and was given with rifapentine instead of rifampicin daily for two months and twice weekly for two months in one trial. Moxifloxacin was added to standard ATT drugs for three to four months in one ongoing trial that reported interim results. Gatifloxacin replaced ethambutol in standard ATT regimens given daily or thrice weekly for four months in two trials. Follow-up ranged from 12 months to 24 months after treatment completion for the majority of participants. Moxifloxacin-containing four-month ATT regimens Moxifloxacin-containing four-month ATT regimens that replaced ethambutol or isoniazid probably increased the proportions who experienced relapse after successful treatment compared to standard ATT regimens (RR 3.56, 95% CI 2.37 to 5.37; 2265 participants, 3 trials; moderate-certainty evidence). For death from any cause, there was probably little or no difference between the two regimens (2760 participants, 3 trials; moderate-certainty evidence). Treatment failure was rare, and there was probably little or no difference in proportions with treatment failure between ATT regimens (2282 participants, 3 trials; moderate-certainty evidence). None of the participants given moxifloxacin-containing regimens developed resistance to rifampicin, and these regimens may not increase the risk of acquired resistance (2282 participants, 3 trials; low-certainty evidence). Severe adverse events were probably little or no different with moxifloxacin-containing four-month regimens that replaced ethambutol or isoniazid, and with three- to four-month regimens that augmented standard ATT with moxifloxacin, when compared to standard six-month ATT regimens (3548 participants, 4 trials; moderate-certainty evidence). Gatifloxacin-containing four-month ATT regimens Gatifloxacin-containing four-month ATT regimens that replaced ethambutol probably increased relapse compared to standard six-month ATT regimens in adults with drug-sensitive pulmonary tuberculosis (RR 2.11, 95% CI 1.56 to 2.84; 1633 participants, 2 trials; moderate-certainty evidence). The four-month regimen probably made little or no difference in death compared to the six-month regimen (1886 participants, 2 trials; moderate-certainty evidence). Treatment failure was uncommon and was probably little or no different between the four-month and six-month regimens (1657 participants, 2 trials; moderate-certainty evidence). Acquired resistance to isoniazid or rifampicin was not detected in those given the gatifloxacin-containing shortened ATT regimen, but we are uncertain whether acquired drug resistance is any different in the four- and six-month regimens (429 participants, 1 trial; very low-certainty evidence). Serious adverse events were probably no different with either regimen (1993 participants, 2 trials; moderate-certainty evidence).

AUTHORS' CONCLUSIONS

Evidence to date does not support the use of shortened ATT regimens in adults with newly diagnosed drug-sensitive pulmonary tuberculosis. Four-month ATT regimens that replace ethambutol with moxifloxacin or gatifloxacin, or isoniazid with moxifloxacin, increase relapse substantially compared to standard six-month ATT regimens, although treatment success and serious adverse events are little or no different. The results of six large ongoing trials will help inform decisions on whether shortened ATT regimens can replace standard six-month ATT regimens. 9 December 2019 Up to date All studies incorporated from most recent search All eligible published studies found in the last search (10 Jul, 2019) were included.

The Potential for Treatment Shortening With Higher Rifampicin Doses: Relating Drug Exposure to Treatment Response in Patients With Pulmonary Tuberculosis

Background

Tuberculosis remains a huge public health problem and the prolonged treatment duration obstructs effective tuberculosis control. Higher rifampicin doses have been associated with better bactericidal activity, but optimal dosing is uncertain. This analysis aimed to characterize the relationship between rifampicin plasma exposure and treatment response over 6 months in a recent study investigating the potential for treatment shortening with high-dose rifampicin.

Methods

Data were analyzed from 336 patients with pulmonary tuberculosis (97 with pharmacokinetic data) treated with rifampicin doses of 10, 20, or 35 mg/kg. The response measure was time to stable sputum culture conversion (TSCC). We derived individual exposure metrics with a previously developed population pharmacokinetic model of rifampicin. TSCC was modeled using a parametric time-to-event approach, and a sequential exposure-response analysis was performed.

