Early cancer detection among rural and urban californians

BACKGROUND: Since the stage of cancer detection generally predicts future mortality rates, a key cancer control strategy is to increase the proportion of cancers found in the early stage. This study compared stage of detection for members of rural and urban communities to determine whether disparities were present. METHODS: The California Cancer Registry (CCR), a total population based cancer registry, was used to examine the proportion of early stage presentation for patients with breast, melanoma, and colon cancer from 1988 to 2003. Cancer stage at time of detection for these cancers was compared for rural and urban areas. RESULTS: In patients with breast cancer, there were significantly more patients presenting at early stage in 2003 compared to 1988, but no difference in the percentage of patients presenting with early stage disease between rural and urban dwellers. There were no differences in incidence in early stage cancer incidence between these groups for melanoma patients, as well. In colorectal cancer in 1988, significantly more patients presented with early stage disease in the urban areas (42% vs 34%, p < 0.02). However, over time the rural patients were diagnosed with early stage disease with the same frequency in 2003 as 1988. CONCLUSION: This analysis demonstrates that people in rural and urban areas have their breast, melanoma or colorectal cancers diagnosed at similar stages. Health care administrators may take this information into account in future strategic planning

Investigating the relationships between unfavourable habitual sleep and metabolomic traits:evidence from multi-cohort multivariable regression and Mendelian randomization analyses

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease.METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions.RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures.CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.</p

Additional file 1 of Sex steroid hormones and risk of breast cancer: a two-sample Mendelian randomization study

Additional file 1. S1. Exposure instruments to proxy hormone levels in the overall breast cancer incidence MR analysis. S2. The strength of the instruments for each hormone including the variance explained and the F statistic. S3. Hormone and breast cancer incidence associations using the alternative MR methods: MR Egger, weighted median, weighted mode and MR-RAPS. S4. MR intercept calculations to identify evidence of pleiotropy. S5. Genetic correlation results between hormones. S6. Exposure instruments to proxy hormone levels in the subtype specific MR analysis. S7. Exposure instruments to proxy hormone levels in the BRCA1 mutated TNBC MR analysis. S8. Power calculations for each hormone and overall and subtype specific BC analysis

Additional file 1 of Sex steroid hormones and risk of breast cancer: a two-sample Mendelian randomization study, Version 1

Additional file 1. S1. Exposure instruments to proxy hormone levels in the overall breast cancer incidence MR analysis. S2. The strength of the instruments for each hormone including the variance explained and the F statistic. S3. Hormone and breast cancer incidence associations using the alternative MR methods: MR Egger, weighted median, weighted mode and MR-RAPS. S4. MR intercept calculations to identify evidence of pleiotropy. S5. Genetic correlation results between hormones. S6. Exposure instruments to proxy hormone levels in the subtype specific MR analysis. S7. Exposure instruments to proxy hormone levels in the BRCA1 mutated TNBC MR analysis. S8. Power calculations for each hormone and overall and subtype specific BC analysis