Examining the Joint Effect of Multiple Risk Factors Using Exposure Risk Profiles: Lung Cancer in Nonsmokers

Bac k g r o u n d: Profile regression is a Bayesian statistical approach designed for investigating the joint effect of multiple risk factors. It reduces dimensionality by using as its main unit of inference the exposure profiles of the subjects that is, the sequence of covariate values that correspond to each subject. Objectives: We applied profile regression to a case–control study of lung cancer in nonsmokers, nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, to estimate the combined effect of environmental carcinogens and to explore possible gene–environment interactions. Me t h o d s: We tailored and extended the profile regression approach to the analysis of case–control studies, allowing for the analysis of ordinal data and the computation of posterior odds ratios. We compared and contrasted our results with those obtained using standard logistic regression and classification tree methods, including multifactor dimensionality reduction. Res u l t s: Profile regression strengthened previous observations in other study populations on the role of air pollutants, particularly particulate matter ≤ 10 μm in aerodynamic diameter (PM 10), in lung cancer for nonsmokers. Covariates including living on a main road, exposure to PM 10 and nitrogen dioxide, and carrying out manual work characterized high-risk subject profiles. Such combinations of risk factors were consistent with a priori expectations. In contrast, other methods gave less interpretable results. Con c l u s i o n s: We conclude that profile regression is a powerful tool for identifying risk profiles that express the joint effect of etiologically relevant variables in multifactorial diseases. Key w o r d s: air pollutants, Bayesian inference, clustering, combined effect, gene–environment interactions. Environ Health Perspect 119:84–91 (2011). doi:10.1289/ehp.1002118 [Onlin

Dementia risk in patients with type 2 diabetes: Comparing metformin with no pharmacological treatment.

INTRODUCTION: Metformin has been suggested as a therapeutic agent for dementia, but the relevant evidence has been partial and inconsistent. METHODS: We established a national cohort of 210,237 type 2 diabetes patients in the UK Clinical Practice Research Datalink. Risks of incident dementia were compared between metformin initiators and those who were not prescribed any anti-diabetes medication during follow-up. RESULTS: Compared with metformin initiators (n = 114,628), patients who received no anti-diabetes medication (n = 95,609) had lower HbA1c and better cardiovascular health at baseline. Both Cox regression and propensity score weighting analysis showed metformin initiators had lower risk of dementia compared to those non-users (adjusted hazard ratio = 0.88 [95% confidence interval: 0.84-0.92] and 0.90 [0.84-0.96]). Patients on long-term metformin treatment had an even lower risk of dementia. DISCUSSION: Metformin may act beyond its glycemic effect and reduce dementia risk to an even lower level than that of patients with milder diabetes and better health profiles. HIGHLIGHTS: Metformin initiators had a significantly lower risk of dementia compared with patients not receiving anti-diabetes medication. Compared with metformin initiators, diabetes patients not receiving pharmacological treatment had better glycemic profiles at baseline and during follow-up. Patients on long-term metformin treatment had an even lower risk of subsequent dementia incidence. Metformin may act beyond its effect on hyperglycemia and has the potential of being repurposed for dementia prevention

Serum retinol and prostate cancer risk: a nested case-control study in the prostate, lung, colorectal, and ovarian cancer screening trial.

Vitamin A (retinol) plays a key role in the regulation of cell growth and differentiation, and has been studied as a potential chemopreventive agent for prostate cancer. However, findings from epidemiologic studies on the association between circulating retinol concentrations and the risk of prostate cancer are inconsistent. We examined whether serum concentrations of retinol were associated with the risk of prostate cancer in a nested case-control study using 692 prostate cancer cases and 844 matched controls from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We estimated the risk of prostate cancer using multivariate, conditional logistic regression to calculate odds ratios and 95% confidence intervals for overall prostate cancer and aggressive disease (stage III or IV or Gleason >7; n = 269). Serum retinol concentrations were not associated with overall prostate cancer risk; however, the highest versus lowest concentrations of serum retinol were associated with a 42% reduction in aggressive prostate cancer risk (P(trend) = 0.02), with the strongest inverse association for high-grade disease (Gleason sum >7; odds ratio, 0.52; 95% confidence interval, 0.32-0.84; P(trend) = 0.01). Our results suggest that higher circulating concentrations of retinol are associated with a decreased risk of aggressive prostate cancer. Further research is needed to better understand the significance of elevations in serum retinol concentrations and the possible biological mechanisms through which retinol affects prostate cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(4):1227-31)

Time for a European initiative for research to prevent cancer: A manifesto for Cancer Prevention Europe (CPE)

