A Bayesian response-adaptive trial in tuberculosis: The endTB trial

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.

Determining the minimum duration of treatment in tuberculosis: An order restricted non-inferiority trial design

Tuberculosis (TB) is one of the biggest killers among infectious diseases worldwide. Together with the identification of drugs that can provide benefits to patients, the challenge in TB is also the optimisation of the duration of these treatments. While conventional duration of treatment in TB is 6 months, there is evidence that shorter durations might be as effective but could be associated with fewer side effects and may be associated with better adherence. Based on a recent proposal of an adaptive order-restricted superiority design that employs the ordering assumptions within various duration of the same drug, we propose a non-inferiority (typically used in TB trials) adaptive design that effectively uses the order assumption. Together with the general construction of the hypothesis testing and expression for type I and type II errors, we focus on how the novel design was proposed for a TB trial concept. We consider a number of practical aspects such as choice of the design parameters, randomisation ratios, and timings of the interim analyses, and how these were discussed with the clinical team.

A comparison of clinical development pathways to advance tuberculosis regimen development

BACKGROUND

Current tuberculosis (TB) regimen development pathways are slow and in urgent need of innovation. We investigated novel phase IIc and seamless phase II/III trials utilizing multi-arm multi-stage and Bayesian response adaptive randomization trial designs to select promising combination regimens in a platform adaptive trial.

METHODS

Clinical trial simulation tools were built using predictive and validated parametric survival models of time to culture conversion (intermediate endpoint) and time to TB-related unfavorable outcome (final endpoint). This integrative clinical trial simulation tool was used to explore and optimize design parameters for aforementioned trial designs.

RESULTS

Both multi-arm multi-stage and Bayesian response adaptive randomization designs were able to reliably graduate desirable regimens in ≥ 95% of trial simulations and reliably stop suboptimal regimens in ≥ 90% of trial simulations. Overall, adaptive phase IIc designs reduced patient enrollment by 17% and 25% with multi-arm multi-stage and Bayesian response adaptive randomization designs respectively compared to the conventional sequential approach, while seamless designs reduced study duration by 2.6 and 3.5 years respectively (typically ≥ 8.5 years for standard sequential approach).

CONCLUSIONS

In this study, we demonstrate that adaptive trial designs are suitable for TB regimen development, and we provide plausible design parameters for a platform adaptive trial. Ultimately trial design and specification of design parameters will depend on clinical trial objectives. To support decision-making for clinical trial designs in contemporary TB regimen development, we provide a flexible clinical trial simulation tool that can be used to explore and optimize design features and parameters.

Rethinking intercurrent events in defining estimands for tuberculosis trials

BACKGROUND/AIMS

Tuberculosis remains one of the leading causes of death from an infectious disease globally. Both choices of outcome definitions and approaches to handling events happening post-randomisation can change the treatment effect being estimated, but these are often inconsistently described, thus inhibiting clear interpretation and comparison across trials.

METHODS

Starting from the ICH E9(R1) addendum's definition of an estimand, we use our experience of conducting large Phase III tuberculosis treatment trials and our understanding of the estimand framework to identify the key decisions regarding how different event types are handled in the primary outcome definition, and the important points that should be considered in making such decisions. A key issue is the handling of intercurrent (i.e. post-randomisation) events (ICEs) which affect interpretation of or preclude measurement of the intended final outcome. We consider common ICEs including treatment changes and treatment extension, poor adherence to randomised treatment, re-infection with a new strain of tuberculosis which is different from the original infection, and death. We use two completed tuberculosis trials (REMoxTB and STREAM Stage 1) as illustrative examples. These trials tested non-inferiority of new tuberculosis treatment regimens versus a control regimen. The primary outcome was a binary composite endpoint, 'favourable' or 'unfavourable', which was constructed from several components.

