ArticleAmerican journal of epidemiology2017
Probabilistic Multiple-Bias Modeling Applied to the Canadian Data From the Interphone Study of Mobile Phone Use and Risk of Glioma, Meningioma, Acoustic Neuroma, and Parotid Gland Tumors.
Article in American journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed.
- A comprehensive mechanism of biological and health effects of anthropogenic extremely low frequency and wireless communication electromagnetic fields.Frontiers in public health · 2025Review
- Regression calibration of self-reported mobile phone use to optimize quantitative risk estimation in the COSMOS study.American journal of epidemiology · 2024Article
- Effect of alcohol consumption on breast cancer: probabilistic bias analysis for adjustment of exposure misclassification bias and confounders.BMC medical research methodology · 2023Article
- Scientific evidence invalidates health assumptions underlying the FCC and ICNIRP exposure limit determinations for radiofrequency radiation: implications for 5G.Environmental health : a global access science source · 2022Article
- Human Health Risk Assessment of 4-12 GHz Radar Waves using CST STUDIO SUITE Software.Journal of biomedical physics & engineering · 2022Article
- Human‑made electromagnetic fields: Ion forced‑oscillation and voltage‑gated ion channel dysfunction, oxidative stress and DNA damage (Review).International journal of oncology · 2021Review
- Health Council of the Netherlands and evaluation of the fifth generation, 5G, for wireless communication and cancer risks.World journal of clinical oncology · 2021Review
- Reply to Comment on Choi, Y.-J., et al. Cellular Phone Use and Risk of Tumors: Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2021Article
- Genetic susceptibility may modify the association between cell phone use and thyroid cancer: A population-based case-control study in Connecticut.Environmental research · 2020Article
- The Association Between Smartphone Use and Breast Cancer Risk Among Taiwanese Women: A Case-Control Study.Cancer management and research · 2020Article
- Effect of Smoking on Breast Cancer by Adjusting for Smoking Misclassification Bias and Confounders Using a Probabilistic Bias Analysis Method.Clinical epidemiology · 2020Article
- Evaluation of the Validity of a Nonlinear J-Shaped Dose-Response Relationship in Cancers Induced by Exposure to Radiofrequency Electromagnetic Fields.Journal of biomedical physics & engineering · 2019Article
- Nonparticipation Selection Bias in the MOBI-Kids Study.Epidemiology (Cambridge, Mass.) · 2019Article
- Comments on the US National Toxicology Program technical reports on toxicology and carcinogenesis study in rats exposed to whole-body radiofrequency radiation at 900 MHz and in mice exposed to whole-body radiofrequency radiation at 1,900 MHz.International journal of oncology · 2019Article
- Commentary: Geographic Variations in the Incidence of Glioblastoma and Prognostic Factors Predictive of Overall Survival in US Adults from 2004-2013.Frontiers in aging neuroscience · 2018Article
- Health effects of Radiofrequency Electromagnetic Fields (RF EMF).Industrial healthArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We undertook a re-analysis of the Canadian data from the 13-country case-control Interphone Study (2001-2004), in which researchers evaluated the associations of mobile phone use with the risks of brain, acoustic neuroma, and parotid gland tumors. In the main publication of the multinational Interphone Study, investigators concluded that biases and errors prevented a causal interpretation. We applied a probabilistic multiple-bias model to address possible biases simultaneously, using validation data from billing records and nonparticipant questionnaires as information on recall error and selective participation. In our modeling, we sought to adjust for these sources of uncertainty and to facilitate interpretation. For glioma, when comparing those in the highest quartile of use (>558 lifetime hours) to those who were not regular users, the odds ratio was 2.0 (95% confidence interval: 1.2, 3.4). After adjustment for selection and recall biases, the odds ratio was 2.2 (95% limits: 1.3, 4.1). There was little evidence of an increase in the risk of meningioma, acoustic neuroma, or parotid gland tumors in relation to mobile phone use. Adjustments for selection and recall biases did not materially affect interpretation in our results from Canadian data.
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