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The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial
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The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial
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The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial
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Journal Article
The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial
2024
Overview
Background
There is increasing interest in the capacity of adaptive designs to improve the efficiency of clinical trials. However, relatively little work has investigated how economic considerations – including the costs of the trial – might inform the design and conduct of adaptive clinical trials.
Methods
We apply a recently published Bayesian model of a value-based sequential clinical trial to data from the ‘Hydroxychloroquine Effectiveness in Reducing symptoms of hand Osteoarthritis’ (HERO) trial. Using parameters estimated from the trial data, including the cost of running the trial, and using multiple imputation to estimate the accumulating cost-effectiveness signal in the presence of missing data, we assess when the trial would have stopped had the value-based model been used. We used re-sampling methods to compare the design’s operating characteristics with those of a conventional fixed length design.
Results
In contrast to the findings of the only other published retrospective application of this model, the equivocal nature of the cost-effectiveness signal from the HERO trial means that the design would have stopped the trial close to, or at, its maximum planned sample size, with limited additional value delivered via savings in research expenditure.
Conclusion
Evidence from the two retrospective applications of this design suggests that, when the cost-effectiveness signal in a clinical trial is unambiguous, the Bayesian value-adaptive design can stop the trial before it reaches its maximum sample size, potentially saving research costs when compared with the alternative fixed sample size design. However, when the cost-effectiveness signal is equivocal, the design is expected to run to, or close to, the maximum sample size and deliver limited savings in research costs.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
Adaptive Clinical Trials as Topic
/ Bayesian statistical decision theory
/ Clinical Trials as Topic - economics
/ Clinical Trials as Topic - methods
/ Clinical Trials as Topic - statistics & numerical data
/ Cost-Benefit Analysis - methods
/ Cost-Benefit Analysis - statistics & numerical data
/ Design
/ Humans
/ Hydroxychloroquine - economics
/ Hydroxychloroquine - therapeutic use
/ Medicine
/ Methods
/ Osteoarthritis - drug therapy
/ Statistical Theory and Methods
/ Statistics for Life Sciences
/ Testing
