Mathematical models of drug-resistant tuberculosis lack bacterial heterogeneity: A systematic review.

Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.

Cost-effectiveness and budget impact of decentralising childhood tuberculosis diagnosis in six high tuberculosis incidence countries: a mathematical modelling study.

Background: The burden of childhood tuberculosis remains high globally, largely due to under-diagnosis. Decentralising childhood tuberculosis diagnosis services to lower health system levels could improve case detection, but there is little empirically based evidence on cost-effectiveness or budget impact. Methods: In this mathematical modelling study, we assessed the cost-effectiveness and budget impact of decentralising a comprehensive diagnosis package for childhood tuberculosis to district hospitals (DH-focused) or primary health centres (PHC-focused) compared to standard of care (SOC). The project was conducted in Cambodia, Cameroon, Côte d'Ivoire, Mozambique, Sierra Leone, and Uganda between August 1st, 2018 and September 30th, 2021. A mathematical model was developed to assess the health and economic outcomes of the intervention from a health system perspective. Estimated outcomes were tuberculosis cases, deaths, disability-adjusted life years (DALYs) and incremental cost-effectiveness ratios (ICERs). We also calculated the budget impact of nationwide implementation. The TB-Speed Decentralization study is registered with ClinicalTrials.gov, NCT04038632. Findings: For the DH-focused strategy versus SOC, ICERs ranged between $263 (Cambodia) and $342 (Côte d'Ivoire) per DALY averted. For the PHC-focused strategy versus SOC, ICERs ranged between $477 (Cambodia) and $599 (Côte d'Ivoire) per DALY averted. Results were sensitive to TB prevalence and the discount rate used. The additional costs of implementing the DH-focused strategy ranged between $12.8 M (range 10.8-16.4) (Cambodia) and $50.4 M (36.5-74.4) (Mozambique), and between $13.9 M (12.6-15.6) (Sierra Leone) and $134.6 M (127.1-143.0) (Uganda) for the PHC-focused strategy. Interpretation: The DH-focused strategy may be cost-effective in some countries, depending on the cost-effectiveness threshold used for policy making. Either intervention would require substantial early investment. Funding: Unitaid.

The Evolving Nature of Health Technology Assessment: A Critical Appraisal of NICE's New Methods Manual.

OBJECTIVES: The National Institute for Health and Care Excellence (NICE) recently completed a review of its methods for health technology assessment, involving a 2-stage public consultation. We appraise proposed methodological changes and analyze key decisions. METHODS: We categorize all changes proposed in the first consultation as "critical," "moderate" or "limited" updates, considering the importance of the topic and the degree of change or the level of reinforcement. Proposals were followed through the review process, for their inclusion, exclusion, or amendment in the second consultation and the new manual. RESULTS: The end-of-life value modifier was replaced with a new "disease severity" modifier and other potential modifiers were rejected. The usefulness of a comprehensive evidence base was emphasized, clarifying when nonrandomized studies can be used, with further guidance on "real-world" evidence developed separately. A greater degree of uncertainty was accepted in circumstances when evidence generation raised challenges, in particular for children, rare diseases, and innovative technologies. For some topics, such as health inequality, discounting, unrelated healthcare costs, and value of information, significant changes were possibly warranted, but NICE decided not to make any revisions at present. CONCLUSION: Most of the changes to NICE's health technology assessment methods are appropriate and modest in impact. Nevertheless, some decisions were not well justified and further research is needed on several topics, including investigation of societal preferences. Ultimately, NICE's role of protecting National Health Services resources for valuable interventions that can contribute toward improving overall population health must be safeguarded, without accepting weaker evidence.

Key recommendations and evidence from the NICE guideline for the acute management of ST-segment-elevation myocardial infarction.

The acute management of ST-segment-elevation myocardial infarction (STEMI) has seen significant changes in the past decade. Although the incidence has been declining in the UK, STEMI still gives rise to around 600 hospitalised episodes per million people each year, with many additional cases resulting in death before hospital admission. In-hospital mortality following acute coronary syndromes has fallen over the past 30 years from around 20% to nearer 5%, and this improved outcome has been attributed to various factors, including timely access to an expanding range of effective interventional and pharmacological treatments. A formal review of the acute management of STEMI is therefore appropriate. The recently published NICE clinical guideline (CG167: The acute management of myocardial infarction with ST-segment elevation) provides evidence-based guidance on the acute management of STEMI, including the choice of reperfusion strategies, procedural aspects of the recommended interventions, the use of additional drugs before and longside reperfusion therapies, and the treatment of patients who are unconscious or in cardiogenic shock. The guideline development methods and detailed reviews of the evidence considered by the Guideline Development Group (GDG) can be found in the full version of the guideline (http://www.nice.org.uk/CG167), and the priority recommendations are summarised in box 1. Other related NICE clinical guidelines deal with the diagnosis of recent-onset chest pain of suspected cardiac origin http://www.nice.org.uk/CG95), the early management of unstable angina and non-STEMI (http://www.nice.org.uk/CG94), and secondary prevention after myocardial infarction (http://www.nice.org.uk/CG48, currently being updated with publication expected end of 2013).