RESULTS

We propose the following improvements in handling the above-mentioned ICEs and loss to follow-up (a post-randomisation event that is not in itself an ICE). First, changes to allocated regimens should not necessarily be viewed as an unfavourable outcome; from the patient perspective, the potential harms associated with a change in the regimen should instead be directly quantified. Second, handling poor adherence to randomised treatment using a per-protocol analysis does not necessarily target a clear estimand; instead, it would be desirable to develop ways to estimate the treatment effects more relevant to programmatic settings. Third, re-infection with a new strain of tuberculosis could be handled with different strategies, depending on whether the outcome of interest is the ability to attain culture negativity from infection with any strain of tuberculosis, or specifically the presenting strain of tuberculosis. Fourth, where possible, death could be separated into tuberculosis-related and non-tuberculosis-related and handled using appropriate strategies. Finally, although some losses to follow-up would result in early treatment discontinuation, patients lost to follow-up before the end of the trial should not always be classified as having an unfavourable outcome. Instead, loss to follow-up should be separated from not completing the treatment, which is an ICE and may be considered as an unfavourable outcome.

CONCLUSION

The estimand framework clarifies many issues in tuberculosis trials but also challenges trialists to justify and improve their outcome definitions. Future trialists should consider all the above points in defining their outcomes.

Bayesian adaptive clinical trial designs for respiratory medicine

The use of Bayesian adaptive designs for clinical trials has increased in recent years, particularly during the COVID‐19 pandemic. Bayesian adaptive designs offer a flexible and efficient framework for conducting clinical trials and may provide results that are more useful and natural to interpret for clinicians, compared to traditional approaches. In this review, we provide an introduction to Bayesian adaptive designs and discuss its use in recent clinical trials conducted in respiratory medicine. We illustrate this approach by constructing a Bayesian adaptive design for a multi‐arm trial that compares two non‐invasive ventilation treatments to standard oxygen therapy for patients with acute cardiogenic pulmonary oedema. We highlight the benefits and some of the challenges involved in designing and implementing Bayesian adaptive trials.

Pyrazinamide Resistance and pncA Mutation Profiles in Multidrug Resistant Mycobacterium Tuberculosis

Purpose

Pyrazinamide (PZA) is a critical component of standardized chemotherapy for tuberculosis (TB) and is recommended for the treatment of multidrug-resistant (MDR) TB. We aimed to characterize mutations in pncA of M. tuberculosis and evaluate their diagnostic accuracy for PZA susceptibility in China. We also combined genotypic methods with phenotypic susceptibility testing and pyrazinamidase (PZAse) activity to confirm PZA-resistant M. tuberculosis isolates.

Results

An evaluation of 82 MDR M. tuberculosis strains revealed that 28.0% (23/82) were phenotypically resistant to 100 mg/L PZA and 15.9% (13/82) showed resistance to 300 mg/L PZA. Mutations in pncA were detected at 33 unique sites, and the majority were point mutations. No evident mutation hotspots or mutations affecting multiple amino acids were found, but the association between pncA mutations and PZA resistance was significant under 100 and 300 mg/L. The sensitivity of pncA mutation detection for predicting PZA susceptibility was 82.6% (19/23), and the specificity was 61.0% (36/59), based on 100 mg/L PZA, whereas the sensitivity was 84.6% (11/13) and the specificity was 55.1% (38/69), based on 300 mg/L PZA. All mutations identified in the highly PZA-resistant (300 mg/L) strains had an 80% loss relative to PZAse activity. No evident PZAse activity loss was observed in one synonymous mutation strain and the loss exceed 60% in all other strains.

Conclusion

The association between pncA mutation and PZA resistance was significant. Relatively, the molecular method have shown better reliability than the phenotypic method for the detection of PZA resistance. This provides a theoretical basis for the clinical diagnosis of drug-resistant TB.

