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Comparative efficiency research (COMER): meta-analysis of cost-effectiveness studies

BACKGROUND: The aim of this study was to create a new meta-analysis method for cost-effectiveness studies using comparative efficiency research (COMER). METHODS: We built a new score named total incremental net benefit (TINB), with inverse variance weighting of incremental net benefits (INB). This p...

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Detalles Bibliográficos
Autores principales: Crespo, Carlos, Monleon, Antonio, Díaz, Walter, Ríos, Martín
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4292992/
https://www.ncbi.nlm.nih.gov/pubmed/25533141
http://dx.doi.org/10.1186/1471-2288-14-139
Descripción
Sumario:BACKGROUND: The aim of this study was to create a new meta-analysis method for cost-effectiveness studies using comparative efficiency research (COMER). METHODS: We built a new score named total incremental net benefit (TINB), with inverse variance weighting of incremental net benefits (INB). This permits determination of whether an alternative is cost-effective, given a specific threshold (TINB > 0 test). Before validation of the model, the structure of dependence between costs and quality-adjusted life years (QoL) was analysed using copula distributions. The goodness-of-fit of a Spanish prospective observational study (n = 498) was analysed using the Independent, Gaussian, T, Gumbel, Clayton, Frank and Placket copulas. Validation was carried out by simulating a copula distribution with log-normal distribution for costs and gamma distribution for disutilities. Hypothetical cohorts were created by varying the sample size (n: 15–500) and assuming three scenarios (1-cost-effective; 2-non-cost-effective; 3-dominant). The COMER result was compared to the theoretical result according to the incremental cost-effectiveness ratio (ICER) and the INB, assuming a margin of error of 2,000 and 500 monetary units, respectively. RESULTS: The Frank copula with positive dependence (−0.4279) showed a goodness-of-fit sufficient to represent costs and QoL (p-values 0.524 and 0.808). The theoretical INB was within the 95% confidence interval of the TINB, based on 15 individuals with a probability > 80% for scenarios 1 and 2, and > 90% for scenario 3. The TINB > 0 test with 15 individuals showed p-values of 0.0105 (SD: 0.0411) for scenario 1, 0.613 (SD: 0.265) for scenario 2 and < 0.0001 for scenario 3. CONCLUSIONS: COMER is a valid tool for combining cost-effectiveness studies and may be of use to health decision makers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2288-14-139) contains supplementary material, which is available to authorized users.