ArticleMedical decision making : an international journal of the Society for Medical Decision Making
A framework for addressing structural uncertainty in decision models.
Article in Medical decision making : an international journal of the Society for Medical Decision Making. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 101 citations in OpenAlex.
- Developing a Comprehensive Framework for Cost-Effectiveness Evaluation in Metastatic Castration-Sensitive Prostate Cancer: Insights from a Systematic Review.PharmacoEconomics · 2025Pooled it
- Methods for Health Economic Evaluation of Vaccines and Immunization Decision Frameworks: A Consensus Framework from a European Vaccine Economics Community.PharmacoEconomics · 2016Pooled it
- Antimicrobial-impregnated central venous catheters for preventing neonatal bloodstream infection: the PREVAIL RCT.Health technology assessment (Winchester, England) · 2020Trial
- A multi-stakeholder survey on communicating cost-effectiveness uncertainties to stakeholders: a case study of ICER.Health affairs scholar · 2026Article
- Evaluating the Role and Policy Implications of Using External Evidence in Survival Extrapolations: A Case Study of Axicabtagene Ciloleucel Therapy for Second-Line DLBCL.PharmacoEconomics · 2025Article
- Defining Biological and Clinical Plausibility: The DICSA Framework for Protocolized Assessment in Survival Extrapolations Across Therapeutic Areas.PharmacoEconomics · 2025Review
- Unravelling the Association Between Uncertainties in Model-based Economic Analysis and Funding Recommendations of Medicines in Australia.PharmacoEconomics · 2025Article
- Comparative Analysis of Traditional and Pharmacometric-Based Pharmacoeconomic Modeling in the Cost-Utility Evaluation of Sunitinib Therapy.PharmacoEconomics · 2025Article
- Calculating the Expected Net Benefit of Sampling for Survival Data: A Tutorial and Case Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Analyzing quality of life among people with opioid use disorder from the National Institute on Drug Abuse Data Share initiative: implications for decision making.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- A Guide to an Iterative Approach to Model-Based Decision Making in Health and Medicine: An Iterative Decision-Making Framework.PharmacoEconomics · 2024Article
- Response to "UNCERTAINTY MANAGEMENT IN REGULATORY AND HEALTH TECHNOLOGY ASSESSMENT DECISION-MAKING ON DRUGS: GUIDANCE OF THE HTAi-DIA WORKING GROUP".International journal of technology assessment in health care · 2023Article
- INES: Interactive tool for construction and extrapolation of partitioned survival models.Cost effectiveness and resource allocation : C/E · 2023Article
- An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Value of Information Analysis in Models to Inform Health Policy.Annual review of statistics and its application · 2022Article
- How Sensitive is Sensitivity Analysis?: Evaluation of Pharmacoeconomic Submissions in Korea.Frontiers in pharmacology · 2022Article
- Predicting the Effectiveness of Endemic Infectious Disease Control Interventions: The Impact of Mass Action versus Network Model Structure.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Article
- After 20 Years of Using Economic Evaluation, Should NICE be Considered a Methods Innovator?PharmacoEconomics · 2020Article
- Influence of Modeling Choices on Value of Information Analysis: An Empirical Analysis from a Real-World Experiment.PharmacoEconomics · 2020Article
- An Evaluation of Survival Curve Extrapolation Techniques Using Long-Term Observational Cancer Data.Medical decision making : an international journal of the Society for Medical Decision Making · 2019Article
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Authors and funding
5 authors at 2 institutions in 1 country.
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Abstract
Decision analytic models used for health technology assessment are subject to uncertainties. These uncertainties can be quantified probabilistically, by placing distributions on model parameters and simulating from these to generate estimates of cost-effectiveness. However, many uncertain model choices, often termed structural assumptions, are usually only explored informally by presenting estimates of cost-effectiveness under alternative scenarios. The authors show how 2 recent research proposals represent parts of a framework to formally account for all common structural uncertainties. First, the model is expanded to include parameters that encompass all possible structural choices. Uncertainty can then arise because these parameters are estimated imprecisely from data, for example, a treatment effect of doubtful significance. Uncertainty can also arise if there are no relevant data. If there are relevant data, uncertainty can be addressed by averaging expected costs and effects generated from probabilistic analysis of the models with and without the parameter. The weights used for averaging are related to the predictive ability of each model, assessed against the data. If there are no data, additional parameters can often be informed by eliciting expert beliefs as probability distributions. These ideas are illustrated in decision models for antiplatelet therapies for vascular disease and new biologic drugs for the treatment of active psoriatic arthritis.
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Registered trials
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.