Results

Higher rifampicin exposures increased the probability of early culture conversion. No maximal limit of the effect was detected within the observed range. The expected proportion of patients with stable culture conversion on liquid medium at week 8 was predicted to increase from 39% (95% confidence interval, 37%-41%) to 55% (49%-61%), with the rifampicin area under the curve increasing from 20 to 175 mg/L·h (representative for 10 and 35 mg/kg, respectively). Other predictors of TSCC were baseline bacterial load, proportion of culture results unavailable, and substitution of ethambutol for either moxifloxacin or SQ109.

Conclusions

Increasing rifampicin exposure shortened TSCC, and the effect did not plateau, indicating that doses >35 mg/kg could be yet more effective. Optimizing rifampicin dosage while preventing toxicity is a clinical priority.

Predicting tuberculosis relapse in patients treated with the standard 6-month regimen: an individual patient data meta-analysis

BACKGROUND

Relapse continues to place significant burden on patients and tuberculosis (TB) programmes worldwide. We aimed to determine clinical and microbiological factors associated with relapse in patients treated with the WHO standard 6-month regimen and then evaluate the accuracy of each factor at predicting an outcome of relapse.

METHODS

A systematic review was performed to identify randomised controlled trials reporting treatment outcomes on patients receiving the standard regimen. Authors were contacted and invited to share patient-level data (IPD). A one-step IPD meta-analysis, using random intercept logistic regression models and receiver operating characteristic curves, was performed to evaluate the predictive performance of variables of interest.

RESULTS

Individual patient data were obtained from 3 of the 12 identified studies. Of the 1189 patients with confirmed pulmonary TB who completed therapy, 67 (5.6%) relapsed. In multipredictor analysis, the presence of baseline cavitary disease with positive smear at 2 months was associated with an increased odds of relapse (OR 2.3(95% CI 1.3 to 4.2)) and a relapse risk of 10%. When area under the curve for each multipredictor model was compared, discrimination between low-risk and higher-risk patients was modest and similar to that of the reference model which accounted for age, sex and HIV status.

CONCLUSION

Despite its poor predictive value, our results indicate that the combined presence of cavitary disease and 2-month positive smear status may be the best currently available marker for identifying individuals at an increased risk of relapse, particularly in resource-limited setting. Further investigation is required to assess whether this combined factor can be used to indicate different treatment requirements in clinical practice.

Centrifugation and decontamination procedures selectively impair recovery of important populations in Mycobacterium smegmatis

Diagnosis and treatment monitoring of patients with tuberculosis (TB) requires detection of all viable mycobacteria in clinical samples. Quantitation of Mycobacterium tuberculosis (Mtb) in sputum is commonly performed by culture after sample decontamination to prevent overgrowth by contaminant organisms. Exponentially growing cultures have cells that predominately lack non-polar lipid bodies whereas stationary cultures have a predominance of cells with non-polar lipid bodies. This may reflect rapidly growing 'active' and non-replicating 'persister' sub-populations respectively in sputum from TB patients. We investigated the effect of decontamination on culture-based quantitation of exponential and stationary phase cultures of Mycobacterium smegmatis in an artificial sputum model. Exponentially growing populations were between 89 and 50 times more susceptible to decontamination than stationary phase cultures when quantified by most probable number and colony forming units. These findings suggest that decontamination selectively eliminates the 'active' population. This may impair diagnostic sensitivity, treatment monitoring, and compromise clinical trials designed to identify new antibiotic combinations with activity against all mycobacterial cell states.

Evaluation of six months sputum culture conversion as a surrogate endpoint in a multidrug resistant-tuberculosis trial

The emergence of multidrug resistant-tuberculosis (MDR-TB), defined as Mycobacterium tuberculosis strains with in vitro resistance to at least isoniazid and rifampicin, has necessitated evaluation and validation of appropriate surrogate endpoints for treatment response in drug trials for MDR-TB. The trial that has demonstrated efficacy of bedaquiline, a diarylquinoline that inhibits mycobacterial ATP synthase, possesses the requisite features to conduct this evaluation. Approval of bedaquiline for use in MDR-TB was based primarily on the results of the controlled C208 Stage II study (ClinicalTrials.gov number, NCT00449644) including 160 patients randomized 1:1 to receive bedaquiline or placebo for 24 weeks when added to an 18-24-month preferred five-drug background regimen. Since randomization in C208 Stage II was preserved until study end, the trial results allow for the investigation of the complex relationship between sustained durable outcome with either Week 8 or Week 24 culture conversion as putative surrogate endpoints. The relationship between Week 120 outcome with Week 8 or Week 24 culture conversion was investigated using a descriptive analysis and with a recently developed statistical methodology for surrogate endpoint evaluation using methods of causal inference. The results demonstrate that sputum culture conversion at 24 weeks is more reliable than sputum culture conversion at 8 weeks when assessing the outcome of adding one new drug to a MDR-TB regimen.