Evaluating newly approved drugs for multidrug-resistant tuberculosis (endTB): study protocol for an adaptive, multi-country randomized controlled trial

BACKGROUND

Treatment of multidrug- and rifampin-resistant tuberculosis (MDR/RR-TB) is expensive, labour-intensive, and associated with substantial adverse events and poor outcomes. While most MDR/RR-TB patients do not receive treatment, many who do are treated for 18 months or more. A shorter all-oral regimen is currently recommended for only a sub-set of MDR/RR-TB. Its use is only conditionally recommended because of very low-quality evidence underpinning the recommendation. Novel combinations of newer and repurposed drugs bring hope in the fight against MDR/RR-TB, but their use has not been optimized in all-oral, shorter regimens. This has greatly limited their impact on the burden of disease. There is, therefore, dire need for high-quality evidence on the performance of new, shortened, injectable-sparing regimens for MDR-TB which can be adapted to individual patients and different settings.

METHODS

endTB is a phase III, pragmatic, multi-country, adaptive, randomized, controlled, parallel, open-label clinical trial evaluating the efficacy and safety of shorter treatment regimens containing new drugs for patients with fluoroquinolone-susceptible, rifampin-resistant tuberculosis. Study participants are randomized to either the control arm, based on the current standard of care for MDR/RR-TB, or to one of five 39-week multi-drug regimens containing newly approved and repurposed drugs. Study participation in all arms lasts at least 73 and up to 104 weeks post-randomization. Randomization is response-adapted using interim Bayesian analysis of efficacy endpoints. The primary objective is to assess whether the efficacy of experimental regimens at 73 weeks is non-inferior to that of the control. A sample size of 750 patients across 6 arms affords at least 80% power to detect the non-inferiority of at least 1 (and up to 3) experimental regimens, with a one-sided alpha of 0.025 and a non-inferiority margin of 12%, against the control in both modified intention-to-treat and per protocol populations.

DISCUSSION

The lack of a safe and effective regimen that can be used in all patients is a major obstacle to delivering appropriate treatment to all patients with active MDR/RR-TB. Identifying multiple shorter, safe, and effective regimens has the potential to greatly reduce the burden of this deadly disease worldwide.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT02754765. Registered on 28 April 2016; the record was last updated for study protocol version 3.3, on 27 August 2019.

Evaluating Bayesian adaptive randomization procedures with adaptive clip methods for multi-arm trials

Bayesian adaptive randomization is a heuristic approach that aims to randomize more patients to the putatively superior arms based on the trend of the accrued data in a trial. Many statistical aspects of this approach have been explored and compared with other approaches; yet only a limited number of works has focused on improving its performance and providing guidance on its application to real trials. An undesirable property of this approach is that the procedure would randomize patients to an inferior arm in some circumstances, which has raised concerns in its application. Here, we propose an adaptive clip method to rectify the problem by incorporating a data-driven function to be used in conjunction with Bayesian adaptive randomization procedure. This function aims to minimize the chance of assigning patients to inferior arms during the early time of the trial. Moreover, we propose a utility approach to facilitate the selection of a randomization procedure. A cost that reflects the penalty of assigning patients to the inferior arm(s) in the trial is incorporated into our utility function along with all patients benefited from the trial, both within and beyond the trial. We illustrate the selection strategy for a wide range of scenarios.

The Bayesian Design of Adaptive Clinical Trials

This paper presents a brief overview of the recent literature on adaptive design of clinical trials from a Bayesian perspective for statistically not so sophisticated readers. Adaptive designs are attracting a keen interest in several disciplines, from a theoretical viewpoint and also—potentially—from a practical one, and Bayesian adaptive designs, in particular, have raised high expectations in clinical trials. The main conceptual tools are highlighted here, with a mention of several trial designs proposed in the literature that use these methods, including some of the registered Bayesian adaptive trials to this date. This review aims at complementing the existing ones on this topic, pointing at further interesting reading material.

Are We There Yet? Short-Course Regimens in TB and HIV: From Prevention to Treatment of Latent to XDR TB

PURPOSE OF REVIEW

Despite broad uptake of antiretroviral therapy (ART), tuberculosis (TB) incidence and mortality among people with HIV remain unacceptably high. Short-course regimens for TB, incorporating both novel and established drugs, offer the potential to enhance adherence and completion rates, thereby reducing the global TB burden. This review will outline short-course regimens for TB among patients with HIV.

