Dataset Information

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

ABSTRACT: BACKGROUND:Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. METHODS:We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. RESULTS:The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. CONCLUSIONS:Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population.

SUBMITTER: Pearce M

PROVIDER: S-EPMC5806391 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

Pearce Michael M Hee Siew Wan SW Madan Jason J Posch Martin M Day Simon S Miller Frank F Zohar Sarah S Stallard Nigel N

BMC medical research methodology 20180208 1

<h4>Background</h4>Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare dise ...[more]

PMID: 29422021

Similar Datasets

Project description:Ethiopia has a large population of small ruminants (sheep and goats) which are mostly kept in traditional subsistence production systems that are poorly described. Understanding these different systems, their population structure, biomass, production, and economic value is essential for further analysis and effective policy making. The objective of this study was to quantify these parameters for small ruminant production systems in Ethiopia to use them as a basis for analysis of disease burden within the Global Burden of Animal Diseases program. Population structure and trends of small ruminants were analyzed using data from ten annual national agriculture surveys. A stochastic herd model was used to simulate the small ruminant population, biomass, and economic value. The model was parameterised stochastically using data from statistical databases and the literature, and sensitivity analysis of main model outputs to the stochastic inputs was done. Small ruminants are held across the country mainly managed under two major production systems: the crop-livestock mixed system and the pastoral system. The small ruminant population has grown in the past 10 years with an average annual growth rate of 4.6% for sheep and 6.7% for goats. The national average small ruminant population for 2021 was projected at 96.4 (range 95.3-97.7) million heads and the mean stock biomass was about 2,129 (range 1,680-2,686) million kilograms. The monetary value of the small ruminant population was estimated at USD 5,953 (range 4,369-7,765) million. The annual monetary value of small ruminant production outputs was estimated at USD 1,969 (range 1,245-2,857) million. Although the small ruminant population is large and rapidly growing, contributing about 2% of national annual GDP, the sub-sector is characterized by low productivity, low offtake rates, and a limited range of production outputs with no signs of intensification. Efforts should be made to reduce small ruminant mortality, improve fertility, and better utilize products such as milk to improve the livelihoods of rural households and to benefit the national economy. The approaches developed in this study can be replicated in other systems and countries to reveal trends in the size and value of livestock systems, providing a better understanding of its economic importance and performance.

Project description:ObjectivesStress urinary incontinence (SUI) and stress-predominant mixed urinary incontinence (MUI) are common conditions that can have a negative impact on the quality of life of patients and serious cost implications for healthcare providers. The objective of this study was to assess the cost-effectiveness of nine different surgical interventions for treatment of SUI and stress-predominant MUI from a National Health Service and personal social services perspective in the UK.MethodsA Markov microsimulation model was developed to compare the costs and effectiveness of nine surgical interventions. The model was informed by undertaking a systematic review of clinical effectiveness and network meta-analysis. The main clinical parameters in the model were the cure and incidence rates of complications after different interventions. The outcomes from the model were expressed in terms of cost per quality-adjusted life-years (QALYs) gained. In addition, expected value of perfect information (EVPI) analyses were conducted to quantify the main uncertainties facing decision-makers.ResultsThe base-case results suggest that retropubic mid-urethral sling (retro-MUS) is the most cost-effective surgical intervention over a 10-year and lifetime time horizon. The probabilistic results show that retro-MUS and traditional sling are the interventions with the highest probability of being cost-effective across all willingness-to-pay thresholds over a lifetime time horizon. The value of information analysis results suggest that the largest value appears to be in removing uncertainty around the incidence rates of complications, the relative treatment effectiveness and health utility values.ConclusionsAlthough retro-MUS appears, at this stage, to be a cost-effective intervention, research is needed on possible long-term complications of all surgical treatments to provide reassurance of safety, or earlier warning of unanticipated adverse effects. The value of information analysis supports the need, as a first step, for further research to improve our knowledge of the actual incidence of complications.

Dataset Information

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

Publications

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets