ArticleResearch synthesis methods2015
Simultaneous synthesis of treatment effects and mapping to a common scale: an alternative to standardisation.
Article in Research synthesis methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review and Network Meta-analysis of Idiopathic Pulmonary Fibrosis Treatments.Journal of managed care & specialty pharmacy · 2017Pooled it
- Synthesis of depression outcomes reported on different scales: A comparison of methods for modelling mean differences.Research synthesis methods · 2025Article
- Uptake of methodological advances for synthesis of continuous and time-to-event outcomes would maximize use of the evidence base.Journal of clinical epidemiology · 2020Review
- Choice of Methodology Impacts Outcome in Indirect Comparisons of Drugs for Idiopathic Pulmonary Fibrosis.Medicina (Kaunas, Lithuania) · 2019Article
- Use of a random effects meta-analysis in the design and analysis of a new clinical trial.Statistics in medicine · 2018Article
- Using Parameter Constraints to Choose State Structures in Cost-Effectiveness Modelling.PharmacoEconomics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveTrials 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
designWe 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.
resultsRatios 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.
conclusionSimultaneous 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.
Indexed as
Identifiers
What 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.