Early Life UV and Risk of Basal and Squamous Cell Carcinoma in New South Wales, Australia

Sun exposure is the main cause of squamous (SCC) and basal cell carcinoma (BCC) although pattern and amount differ by cancer type, and sun sensitivity is the major host risk factor. Our study investigated risk factors and residential ambient UV in a population‐based sample of Australian 45 and Up Study participants: 916 BCC cases, 433 SCC cases, 1224 controls. Unconditional logistic regression models adjusting for key covariates demonstrated 60% increased BCC risk and two‐fold increased SCC risk with sun sensitivity, and three‐ and four‐fold increased risk, respectively, with solar keratoses. BCC but not SCC risk increased with higher early‐life residential UV in all participants (odds ratio (OR) = 1.54; 95% CI 1.22–1.96 for intermediate; OR = 1.31; 95% CI 1.03–1.68 for high UV at birthplace) and similarly in Australian‐born participants (P‐values < 0.05). Risk of SCC but not BCC increased with long‐term cumulative sun exposure assessed by self‐reported outdoor work (OR 1.74, 95% CI 1.21–2.49). In conclusion, sun sensitivity is important for both cancers, early‐life UV but not cumulative UV appears to increase BCC risk, the former an apparently novel finding, and SCC risk appears only to be related to long‐term cumulative sun exposure

Cutaneous b HPVs, Sun Exposure, and Risk of Squamous and Basal Cell Skin Cancers in Australia

Background: Sun exposure causes cutaneous squamous (SCC) and basal cell (BCC) carcinomas. Human papillomavirus (HPV) infection might cause SCC. Methods: We examined associations of b and g HPV infection in skin-swab DNA and serum antibodies with skin cancer risk, and modification of the carcinogenic effects of sun exposure by them, in case–control studies of 385 SCC cases, 832 BCC cases, and 1,100 controls nested in an Australian prospective cohort study (enrolled 2006–2009). Results: Presence of b-1 and b-3 HPV DNA appeared to increase risks for SCC and BCC by 30% to 40% (P adjusted <0.01). BCC was also associated with genus b DNA, OR = 1.48; 95% confidence interval (CI), 1.10 to 2.00 (P adjusted < 0.01). Associations were strengthened with each additional positive b HPV DNA type: SCC (OR = 1.07; 95% CI, 1.02–1.12) and BCC (OR = 1.06; 95% CI, 1.03–1.10), Ptrend < 0.01. Positivity to genus b or g in serology, and genus g in DNA, was not associated with either cancer. There was little evidence that any b HPV type was more strongly associated than others with either cancer. A weaker association of sun exposure with SCC and BCC in the presence of b-3 HPVs than in their absence suggests that b-3 HPVs modify sun exposure’s effect. Conclusions: Our substantive findings are at the level of genus b HPV. Like SCC, BCC risk may increase with increasing numbers of b HPV types on skin. Impact: The consistency in our findings that HPV infection may moderate the effects of sun exposure, the main environmental cause of SCC and BCC, merits further investigation

Myocardial infarction, ST-elevation and non-ST-elevation myocardial infarction and modelled daily pollution concentrations; a case-crossover analysis of MINAP data

Objectives: To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI). Methods: Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km x 5 km horizontal resolution, were linked to 202,550 STEMI and 322,198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003-2010. A case-crossover design was used, stratified by year, month, and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0-2 days. Results are presented as percentage change in risk per 10 µg/m3 increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly flu consultation rates, and a sine-cosine annual cycle. Results: There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulphate and elemental carbon). For NSTEMI there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI: 0.01 to 0.54)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. Conclusions: The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required

Post-treatment levels of plasma 25- and 1,25-dihydroxy vitamin D and mortality in men with aggressive prostate cancer.