RECENT FINDINGS

After many years without new agents, there is now active testing of many novel drugs to treat TB, both for latent infection and active disease. Though not all studies have included patients with HIV, many have, and there are ongoing trials to address key implementation challenges such as potent drug-drug interactions with ART. The goal of short-course regimens for TB is to enhance treatment completion without compromising efficacy. Particularly among patients with HIV, studying these shortened regimens and integrating them into clinical care are of urgent importance. There are now multiple short-course regimens for latent infection and active disease that are safe and effective among patients with HIV.

A Bayesian response-adaptive dose-finding and comparative effectiveness trial

BACKGROUND/AIMS

Combinations of treatments that have already received regulatory approval can offer additional benefit over Each of the treatments individually. However, trials of these combinations are lower priority than those that develop novel therapies, which can restrict funding, timelines and patient availability. This article develops a novel trial design to facilitate the evaluation of New combination therapies. This trial design combines elements of phase II and phase III trials to reduce the burden of evaluating combination therapies, while also maintaining a feasible sample size. This design was developed for a randomised trial that compares the properties of three combination doses of ketamine and dexmedetomidine, given intranasally, to ketamine delivered intravenously for children undergoing a closed reduction for a fracture or dislocation.

METHODS

This trial design uses response-adaptive randomisation to evaluate different dose combinations and increase the information collected for successful novel drug combinations. The design then uses Bayesian dose-response modelling to undertake a comparative effectiveness analysis for the most successful dose combination against a relevant comparator. We used simulation methods determine the thresholds for adapting the trial and making conclusions. We also used simulations to evaluate the probability of selecting the dose combination with the highest true effectiveness the operating characteristics of the design and its Bayesian predictive power.

RESULTS

With 410 participants, five interim updates of the randomisation ratio and a probability of effectiveness of 0.93, 0.88 and 0.83 for the three dose combinations, we have an 83% chance of randomising the largest number of patients to the drug with the highest probability of effectiveness. Based on this adaptive randomisation procedure, the comparative effectiveness analysis has a type I error of less than 5% and a 93% chance of correcting concluding non-inferiority, when the probability of effectiveness for the optimal combination therapy is 0.9. In this case, the trial has a greater than 77% chance of meeting its dual aims of dose-finding and comparative effectiveness. Finally, the Bayesian predictive power of the trial is over 90%.

CONCLUSIONS

By simultaneously determining the optimal dose and collecting data on the relative effectiveness of an intervention, we can minimise administrative burden and recruitment time for a trial. This will minimise the time required to get effective, safe combination therapies to patients quickly. The proposed trial has high potential to meet the dual study objectives within a feasible overall sample size.

The design and statistical aspects of VIETNARMS: a strategic post-licensing trial of multiple oral direct-acting antiviral hepatitis C treatment strategies in Vietnam

BACKGROUND

Eliminating hepatitis C is hampered by the costs of direct-acting antiviral treatment and the need to treat hard-to-reach populations. Access could be widened by shortening or simplifying treatment, but limited research means it is unclear which approaches could achieve sufficiently high cure rates to be acceptable. We present the statistical aspects of a multi-arm trial designed to test multiple strategies simultaneously and a monitoring mechanism to detect and stop individual randomly assigned groups with unacceptably low cure rates quickly.

METHODS

The VIETNARMS trial will factorially randomly assign patients to two drug regimens, three treatment-shortening strategies or control, and adjunctive ribavirin or no adjunctive ribavirin with shortening strategies (14 randomly assigned groups). We will use Bayesian monitoring at interim analyses to detect and stop recruitment into unsuccessful strategies, defined by more than 0.95 posterior probability that the true cure rate is less than 90% for the individual randomly assigned group (non-comparative). Final comparisons will be non-inferiority for regimens (margin 5%) and strategies (margin 10%) and superiority for adjunctive ribavirin. Here, we tested the operating characteristics of the stopping guideline for individual randomly assigned groups, planned interim analysis timings and explored power at the final analysis.

