ArticleMedical decision making : an international journal of the Society for Medical Decision Making2016
Changing Cycle Lengths in State-Transition Models: Challenges and Solutions.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Trial
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- Examining chronic kidney disease screening frequency among diabetics: a POMDP approach.Health care management science · 2024Article
- Cost saving analysis of prediabetes intervention modalities in comparison with inaction using Markov state transition model-A multiregional case study.Journal of diabetes · 2024Article
- Comparative pharmacoeconomic analysis of rituximab and traditional tacrolimus regimens in membranous nephropathy in China.Frontiers in pharmacology · 2023Article
- Optimizing diabetes screening frequencies for at-risk groups.Health care management science · 2022Article
- Article
- Cost-utility analysis of esketamine and electroconvulsive therapy in adults with treatment-resistant depression.BMC psychiatry · 2021Article
- Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals.PharmacoEconomics · 2021Review
- Comparison of Decision Modeling Approaches for Health Technology and Policy Evaluation.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Article
- Modeling the coronavirus disease 2019 pandemic: A comprehensive guide of infectious disease and decision-analytic models.Journal of clinical epidemiology · 2021Review
- Treatment for Severe Lupus Nephritis: A Cost-Effectiveness Analysis in China.Frontiers in pharmacology · 2021Article
- Estimating Transition Probabilities from Published Evidence: A Tutorial for Decision Modelers.PharmacoEconomics · 2020Article
- Telemonitoring Versus Usual Care for Elderly Patients With Heart Failure Discharged From the Hospital in the United States: Cost-Effectiveness Analysis.JMIR mHealth and uHealth · 2020Article
- Estimating Long-Term Drinking Patterns for People with Lifetime Alcohol Use Disorder.Medical decision making : an international journal of the Society for Medical Decision Making · 2019Article
- Verification of Decision-Analytic Models for Health Economic Evaluations: An Overview.PharmacoEconomics · 2017Review
- Current recommendations on the estimation of transition probabilities in Markov cohort models for use in health care decision-making: a targeted literature review.ClinicoEconomics and outcomes research : CEOR · 2017Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The choice of a cycle length in state-transition models should be determined by the frequency of clinical events and interventions. Sometimes there is need to decrease the cycle length of an existing state-transition model to reduce error in outcomes resulting from discretization of the underlying continuous-time phenomena or to increase the cycle length to gain computational efficiency. Cycle length conversion is also frequently required if a new state-transition model is built using observational data that have a different measurement interval than the model's cycle length. We show that a commonly used method of converting transition probabilities to different cycle lengths is incorrect and can provide imprecise estimates of model outcomes. We present an accurate approach that is based on finding the root of a transition probability matrix using eigendecomposition. We present underlying mathematical challenges of converting cycle length in state-transition models and provide numerical approximation methods when the eigendecomposition method fails. Several examples and analytical proofs show that our approach is more general and leads to more accurate estimates of model outcomes than the commonly used approach. MATLAB codes and a user-friendly online toolkit are made available for the implementation of the proposed methods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.