Evidence map›Paper›PMID 27406637›Full record

SynthesisBMJ open2016

Plea for routinely presenting prediction intervals in meta-analysis.

Joanna IntHout, John P A Ioannidis, Maroeska M Rovers, Jelle J Goeman

Registry-linked trialAbstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07190989 (Inter-individual Variability of Sleep Outcome Measures in Response to Nutritional Blend Supplementation), which is not on this map. Cited by 1,015 papers, 114 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,015citing papers in PubMed, 114 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT07190989 nacompletednot on this mapstarted 2025, after this paper: background citation

Inter-individual Variability of Sleep Outcome Measures in Response to Nutritional Blend Supplementation: a Replicate Crossover Trial

TypeinterventionalSponsorAspire AcademyRan2025 to 2025Enrolled15ConditionsHealthyArmsNutritional Supplement, Maltodextrin (Placebo)
3 · Its place in the literature

Who cites it

1,015 citing papers in PubMed, 114 syntheses or guidelines pooled it.

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  2. Ceftriaxone for methicillin-susceptibleAnnals of medicine · 2026
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  11. Prevalence of Professional Interpreter Use in Emergency Departments: A Systematic Review and Meta-Analysis.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026
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955 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Joanna IntHoutRadboud University Medical Center, Radboud Institute for Health Sciences (RIHS), Nijmegen, The Netherlands.
John P A IoannidisDepartment of Medicine, Stanford Prevention Research Center, Stanford University School of Humanities and Sciences, Stanford, California, USA Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, California, USA Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA.
Maroeska M RoversRadboud University Medical Center, Radboud Institute for Health Sciences (RIHS), Nijmegen, The Netherlands.
Jelle J GoemanRadboud University Medical Center, Radboud Institute for Health Sciences (RIHS), Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEvaluating the variation in the strength of the effect across studies is a key feature of meta-analyses. This variability is reflected by measures like τ(2) or I(2), but their clinical interpretation is not straightforward. A prediction interval is less complicated: it presents the expected range of true effects in similar studies. We aimed to show the advantages of having the prediction interval routinely reported in meta-analyses.

designWe show how the prediction interval can help understand the uncertainty about whether an intervention works or not. To evaluate the implications of using this interval to interpret the results, we selected the first meta-analysis per intervention review of the Cochrane Database of Systematic Reviews Issues 2009-2013 with a dichotomous (n=2009) or continuous (n=1254) outcome, and generated 95% prediction intervals for them.

resultsIn 72.4% of 479 statistically significant (random-effects p<0.05) meta-analyses in the Cochrane Database 2009-2013 with heterogeneity (I(2)>0), the 95% prediction interval suggested that the intervention effect could be null or even be in the opposite direction. In 20.3% of those 479 meta-analyses, the prediction interval showed that the effect could be completely opposite to the point estimate of the meta-analysis. We demonstrate also how the prediction interval can be used to calculate the probability that a new trial will show a negative effect and to improve the calculations of the power of a new trial.

conclusionsThe prediction interval reflects the variation in treatment effects over different settings, including what effect is to be expected in future patients, such as the patients that a clinician is interested to treat. Prediction intervals should be routinely reported to allow more informative inferences in meta-analyses.

Indexed as

Meta-Analysis as TopicProbabilityPublishingResearch ReportHumansClinical trialCochrane Database of Systematic ReviewsHeterogeneityMeta-analysisPrediction intervalRandom effects

Identifiers

PMID27406637
PMCPMC4947751

What OpenQuestion holds

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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.