Printed by Department of Medical Illustration, Christie Hospital NHS Trust, Manchester. Tel:0161 446 3305/6. Email: Illustration@physics.cr.man.ac.uk We [1] and others have quantified the associations between increasing body mass index (BMI) – as a surrogate of body fatness – and the incident risk of several common and less common cancers (Table). In the main, these malignancies are non-smoking related. This adds substantially to the evidence that excess body weight is causally related to cancer development. Additionally, there is an increasing body of observational evidence that weight loss in overweight populations reduces risk of subsequent cancer development – thus offering an important strategy in the prevention of non-smoking related cancers. Obesity & cancer Mapping Obesity-related Cancers – linking with e-Health Plus Andrew G Renehan and Iain Buchan on behalf of the Cancer Prevention Research Network (CPRN), obesity e-lab and the North West Institute for BioHealth Informatics (NIBHI), Manchester (UK) correspondence: arenehan@picr.man.ac.uk References website: h ttp://www.ihs.manchester.ac.uk/ResearchNetworks/Preventioncancer/ 1. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 2008;371:569-578. 2. Steve Sutton paper Spread of obesity-related cancers in Europe with time (hypothetical model) 2010 2005 2002 > 15% of total cancers attributable to excess weight 10 to 14% of total cancers attributable to excess weight Linking e-Health Plus There are tremendous opportunities for mutual benefits through linking this the “Mapping obesity-related cancer” project and e-Health Plus. The “mapping” process, as applied to countries, may be down-scaled to regional and county level, and ultimately, to different ethic levels. This will deliver a prescriptive approach at either : 1. a regional level – for example, for local health strategies, or 2. a personalised level for individuals to supplement other anti-weight gaining wellbeing strategies. Examples of these types of approaches have been successful for smoking cessation programmes [2]. In a collaboration including the Universities of Manchester (Renehan & Buchan), Bern, Switzerland (Egger & Zwahlen) and Erasmus, the Netherlands (Coebergh), we are currently determining the gender-specific proportions of cancers attributable to excess weight (BMI > 25 kg/m2) across 30 European countries for 10 obesity-related cancer types. This will give us the basis for the following: 1. Predict trends for obesity-related cancers for the future using the PREVENT bio- mathematical disease prediction tool (see figure). 2. Estimate the impact of changes in prevalences and patterns on other diseases, and not just cancer in isolation (i.e. competing risks). 3. Map the distribution of obesity-related cancers exploring clustering effects i.e. temporal spatial analysis. This is illustrated in a hypothetical model in the Figure for European countries, but could readily be extrapolated for counties in the UK. Additional options include the use of the DYNAMO tool for micro-simulating future predictions. Going forward University of Manchester Dr Andrew Renehan (Colorectal oncology, obesity) Professor Iain Buchan (obesity and bio-informatics) Professor Tony Howell (breast oncology, energy restriction research) Dr Michelle Harvie (diet, physical activity and cancer) Professor Gareth Evans (cancer genetics) Professor Chris Todd (behavioural research in cancer) Dr Dexter Canoy (obesity epidemiology) University of Erasmus Professor Jan Willem Coebergh (cancer epidemiology) Dr Isabelle Soerjomataram (modeller) University of Bern Professor Matthias Egger (epidemiology) Dr Marcel Zwahlen (statistics) Team Websites Colon cancer Rectal cancer Gallbladder Leukaemia Malignant melanoma Multiple myeloma Non-Hodgkin lymphoma Oesophageal adenocarcinoma Renal cancer Thyroid cancer Prostate cancer Post-menopausal breast cancer Endometrial cancer 1.24 (1.20 – 1.28) 1.09 (1.06 – 1.12) 1.08 (1.02 – 1.14) 1.17 (1.05 – 1.30) 1.11 (1.05 – 1.18) 1.03 (1.00 – 1.07) 1.52 (1.33 – 1.74) 1.24 (1.15 – 1.34) 1.33 (1.04 – 1.70) 1.03 (1.00 – 1.07) 1.09 (1.05 – 1.13) 1.59 (1.02 – 2.47) 1.17 (1.04 – 1.32) 1.11 (1.07 – 1.15) 1.07 (1.00 – 1.14) 1.51 (1.31 – 1.74) 1.34 (1.25 – 1.43) 1.14 (1.06 – 1.23) 1.12 (1.08 – 1.16) 1.59 (1.50 – 1.68) MEN Risk ratio (per 5 kg/m2) WOMEN Risk ratio (per 5 kg/m 2 ) Table Gender-specific BMI-cancer associations (from Ref. 1)