Robust Bayesian nonlinear mixed-effects modeling of time to positivity in tuberculosis trials

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti-TB drugs. The EBA of anti-TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long-term efficacy of anti-TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed-effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed-effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent "deletion" of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.

Moxifloxacin Replacement in Contemporary Tuberculosis Drug Regimens Is Ineffective against Persistent Mycobacterium tuberculosis in the Cornell Mouse Model

Tuberculosis (TB), which is caused by Mycobacterium tuberculosis, remains a leading killer worldwide, and disease control is hampered by the ineffective control of persistent infections. Substitution of moxifloxacin for isoniazid or ethambutol in standard anti-TB regimens reduces the treatment duration and relapse rates in animal studies, and 4-month regimens were not noninferior in clinical trials. Resuscitation-promoting factor (RPF)-dependent bacilli have recently been implicated in M. tuberculosis persistence. We aimed to investigate the therapeutic effects of the substitution of moxifloxacin for a drug used in the standard drug regimen in eradicating CFU count-positive and RPF-dependent persistent M. tuberculosis using the Cornell murine model. M. tuberculosis-infected mice were treated with regimens in which either isoniazid or ethambutol was replaced by moxifloxacin in the standard regimen. The efficacy of the regimens for bacterial CFU count elimination and removal of persistent tubercle bacilli, evaluated using culture filtrate (CF) derived from M. tuberculosis strain H37Rv, was compared to that of the standard regimen. We also measured disease relapse rates. The regimen in which moxifloxacin replaced isoniazid achieved total organ CFU count clearance at 11 weeks posttreatment, which was faster than that by the standard regimen (14 weeks), and showed a 34% lower relapse rate. The regimen in which moxifloxacin replaced ethambutol was similar to standard regimens in these regards. Importantly, neither the regimen in which moxifloxacin replaced isoniazid or ethambutol nor the standard regimen could remove CF-dependent persistent bacilli. The finding of CF-dependent persistent M. tuberculosis in TB treatment requires confirmation in human studies and has implications for future drug design, testing, and clinical applications.

Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model

If improvements are to be made in tuberculosis (TB) treatment, an increased understanding of disease in the lung is needed. Studies have shown that bacteria in a less metabolically active state, associated with the presence of lipid bodies, are less susceptible to antibiotics, and recent results have highlighted the disparity in concentration of different compounds into lesions. Treatment success therefore depends critically on the responses of the individual bacteria that constitute the infection. We propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the cellular level, linking the behaviour of individual bacteria and host cells with the macroscopic behaviour of the microenvironment. The individual elements (bacteria, macrophages and T cells) are modelled using cellular automaton (CA) rules, and the evolution of oxygen, drugs and chemokine dynamics are incorporated in order to study the effects of the microenvironment in the pathological lesion. We allow bacteria to switch states depending on oxygen concentration, which affects how they respond to treatment. This is the first multiscale model of its type to consider both oxygen-driven phenotypic switching of the Mycobacterium tuberculosis and antibiotic treatment. Using this model, we investigate the role of bacterial cell state and of initial bacterial location on treatment outcome. We demonstrate that when bacteria are located further away from blood vessels, less favourable outcomes are more likely, i.e. longer time before infection is contained/cleared, treatment failure or later relapse. We also show that in cases where bacteria remain at the end of simulations, the organisms tend to be slower-growing and are often located within granulomas, surrounded by caseous material.