A landmark resolution on cancer prevention and control was adopted by Member States at the World Health Assembly 2017, noting that “risk reduction has the potential to prevent around half of all cancers” and urging “to promote cancer research to improve the evidence base for cancer prevention and control”. Public health oriented strategies for cancer prevention and their optimal application in effective real-life programmes will be vital to circumvent the dramatic health and economic implications of a strategy and healthcare expenditure based primarily on cancer treatment. The inter-disciplinary nature of cancer prevention stretches from the sub-microscopic study of cancer pathways through to the supra-macroscopic analysis of the “causes of the causes”, encompassing socio-economic and environmental factors. Research is required to provide new evidence-based preventive interventions and to understand the factors that hamper their implementation within health care systems and in the community. Successful implementation of cancer prevention requires long-term vision, a dedicated research agenda and funding, sustainable infrastructure and cooperation between countries and programmes. In order to develop world class prevention research in Europe that translates into effective cancer prevention guidelines and policies, we report on the creation of Cancer Prevention Europe. This international and multidisciplinary consortium of research institutes, organisations and networks of excellence with a common mission of reducing cancer morbidity and mortality in European populations through prevention, brings together different fields of expertise, from laboratory science through to policy research, as well as dissemination of the best evidence, the best quality indicators and the best practices used

Studies of jet quenching within a partonic transport model

Background: Finite mixture models posit the existence of a latent categorical variable and can be used for probabilistic classification. The authors illustrate the use of mixture models for dietary pattern analysis. An advantage of this approach is taking classification uncertainty into account. Methods: Participants were a random sample of women from the European Prospective Investigation into Cancer. Food consumption was measured using dietary questionnaires. Mixture models identified latent classes in food consumption data, which were interpreted as dietary patterns. Results: Among various assumptions examined, models allowing the variance of foods to vary within and between classes fit better than alternatives assuming constant variance (the K-means method of cluster analysis also makes the latter assumption). An eight-class model was best fitting and five patterns validated well in a second random sample. Patterns with lower classification uncertainty tended to be better validated. One pattern showed low consumption of foods despite being associated with moderate body mass index. Conclusion: Mixture modelling for dietary pattern analysis has advantages over both factor and cluster analysis. In contrast to these other methods, it is easy to estimate pattern prevalence, to describe patterns and to use patterns to predict disease taking classification uncertainty into account. Owing to substantial error in food consumptions, any analysis will usually find some patterns that cannot be well validated. While knowledge of classification uncertainty may aid pattern evaluation, any method will better identify patterns from food consumptions measured with less error. Mixture models may be useful to identify individuals who under-report food consumption

Fibre intake and the development of inflammatory bowel disease – a European prospective multi-centre cohort study (EPIC-IBD)

Background and Aims: Population-based prospective cohort studies investigating fibre intake and development of inflammatory bowel disease (IBD) are lacking. Our aim was to investigate the association between fibre intake and the development of Crohn’s disease (CD) and ulcerative colitis (UC) in a large European population. Methods: 401 326 participants, aged 20–80 years, were recruited in 8 countries in Europe between 1991 and 1998. At baseline, fibre intake (total fibres, fibres from fruit, vegetables and cereals) was recorded using food frequency questionnaires. The cohort was monitored for the development of IBD. Each case was matched with four controls and odds ratios (ORs) for the exposures were calculated using conditional logistic regression. Sensitivity analyses according to smoking status were computed. Results: In total, 104 and 221 participants developed incident CD and UC, respectively. For both CD and UC, there were no statistically significant associations with either quartiles, or trends across quartiles, for total fibre, or any of the individual sources. The associations were not affected by adjusting for smoking and energy intake. Stratification according to smoking status showed null findings apart from an inverse association with cereal fibre and CD in non-smokers (Quartile 4 vs 1 OR=0.12, 95% CI=0.02–0.75, P=0.023, OR trend across quartiles=0.50, 95% CI=0.29–0.86, P=0.017). Conclusion: The results do not support the hypothesis that dietary fibre is involved in the aetiology of UC, although future work should investigate whether there may be a protective effect of specific types of fibre according to smoking status in CD

Lifestyle, dietary factors and antibody levels to oral bacteria in cancer-free participants of a European cohort study

Background—Increasing evidence suggests that oral microbiota play a pivotal role in chronic diseases, in addition to the well-established role in periodontal disease. Moreover, recent studies suggest that oral bacteria may also be involved in carcinogenesis; periodontal disease has been linked several cancers. In this study, we examined whether lifestyle factors have an impact on antibody levels to oral bacteria. Methods—Data on demographic characteristics, lifestyle factors, and medical conditions were obtained at the time of blood sample collection. For the current analysis, we measured antibody levels to 25 oral bacteria in 395 cancer-free individuals using an immunoblot array. Combined total immunglobin G (IgG) levels were obtained by summing concentrations for all oral bacteria measured. Results—IgG antibody levels were substantially lower among current and former smokers (1697 and 1677 ng/mL, respectively) than never smokers (1960 ng/mL; p-trend = 0.01), but did not vary by other factors, including BMI, diabetes, physical activity, or by dietary factors, after adjusting for age, sex, education, country and smoking status. The highest levels of total IgG were found among individuals with low education (2419 ng/mL). Conclusions—Our findings on smoking are consistent with previous studies and support the notion that smokers have a compromised humoral immune response. Moreover, other major factors known to be associated with inflammatory markers, including obesity, were not associated with antibody levels to a large number of oral bacteria