Standardized mean differences cause funnel plot distortion in publication bias assessments
- University Medical Center Utrecht, Netherlands
- University of Edinburgh, United Kingdom
- University of Tasmania, Australia
- Radboud Institute for Health Sciences, Radboud University Medical Center, Netherlands
- The University of Edinburgh, United Kingdom
- Radboud University Medical Center, Netherlands
Abstract
Meta-analyses are increasingly used for synthesis of evidence, and often include an assessment of publication bias based on detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.
Article and author information
Author details
Funding
National Institute of Environmental Health Sciences (National Toxicology Program research funding)
- Kimberley E Wever
Netherlands Cardiovascular Research Initiative (CVON-HUSTCARE)
- Steven AJ Chamuleau
National Centre for the Replacement, Refinement and Reduction of Animals in Research (Infrastructure Award)
- Emily S Sena
- Malcolm R MacLeod
Alexander Suerman program (PhD student Scholarship)
- Peter-Paul Zwetsloot
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- M Dawn Teare, University of Sheffield, United Kingdom
Version history
- Received: December 14, 2016
- Accepted: August 21, 2017
- Accepted Manuscript published: September 8, 2017 (version 1)
- Version of Record published: September 29, 2017 (version 2)
Copyright
© 2017, Zwetsloot et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Standardized mean differences cause funnel plot distortion in publication bias assessments
eLife 6:e24260.
https://doi.org/10.7554/eLife.24260
Further reading
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Background:
Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.
Methods:
Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs).
Results:
Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p<0.001; Beta = –0.98 in women, p<0.001).
Conclusions:
Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle.
Funding:
This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).
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