Effects of recall and selection biases on modeling cancer risk from mobile phone use: Results from a case-control simulation study
BOUAOUN L. 1, BYRNES G. 1, LAGORIO S. 2, FEYCHTING M. 3, ABOU-BAKRE A. 4, BERANGER R. 4, SCHÜZ J. 1
1 Environment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer - World Health Organization (IARC/WHO) , LYON, France; 2 Department of Oncology and Molecular Medicine, Istituto Superiore Di Sanità, Rome, Italy; 3 Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; 4 Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), UMR_S 1085, Rennes, France
Background: The largest case-control study (Interphone Study) conducted in 13 different countries, between 2000 and 2005 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.
Objectives: The main objective was to examine whether the increased risk of glioma observed among the 10% heaviest regular mobile phone users is compatible with an assumption of no real effect of mobile phone use when the various forms of biases present in the Interphone study are accounted for.
Methods: We conducted Monte-Carlo simulations examining the effects of multiple biases in self-reported mobile phone use on risk estimates in a case-control study design. 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.
Results: We found that the scenario simultaneously modeling systematic and random reporting errors in the absence of any real effect, 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 mobile phone users (odds ratio = 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.
Conclusions: Our simulations suggest that, in the absence of any real effect, the most likely biased model is fully compatible with the J-shaped relationship observed in the main Interphone study. Some uncertainty remains, as the validation studies themselves included samples and may therefore be subject to bias. Nevertheless, 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.