Temporal & spatial patterns of Glioblastoma Multiforme & other brain cancer subtypes in relation to mobile phones using synthetic counterfactuals

2018 · Mixed · Low evidence

← Research stream

MixedLow evidencePaper 1977

Study snapshot

Publicationmanual · 2018

Study typeecological

Reported directionMixed

Evidence ratingLow

Abstract

Temporal & spatial patterns of Glioblastoma Multiforme & other brain cancer subtypes in relation to mobile phones using synthetic counterfactuals de Vocht F. Analyses of temporal and spatial patterns of Glioblastoma Multiforme and other brain cancers subtypes in relation to mobile phones using synthetic counterfactuals. Environmental Research. Available online 17 October 2018. doi.org. Highlights • English 1985-2005 brain cancer subtype rates were compared to counterfactual trends • Excess GBM increases were found in the frontal and temporal lobes, and cerebellum • Mobile phone use was unlikely to have been an important putative factor • No evidence of an effect of mobile phone use on acoustic neuroma and meningioma Abstract This study assesses whether temporal trends in glioblastoma multiforme (GBM) in different brain regions, and of different malignant and benign (including acoustic neuroma and meningioma) subtypes in the temporal lobe, could be associated with mobile phone use. Annual 1985-2005 incidence of brain cancer subtypes for England were linked to population-level covariates. Bayesian structural timeseries were used to create 2006-2014 counterfactual trends, and differences with measured newly diagnosed cases were interpreted as causal effects. Increases in excess of the counterfactuals for GBM were found in the temporal (+38% [95% Credible Interval - 7%,78%]) and frontal (+36% [-8%,77%]) lobes, which were in agreement with hypothesised temporal and spatial mechanisms of mobile phone usage, and cerebellum (+59% [-0%,120%]). However, effects were primarily present in older age groups, with largest effects in 75+ and 85+ groups, indicating mobile phone use is unlikely to have been an important putative factor. There was no evidence of an effect of mobile phone use on incidence of acoustic neuroma and meningioma. Although 1985-2014 trends in GBM in the temporal and frontal lobes, and probably cerebellum, seem consistent with mobile phone use as an important putative factor, age-group specific analyses indicate that it is unlikely that this correlation is causal. Excerpts Assessment of specific cancer subtypes in the temporal lobe indicated that the excess incidence was mainly found for GBM, with similar trends observed in the frontal lobe and cerebellum The increased rates of specific brain cancer subtypes in excess of the counterfactuals correspond to the spatial and temporal patterns that would be expected if exposure to RF from mobile phones were an important putative factor (Cardis et al., 2008, Morgan et al., 2016) However, age group-specific analyses indicate that the excess relative impacts increased with age over 65 years and were primarily found in the very old (75/85+ years of age) for whom it is unlikely that mobile phone use had been an important causal factor. In addition, excess numbers of newly diagnosed cases were also observed in the young (<24 years of age) for whom mobile phone use is also an unlikely causal factor.... The assumption that a 10-year lag was the most plausible period between first exposure and when increased risk could be observed in registry data was based on the previous analyses (De Vocht (2016)). Although sensitivity analysis using a 15-year lag showed no evidence of excesses relative to counterfactuals, this may still have been too short.... This study, in agreement with other data from the UK and elsewhere, shows that the incidence of glioblastoma multiforme (astrocytoma grade IV) has increased significantly since the 1980s, especially in the frontal and temporal lobes and cerebellum. However, it further provides evidence that the trend of increasing numbers of newly diagnosed cases of glioblastoma multiforme in the temporal lobe (but likely in the frontal lobe and cerebellum as well) since the mid-1980s, although seemingly consistent with the hypothesis of exposure to radiofrequency radiation from mobile phones being an important putative factor, should to a large extent (if not exclusively) be attributed to another factor or factors; of which improvements in diagnostic techniques, especially in the elderly, seems the most plausible. Although these analyses indicate that it is unlikely that exposure to RF from mobile phones is an important putative factor, they also cannot exclude it as a contributing factor completely. It is therefore important to keep monitoring incidence trend data. Competing financial interests declaration: The author has previously done consulting for EPRI [Electric Power Research Institute], not related to this work. Financial support: No external funding was obtained for this study. sciencedirect.com My comment: The study found that the two age groups most vulnerable to carcinogenic effects from cell phone use