RESULTS

A beta (4.5, 0.5) prior for the true cure rate produces less than 0.05 probability of incorrectly stopping an individual randomly assigned group with a true cure rate of more than 90%. Groups with very low cure rates (<60%) are very likely (>0.9 probability) to stop after about 25% of patients are recruited. Groups with moderately low cure rates (80%) are likely to stop (0.7 probability) before overall recruitment finishes. Interim analyses 7, 10, 13 and 18 months after recruitment commences provide good probabilities of stopping inferior individual randomly assigned groups. For an overall true cure rate of 95%, power is more than 90% to confirm non-inferiority in the regimen and strategy comparisons, regardless of the control cure rate, and to detect a 5% absolute difference in the ribavirin comparison.

CONCLUSIONS

The operating characteristics of the stopping guideline are appropriate, and interim analyses can be timed to detect individual randomly assigned groups that are highly likely to have suboptimal performance at various stages. Therefore, our design is suitable for evaluating treatment-shortening or -simplifying strategies.

TRIAL REGISTRATION

ISRCTN registry: ISRCTN61522291. Registered on 4 October 2019.

Advances in clinical trial design: Weaving tomorrow's TB treatments

Christian Lienhardt and co-authors discuss the conclusions of the PLOS Medicine Collection on advances in clinical trial design for development of new tuberculosis treatments.

An introduction to clinical trial design

Clinicians and other decision makers in healthcare use results from clinical trials to inform practice. Interpretation of clinical trial results can be challenging, as weaknesses in trial design, data collection, analysis or reporting, can compromise the usefulness of results. A good working knowledge of clinical trial design is essential to expertly interpret and determine the validity and generalizability of the results. This manuscript will give a brief overview of clinical trial design including the strengths and limitations of various approaches. The focus will be on confirmatory clinical trials.

Frequentist operating characteristics of Bayesian optimal designs via simulation

Bayesian adaptive designs have become popular because of the possibility of increasing the number of patients treated with more beneficial treatments, while still providing sufficient evidence for treatment efficacy comparisons. It can be essential, for regulatory and other purposes, to conduct frequentist analyses both before and after a Bayesian adaptive trial, and these remain challenging. In this paper, we propose a general simulation-based approach to compare frequentist designs with Bayesian adaptive designs based on frequentist criteria such as power and to compute valid frequentist p-values. We illustrate our approach by comparing the power of an equal randomization (ER) design with that of an optimal Bayesian adaptive (OBA) design. The Bayesian design considered here is the dynamic programming solution of the optimization of a specific utility function defined by the number of successes in a patient horizon, including patients whose treatment will be affected by the trial's results after the end of the trial. While the power of an ER design depends on treatment efficacy and the sample size, the power of the OBA design also depends on the patient horizon size. Our results quantify the trade-off between power and the optimal assignment of patients to treatments within the trial. We show that, for large patient horizons, the two criteria are in agreement, while for small horizons, differences can be substantial. This has implications for precision medicine, where patient horizons are decreasing as a result of increasing stratification of patients into subpopulations defined by molecular markers.

The endTB observational study protocol: treatment of MDR-TB with bedaquiline or delamanid containing regimens

Background

At a time when programs were struggling to design effective regimens for the treatment of multidrug-resistant tuberculosis (MDR-TB), the marketing authorization of bedaquiline and delamanid was a critical development in the MDR-TB treatment landscape. However, despite their availability for routine programmatic use, the uptake of these drugs has remained slow; concerns included a lack of evidence on safety and efficacy and the need to protect the new drugs from the development of acquired resistance. As part of the endTB Project, we aimed to address these barriers by generating evidence on safety and efficacy of bedaquiline or delamanid based MDR-TB regimens.

