ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2021
Bayesian modeling of health state preferences: could borrowing strength from existing countries' valuations produce better estimates.
Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Use of a Non-parametric Bayesian Method to Model Health State Preferences: An Application to Polish and Irish EQ-5D-5L Valuations.Frontiers in public health · 2022Article
- Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?International journal of environmental research and public health · 2021Article
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
Abstract
backgroundValuations of preference-based measure such as EQ-5D and/or SF6D have been conducted in different countries. There is potential to borrow strength from existing countries' valuations to generate better representative utility estimates. This is explored using two case studies modelling UK data alongside Japan samples to generate Japan estimates.
methodsData from two SF-6D valuation studies were analyzed, where using similar standard gamble protocols, values for 241 and 249 states were devised from representative samples of Japan and UK general adult populations, respectively. Two nonparametric Bayesian models were applied to estimate a Japan value set, where the UK results were used as informative priors in the first model and subsets of the Japan data set for 25 and 50 health states were modelled alongside the full UK data set in the second. Generated estimates were compared to a Japan value set estimated using Japan values alone using different prediction criterion.
resultsThe results allowed the UK data to provide significant prior information to the Japan analysis by generating better estimates than using Japan data alone. Also, using Japan data elicited for 50 health states alongside the existing UK data produces roughly similar predicted valuations as the Japan data by itself.
conclusionThe promising results suggest that the existing preference data could be combined with data from a valuation study in a new country to generate preference weights, thus making own country value sets more achievable for low-middle income countries. Further research and application to other countries and preference-based measures are encouraged.
Indexed as
Identifiers
33761028What 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.