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeecological

Effect directionmixed

PopulationEngland population (brain cancer incidence registry data), 1985–2014; analyses include age-group specific patterns (e.g., <24, 75+, 85+)

Sample sizeNot supplied

ExposureRF · Assumed lag periods of 10 years (primary) and 15 years (sensitivity) between first exposure and observable risk in registry data

Evidence strengthLowConfidence: 78% · Peer reviewed: yes

Main findings

Using Bayesian structural time series to generate 2006–2014 counterfactual trends from 1985–2005 data, the study found excess GBM incidence relative to counterfactuals in the temporal (+38% [95% CrI −7%, 78%]) and frontal (+36% [−8%, 77%]) lobes and cerebellum (+59% [−0%, 120%]). However, excesses were primarily in older age groups (largest in 75+ and 85+), leading the author to conclude mobile phone use was unlikely to have been an important causal factor; no evidence of an effect was found for acoustic neuroma or meningioma.

Outcomes measured

Incidence trends of glioblastoma multiforme (GBM) by brain region (temporal lobe, frontal lobe, cerebellum)
Incidence of acoustic neuroma
Incidence of meningioma
Incidence of malignant and benign brain cancer subtypes in the temporal lobe

Limitations

Ecological design using population-level incidence and covariates; individual mobile phone use not measured
Causal interpretation depends on model assumptions and choice of lag period (10-year primary; 15-year sensitivity showed no evidence of excesses)
Credible intervals for reported excesses include values near or below zero for some regions (e.g., temporal and frontal lobes)
Potential alternative explanations noted (e.g., improvements in diagnostic techniques, especially in the elderly)

View raw extracted JSON

{
  "study_type": "ecological",
  "exposure": {
    "band": "RF",
    "source": "mobile phone",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": "Assumed lag periods of 10 years (primary) and 15 years (sensitivity) between first exposure and observable risk in registry data"
  },
  "population": "England population (brain cancer incidence registry data), 1985–2014; analyses include age-group specific patterns (e.g., <24, 75+, 85+)",
  "sample_size": null,
  "outcomes": [
    "Incidence trends of glioblastoma multiforme (GBM) by brain region (temporal lobe, frontal lobe, cerebellum)",
    "Incidence of acoustic neuroma",
    "Incidence of meningioma",
    "Incidence of malignant and benign brain cancer subtypes in the temporal lobe"
  ],
  "main_findings": "Using Bayesian structural time series to generate 2006–2014 counterfactual trends from 1985–2005 data, the study found excess GBM incidence relative to counterfactuals in the temporal (+38% [95% CrI −7%, 78%]) and frontal (+36% [−8%, 77%]) lobes and cerebellum (+59% [−0%, 120%]). However, excesses were primarily in older age groups (largest in 75+ and 85+), leading the author to conclude mobile phone use was unlikely to have been an important causal factor; no evidence of an effect was found for acoustic neuroma or meningioma.",
  "effect_direction": "mixed",
  "limitations": [
    "Ecological design using population-level incidence and covariates; individual mobile phone use not measured",
    "Causal interpretation depends on model assumptions and choice of lag period (10-year primary; 15-year sensitivity showed no evidence of excesses)",
    "Credible intervals for reported excesses include values near or below zero for some regions (e.g., temporal and frontal lobes)",
    "Potential alternative explanations noted (e.g., improvements in diagnostic techniques, especially in the elderly)"
  ],
  "evidence_strength": "low",
  "confidence": 0.78,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "glioblastoma multiforme",
    "GBM",
    "brain cancer",
    "incidence trends",
    "England",
    "Bayesian structural time series",
    "synthetic counterfactuals",
    "mobile phones",
    "radiofrequency",
    "acoustic neuroma",
    "meningioma",
    "temporal lobe",
    "frontal lobe",
    "cerebellum"
  ],
  "suggested_hubs": [
    {
      "slug": "mobile-phones-brain-cancer",
      "weight": 0.95,
      "reason": "Assesses brain cancer subtype incidence patterns in relation to mobile phone (RF) use, including GBM, acoustic neuroma, and meningioma."
    }
  ]
}

AI can be wrong. Always verify against the paper.

AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1016/j.envres.2018.10.011
PubMed: Not supplied

Read the original paper →

Related papers

← Back to the Research Library