Interphone and beyond evidence for harm or safety armstrong

SYDNEY SCHOOL OF PUBLIC HEALTH

Interphone and beyond: Evidence for harm or safety

(and managing mobile phone fears)

Bruce Armstrong Sydney School of Public Health


Principal objectives of Interphone

To investigate whether• mobile phone use increases the risk of

tumours and• whether RF fields emitted by mobile

phones are tumourigenic

INTERPHONE Study Group. Brain tumour risk in relation to mobile telephone use: results of the INTERPHONE international case-control study. International Journal of Epidemiology 2010; 39: 675-94


A case-control study

• Cases – people aged 30-59 years in defined populations with confirmed– Cerebral glioma or meningioma– Vestibular schwannoma– (Parotid gland cancer)

• Controls – people of the same age representative of those populations and not cases


Mobile phone data collection

• Face to face or telephone interview, occasionally by proxy

• Based on a mobile phone use “biography”


Dimensions• 16 centres in 13 countries (excluding USA

and including Japan)• Cases diagnosed between 2000 and 2004


DimensionsAscertained Participated Participation

%Glioma 4,301 2,765 64Meningioma 3,115 2,425 78Vestibular Schwannoma

1,361 1,121 82

Parotid gland cancer

146 109 75

Controls 14,354 7,658 53Total 23,277 14,078 60


Results for meningioma and gliomaBased on analyses of estimates of cumulative use that exclude periods during which a hands-free device was used.


Regular use Any 1+ years before vs Never


Time since first use 10+ years vs Never regular use


Cumulative call time (hours) 1,640+ hours vs Never regular use


Cumulative number of calls (‘000s) 27,000+ calls vs Never regular use


1,640+ hours of call time by side of use relative to tumour


1,640+ hours of call time by lobe of tumour

Meningioma Glioma


Possible explanations for an association

• Chance• Bias• Confounding• A causal relationship


Evidence of bias

• Participation bias• Recall bias

– Amount of use• Implausible values• Retrospective validation study

– Side of use• Inconsistencies in results


Reasons for non-participationParticipation outcome

Controls Glioma Meningioma

Participated 53% 64% 78%

Not contacted

13% 4% 3%

Refused 31% 16% 13%

Other 3% 17% 5%

Vrijheid et al Annals of Epidemiology 2009; 19:33-42


Effect of non-participation on mobile phone use

• 12 centres asked refusers some questions• 57% of control and 41% of case refusers

answeredEver regular mobile phone use

Refusers Participants

Controls 56% 69%

Cases 50% 66%


Effect of non-participation on RR for brain tumours with mobile phone use

• Greater non-participation in controls– leads to

• A greater proportion of mobile phone users in controls– leads to

• Downward bias in the RR for any regular use of a mobile phone


An approach to bias correction

“One means of correcting, at least crudely, for downward bias in the risk estimates for mobile phone use might be to undertake analyses using the lowest category of users as the reference category for risk estimates in higher categories.”


Adjusted relative risks of glioma by cumulative call time

Appendix 2 in: INTERPHONE Study Group. International Journal of Epidemiology 2010; 39: 675-94


Bias in recall of amount of use

• Implausible values for accumulated call time– 38 glioma cases and 22 glioma controls

reported >5 hours of calls a day in any period

– Their exclusion caused a fall in the RR for 1,640+ hours accumulated call time

• Included 1.40 (95% CI 1.03–1.89)

• Excluded 1.27 (95% CI 0.92–1.75)


Biased recall in longer term users• Recall compared with corresponding

billing records in– 212 cases and 296 controls in– 6 centres in 3 countries

• Mean ratios of recalled to recorded calls (~0.8) and call time (~1.4) were similar in cases and controls

• Ratios increased with recall interval, more in cases than controls

Vrijheid et al JES&EE 2009; 19:369-81


Mean ratio of recalled to recorded number of calls by recall interval

Cases

Controls


Mean ratio of recalled to recorded duration of calls by recall interval

Cases

Controls


Bias in recall of side of use• Sub-study in 3 centres

– 332 cases and 340 controls asked to put a phone to their ear as if answering it

– Side of use recorded• Side concordance

– Meningioma 66%, Glioma 72%– Controls 95%

• Direction of error in cases– 48% ipsilateral, 52% contralateral


Ratios of relative risk of ipsilateral use to relative risk of contralateral use


Conclusion

“There were suggestions of an increased risk of glioma at the highest exposure levels, but biases and errors limit the strength of the conclusions we can draw from these analyses and prevent a causal interpretation.”


How do Interphone’s results compare with results of similar studies?