Detecting Phenotypically Resistant Mycobacterium tuberculosis Using Wavelength Modulated Raman Spectroscopy

Raman spectroscopy is a non-destructive and label-free technique. Wavelength modulated Raman (WMR) spectroscopy was applied to investigate Mycobacterium tuberculosis cell state, lipid rich (LR) and lipid poor (LP). Compared to LP cells, LR cells can be up to 40 times more resistant to key antibiotic regimens. Using this methodology single lipid rich (LR) from lipid poor (LP) bacteria can be differentiated with both high sensitivity and specificity. It can also be used to investigate experimentally infected frozen tissue sections where both cell types can be differentiated. This methodology could be utilized to study the phenotype of mycobacterial cells in other tissues.

A comparison of liquid and solid culture for determining relapse and durable cure in phase III TB trials for new regimens

BACKGROUND

Tuberculosis kills more people than any other infectious disease, and new regimens are essential. The primary endpoint for confirmatory phase III trials for new regimens is a composite outcome that includes bacteriological treatment failure and relapse. Culture methodology is critical to the primary trial outcome. Patients in clinical trials can have positive cultures after treatment ends that may not necessarily indicate relapse, which was ascribed previously to laboratory cross-contamination or breakdown of old lesions. Löwenstein-Jensen (LJ) medium was the previous standard in clinical trials, but almost all current and future trials will use the Mycobacteria Growth Indicator Tube (MGIT) system due to its simplicity and consistency of use, which will affect phase III trial results. LJ was used for the definition of the primary endpoint in the REMoxTB trial, but every culture was also inoculated in parallel into the MGIT system. The data from this trial, therefore, provide a unique opportunity to investigate and compare the incidence of false 'isolated positives' in liquid and solid media and their potential impact on the primary efficacy results.

METHODS

All post-treatment positive cultures were reviewed in the REMoxTB clinical trial. Logistic regression models were used to model the incidence of isolated positive cultures on MGIT and LJ.

RESULTS

A total of 12,209 sputum samples were available from 1652 patients; cultures were more often positive on MGIT than LJ. In 1322 patients with a favourable trial outcome, 126 (9.5%) had cultures that were positive in MGIT compared to 34 (2.6%) patients with positive cultures on LJ. Among patients with a favourable outcome, the incidence of isolated positives on MGIT differed by study laboratory (p < 0.0001) with 21.9% of these coming from one laboratory investigating only 4.9% of patients. No other baseline factors predicted isolated positives on MGIT after adjusting for laboratory. There was evidence of clustering of isolated positive cultures in some patients even after adjusting for laboratory, p < 0.0001. The incidence of isolated positives on MGIT did not differ by treatment arm (p = 0.845, unadjusted). Compared to negative MGIT cultures, positive MGIT cultures were more likely to be associated with higher grade TB symptoms reported within 7 days either side of sputum collection in patients with an unfavourable primary outcome (p < 0.0001) but not in patients with a favourable outcome (p = 0.481).

CONCLUSIONS

Laboratory cross-contamination was a likely cause of isolated positive MGIT cultures which were clustered in some laboratories. Certain patients had repeated positive MGIT cultures that did not meet the definition of a relapse. This pattern was too common to be explained by cross-contamination only, suggesting that host factors were also responsible. We conclude that MGIT can replace LJ in phase III TB trials, but there are implications for the definition of the primary outcome and patient management in trials in such settings. Most importantly, the methodologies differ in the incidence of isolated positives and in their capacity for capturing non-tuberculosis mycobacteria. It emphasises the importance of effective medical monitoring after treatment ends and consideration of clinical signs and symptoms for determining treatment failure and relapse.

Robust fit of Bayesian mixed effects regression models with application to colony forming unit count in tuberculosis research

Early bactericidal activity of tuberculosis drugs is conventionally assessed using statistical regression modeling of colony forming unit (CFU) counts over time. Typically, most CFU counts deviate little from the regression curve, but gross outliers due to erroneous sputum sampling are occasionally present and can markedly influence estimates of the rate of change in CFU count, which is the parameter of interest. A recently introduced Bayesian nonlinear mixed effects regression model was adapted to offer a robust approach that accommodates both outliers and potential skewness in the data. At its most general, the proposed regression model fits the skew Student t distribution to residuals and random coefficients. Deviance information criterion statistics and compound Laplace-Metropolis marginal likelihoods were used to discriminate between alternative Bayesian nonlinear mixed effects regression models. We present a relatively easy method to calculate the marginal likelihoods required to determine compound Laplace-Metropolis marginal likelihoods, by adapting methods available in currently available statistical software. The robust methodology proposed in this paper was applied to data from 6 clinical trials. The results provide strong evidence that the distribution of CFU count is often heavy tailed and negatively skewed (suggesting the presence of outliers). Therefore, we recommend that robust regression models, such as those proposed here, should be fitted to CFU count.

