ArticlePharmacoEconomics2025
Unravelling the Association Between Uncertainties in Model-based Economic Analysis and Funding Recommendations of Medicines in Australia.
Article in PharmacoEconomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessing Value for Money in Theranostic Nuclear Medicine: A Systematic Review.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026Pooled it
- Precision in Pharmacoeconomics: A Comparative Cost-Utility Analysis of Osimertinib in EGFR-Mutant NSCLC Using Traditional and Pharmacometric Models.Therapeutic innovation & regulatory science · 2026Article
- The evolution of cancer therapies and their Implications for health technology assessment in Australia.Cost effectiveness and resource allocation : C/E · 2026Review
- How policymakers value end-of-life treatments for rare and common diseases in China: evidence from a contingent valuation study.Global health research and policy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveHealth technology assessment is used extensively by the Pharmaceutical Benefits Advisory Committee (PBAC) to inform medicine funding recommendations in Australia. The PBAC often does not recommend medicines due to uncertainties in economic modelling that result in delaying access to medicines for patients. The systematic identification of which uncertainties can be reduced with alternative evidence or the collection of additional data can help inform recommendations. This study aims to characterise different types of uncertainty in economic models and empirically assess their association with the PBAC recommendations.
methodsA framework was developed to characterise four types of uncertainties: methodological, structural, generalisability and parameter uncertainty. The first two types were further subcategorised into parameterisable and unparameterisable uncertainty. Data on uncertainty and other factors were extracted from PBAC's Public Summary Documents of first submissions for 193 medicine (vaccine)-indication pairs including economic modelling between 2014 and 2021. Logistic regression was used to estimate the average marginal effect of each type of uncertainty on the probability of a positive recommendation.
resultsThe PBAC more often raised issues regarding parameter uncertainty (95%) and parameterisable structural uncertainty (83%) than generalisability uncertainty (48%) and unparameterisable methodological uncertainty (56%). The logistic regression results suggested that the PBAC was more likely to recommend a medicine without unparameterisable methodological, generalisability, and parameterisable structural uncertainty by 15.0%, 10.2 %, and 17.6%, respectively. Parameterisable methodological, unparameterisable structural and parameter uncertainty were not significantly associated with the PBAC recommendations.
conclusionsThis study identified the uncertainties that had significant associations with PBAC recommendations based on the first submission. This may help improve model quality and reduce resubmissions in the future, thus improving patients' access to medicines.
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What 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.