Explaining disparities in colorectal cancer screening among five Asian ethnic groups: A population-based study in California

<p>Abstract</p> <p>Background</p> <p>Data from the California Health Interview Survey (CHIS) indicate that levels and temporal trends in colorectal cancer (CRC) screening prevalence vary among Asian American groups; however, the reasons for these differences have not been fully investigated.</p> <p>Methods</p> <p>Using CHIS 2001, 2003 and 2005 data, we conducted hierarchical regression analyses progressively controlling for demographic characteristics, English proficiency and access to care in an attempt to identify factors explaining differences in screening prevalence and trends among Chinese, Filipino, Vietnamese, Korean and Japanese Americans (N = 4,188).</p> <p>Results</p> <p>After controlling for differences in gender and age, all Asian subgroups had significantly lower odds of having ever received screening in 2001 than the reference group of Japanese Americans. In addition, Korean Americans were the only subgroup that had a statistically significant decline in screening prevalence from 2001 to 2005 compared to the trend among Japanese Americans. After controlling for differences in education, marital status, employment status and federal poverty level, Korean Americans were the only group that had significantly lower screening prevalence than Japanese Americans in 2001, and their trend to 2005 remained significantly depressed. After controlling for differences in English proficiency and access to care, screening prevalences in 2001 were no longer significantly different among the Asian subgroups, but the trend among Korean Americans from 2001 to 2005 remained significantly depressed. Korean and Vietnamese Americans were less likely than other groups to report a recent doctor recommendation for screening and more likely to cite a lack of health problems as a reason for not obtaining screening.</p> <p>Conclusions</p> <p>Differences in CRC screening trends among Asian ethnic groups are not entirely explained by differences in demographic characteristics, English proficiency and access to care. A better understanding of mutable factors such as rates of doctor recommendation and health beliefs will be crucial for designing culturally appropriate interventions to promote CRC screening.</p

Graphene Bilayer Field-Effect Phototransistor for Terahertz and Infrared Detection

A graphene bilayer phototransistor (GBL-PT) is proposed and analyzed. The GBL-PT under consideration has the structure of a field-effect transistor with a GBL as the channel and the back and top gates. The positive bias of the back gate results in the formation of conducting source and drain sections in the channel, while the negatively biased top gate provides the potential barrier which is controlled by the charge of the photogenerated holes. The features of the GBL-PT operation are associated with the variations of both the potential distribution and the energy gap in different sections of the channel when the gate voltages and the charge in the barrier section change. Using the developed GBL-PT device model, the spectral characteristics, dark current, responsivity and detectivity are calculated as functions of the applied voltages, energy of incident photons, intensity of electron and hole scattering, and geometrical parameters. It is shown that the GBL-PT spectral characteristics are voltage tuned. The GBL-PT performance as photodetector in the terahertz and infrared photodetectors can markedly exceed the performance of other photodetectors.Comment: 7 Pages, 7 figure

Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines

Background: Melanoma risk prediction models could be useful for matching preventive interventions to patients’ risk. Objectives: To develop and validate a model for incident first‐primary cutaneous melanoma using clinically assessed risk factors. Methods: We used unconditional logistic regression with backward selection from the Australian Melanoma Family Study (461 cases and 329 controls) in which age, sex and city of recruitment were kept in each step, and we externally validated it using the Leeds Melanoma Case–Control Study (960 cases and 513 controls). Candidate predictors included clinically assessed whole‐body naevi and solar lentigines, and self‐assessed pigmentation phenotype, sun exposure, family history and history of keratinocyte cancer. We evaluated the predictive strength and discrimination of the model risk factors using odds per age‐ and sex‐adjusted SD (OPERA) and the area under curve (AUC), and calibration using the Hosmer–Lemeshow test. Results: The final model included the number of naevi ≥ 2 mm in diameter on the whole body, solar lentigines on the upper back (a six‐level scale), hair colour at age 18 years and personal history of keratinocyte cancer. Naevi was the strongest risk factor; the OPERA was 3·51 [95% confidence interval (CI) 2·71–4·54] in the Australian study and 2·56 (95% CI 2·23–2·95) in the Leeds study. The AUC was 0·79 (95% CI 0·76–0·83) in the Australian study and 0·73 (95% CI 0·70–0·75) in the Leeds study. The Hosmer–Lemeshow test P‐value was 0·30 in the Australian study and < 0·001 in the Leeds study. Conclusions: This model had good discrimination and could be used by clinicians to stratify patients by melanoma risk for the targeting of preventive interventions. What's already known about this topic? Melanoma risk prediction models may be useful in prevention by tailoring interventions to personalized risk levels. For reasons of feasibility, time and cost many melanoma prediction models use self‐assessed risk factors. However, individuals tend to underestimate their naevus numbers. What does this study add? We present a melanoma risk prediction model, which includes clinically‐assessed whole‐body naevi and solar lentigines, and self‐assessed risk factors including pigmentation phenotype and history of keratinocyte cancer. This model performs well on discrimination, the model's ability to distinguish between individuals with and without melanoma, and may assist clinicians to stratify patients by melanoma risk for targeted preventive interventions