Methods

This is a protocol for a multi-center prospective cohort study to enroll 2600 patients from April 2015 through September 2018 in 17 countries. The protocol describes inclusion of patients started on treatment with bedaquiline- or delamanid- containing regimens under routine care, who consented to participate in the endTB observational study. Patient follow-up was according to routine monitoring schedules recommended for patients receiving bedaquiline or delamanid as implemented at each endTB site. Therefore, no additional tests were performed as a part of the study. Data were to be collected in a customized, open-source electronic medical record (EMR) system developed as a part of the endTB Project across all 17 countries.

Discussion

The endTB observational study will generate evidence on safety and efficacy of bedaquiline- and delamanid-containing regimens in a large, extremely heterogeneous group of MDR-TB patients, from 17 epidemiologically diverse countries. The systematic, prospective data collection of repeated effectiveness and safety measures, and analyses performed on these data, will improve the quality of evidence available to inform MDR-TB treatment and policy decisions. Further, the resources available to countries through implementation of the endTB project will have permitted countries to: gain experience with the use of these drugs in MDR-TB regimens, improve local capacity to record and report adverse events (pharmacovigilance), and enhance significantly the body of data available for safety evaluation of these drugs and other novel treatments.

Trial registration

This study was registered on 24 August 2017 at clincaltrials.gov (Registration number: NCT03259269).

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4378-4) contains supplementary material, which is available to authorized users.

Optimising trial designs to identify appropriate antibiotic treatment durations

BACKGROUND

For many infectious conditions, the optimal antibiotic course length remains unclear. The estimation of course length must consider the important trade-off between maximising short- and long-term efficacy and minimising antibiotic resistance and toxicity.

MAIN BODY

Evidence on optimal treatment durations should come from randomised controlled trials. However, most antibiotic randomised controlled trials compare two arbitrarily chosen durations. We argue that alternative trial designs, which allow allocation of patients to multiple different treatment durations, are needed to better identify optimal antibiotic durations. There are important considerations when deciding which design is most useful in identifying optimal treatment durations, including the ability to model the duration-response relationship (or duration-response 'curve'), the risk of allocation concealment bias, statistical efficiency, the possibility to rapidly drop arms that are clearly inferior, and the possibility of modelling the trade-off between multiple competing outcomes.

CONCLUSION

Multi-arm designs modelling duration-response curves with the possibility to drop inferior arms during the trial could provide more information about the optimal duration of antibiotic therapies than traditional head-to-head comparisons of limited numbers of durations, while minimising the probability of assigning trial participants to an ineffective treatment regimen.

Adding experimental arms to platform clinical trials: randomization procedures and interim analyses

Multi-arm clinical trials use a single control arm to evaluate multiple experimental treatments. In most cases this feature makes multi-arm studies considerably more efficient than two-arm studies. A bottleneck for implementation of a multi-arm trial is the requirement that all experimental treatments have to be available at the enrollment of the first patient. New drugs are rarely at the same stage of development. These limitations motivate our study of statistical methods for adding new experimental arms after a clinical trial has started enrolling patients. We consider both balanced and outcome-adaptive randomization methods for experimental designs that allow investigators to add new arms, discuss their application in a tuberculosis trial, and evaluate the proposed designs using a set of realistic simulation scenarios. Our comparisons include two-arm studies, multi-arm studies, and the proposed class of designs in which new experimental arms are added to the trial at different time points.

A Trial of a Shorter Regimen for Rifampin-Resistant Tuberculosis

BACKGROUND

Cohort studies in Bangladesh showed promising cure rates among patients with multidrug-resistant tuberculosis who received existing drugs in regimens shorter than that recommended by the World Health Organization (WHO) in 2011.

