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How to read a funnel plot in a meta-analysis
Abstract
Researchers undertook a meta-analysis of the effects of home blood pressure monitoring on blood pressure levels. Randomised controlled trials were included if home or “self” monitoring was compared with standard monitoring in the healthcare system. Participants were patients with essential hypertension, followed for two to 36 months. The main outcomes included measurements of systolic and diastolic blood pressure and the achievement of hypertension targets.1 Eighteen trials were eligible for inclusion. When the results of the trials were combined, home monitoring resulted in significantly lower systolic blood pressure than standard monitoring (mean difference 4.2 mm Hg, 95% confidence interval 1.5 to 6.9) and significantly lower diastolic blood pressure (2.4 mm Hg, 1.2 to 3.5). Home monitoring patients were more likely to achieve predetermined targets (relative risk 1.11, 1.00 to 1.11). The researchers presented funnel plots for the outcomes of systolic and diastolic blood pressure (figure⇓). Egger’s test gave P=0.038 for systolic blood pressure and P=0.095 for diastolic blood pressure. Funnel plots for the meta-analysis of the effects on blood pressure of home monitoring compared with standard monitoring in the healthcare system It was concluded that home monitoring results in lower blood pressure than standard monitoring. Although the difference in blood pressure between the two methods was small it may contribute to an important reduction in vascular complications in the hypertensive population. Which of the following statements, if any, are true?
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“We analyzed publication bias using funnel plots (55) and Rosenthal’s fail-safe N.”
From Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review (2024) · cites this paper as [55]
In the citing paper
“Analysis of funnel plots ( Supplementary Material 8 ) and Rosenthal’s fail-safe N ( Table 2 ) showed that most reported outcomes presented a low degree of publication bias (p<0.05), except for anxiety and dropouts in the NMA (55).”
From Examining the role of AI technology in online mental healthcare: opportunities, challenges, and implications, a mixed-methods review (2024) · cites this paper as [55]
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Metadata
- Authors
- Sedgwick, P., & Marston, L.
- Affiliations
- St George's, University of London (GB)
- University College London (GB)
- Corresponding author
- Sedgwick, Philip
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2015-09-16
- Volume
- 351
- Pages
- h4718
- ISSN
- 1756-1833 (ISSN-L)
- OpenAlex
- W2211524874
- Cited by
- 318
- References
- 4
- Citations by year
- 2026: 34 · 2025: 37 · 2024: 34 · 2023: 32 · 2022: 37 · 2021: 31 · 2020: 35 · 2019: 34 · 2018: 25 · 2017: 11 · 2016: 7
- FWCI
- 13.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- BMJ (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- funnel plot, publication bias, Egger's test, home blood pressure monitoring, self-monitoring, essential hypertension, systolic blood pressure, diastolic blood pressure, meta-analysis interpretation
- MeSH terms
- Blood Pressure Determination, Clinical Trials as Topic, Humans, Meta-Analysis as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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