Using biomarkers to predict TB treatment duration (Predict TB): a prospective, randomized, noninferiority, treatment shortening clinical trial

Background: By the early 1980s, tuberculosis treatment was shortened from 24 to 6 months, maintaining relapse rates of 1-2%. Subsequent trials attempting shorter durations have failed, with 4-month arms consistently having relapse rates of 15-20%. One trial shortened treatment only among those without baseline cavity on chest x-ray and whose month 2 sputum culture converted to negative. The 4-month arm relapse rate decreased to 7% but was still significantly worse than the 6-month arm (1.6%, P<0.01).  We hypothesize that PET/CT characteristics at baseline, PET/CT changes at one month, and markers of residual bacterial load will identify patients with tuberculosis who can be cured with 4 months (16 weeks) of standard treatment.

Methods: This is a prospective, multicenter, randomized, phase 2b, noninferiority clinical trial of pulmonary tuberculosis participants. Those eligible start standard of care treatment. PET/CT scans are done at weeks 0, 4, and 16 or 24. Participants who do not meet early treatment completion criteria (baseline radiologic severity, radiologic response at one month, and GeneXpert-detectable bacilli at four months) are placed in Arm A (24 weeks of standard therapy). Those who meet the early treatment completion criteria are randomized at week 16 to continue treatment to week 24 (Arm B) or complete treatment at week 16 (Arm C). The primary endpoint compares the treatment success rate at 18 months between Arms B and C.

Discussion: Multiple biomarkers have been assessed to predict TB treatment outcomes. This study uses PET/CT scans and GeneXpert (Xpert) cycle threshold to risk stratify participants. PET/CT scans are not applicable to global public health but could be used in clinical trials to stratify participants and possibly become a surrogate endpoint. If the Predict TB trial is successful, other immunological biomarkers or transcriptional signatures that correlate with treatment outcome may be identified. Trial Registration: NCT02821832

Biomarkers of Tuberculosis Severity and Treatment Effect: A Directed Screen of 70 Host Markers in a Randomized Clinical Trial

More efficacious treatment regimens are needed for tuberculosis, however, drug development is impeded by a lack of reliable biomarkers of disease severity and of treatment effect. We conducted a directed screen of host biomarkers in participants enrolled in a tuberculosis clinical trial to address this need. Serum samples from 319 protocol-correct, culture-confirmed pulmonary tuberculosis patients treated under direct observation as part of an international, phase 2 trial were screened for 70 markers of infection, inflammation, and metabolism. Biomarker assays were specifically developed for this study and quantified using a novel, multiplexed electrochemiluminescence assay. We evaluated the association of biomarkers with baseline characteristics, as well as with detailed microbiologic data, using Bonferroni-adjusted, linear regression models. Across numerous analyses, seven proteins, SAA1, PCT, IL-1β, IL-6, CRP, PTX-3 and MMP-8, showed recurring strong associations with markers of baseline disease severity, smear grade and cavitation; were strongly modulated by tuberculosis treatment; and had responses that were greater for patients who culture-converted at 8weeks. With treatment, all proteins decreased, except for osteocalcin, MCP-1 and MCP-4, which significantly increased. Several previously reported putative tuberculosis-associated biomarkers (HOMX1, neopterin, and cathelicidin) were not significantly associated with treatment response. In conclusion, across a geographically diverse and large population of tuberculosis patients enrolled in a clinical trial, several previously reported putative biomarkers were not significantly associated with treatment response, however, seven proteins had recurring strong associations with baseline radiographic and microbiologic measures of disease severity, as well as with early treatment response, deserving additional study.

