The Melanoma Care Study: Protocol of a randomised controlled trial of a psycho-educational intervention for melanoma survivors at high risk of developing new primary disease

Background: Despite a good prognosis for most melanoma survivors, many experience substantial fear of new or recurrent melanoma, worry and anxiety about the future, and unmet healthcare needs. In this protocol, we outline the design and methods of the Melanoma Care Study for melanoma survivors at high risk of developing new primary disease. The objective of this study is to evaluate the efficacy and cost-effectiveness of a psycho-educational intervention for improving psychological and behavioural adjustment to melanoma risk. Design: The study design is a two-arm randomised controlled trial comparing a psycho-educational intervention to usual care. Methods: The intervention is comprised of a newly-developed psycho-educational booklet and three telephone sessions delivered by a trained psychologist. A total of 154 melanoma survivors at high risk of developing new primary disease who are attending one of three melanoma high risk clinics in New South Wales, Australia, will be recruited. Participants will be assessed at baseline (6 weeks before their high risk clinic dermatological appointment), and then 4 weeks and 6 months after their appointment. If effectiveness of the intervention is demonstrated at 6 months, an additional assessment at 12 months is planned. The primary outcome is fear of new or recurrent melanoma, as assessed by the Fear of Cancer Recurrence Inventory (FCRI). Secondary outcomes include anxiety, depression, unmet supportive care needs, satisfaction with clinical care, knowledge, behavioural adjustment to melanoma risk, quality of life, and cost-effectiveness of the intervention from a health system perspective. Following the intention-to-treat principle, linear mixed models will be used to analyse the data to account for repeated measures. A process evaluation will also be carried out to inform and facilitate potential translation and implementation into clinical practice. Discussion: This study will provide high quality evidence on the efficacy and cost-effectiveness of a psycho-educational intervention aimed at improving psychological and behavioural adjustment amongst melanoma survivors at high risk of new primary disease

An approach for improving the quality of country-level TB modelling.

Mathematical modelling is increasingly used to inform budgeting and strategic decision-making by national TB programmes. Despite the importance of these decisions, there is currently no mechanism to review and confirm the appropriateness of modelling analyses. We have developed a benchmarking, reporting, and review (BRR) approach and accompanying tools to allow constructive review of country-level TB modelling applications. This approach has been piloted in five modelling applications and the results of this study have been used to revise and finalise the approach. The BRR approach consists of 1) quantitative benchmarks against which model assumptions and results can be compared, 2) standardised reporting templates and review criteria, and 3) a multi-stage review process providing feedback to modellers during the application, as well as a summary evaluation after completion. During the pilot, use of the tools prompted important changes in the approaches taken to modelling. The pilot also identified issues beyond the scope of a review mechanism, such as a lack of empirical evidence and capacity constraints. This approach provides independent evaluation of the appropriateness of modelling decisions during the course of an application, allowing meaningful changes to be made before results are used to inform decision-making. The use of these tools can improve the quality and transparency of country-level TB modelling applications

Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis

HIV has fuelled increasing tuberculosis (TB) incidence in sub-Saharan Africa. Better control of TB in this region may be achieved directly through TB programme improvements and indirectly through expanded use of antiretroviral therapy (ART) among those with HIV. We used a mathematical model of TB and HIV in South Africa to examine the potential epidemiological impact in scenarios involving improvements in three dimensions of TB programmes: coverage, diagnosis and treatment effectiveness, as well as expanded ART use through broadened eligibility. We projected the effect of alternative scenarios on TB prevalence, incidence and TB-related mortality over 20 years. Of the three dimensions of TB programme improvement, expanding coverage would produce the greatest reduction in TB burden. Compared with current performance, combined TB programme improvements were projected to decrease TB incidence by 30% over 5 years and 46% over 20 years, and decrease TB-related mortality by 45% over 5 years and 69% over 20 years. Expanded ART eligibility was projected to decrease TB incidence by 22% over 5 years and 45% over 20 years, and TB-related mortality by 22% over 5 years and 50% over 20 years. We found that over a 20-year horizon, TB-specific and HIV-specific programme changes contribute equally to incidence reductions, whereas the TB-specific changes produce a majority of the mortality benefits. An aggressive expansion of ART alongside traditional TB-specific control measures has the potential to greatly reduce TB burden, with the different elements of a combined approach having a synergistic effect in reducing long-term TB incidence and mortality

Impact and cost-effectiveness of current and future tuberculosis diagnostics: the contribution of modelling.

The landscape of diagnostic testing for tuberculosis (TB) is changing rapidly, and stakeholders need urgent guidance on how to develop, deploy and optimize TB diagnostics in a way that maximizes impact and makes best use of available resources. When decisions must be made with only incomplete or preliminary data available, modelling is a useful tool for providing such guidance. Following a meeting of modelers and other key stakeholders organized by the TB Modelling and Analysis Consortium, we propose a conceptual framework for positioning models of TB diagnostics. We use that framework to describe modelling priorities in four key areas: Xpert(®) MTB/RIF scale-up, target product profiles for novel assays, drug susceptibility testing to support new drug regimens, and the improvement of future TB diagnostic models. If we are to maximize the impact and cost-effectiveness of TB diagnostics, these modelling priorities should figure prominently as targets for future research

Improving the quality of modelling evidence used for tuberculosis policy evaluation.

