ReviewPharmacoEconomics2015
Exploring structural uncertainty in model-based economic evaluations.
Review in PharmacoEconomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Impact of Structural Differences on the Modeled Cost-Effectiveness of Noninvasive Prenatal Testing.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Pooled it
- Cost-effectiveness analysis of sacituzumab tirumotecan vs. chemotherapy for patients with EGFR-TKI-resistant, EGFR-mutated advanced non-small cell lung cancer in China.Frontiers in public health · 2026Article
- A systematic review of the current application status of decision-analytical models in the pharmacoeconomic evaluation of targeted therapies for pulmonary arterial hypertension.Cost effectiveness and resource allocation : C/E · 2025Article
- Unravelling the Association Between Uncertainties in Model-based Economic Analysis and Funding Recommendations of Medicines in Australia.PharmacoEconomics · 2025Article
- Bring Out Your Dead: A Review of the Cost Minimisation Approach in Health Technology Assessment Submissions to the Australian Pharmaceutical Benefits Advisory Committee.PharmacoEconomics · 2024Review
- Response to uncertainty management in regulatory and health technology assessment decision-making on drugs: guidance of the HTAi-DIA Working Group - author's reply.International journal of technology assessment in health care · 2023Article
- 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
- Calibrating Natural History of Cancer Models in the Presence of Data Incompatibility: Problems and Solutions.PharmacoEconomics · 2022Article
- How Sensitive is Sensitivity Analysis?: Evaluation of Pharmacoeconomic Submissions in Korea.Frontiers in pharmacology · 2022Article
- Accurately Reflecting Uncertainty When Using Patient-Level Simulation Models to Extrapolate Clinical Trial Data.Medical decision making : an international journal of the Society for Medical Decision Making · 2020Article
- Model Structuring for Economic Evaluations of New Health Technologies.PharmacoEconomics · 2018Review
- Towards a New Framework for Addressing Structural Uncertainty in Health Technology Assessment Guidelines.PharmacoEconomics · 2018Article
- Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment.PharmacoEconomics · 2018Article
- Exploring Uncertainty in Economic Evaluations of Drugs and Medical Devices: Lessons from the First Review of Manufacturers' Submissions to the French National Authority for Health.PharmacoEconomics · 2016Article
- Development and Use of Disease-Specific (Reference) Models for Economic Evaluations of Health Technologies: An Overview of Key Issues and Potential Solutions.PharmacoEconomics · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given the inherent uncertainty in estimates produced by decision analytic models, the assessment of uncertainty in model-based evaluations is an essential part of the decision-making process. Although the impact of uncertainty around the choice of model structure and making incorrect structural assumptions on model predictions is noted, relatively little attention has been paid to characterising this type of uncertainty in guidelines developed by national funding bodies such as the Australian Pharmaceutical Benefits Advisory Committee (PBAC). The absence of a detailed description and evaluation of structural uncertainty can add further uncertainty to the decision-making process, with potential impact on the quality of funding decisions. This paper provides a summary of key elements of structural uncertainty describing why it matters and how it could be characterised. Five alternative approaches to characterising structural uncertainty are discussed, including scenario analysis, model selection, model averaging, parameterization and discrepancy. We argue that the potential effect of structural uncertainty on model predictions should be considered in submissions to national funding bodies; however, the characterisation of structural uncertainty is not well defined within the guidelines of these bodies. There has been little consideration of the forms of structural sensitivity analysis that might best inform applied decision-making processes, and empirical research in this area is required.
Indexed as
Identifiers
25601288What OpenQuestion holds
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.