• One other study has examined the relationship of mobile phone use with risk of recently diagnosed brain tumours; that of Hardell and colleagues from Sweden.

• It’s results are rather different, as can be seen in context in a recent meta-analysis


Mobile phone use and risk of tumors: A meta-analysis

• Selection criteria– Case-control studies– Association of mobile/cell phones or cordless

phones & malignant of benign tumours– Reported outcome measures with odds ratios

and 95% CIs or data from which they could be calculated

Myung et al Journal of Clinical Oncology 2009; 27: 5565-72


Mobile phone use and risk of tumors: A meta-analysis

• 23 studies included– Brain tumours (glioma, meningioma,

vestibular schwannoma, pituitary) (14)– Ocular melanoma (1)– Salivary gland tumours (4)– Intratemporal facial nerve (1)– Non-Hodgkin lymphoma (2)– Testicular cancer (1)

Myung et al Journal of Clinical Oncology 2009; 27: 5565-72

Any mobile phone use vs never or rarely used a mobile phone

Mobile phone use of 10 years of longer vs never or rarely used


Is there something wrong with Hardell’s study?

• Not obviously• Features

– Population-based – 729 cases and 692 controls– Histopathologically confirmed cases– Self completed questionnaire and telephone interview– Interviewers blind to case/control status– Case participation 67% (18% died)– Control participation 84% (full accounting not given)– Matching broken in analysis but adjusted for matching

variables (age, sex, reference year)


Summary of Hardell’s results

Hardell et al. Neuroepidemiology 2005; 25: 120-8 Hardell et al. Environmental Research 2006; 100: 232-41


Future directions for Interphone

• Report on results for vestibular schwannoma

• Report on parotid gland tumours• Report on risk by estimated RFE exposure

to the site of the tumour (case only analyses)

• Report on analyses using more sophisticated methods for bias correction


Other directions• Case-control studies of mobile phone use

and brain tumours in children, adolescents and young adults

• Cohort studies of health effects of mobile phone use

• Studies of effects of base station exposure• Monitoring trends in brain tumour

incidence• IARC monograph


COSMOS• Collaborative cohort study in UK, Denmark,

Sweden, Finland, The Netherlands• Recruitment through mobile phone service providers • 30-45 minute questionnaire covering mobile phone

use, health and lifestyle• ~250,000 participants & 25+ years follow-up• Initial and ongoing monitoring of use through mobile

phone service provider• Updating service provider details annually• Outcomes through cancer registers, hospital data &

follow-up questionnaires


COSMOS participation rates

Schuz et al. Cancer Epidemiology 2010 – doi:10.1016/j.canep.2010.08.001


Base stations and childhood cancer

• Case-control study• 72% of all brain tumours, leukaemia and

NHL in children 0-4 years of age in UK in 1999-2001 – 1,397 cases

• 5,588 controls from birth register, individually matched 4:1 by sex and birth dateElliott P et al. BMJ 2010; 340: c3077



• Exposure assessed using GIS information for residence at birth and macrocell base stations

• Three exposure metrics– Distance from nearest base station tower– Total power output of all base stations within

700 metres– Modelled power density from all base stations

within 1,400 metres



• Modelled power density validated empirically – Spearman’s r 0.66

• Three metrics reasonably highly correlated– Total power with modelled density r 0.62– Total power with distance r 0.82– Modelled density with distance r 0.74

• Estimated power density for controls– Median 0.32 mW/m2 Maximum 8.6 mW/m2



Adjustments:Education and SES+ population density and population mixing


Global trends in mobile phone use

Khurana et al. Surgical Neurology 72 (2009) 205–215


Brain cancer incidence in men Australia 1982-2006

http://www.aihw.gov.au/cancer/data/acim_books/index.cfm


Brain cancer incidence in women Australia 1982-2006

http://www.aihw.gov.au/cancer/data/acim_books/index.cfm


What should people do?

http://www.arpansa.gov.au/news/MediaReleases/mr1_170510.cfm


What should mobile phone manufacturers do?

• Continue to reduce SAR values by innovation in mobile phone design

• Make comparative SAR data easily and usefully available online and at the point of sale


What should mobile phone service providers do?

• Make available easily accessible and understandable information on exposure from base stations at postal address level

• Support independent and expert modelling that would help to identify optimum cell sizes and base station distributions considering:– Exposure in use– Exposure from base stations– Impact of base stations on amenity


What should we all do?

• Be honest about the present uncertainty regarding health effects of personal use of a mobile phone

Interphone and beyond evidence for harm or safety armstrong

Health & Medicine

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