Label-free optical vibrational spectroscopy to detect the metabolic state of M. tuberculosis cells at the site of disease

Tuberculosis relapse is a barrier to shorter treatment. It is thought that lipid rich cells, phenotypically resistant to antibiotics, may play a major role. Most studies investigating relapse use sputum samples although tissue bacteria may play an important role. We developed a non-destructive, label-free technique combining wavelength modulated Raman (WMR) spectroscopy and fluorescence detection (Nile Red staining) to interrogate Mycobacterium tuberculosis cell state. This approach could differentiate single "dormant" (lipid rich, LR) and "non-dormant" (lipid poor, LP) cells with high sensitivity and specificity. We applied this to experimentally infected guinea pig lung sections and were able to distinguish both cell types showing that the LR phenotype dominates in infected tissue. Both in-vitro and ex-vivo spectra correlated well, showing for the first time that Mycobacterium tuberculosis, likely to be phenotypically resistant to antibiotics, are present in large numbers in tissue. This is an important step in understanding the pathology of relapse supporting the idea that they may be caused by M. tuberculosis cells with lipid inclusions.

Assessment of treatment response by colony forming units, time to culture positivity and the molecular bacterial load assay compared in a mouse tuberculosis model

The aim of the study is to compare counting of colony forming units (CFU), the time to positivity (TTP) assay and the molecular bacterial load (MBL) assay, and explore whether the last assays can detect a subpopulation which is unable to grown on solid media. CFU counting, TTP and the MBL assay were used to determine the mycobacterial load in matched lung samples of a murine tuberculosis model. Mice were treated for 24 weeks with 4 treatment arms: isoniazid (H) - rifampicin (R) - pyrazinamide (Z), HRZ-Streptomycin (S), HRZ - ethambutol (E) or ZES. Inverse relationships were observed when comparing TPP with CFU or MBL. Positive associations were observed when comparing CFU with MBL. Description of the net elimination of bacteria was performed for CFU vs. time, MBL vs. time and 1/TTP vs. time and fitted by nonlinear regression. CFU vs. time and 1/TTP vs. time showed bi-phasic declines with the exception of HRZE. A similar rank order, based on the alpha slope, was found comparing CFU vs. time and TTP vs. time, respectively HRZE, HRZ, HRZS and ZES. In contrast, MBL vs. time showed a mono-phasic decline with a flat gradient of elimination and a different rank order respectively, ZES, HRZ, HRZE and HRZS. The correlations found between methods reflects the ability of each to discern the general mycobacterial load. Based on the description of net elimination, we conclude that the MBL assay can detect a subpopulation of Mycobacterium tuberculosis which is not detected by the CFU or TTP assays.

Sharing the spotlight in Durban: A report from IAS TB2016 at AIDS2016

Tuberculosis (TB) is now recognized as the number one cause of death worldwide due to a single infectious pathogen and is the cause of death in one-third of people living with HIV worldwide. An inaugural pre-conference focused on TB (TB2016) was held at the International AIDS Society Conference AIDS2016. This report focuses on key messages from the TB2016 conference that are important for the medical, public health, activist, and scientific communities.

Bacterial Loads Measured by the Xpert MTB/RIF Assay as Markers of Culture Conversion and Bacteriological Cure in Pulmonary TB

INTRODUCTION

Biomarkers are needed to monitor tuberculosis (TB) treatment and predict treatment outcomes. We evaluated the Xpert MTB/RIF (Xpert) assay as a biomarker for TB treatment during and at the end of the 24 weeks therapy.

METHODS

Sputum from 108 HIV-negative, culture-positive pulmonary TB patients was analyzed using Xpert at time points before and during anti-TB therapy. Results were compared against culture. Direct Xpert cycle-threshold (Ct), a change in the Ct (delta Ct), or a novel "percent closing of baseline Ct deficit" (percent closing) were evaluated as classifiers of same-day and end-of-treatment culture and therapeutic outcomes.

RESULTS

Xpert was positive in 29/95 (30.5%) of subjects at week 24; and positive one year after treatment in 8/64 (12.5%) successfully-treated patients who remained free of tuberculosis. We identified a relationship between initial bacterial load measured by baseline Xpert Ct and time to culture conversion (hazard ratio 1.06, p = 0.0023), and to the likelihood of being among the 8 treatment failures at week 24 (AUC = 72.8%). Xpert Ct was even more strongly associated with culture conversion on the day the test was performed with AUCs 96.7%, 99.2%, 86.0% and 90.2%, at Day 7, Week 4, 8 and 24, respectively. Compared to baseline Ct measures alone, a combined measure of baseline Ct plus either Delta Ct or percent closing improved the classification of treatment failure status to a 75% sensitivity and 88.9% specificity.

