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Purpose <p>Conventional value-of-information (VOI) analysis bases decisions on a composite cost-effectiveness measure that aggregates clinical and cost outcomes. We sought to highlight potentially informative tradeoffs by estimating and reporting the “disaggregated” components, allowing stakeholders—such as clinicians, patients, trial funders, policymakers, and trial networks—to identify what drives the value of additional research.</p> Methods <p>We used a microsimulation to project the value of a hypothetical trial comparing mortality associated with different tuberculosis screening strategies among hospitalized patients with human immunodeficiency virus (HIV) in South Africa. Apart from expressing VOI as conventional, “aggregated” net monetary benefit (NMB), we assessed “disaggregated” outcomes that contribute to NMB calculations: tuberculosis cases detected, deaths, life-years, and healthcare costs associated with trial-informed decisions. We varied key parameters in probabilistic sensitivity analysis. We considered two willingness-to-pay thresholds: US $3000/year of life saved (YLS) (~50% of South Africa’s per-capita gross domestic product [GDP]); and $780/YLS, the willingness-to-pay value where decision uncertainty is highest, per the baseline analysis.</p> Results <p>At willingness to pay = $3000/YLS, implementing the post-trial optimal strategy would produce favorable incremental NMB ($654.3 million) and better clinical outcomes (57,000 additional tuberculosis cases detected, 16,000 fewer deaths, and 294,000 more life-years), but it would incur an additional $37.4 million in healthcare costs over 5 years. At willingness to pay = $780/YLS, implementing the post-trial optimal strategy would yield positive incremental NMB of $2.5 million while lowering healthcare costs by $11 million, but it would produce worse clinical outcomes: 18,000 fewer tuberculosis cases detected, 6,000 additional deaths, and 80,000 fewer life-years.</p> Conclusions <p>Though a trial may yield positive NMB in conventional VOI analysis owing to expected cost savings, some clinical outcomes might be unfavorable. To better inform priorities, VOI studies should include disaggregated outcomes alongside aggregated NMB.</p>

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Component Clinical and Cost Outcomes Complementing Value of Information: Case Study of a Tuberculosis Diagnostics Clinical Trial

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月6日

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  • Pamela Pei,
  • Livia Qoshe,
  • Grady Florance,
  • Ankur Pandya,
  • Milton C. Weinstein,
  • Kenneth A. Freedberg,
  • A. David Paltiel,
  • Krishna P. Reddy

摘要

Purpose

Conventional value-of-information (VOI) analysis bases decisions on a composite cost-effectiveness measure that aggregates clinical and cost outcomes. We sought to highlight potentially informative tradeoffs by estimating and reporting the “disaggregated” components, allowing stakeholders—such as clinicians, patients, trial funders, policymakers, and trial networks—to identify what drives the value of additional research.

Methods

We used a microsimulation to project the value of a hypothetical trial comparing mortality associated with different tuberculosis screening strategies among hospitalized patients with human immunodeficiency virus (HIV) in South Africa. Apart from expressing VOI as conventional, “aggregated” net monetary benefit (NMB), we assessed “disaggregated” outcomes that contribute to NMB calculations: tuberculosis cases detected, deaths, life-years, and healthcare costs associated with trial-informed decisions. We varied key parameters in probabilistic sensitivity analysis. We considered two willingness-to-pay thresholds: US $3000/year of life saved (YLS) (~50% of South Africa’s per-capita gross domestic product [GDP]); and $780/YLS, the willingness-to-pay value where decision uncertainty is highest, per the baseline analysis.

Results

At willingness to pay = $3000/YLS, implementing the post-trial optimal strategy would produce favorable incremental NMB ($654.3 million) and better clinical outcomes (57,000 additional tuberculosis cases detected, 16,000 fewer deaths, and 294,000 more life-years), but it would incur an additional $37.4 million in healthcare costs over 5 years. At willingness to pay = $780/YLS, implementing the post-trial optimal strategy would yield positive incremental NMB of $2.5 million while lowering healthcare costs by $11 million, but it would produce worse clinical outcomes: 18,000 fewer tuberculosis cases detected, 6,000 additional deaths, and 80,000 fewer life-years.

Conclusions

Though a trial may yield positive NMB in conventional VOI analysis owing to expected cost savings, some clinical outcomes might be unfavorable. To better inform priorities, VOI studies should include disaggregated outcomes alongside aggregated NMB.