Mobile Phone Use and Acoustic Neuromas
Bibliographic record
Abstract
To the Editor: We read with interest the publication by Lönn et al1 who studied the association between time since first regular mobile phone use and acoustic neuroma. They found an increased risk of acoustic neuroma among subjects with at least 10 years since first regular use of analog mobile phones (odds ratio [OR] = 1.8; 95% confidence interval [CI] = 0.8–4.3). If one accepts that acoustic neuroma is a slow-growing tumor initiated years before clinical diagnosis,2 the only etiologically valid analysis would be among subjects who were exposed to mobile phones at least several years before the reference date. For subjects with few years since first exposure, the exposure cannot be causally involved in the etiology of acoustic neuroma. Assuming that analog radiofrequency devices increase the risk of cancer, some epidemiologic findings would fit together. Auvinen et al3 undertook a register-based case-control study on cellular phone and brain tumors in Finland. This study did not have any nonresponse bias or differential exposure misclassification by study design. They found an OR of 2.1 (95% CI = 1.3–3.4) for glioma among subjects ever exposed to analog mobile phones. This ever/never analysis can only suffer from nondifferential exposure misclassification by definition and therefore can be considered as a conservative effect estimate. The same analysis for digital mobile phone use revealed an OR of 1.0 (0.5–2.0). In our case-control study on uveal melanoma,4 we found an increased risk among subjects exposed to radio sets that use analog techniques. We therefore started a new case-control study5 on radiofrequency radiation and uveal melanoma risk, for which we expect results in 2005. Muscat et al6 found an increased risk of acoustic neuroma among subjects who used mobile phones for at least 3 to 6 years (the longest interval in their study) in a case-control study in the United States with 88% of all mobile phone users using analog phones. Furthermore, the recent case-control study of Hardell et al,7 which has some methodologic limitation, showed increased risks of brain tumors among subjects exposed to analog mobile phones with a latency of more than 10 years. The study by Lönn et al1 makes it more difficult to ignore the accumulating, although vague, evidence that may hint to an etiologic role of analog mobile phones in the causation of acoustic neuroma and other tumors. Andreas Stang Andrea Schmidt-Pokrzywniak Institute of Medical Epidemiology, Biometry and Epidemiology, University Hospital of Halle, Halle, Germany, [email protected] Karl-Heinz Jöckel Institute of Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, Germany
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".