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1.  A regression model for risk difference estimation in population-based case–control studies clarifies gender differences in lung cancer risk of smokers and never smokers 
Background
Additive risk models are necessary for understanding the joint effects of exposures on individual and population disease risk. Yet technical challenges have limited the consideration of additive risk models in case–control studies.
Methods
Using a flexible risk regression model that allows additive and multiplicative components to estimate absolute risks and risk differences, we report a new analysis of data from the population-based case–control Environment And Genetics in Lung cancer Etiology study, conducted in Northern Italy between 2002–2005. The analysis provides estimates of the gender-specific absolute risk (cumulative risk) for non-smoking- and smoking-associated lung cancer, adjusted for demographic, occupational, and smoking history variables.
Results
In the multiple-variable lexpit regression, the adjusted 3-year absolute risk of lung cancer in never smokers was 4.6 per 100,000 persons higher in women than men. However, the absolute increase in 3-year risk of lung cancer for every 10 additional pack-years smoked was less for women than men, 13.6 versus 52.9 per 100,000 persons.
Conclusions
In a Northern Italian population, the absolute risk of lung cancer among never smokers is higher in women than men but among smokers is lower in women than men. Lexpit regression is a novel approach to additive-multiplicative risk modeling that can contribute to clearer interpretation of population-based case–control studies.
doi:10.1186/1471-2288-13-143
PMCID: PMC3840559  PMID: 24252624
Additive risk; Absolute risk; Case–control study; EAGLE; Lung cancer; Risk assessment; Sex factors; Smoking
2.  Clinical trial participant characteristics and saliva and DNA metrics 
Background
Clinical trial and epidemiological studies need high quality biospecimens from a representative sample of participants to investigate genetic influences on treatment response and disease. Obtaining blood biospecimens presents logistical and financial challenges. As a result, saliva biospecimen collection is becoming more frequent because of the ease of collection and lower cost. This article describes an assessment of saliva biospecimen samples collected through the mail, trial participant demographic and behavioral characteristics, and their association with saliva and DNA quantity and quality.
Methods
Saliva biospecimens were collected using the Oragene® DNA Self-Collection Kits from participants in a National Cancer Institute funded smoking cessation trial. Saliva biospecimens from 565 individuals were visually inspected for clarity prior to and after DNA extraction. DNA samples were then quantified by UV absorbance, PicoGreen®, and qPCR. Genotyping was performed on 11 SNPs using TaqMan® SNP assays and two VNTR assays. Univariate, correlation, and analysis of variance analyses were conducted to observe the relationship between saliva sample and participant characteristics.
Results
The biospecimen kit return rate was 58.5% among those invited to participate (n = 967) and 47.1% among all possible COMPASS participants (n = 1202). Significant gender differences were observed with males providing larger saliva volume (4.7 vs. 4.5 ml, p = 0.019), samples that were more likely to be judged as cloudy (39.5% vs. 24.9%, p < 0.001), and samples with greater DNA yield as measured by UV (190.0 vs. 138.5, p = 0.002), but reduced % human DNA content (73.2 vs. 77.6 p = 0.005) than females. Other participant characteristics (age, self-identified ethnicity, baseline cigarettes per day) were associated with saliva clarity. Saliva volume and saliva and DNA clarity were positively correlated with total DNA yield by all three quantification measurements (all r > 0.21, P < 0.001), but negatively correlated with % human DNA content (saliva volume r = -0.148 and all P < 0.010). Genotyping completion rate was not influenced by saliva or DNA clarity.
Conclusion
Findings from this study show that demographic and behavioral characteristics of smoking cessation trial participants have significant associations with saliva and DNA metrics, but not with the performance of TaqMan® SNP or VNTR genotyping assays.
Trial registration
COMPASS; registered as NCT00301145 at clinicaltrials.gov.
doi:10.1186/1471-2288-9-71
PMCID: PMC2776600  PMID: 19874586

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