Decision Analytic Modeling for Global Clinical Trial Planning: A Case for HIV-Positive Patients at High Risk for Mycobacterium tuberculosis Sepsis in Uganda

Jessica Keim-Malpass (), Scott K. Heysell, Tania A. Thomas, Jennifer M. Lobo, Stellah G. Mpagama, Conrad Muzoora and Christopher C. Moore
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Jessica Keim-Malpass: School of Nursing, University of Virginia, Charlottesville, VA 22908, USA
Scott K. Heysell: Division of Infectious Diseases and International Health, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
Tania A. Thomas: Division of Infectious Diseases and International Health, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
Jennifer M. Lobo: Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
Stellah G. Mpagama: Kibong’oto Infectious Diseases Hospital, Kilimanjaro P.O. Box 447, Tanzania
Conrad Muzoora: Department of Medicine, Mbarara University of Science and Technology, Mbarara P.O. Box 1410, Uganda
Christopher C. Moore: Division of Infectious Diseases and International Health, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA

IJERPH, 2023, vol. 20, issue 6, 1-8

Abstract: Sepsis is a significant cause of mortality among people living with human immunodeficiency virus (HIV) in sub-Saharan Africa. In the planning period prior to the start of a large multi-country clinical trial studying the efficacy of the immediate empiric addition of anti-tuberculosis therapy to standard-of-care antibiotics for sepsis in people living with HIV, we used decision analysis to assess the costs and potential health outcome impacts of the clinical trial design based on preliminary data and epidemiological parameter estimates. The purpose of this analysis was to highlight this approach as a case example where decision analysis can estimate the cost effectiveness of a proposed clinical trial design. In this case, we estimated the impact of immediate empiric anti-tuberculosis (TB) therapy versus the diagnosis-dependent standard of care using three different TB diagnostics: urine TB-LAM, sputum Xpert-MTB/RIF, and the combination of LAM/Xpert. We constructed decision analytic models comparing the two treatment strategies for each of the three diagnostic approaches. Immediate empiric-therapy demonstrated favorable cost-effectiveness compared with all three diagnosis-dependent standard of care models. In our methodological case exemplar, the proposed randomized clinical trial intervention demonstrated the most favorable outcome within this decision simulation framework. Applying the principles of decision analysis and economic evaluation can have significant impacts on study design and clinical trial planning.

Keywords: clinical trial planning decision analysis; decision tree; diagnostic; economic evaluation; HIV; sepsis; tuberculosis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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