CONCLUSIONS

Genome loads measured by Xpert provide a potentially-useful biomarker for classifying same day culture status and predicting response to therapy.

Defining dormancy in mycobacterial disease

Tuberculosis remains a threat to global health and recent attempts to shorten therapy have not succeeded mainly due to cases of clinical relapse. This has focussed attention on the importance of "dormancy" in tuberculosis. There are a number of different definitions of the term and a similar multiplicity of different in vitro and in vivo models. The danger with this is the implicit assumption of equivalence between the terms and models, which will make even more difficult to unravel this complex conundrum. In this review we summarise the main models and definitions and their impact on susceptibility of Mycobacterium tuberculosis. We also suggest a potential nomenclature for debate. Dormancy researchers agree that factors underpinning this phenomenon are complex and nuanced. If we are to make progress we must agree the terms to be used and be consistent in using them.

A new trial design to accelerate tuberculosis drug development: the Phase IIC Selection Trial with Extended Post-treatment follow-up (STEP)

BACKGROUND

The standard 6-month four-drug regimen for the treatment of drug-sensitive tuberculosis has remained unchanged for decades and is inadequate to control the epidemic. Shorter, simpler regimens are urgently needed to defeat what is now the world's greatest infectious disease killer.

METHODS

We describe the Phase IIC Selection Trial with Extended Post-treatment follow-up (STEP) as a novel hybrid phase II/III trial design to accelerate regimen development. In the Phase IIC STEP trial, the experimental regimen is given for the duration for which it will be studied in phase III (presently 3 or 4 months) and patients are followed for clinical outcomes of treatment failure and relapse for a total of 12 months from randomisation. Operating characteristics of the trial design are explored assuming a classical frequentist framework as well as a Bayesian framework with flat and sceptical priors. A simulation study is conducted using data from the RIFAQUIN phase III trial to illustrate how such a design could be used in practice.

RESULTS

With 80 patients per arm, and two (2.5 %) unfavourable outcomes in the STEP trial, there is a probability of 0.99 that the proportion of unfavourable outcomes in a potential phase III trial would be less than 12 % and a probability of 0.91 that the proportion of unfavourable outcomes would be less than 8 %. With six (7.5 %) unfavourable outcomes, there is a probability of 0.82 that the proportion of unfavourable outcomes in a potential phase III trial would be less than 12 % and a probability of 0.41 that it would be less than 8 %. Simulations using data from the RIFAQUIN trial show that a STEP trial with 80 patients per arm would have correctly shown that the Inferior Regimen should not proceed to phase III and would have had a high chance (0.88) of either showing that the Successful Regimen could proceed to phase III or that it might require further optimisation.

CONCLUSIONS

Collection of definitive clinical outcome data in a relatively small number of participants over only 12 months provides valuable information about the likelihood of success in a future phase III trial. We strongly believe that the STEP trial design described herein is an important tool that would allow for more informed decision-making and accelerate regimen development.

Uniting to end the TB epidemic: advances in disease control from prevention to better diagnosis and treatment

Tuberculosis is a major global cause of morbidity and mortality. Despite recent advances in containing the epidemic, several challenges continue to slow progress towards elimination including the continuing impact of drug resistant disease, and the lack of appropriate tools. Curtailing the transmission of tuberculosis remains a challenge especially in high burden countries. New developments in measuring correlates of protection are urgently needed to support the evaluation of vaccines. Similarly, despite progress in molecular diagnostics, better tools are required to identify resistance to antibiotics in multi and extensively drug resistant tuberculosis. Whole Genome Sequencing may lead to the next generation of assays to rapidly detect resistance and evaluate transmission. Advances on shortening treatment are hampered by the lack of a biomarker of cure which obviates the current long wait for relapses in trials. New research is urgently needed to support development of new vaccines and better diagnostics tools and shorter treatment for drug sensitive and resistant tuberculosis.