Mathematical modelling is commonly used to evaluate policy options for tuberculosis (TB) control in high-burden countries. Although major policy and funding decisions are made based on these analyses, there is concern about the variability of results produced using modelled policy analyses. We discuss new guidance for country-level TB policy modelling. The guidance was developed by the TB Modelling and Analysis Consortium in collaboration with the World Health Organization Global TB Programme, with input from a range of TB stakeholders (funders, modelling groups, country TB programme staff and subject matter experts). The guidance describes principles for country-level TB modelling, as well as good practices for operationalising the principles. The principles cover technical concerns such as model design, parameterisation and validation, as well as approaches for incorporating modelling into country-led policy making and budgeting. For modellers, this guidance suggests approaches to improve the quality and relevance of modelling undertaken to support country-level planning. For non-modellers, this guidance describes considerations for engaging modelling technical assistance, contributing to a modelling exercise and reviewing the results of modelled analyses. If routinely adopted, this guidance should improve the reliability, transparency and usefulness of modelling for country-level TB policy making. However, this guidance will not address all challenges facing modelling, and ongoing work is needed to improve the empirical evidence base for TB policy evaluation and develop stronger mechanisms for validating models. Increasing country ownership of the modelling process remains a challenge, requiring sustained engagement and capacity building

Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods

Value of information (VOI) analyses can help policy makers make informed decisions about whether to conduct and how to design future studies. Historically a computationally expensive method to compute the expected value of sample information (EVSI) restricted the use of VOI to simple decision models and study designs. Recently, 4 EVSI approximation methods have made such analyses more feasible and accessible. Members of the Collaborative Network for Value of Information (ConVOI) compared the inputs, the analyst's expertise and skills, and the software required for the 4 recently developed EVSI approximation methods. Our report provides practical guidance and recommendations to help inform the choice between the 4 efficient EVSI estimation methods. More specifically, this report provides: (1) a step-by-step guide to the methods' use, (2) the expertise and skills required to implement the methods, and (3) method recommendations based on the features of decision-analytic problems

Analysis of multi drug resistant tuberculosis (MDR-TB) financial protection policy : MDR-TB health insurance schemes, in Chhattisgarh state, India

INTRODUCTION: There are significant financial barriers to access treatment for multi drug resistant tuberculosis (MDR-TB) in India. To address these challenges, Chhattisgarh state in India has established a MDR-TB financial protection policy by creating MDR-TB benefit packages as part of the universal health insurance scheme that the state has rolled out in their effort towards attaining Universal Health Coverage for all its residents. In these schemes the state purchases health insurance against set packages of services from third party health insurance agencies on behalf of all its residents. Provider payment reform by strategic purchasing through output based payments (lump sum fee is reimbursed as per the MDR-TB benefit package rates) to the providers - both public and private health facilities empanelled under the insurance scheme was the key intervention. AIM: To understand the implementation gap between policy and practice of the benefit packages with respect to equity in utilization of package claims by the poor patients in public and private sector. METHODS: Data from primary health insurance claims from January 2013 to December 2015, were analysed using an extension of 'Kingdon's multiple streams for policy implementation framework' to explain the implementation gap between policy and practice of the MDR-TB benefit packages. RESULTS: The total number of claims for MDR-TB benefit packages increased over the study period mainly from poor patients treated in public facilities, particularly for the pre-treatment evaluation and hospital stay packages. Variations and inequities in utilizing the packages were observed between poor and non-poor beneficiaries in public and private sector. Private providers participation in the new MDR-TB financial protection mechanism through the universal health insurance scheme was observed to be much lower than might be expected given their share of healthcare provision overall in India. CONCLUSION: Our findings suggest that there may be an implementation gap due to weak coupling between the problem and the policy streams, reflecting weak coordination between state nodal agency and the state TB department. There is a pressing need to build strong institutional capacity of the public and private sector for improving service delivery to MDR-TB patients through this new health insurance mechanism

Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions

Mathematical modelling is commonly used to evaluate infectious disease control policy and is influential in shaping policy and budgets. Mathematical models necessarily make assumptions about disease natural history and, if these assumptions are not valid, the results of these studies can be biased. We did a systematic review of published tuberculosis transmission models to assess the validity of assumptions about progression to active disease after initial infection (PROSPERO ID CRD42016030009). We searched PubMed, Web of Science, Embase, Biosis, and Cochrane Library, and included studies from the earliest available date (Jan 1, 1962) to Aug 31, 2017. We identified 312 studies that met inclusion criteria. Predicted tuberculosis incidence varied widely across studies for each risk factor investigated. For population groups with no individual risk factors, annual incidence varied by several orders of magnitude, and 20-year cumulative incidence ranged from close to 0% to 100%. A substantial proportion of modelled results were inconsistent with empirical evidence: for 10-year cumulative incidence, 40% of modelled results were more than double or less than half the empirical estimates. These results demonstrate substantial disagreement between modelling studies on a central feature of tuberculosis natural history. Greater attention to reproducing known features of epidemiology would strengthen future tuberculosis modelling studies, and readers of modelling studies are recommended to assess how well those studies demonstrate their validity