Adjustment for reporting bias in network meta-analysis of antidepressant trials
Open accessAbstract
BACKGROUND: Network meta-analysis (NMA), a generalization of conventional MA, allows for assessing the relative effectiveness of multiple interventions. Reporting bias is a major threat to the validity of MA and NMA. Numerous methods are available to assess the robustness of MA results to reporting bias. We aimed to extend such methods to NMA. METHODS: We introduced 2 adjustment models for Bayesian NMA. First, we extended a meta-regression model that allows the effect size to depend on its standard error. Second, we used a selection model that estimates the propensity of trial results being published and in which trials with lower propensity are weighted up in the NMA model. Both models rely on the assumption that biases are exchangeable across the network. We applied the models to 2 networks of placebo-controlled trials of 12 antidepressants, with 74 trials in the US Food and Drug Administration (FDA) database but only 51 with published results. NMA and adjustment models were used to estimate the effects of the 12 drugs relative to placebo, the 66 effect sizes for all possible pair-wise comparisons between drugs, probabilities of being the best drug and ranking of drugs. We compared the results from the 2 adjustment models applied to published data and NMAs of published data and NMAs of FDA data, considered as representing the totality of the data. RESULTS: Both adjustment models showed reduced estimated effects for the 12 drugs relative to the placebo as compared with NMA of published data. Pair-wise effect sizes between drugs, probabilities of being the best drug and ranking of drugs were modified. Estimated drug effects relative to the placebo from both adjustment models were corrected (i.e., similar to those from NMA of FDA data) for some drugs but not others, which resulted in differences in pair-wise effect sizes between drugs and ranking. CONCLUSIONS: In this case study, adjustment models showed that NMA of published data was not robust to reporting bias and provided estimates closer to that of NMA of FDA data, although not optimal. The validity of such methods depends on the number of trials in the network and the assumption that conventional MAs in the network share a common mean bias mechanism.
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A network funnel plot was generated and visually inspected using the criterion of symmetry to check for bias due to small-scale studies.
“To check for the presence of bias due to small‐scale studies, which may lead to publication bias in NMA, a network funnel plot was generated (Figure S8) and visually inspected using the criterion of symmetry. 37”
From What exercise prescription is optimal to improve body composition and cardiorespiratory fitness in adults living with obesity? A network meta‐analysis (2021) · cites this paper as [37]
Small-scale studies may lead to publication bias in network meta-analysis.
“To check for the presence of bias due to small‐scale studies, which may lead to publication bias in NMA, a network funnel plot was generated (Figure S8) and visually inspected using the criterion of symmetry. 37”
From What exercise prescription is optimal to improve body composition and cardiorespiratory fitness in adults living with obesity? A network meta‐analysis (2021) · cites this paper as [37]
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- Authors
- Trinquart, L., Chatellier, G., & Ravaud, P.
- Affiliations
- Cochrane (GB)
- Inserm (FR)
- Corresponding author
- Trinquart, Ludovic
- Venue
- BMC Medical Research Methodology
- Published
- 2012-09-27
- Volume
- 12
- Issue
- 1
- Pages
- 150-150
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC3537713
- OpenAlex
- W2103017208
- Cited by
- 122
- References
- 55
- Citations by year
- 2026: 2 · 2025: 13 · 2024: 8 · 2023: 9 · 2022: 5 · 2021: 18 · 2020: 16 · 2019: 11 · 2018: 11 · 2017: 9 · 2016: 5 · 2015: 4 · 2014: 6 · 2013: 5
- FWCI
- 1.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- reporting bias, network meta-analysis, antidepressants, Bayesian network meta-analysis, meta-regression, selection model, publication bias, drug ranking, bias correction
- MeSH terms
- Antidepressive Agents, Clinical Trials as Topic, Humans, Regression Analysis, Research Design, Meta-Analysis as Topic, Bias, Case-Control Studies, Publication Bias
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