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Alternative Conversion Methods for Transition Probabilities in State-Transition Models: Validity and Impact on
Beate Jahn1, Christina Kurzthaler1,2, Jagpreet Chhatwal3
1Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria.
Summary
Matrix transformation methods (Eigenvalue and Schure-Padé) are more accurate than separate probability conversion in state-transition models. These methods improve accuracy for long-term outcomes and complex models.
Area of Science:
- Health economics
- Mathematical modeling
- Pharmacoeconomics
Background:
- State-transition models (STMs) use health states and transitions over time cycles.
- The common method (C) for cycle length conversion inaccurately transforms probabilities separately in STMs with >2 states.
- Accurate cycle length conversion is crucial for reliable STM outcomes.
Purpose of the Study:
- Compare the accuracy of matrix transformation methods (Eigenvalue [E], Schure-Padé [SP]) against the common method (C).
- Evaluate performance in STMs for breast cancer treatment strategies.
- Assess impact on transition matrices and long-term outcomes (life years, QALYs, costs, ICERs).
Main Methods:
- Compared methods C, E, and SP for annual-to-monthly cycle conversion in STMs.
- Applied methods to breast cancer treatment strategies and randomly generated matrices (4-20 states).
- Evaluated transformation errors and impact on long-term economic and clinical outcomes.
Main Results:
- No single transformation method is universally correct; SP showed smallest discrepancies in most simulations.
- Method E performed best for higher-dimensional models (>4 states).
- Method C induced the largest discrepancies, particularly for cost estimations.
Conclusions:
- Matrix transformation methods (E, SP) outperform separate probability conversion (C) in STMs.
- Alternative conversion methods (E, SP) should be used in sensitivity analyses.
- Accurate cycle length conversion is essential for reliable health economic evaluations.
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