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Updated: May 11, 2026
08:13
Tail Vein Transection Bleeding Model in Fully Anesthetized Hemophilia A Mice
Published on: September 30, 2021
Estimating unknown parameters in haemophilia using expert judgement elicitation
K Fischer1, D Lewandowski, M P Janssen
1Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands. k.fischer@umcutrecht.nl
Summary
Expert judgement elicitation provided crucial quantitative data for severe haemophilia A treatment models. This study estimated bleeding frequency and prophylaxis needs, generating valuable insights for clinical care and research.
Area of Science:
- Hematology
- Medical Economics
- Biostatistics
Background:
- Growing demand for quantitative data on patient and treatment characteristics in hemophilia.
- Challenges in obtaining precise data due to the nature of the condition.
- Need for efficient healthcare and cost-effective treatments.
Purpose of the Study:
- To estimate key parameters for treatment models in severe hemophilia A using expert judgement elicitation (EJE).
- To generate currently unavailable quantitative data for patient and treatment characteristics.
- To inform computer modeling, clinical care, and trial design in hemophilia management.
Main Methods:
- Formal expert elicitation procedure involving 19 international experts.
- Quantitative estimates (median, P10, P90) collected for bleeding frequency, treatment, prophylaxis, and life expectancy.
- Graphical methods used to combine expert estimates.
Main Results:
- High agreement on bleeding frequencies: median 12 joint bleeds/year for pediatric patients and 11 for adults on demand.
- Lower agreement on secondary prophylaxis dose for adults (median 2000 IU every other day).
- Consensus that a single minor joint bleed can cause irreversible damage; acceptance of limited bleeds on prophylaxis.
Conclusions:
- Expert judgement elicitation successfully captured quantitative expert estimates for hemophilia A.
- Generated novel data applicable to treatment modeling and clinical decision-making.
- Data can enhance computer modeling, guide clinical care, and inform trial design for hemophilia.
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