Standards for clinical trials for treating TB.

BACKGROUND: The value, speed of completion and robustness of the evidence generated by TB treatment trials could be improved by implementing standards for best practice.METHODS: A global panel of experts participated in a Delphi process, using a 7-point Likert scale to score and revise draft standards until consensus was reached.RESULTS: Eleven standards were defined: Standard 1, high quality data on TB regimens are essential to inform clinical and programmatic management; Standard 2, the research questions addressed by TB trials should be relevant to affected communities, who should be included in all trial stages; Standard 3, trials should make every effort to be as inclusive as possible; Standard 4, the most efficient trial designs should be considered to improve the evidence base as quickly and cost effectively as possible, without compromising quality; Standard 5, trial governance should be in line with accepted good clinical practice; Standard 6, trials should investigate and report strategies that promote optimal engagement in care; Standard 7, where possible, TB trials should include pharmacokinetic and pharmacodynamic components; Standard 8, outcomes should include frequency of disease recurrence and post-treatment sequelae; Standard 9, TB trials should aim to harmonise key outcomes and data structures across studies; Standard 10, TB trials should include biobanking; Standard 11, treatment trials should invest in capacity strengthening of local trial and TB programme staff.CONCLUSION: These standards should improve the efficiency and effectiveness of evidence generation, as well as the translation of research into policy and practice.

TB therapeutic drug monitoring - analysis of opportunities in Romania and Ukraine.

INTRODUCTION: Therapeutic drug monitoring (TDM) could improve TB treatment outcomes by avoiding drug toxicity or underdosing. In this study, we describe the patient burden in three TB centres in Romania and Ukraine with a TDM indication, as per the current guidelines, in order to estimate the feasibility of implementing TDM.METHODS: A retrospective multi-centre study was conducted at the Iasi Lung Hospital (Iasi, Romania), Bucharest Marius Nasta Institute (Bucharest, Romania) and Chernivtsi TB Centre (Chernivtsi, Ukraine) in adult hospitalised TB patients.RESULTS: A total of 927 participants were admitted, of whom 37.8% had at least one indication for TDM, the most frequent being slow response to TB treatment (202/345, 58.6%); 55.5% had at least one cavity present on chest X-ray. Patients with a TDM indication stayed in the hospital for a median of 67 days and took on average 2 months more to reach a successful TB outcome.CONCLUSION: TDM could be a valuable tool to improve management of selected TB patients. The decision on whether to perform TDM is often delayed by 2 months due to waiting for culture results after treatment initiation. A randomised control trial should be performed in order to define TDM's precise role in TB therapy.

eHealth in TB clinical management.

BACKGROUND: The constant expansion of internet and mobile technologies has created new opportunities in the field of eHealth, or the digital delivery of healthcare services. This TB meta-analysis aims to examine eHealth and its impact on TB clinical management in order to formulate recommendations for further development.METHODS: A systematic search was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework in PubMed and Embase of articles published up to April 2021. Screening, extraction and quality assessment were performed by two independent researchers. Studies evaluating an internet and/or mobile-based eHealth intervention with an impact on TB clinical management were included. Outcomes were organised following the five domains described in the WHO "Recommendations on Digital Interventions for Health System Strengthening" guideline.RESULTS: Search strategy yielded 3,873 studies, and 89 full texts were finally included. eHealth tended to enhance screening, diagnosis and treatment indicators, while being cost-effective and acceptable to users. The main challenges concern hardware malfunction and software misuse.CONCLUSION: This study offers a broad overview of the innovative field of eHealth applications in TB. Different studies implementing eHealth solutions consistently reported on benefits, but also on specific challenges. eHealth is a promising field of research and could enhance clinical management of TB.

Population Pharmacokinetic Model and Optimal Sampling Strategies for Micafungin in Critically Ill Patients Diagnosed with Invasive Candidiasis.

Candida bloodstream infections are associated with high attributable mortality, where early initiation of adequate antifungal therapy is important to increase survival in critically ill patients. The exposure variability of micafungin, a first-line agent used for the treatment of invasive candidiasis, in critically ill patients is significant, potentially resulting in underexposure in a substantial portion of these patients. The objective of this study was to develop a population pharmacokinetic model including appropriate sampling strategies for assessing micafungin drug exposure in critically ill patients to support adequate area under the concentration-time curve (AUC) determination. A two-compartment pharmacokinetic model was developed using data from intensive care unit (ICU) patients (n = 19), with the following parameters: total body clearance (CL), volume of distribution of the central compartment (V1), inter-compartmental clearance (CL12), and volume of distribution of the peripheral compartment (V2). The final model was evaluated with bootstrap analysis and the goodness-of-fit plots for the population and individual predicted micafungin plasma concentrations. Optimal sampling strategies (with sampling every hour, 24 h per day) were developed with 1- and 2-point sampling schemes. Final model parameters (±SD) were: CL = 1.03 (0.37) (L/h/1.85 m2), V1 = 0.17 (0.07) (L/kg LBMc), CL12 = 1.80 (4.07) (L/h/1.85 m2), and V2 = 0.12 (0.06) (L/kg LBMc). Sampling strategies with acceptable accuracy and precision were developed to determine the micafungin AUC. The developed model with optimal sampling procedures provides the opportunity to achieve quick optimization of the micafungin exposure from a single blood sample using Bayesian software and may be helpful in guiding early dose decision-making.

