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Simultaneous synthesis of treatment effects and mapping to a common scale: an alternative to standardisation

OBJECTIVE: Trials often may report several similar outcomes measured on different test instruments. We explored a method for synthesising treatment effect information both within and between trials and for reporting treatment effects on a common scale as an alternative to standardisation STUDY DESIG...

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Detalles Bibliográficos
Autores principales: Ades, AE, Lu, Guobing, Dias, Sofia, Mayo-Wilson, Evan, Kounali, Daphne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433769/
https://www.ncbi.nlm.nih.gov/pubmed/26035473
http://dx.doi.org/10.1002/jrsm.1130
Descripción
Sumario:OBJECTIVE: Trials often may report several similar outcomes measured on different test instruments. We explored a method for synthesising treatment effect information both within and between trials and for reporting treatment effects on a common scale as an alternative to standardisation STUDY DESIGN: We applied a procedure that simultaneously estimates a pooled treatment effect and the “mapping” ratios between the treatment effects on test instruments in a connected network. Standardised and non-standardised treatment effects were compared. The methods were illustrated in a dataset of 22 trials of selective serotonin reuptake inhibitors against placebo for social anxiety disorder, each reporting treatment effects on between one and six of a total nine test instruments. RESULTS: Ratios of treatment effects on different test instruments varied from trial to trial, with a coefficient of variation of 18% (95% credible interval 11–29%). Standardised effect models fitted the data less well, and standardised treatment effects were estimated with less relative precision than non-standardised effects and with greater relative heterogeneity. CONCLUSION: Simultaneous synthesis of treatment effects and mapping to a common scale make fewer assumptions than standardising by dividing effects by the sample standard deviation, allow results to be reported on a common scale, and deliver estimates with superior relative precision. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.