Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses.
By J. Brok, K. Thorlund, C. Gluud, J. Wetterslev. Journal of Clinical Epidemiology, 2008
985 citations recorded by the source corpus.
Subfields: Pediatrics, Perinatology and Child Health, Public Health, Environmental and Occupational Health, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5c0f590f777e2d6dedd57a1e38af633fe1c2d778
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Pediatrics, Perinatology and Child Health
In Public Health, Environmental and Occupational Health
- Rebecca M. Turner
- C. Gluud
- J. Wetterslev
- M. V. Boscha
- Ode Sangc
- Julian P. T. Higgins
- J. Jakobsen
- Dan Jackson
In Statistics and Probability
- J. Jakobsen
- J. Wetterslev
- C. Gluud
- Rebecca M. Turner
- Julian P. T. Higgins
- M. V. Boscha
- Ode Sangc
- John P. A. Ioannidis
Citations in the corpus
- Trial Sequential Analysis in systematic reviews with meta-analysis (2017, positive): “Among meta-analyses of interventions for neonatal patients, there were approximately 25% to 30% false positive results [5, 50].”
- Urban natural environments as nature-based solutions for improved public health - A systematic review of reviews. (2017, background): “green infrastructure, biodiversity, or blue environments), and its effect on several different pathways and health outcomes, we considered the challenge of unpicking each included review, extracting the results from each individual study included, and the subsequent combination of the results, to be”
- The Impact of Study Size on Meta-analyses: Examination of Underpowered Studies in Cochrane Reviews (2013, result): “[20], who had, however, excluded both reviews with fewer than three trials and those in which all trials had a high risk of bias, in which metaanalytic size is likely to have been smaller.”