METHODS

We conducted a phase 3 noninferiority trial in participants with rifampin-resistant tuberculosis that was susceptible to fluoroquinolones and aminoglycosides. Participants were randomly assigned, in a 2:1 ratio, to receive a short regimen (9 to 11 months) that included high-dose moxifloxacin or a long regimen (20 months) that followed the 2011 WHO guidelines. The primary efficacy outcome was a favorable status at 132 weeks, defined by cultures negative for Mycobacterium tuberculosis at 132 weeks and at a previous occasion, with no intervening positive culture or previous unfavorable outcome. An upper 95% confidence limit for the between-group difference in favorable status that was 10 percentage points or less was used to determine noninferiority.

RESULTS

Of 424 participants who underwent randomization, 383 were included in the modified intention-to-treat population. Favorable status was reported in 79.8% of participants in the long-regimen group and in 78.8% of those in the short-regimen group - a difference, with adjustment for human immunodeficiency virus status, of 1.0 percentage point (95% confidence interval [CI], -7.5 to 9.5) (P = 0.02 for noninferiority). The results with respect to noninferiority were consistent among the 321 participants in the per-protocol population (adjusted difference, -0.7 percentage points; 95% CI, -10.5 to 9.1). An adverse event of grade 3 or higher occurred in 45.4% of participants in the long-regimen group and in 48.2% in the short-regimen group. Prolongation of either the QT interval or the corrected QT interval (calculated with Fridericia's formula) to 500 msec occurred in 11.0% of participants in the short-regimen group, as compared with 6.4% in the long-regimen group (P = 0.14); because of the greater incidence in the short-regimen group, participants were closely monitored and some received medication adjustments. Death occurred in 8.5% of participants in the short-regimen group and in 6.4% in the long-regimen group, and acquired resistance to fluoroquinolones or aminoglycosides occurred in 3.3% and 2.3%, respectively.

CONCLUSIONS

In persons with rifampin-resistant tuberculosis that was susceptible to fluoroquinolones and aminoglycosides, a short regimen was noninferior to a long regimen with respect to the primary efficacy outcome and was similar to the long regimen in terms of safety. (Funded by the U.S. Agency for International Development and others; Current Controlled Trials number, ISRCTN78372190; ClinicalTrials.gov number, NCT02409290.).

Trial Refresh: A Case for an Adaptive Platform Trial for Pulmonary Exacerbations of Cystic Fibrosis

Cystic fibrosis is a genetic disease typically characterized by progressive lung damage and premature mortality. Pulmonary exacerbations, or flare-ups of the lung disease, often require hospitalization for intensive treatment. Approximately 25% of patients with cystic fibrosis do not recover their baseline lung function after pulmonary exacerbations. There is a relative paucity of evidence to inform treatment strategies for exacerbations. Compounding this lack of evidence, there are a large number of treatment options already as well as becoming available. This results in significant variability between medication regimens prescribed by different physicians, treatment centers and regions with potentially adverse impact to patients. The conventional strategy is to undertake essential randomized clinical trials to inform treatment decisions and improve outcomes for patients with exacerbations. However, over the past several decades, clinical trials have generally failed to provide information critical to improved treatment and management of exacerbations. Bayesian adaptive platform trials hold the promise of addressing clinical uncertainties and informing treatment. Using modeling and response adaptive randomization, they allow for the evaluation of multiple treatments across different management domains, and progressive improvement in patient outcomes throughout the course of the trial. Bayesian adaptive platform trials require substantial amounts of preparation. Basic preparation includes extensive stakeholder involvement including elicitation of consumer preferences and clinician understanding of the research topic, defining the research questions, determining the best outcome measures, delineating study sub-groups, in depth statistical modeling, designing end-to-end digital solutions seamlessly supporting clinicians, researchers and patients, constructing randomisation algorithms and importantly, defining pre-determined intra-study end-points. This review will discuss the motivation and necessary steps required to embark on a Bayesian adaptive platform trial to optimize medication regimens for the treatment of pulmonary exacerbations of cystic fibrosis.

