Effects of recall and selection biases on modeling cancer risk from mobile phone use: Results from a case-control simulation study
The largest case-control study (Interphone Study) investigating glioma risk related to mobile phone use showed a J-shaped relationship with reduced relative risks for moderate use and a 40% increased relative risk among the 10% heaviest regular mobile phone users, using a categorical risk model base...
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Veröffentlicht in: | Epidemiology (Cambridge, Mass.) Mass.), 2024, Vol.35 (4), p.437-446 |
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Zusammenfassung: | The largest case-control study (Interphone Study) investigating glioma risk related to mobile phone use showed a J-shaped relationship with reduced relative risks for moderate use and a 40% increased relative risk among the 10% heaviest regular mobile phone users, using a categorical risk model based on deciles of lifetime duration of use among ever regular users.
We conducted Monte-Carlo simulations examining whether the reported estimates are compatible with an assumption of no effect of mobile phone use on glioma risk when the various forms of biases present in the Interphone study are accounted for. Four scenarios of sources of error in self-reported mobile phone use were considered, along with selection bias. Input parameters used for simulations were those obtained from Interphone validation studies on reporting accuracy and from using a non-response questionnaire.
We found that the scenario simultaneously modeling systematic and random reporting errors produced a J-shaped relationship perfectly compatible with the observed relationship from the main Interphone study with a simulated spurious increased relative risk among heaviest users (OR = 1.91) compared to never regular users. The main determinant for producing this J shape was higher reporting error variance in cases compared to controls, as observed in the validation studies. Selection bias contributed to the reduced risks as well.
Some uncertainty remains, but the evidence from the present simulation study shifts the overall assessment to making it less likely that heavy mobile phone use is causally related to an increased glioma risk. |
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ISSN: | 1044-3983 1531-5487 1531-5487 |
DOI: | 10.1097/EDE.0000000000001749 |