Vitamin D may reduce mortality from prostate cancer (PC). We examined the associations of post-treatment plasma 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D concentrations with PC mortality. Participants were PC cases from the New South Wales Prostate Cancer Care. All contactable and consenting participants, at 4.9 to 8.6 years after diagnosis, were interviewed and had plasma 25-hydroxyvitamin D (25(OH)D) and 1,25-dihydroxyvitamin D (1,25(OH)2D) measured in blood specimens. Cox regression allowing for left-truncation was used to calculate adjusted mortality hazards ratios (HR) and 95% confidence intervals (95% CI) for all-cause and PC-specific mortality in relation to vitamin D levels and other potentially-predictive variables. Of the participants (n = 111; 75·9% response rate), there were 198 deaths from any cause and 41 from PC in the study period. Plasma 25(OH)D was not associated with all-cause or PC-specific mortality (p-values > 0·10). Plasma 1,25(OH)2D was inversely associated with all-cause mortality (HR for highest relative to lowest quartile = 0·45; 95% CI: 0·29-0·69), and PC-specific mortality (HR = 0·40; 95% CI: 0·14-1·19). These associations were apparent only in men with aggressive PC: all-cause mortality HR = 0·28 (95% CI·0·15-0·52; p-interaction = 0·07) and PC-specific mortality HR = 0·26 (95% CI: 0·07-1.00). Time spent outdoors was also associated with lower all-cause (HR for 4th relative to 1st exposure quartile = 0·42; 95% CI: 0·24-0·75) and PC-specific (HR = 0·48; 95% CI: 0·14-1·64) mortality, although the 95% CI for the latter was wide. The inverse association between post-treatment plasma 1,25(OH)2D levels and all-cause and PC-specific mortality in men with aggressive PC, suggest a possible beneficial effect of vitamin D supplementation in these men

Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO2, O3, PM10 and PM2.5 for 2001-2010

This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km  ×  5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model–measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2. 5, and PM10 (daily maximum 8 h running mean for O3). The comparison was temporally and spatially comprehensive, covering a 10-year period (2 years for PM2. 5) and all non-roadside measurement data from the UK national reference monitor network, which applies consistent operational and QA/QC procedures for each pollutant (44, 47, 24, and 30 sites for NO2, O3, PM2. 5, and PM10, respectively). Two important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards – correlation and bias – together with root mean square error, were evaluated by site type, year, month, and day-of-week. Model–measurement statistics were generally better than, or comparable to, values that allow for realistic magnitudes of measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2, and PM2. 5 at both rural and urban background sites (median values of r across sites in the range 0.70–0.76 for O3 and NO2, and 0.65–0.69 for PM2. 5), but poorer for PM10 (0.47–0.50). Bias differed between environments, with generally less bias at rural background sites (median normalized mean bias (NMB) values for daily O3 and NO2 of 8 and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB  =  −29 %) and PM2. 5 (−26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km  ×  5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions (e.g. closer to traffic sources) than the grid average. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. some components of wind-blown dust. There were instances of monthly and weekday/weekend variations in the extent of model–measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model–measurement differences (aside from grid versus monitor spatial representivity) was inaccuracy of model emissions – both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals – rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models

Disease proportions attributable to environment

Population disease proportions attributable to various causal agents are popular as they present a simplified view of the contribution of each agent to the disease load. However they are only summary figures that may be easily misinterpreted or over-interpreted even when the causal link between an exposure and an effect is well established. This commentary discusses several issues surrounding the estimation of attributable proportions, particularly with reference to environmental causes of cancers, and critically examines two recently published papers. These issues encompass potential biases as well as the very definition of environment and of environmental agent. The latter aspect is not just a semantic question but carries implications for the focus of preventive actions, whether centred on the material and social environment or on single individuals

Survival gains needed to offset persistent adverse treatment effects in localised prostate cancer