Introducing molecular testing of pyrazinamide susceptibility improves multidrug-resistant tuberculosis treatment outcomes: a prospective cohort study

The current treatment for multidrug-resistant tuberculosis (MDR-TB) takes a lengthy period of 18-24 months and has a poor cure rate of 50-60%. A multicenter, prospective cohort study was conducted to assess the role of testing for molecular susceptibility to pyrazinamide (PZA) in optimising treatment for MDR-TB.We assigned 76 patients to an optimised molecular susceptibility group and 159 patients to a regular treatment group where PZA susceptibility was not determined. Of these patients, 152 were matched after propensity score matching (76 in the optimised group and 76 in the regular group). Treatment success rate was measured in the propensity-matched cohort as the primary outcome.Patients in the optimised group achieved a higher treatment success rate than those in the regular group (76.3% versus 55.3%, p=0.006). Of 51 patients with isolates that were susceptible to PZA and who were receiving a 12-month regimen, 42 (82.4%) were treated successfully. The optimised group showed faster culture conversion than the regular group (p=0.024). After exclusion of pre-extensively drug-resistant TB (pre-XDR-TB), the treatment outcome in the optimised group was still better than the regular group (83.1% versus 62.1%, p=0.009).Introducing molecular susceptibility testing for PZA improved the treatment outcomes for MDR-TB without the use of new drugs. Introducing PZA for patients with PZA-susceptible (PZA-S) MDR-TB allows the current regimen to be shortened to 12 months with comparable success rates to the World Health Organization (WHO) recommended shorter regimen.

Keeping phase III tuberculosis trials relevant: Adapting to a rapidly changing landscape

In a Collection Review, Patrick Phillips and colleagues discuss developments in clinical trial design for the evaluation of TB therapeutics.

Learning health systems, clinical equipoise and the ethics of response adaptive randomisation

To give substance to the rhetoric of 'learning health systems', a variety of novel trial designs are being explored to more seamlessly integrate research with medical practice, reduce study duration and reduce the number of participants allocated to ineffective interventions. Many of these designs rely on response adaptive randomisation (RAR). However, critics charge that RAR is unethical on the grounds that it violates the principle of equipoise. In this paper, I reconstruct critiques of RAR as holding that it is inconsistent with five important ethical principles. I then argue that these criticisms rest on a faulty view of equipoise encouraged by the idea that a RAR study models the beliefs of a single rational agent about the relative merits of the interventions being studied. I outline a view in which RAR models an idealised health system in which diverse communities of fully informed experts shrink or grow as their constituent members update their expert opinions in light of reliable medical evidence. I show how a proper understanding of clinical equipoise can reconcile this conception of RAR with these five ethical principles. This analysis removes an in-principle objection to RAR and sheds important light on the relationship between clinical equipoise and transient diversity in the scientific community.

Pediatric multidrug-resistant tuberculosis clinical trials: challenges and opportunities

On June 17, 2016, RESIST-TB, IMPAACT, Vital Strategies, and New Ventures jointly hosted the Pediatric Multidrug Resistant Tuberculosis Clinical Trials Landscape Meeting in Arlington, Virginia, USA. The meeting provided updates on current multidrug-resistant tuberculosis (MDR-TB) trials targeting pediatric populations and adult trials that have included pediatric patients. A series of presentations were given that discussed site capacity needs, community engagement, and additional interventions necessary for clinical trials to improve the treatment of pediatric MDR-TB. This article presents a summary of topics discussed, including the following: current trials ongoing and planned; the global burden of MDR-TB in children; current regimens for MDR-TB treatment in children; pharmacokinetics of second-line anti-tuberculosis medications in children; design, sample size, and statistical considerations for MDR-TB trials in children; selection of study population, design, and treatment arms for a trial of novel pediatric MDR-TB regimens; practical aspects of pediatric MDR-TB treatment trials; and strategies for integrating children into adult tuberculosis trials. These discussions elucidated barriers to pediatric MDR-TB clinical trials and provided insight into necessary next steps for progress in this field. Investigators and funding agencies need to respond to these recommendations so that important studies can be implemented, leading to improved treatment for children with MDR-TB.