Clinical standards for the dosing and management of TB drugs.

BACKGROUND: Optimal drug dosing is important to ensure adequate response to treatment, prevent development of drug resistance and reduce drug toxicity. The aim of these clinical standards is to provide guidance on 'best practice´ for dosing and management of TB drugs.METHODS: A panel of 57 global experts in the fields of microbiology, pharmacology and TB care were identified; 51 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all participants.RESULTS: Six clinical standards were defined: Standard 1, defining the most appropriate initial dose for TB treatment; Standard 2, identifying patients who may be at risk of sub-optimal drug exposure; Standard 3, identifying patients at risk of developing drug-related toxicity and how best to manage this risk; Standard 4, identifying patients who can benefit from therapeutic drug monitoring (TDM); Standard 5, highlighting education and counselling that should be provided to people initiating TB treatment; and Standard 6, providing essential education for healthcare professionals. In addition, consensus research priorities were identified.CONCLUSION: This is the first consensus-based Clinical Standards for the dosing and management of TB drugs to guide clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment to improve patient care.

Clinical standards for drug-susceptible pulmonary TB.

BACKGROUND: The aim of these clinical standards is to provide guidance on 'best practice´ for diagnosis, treatment and management of drug-susceptible pulmonary TB (PTB).METHODS: A panel of 54 global experts in the field of TB care, public health, microbiology, and pharmacology were identified; 46 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all 46 participants.RESULTS: Seven clinical standards were defined: Standard 1, all patients (adult or child) who have symptoms and signs compatible with PTB should undergo investigations to reach a diagnosis; Standard 2, adequate bacteriological tests should be conducted to exclude drug-resistant TB; Standard 3, an appropriate regimen recommended by WHO and national guidelines for the treatment of PTB should be identified; Standard 4, health education and counselling should be provided for each patient starting treatment; Standard 5, treatment monitoring should be conducted to assess adherence, follow patient progress, identify and manage adverse events, and detect development of resistance; Standard 6, a recommended series of patient examinations should be performed at the end of treatment; Standard 7, necessary public health actions should be conducted for each patient. We also identified priorities for future research into PTB.CONCLUSION: These consensus-based clinical standards will help to improve patient care by guiding clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment for PTB.

Optimization of Fluconazole Dosing for the Prevention and Treatment of Invasive Candidiasis Based on the Pharmacokinetics of Fluconazole in Critically Ill Patients.

The efficacy of fluconazole is related to the area under the plasma concentration-time curve (AUC) over the MIC of the microorganism. Physiological changes in critically ill patients may affect the exposure of fluconazole, and therefore dosing adjustments might be needed. The aim of this study was to evaluate variability in fluconazole drug concentration in intensive care unit (ICU) patients and to develop a pharmacokinetic model to support personalized fluconazole dosing. A prospective observational pharmacokinetic study was performed in critically ill patients receiving fluconazole either as prophylaxis or as treatment. The association between fluconazole exposure and patient variables was studied. Pharmacokinetic modeling was performed with a nonparametric adaptive grid (NPAG) algorithm using R package Pmetrics. Data from 33 patients were available for pharmacokinetic analysis. Patients on dialysis and solid organ transplant patients had a significantly lower exposure to fluconazole. The population was best described with a one-compartment model, where the mean volume of distribution was 51.52 liters (standard deviation [SD], 19.81) and the mean clearance was 0.767 liters/h (SD, 0.46). Creatinine clearance was tested as a potential covariate in the model, but was not included in the final population model. A significant positive correlation was found between the fluconazole exposure (AUC) and the trough concentration (Cmin). Substantial variability in fluconazole plasma concentrations in critically ill adults was observed, where the majority of patients were underexposed. Fluconazole Cmin therapeutic drug monitoring (TDM)-guided dosing can be used to optimize therapy in critically ill patients. (This study has been registered at ClinicalTrials.gov under identifier NCT02491151.).