SynthesisThe European journal of health economics : HEPAC : health economics in prevention and care2026
Cost-effectiveness of testing biofluid biomarkers to diagnose Alzheimer's disease: a systematic review.
Synthesis in The European journal of health economics : HEPAC : health economics in prevention and care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
backgroundAlzheimer's disease (AD) affects tens of millions of individuals and their families in the world. As AD progresses, the effectiveness of treatment declines, making a timely diagnosis crucial. One promising approach for timely diagnosis is testing biofluid biomarkers in patients' blood and cerebrospinal fluid (CSF). However, a comprehensive evaluation of whether these tests are cost-effective is missing. Here, we conducted a systematic review to assess the cost-effectiveness of testing biofluid biomarkers to diagnose AD.
methodWe searched PubMed, Embase, Cochrane Library, and Web of Science for studies published until October 2024. Studies were included if published in English, conducted an economic evaluation of CSF or blood biomarker testing to diagnose AD, and provided economic outcomes. We assessed the quality of studies using the CHEERS 2022 criteria.
resultsNine studies were included: six evaluated CSF biomarker tests and three on blood biomarker tests. All studies used model-based simulations (decision trees or Markov models) rather than trial-based evaluations. CSF biomarker tests were mostly cost-effective compared to neurocognitive assessments or neuroimaging, while blood biomarker tests showed mixed results. Key cost-effectiveness contributors included AD prevalence, diagnostic accuracy, and treatment effectiveness. Studies met ~ 80% of the CHEERS criteria, with missing information on patient engagement.
conclusionOur review supports that biofluid biomarker testing could be cost-effective to diagnose AD. Given the lack of trial-based economic evaluations, model-based studies are a valuable starting point. Future evaluations should incorporate patient-centered outcomes and consider the emotional value and other socio-economic factors that affect patients and families suffering from AD.
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