BACKGROUND: Men diagnosed with localised prostate cancer (LPC) face difficult choices between treatment options that can cause persistent problems with sexual, urinary and bowel function. Controlled trial evidence about the survival benefits of the full range of treatment alternatives is limited, and patients' views on the survival gains that might justify these problems have not been quantified. METHODS: A discrete choice experiment (DCE) was administered in a random subsample (n=357, stratified by treatment) of a population-based sample (n=1381) of men, recurrence-free 3 years after diagnosis of LPC, and 65 age-matched controls (without prostate cancer). Survival gains needed to justify persistent problems were estimated by substituting side effect and survival parameters from the DCE into an equation for compensating variation (adapted from welfare economics). RESULTS: Median (2.5, 97.5 centiles) survival benefits needed to justify severe erectile dysfunction and severe loss of libido were 4.0 (3.4, 4.6) and 5.0 (4.9, 5.2) months. These problems were common, particularly after androgen deprivation therapy (ADT): 40 and 41% overall (n=1381) and 88 and 78% in the ADT group (n=33). Urinary leakage (most prevalent after radical prostatectomy (n=839, mild 41%, severe 18%)) needed 4.2 (4.1, 4.3) and 27.7 (26.9, 28.5) months survival benefit, respectively. Mild bowel problems (most prevalent (30%) after external beam radiotherapy (n=106)) needed 6.2 (6.1, 6.4) months survival benefit. CONCLUSION: Emerging evidence about survival benefits can be assessed against these patient-based benchmarks. Considerable variation in trade-offs among individuals underlines the need to inform patients of long-term consequences and incorporate patient preferences into treatment decisions. © 2012 Cancer Research UK. All rights reserved

Folate pathway gene polymorphisms and risk of childhood brain tumors: Results from an Australian case-control study

Background: Recent research suggests that maternal folic acid supplementation is associated with a reduced risk of childhood brain tumors (CBT); polymorphisms in folate pathway genes could modify this association or directly influence CBT risk. Methods: Associations between risk of CBT and folate pathway polymorphisms were investigated in a population-based case- control study in Australia (2005-2010). Cases were recruited through all Australian pediatric oncology centers and controls by national random digit dialing. Data were available from 321 cases and 552 controls. Six polymorphisms were genotyped in children and parents (MTHFR 677C>T, MTHFR 1298A>C, MTRR 66A>G, MTR 2756A>G, MTR 5049C>A, and CBS 2199 T>C). Maternal folic acid use was ascertained via questionnaire. ORs were estimated using unconditional logistic regression. Case-parent trio analyses were also undertaken. Results: There was weak evidence of a reduced risk of CBT for the MTRR 66GG genotype in the child or father: ORs 0.71 [95% confidence interval (CI), 0.48-1.07]; 0.54 (95% CI, 0.34-0.87), respectively. Maternal prepregnancy folic acid supplementation showed a stronger negative association with CBT risk where the child, mother, or father had the MTRR 66GG genotype (Pinteraction = 0.07, 0.10, and 0.18, respectively). Conclusions: Evidence for an association between folate pathway genotypes and CBT is limited in this study. There was possible protection by the MTRR 66GG genotype, particularly when combined with maternal prepregnancy folic acid supplementation; these results are novel and require replication. Impact: The possible interaction between folic acid supplementation and MTRR 66A>G, if confirmed, would strengthen evidence for prepregnancy folate protection against CBT

Advantages and disadvantages of an objective selection process for early intervention in employees at risk for sickness absence

<p>Abstract</p> <p>Background</p> <p>It is unclear if objective selection of employees, for an intervention to prevent sickness absence, is more effective than subjective 'personal enlistment'. We hypothesize that objectively selected employees are 'at risk' for sickness absence and eligible to participate in the intervention program.</p> <p>Methods</p> <p>The dispatch of 8603 screening instruments forms the starting point of the objective selection process. Different stages of this process, throughout which employees either dropped out or were excluded, were described and compared with the subjective selection process. Characteristics of ineligible and ultimately selected employees, for a randomized trial, were described and quantified using sickness absence data.</p> <p>Results</p> <p>Overall response rate on the screening instrument was 42.0%. Response bias was found for the parameters sex and age, but not for sickness absence. Sickness absence was higher in the 'at risk' (N = 212) group (42%) compared to the 'not at risk' (N = 2503) group (25%) (OR 2.17 CI 1.63–2.89; p = 0.000). The selection process ended with the successful inclusion of 151 eligible, i.e. 2% of the approached employees in the trial.</p> <p>Conclusion</p> <p>The study shows that objective selection of employees for early intervention is effective. Despite methodological and practical problems, selected employees are actually those at risk for sickness absence, who will probably benefit more from the intervention program than others.</p