The role of mathematical modelling in the development of recommendations in the 2013 WHO consolidated antiretroviral therapy guidelines

Abstract

Despite the exponential growth in the literature on modelling and simulation studies of impact and cost-effectiveness in different aspects of healthcare, there is no clear consensus on the appropriate role of modelling in the development of recommendations in clinical guidelines. This is compounded both by the lack of a standardised approach to assess the quality of modelling, and lack of clarity on its positioning within the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) method for decision-making in the development of WHO guidelines, that considers both evidence from systematic reviews of randomized clinical trials (RTCs) or observational studies, together with stakeholder values and preferences, resource use, and feasibility issues. In the development of the 2013 WHO Consolidated Guidelines on the use of Antiretroviral drugs for treating and preventing HIV infection, a series of modelling projects were undertaken to inform the recommendations on eligibility criteria for ART initiation, and approaches to monitoring for treatment response. We report our experiences, challenges encountered, and several key considerations to guide the future use of modelling in the development of WHO guidelines. These are: (1) Transparency in the conduct and reporting of model inputs and results; (2) The need for agreed standards for critical appraisal and use of modelling data in healthcare policy making; (3) recognition that modelling of cost-effectiveness is only one component of decision-making in development of WHO recommendations and in priority-setting; (4) The need for closer interaction and an ongoing dialogue between modellers and model end-users or decision-makers; (5) the important role of WHO in convening and facilitating comparative assessment of multiple models; and (6) The need to optimize research and data collection to inform modelling studies.

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The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary

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