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Rates of hypersensitivity reaction at UNC are similar to rates seen in other areas of the southeastern United States and higher than in other regions of the United States and Europe. Rates of both hypersensitivity reactions and grade 3 to 4 hypersensitivity reactions have not substantially changed over time. Geography, allergy history, and perhaps smoking or cancer type may help predict who will react to cetuximab. Steroids should be strongly considered as premedication in addition to diphenhydramine.

The National Birth Defects Prevention Study (NBDPS) is a case-control study of birth defects conducted across 10 U.S. states. Researchers are interested in characterizing the etiologic role of maternal diet, collected using a food frequency questionnaire. Because diet is multi-dimensional, dimension reduction methods such as cluster analysis are often used to summarize dietary patterns. In a large, heterogeneous population, traditional clustering methods, such as latent class analysis, used to estimate dietary patterns can produce a large number of clusters due to a variety of factors, including study size and regional diversity. These factors result in a loss of interpretability of patterns that may differ due to minor consumption changes.Based on adaptation of the local partition process, we propose a new method, Robust Profile Clustering, to handle these data complexities. Here, participants may be clustered at two levels: (1) globally, where women are assigned to an overall population-level cluster via an overfitted finite mixture model, and (2) locally, where regional variations in diet are accommodated via a beta-Bernoulli process dependent on subpopulation differences. We use our method to analyze the NBDPS data, deriving pre-pregnancy dietary patterns for women in the NBDPS while accounting for regional variability.

Background Latent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations. Objectives This study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC). Methods A total of 11,320 individuals aged 18–74 y from the Hispanic Community Health Study/Study of Latinos (2008–2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM. Results The LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DICRPC = 2.3 × 104, DICLCM  = 9.5 × 106]. Conclusions Dietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.

IntroductionLung cancer is the leading cause of cancer death, yet public engagement with efforts against lung cancer is low. Public engagement with a cancer is critical to efforts to combat it, yet the reasons for low support for efforts against lung cancer have not been systematically characterized.MethodsWe conducted a telephone survey of 1,071 people to determine levels of engagement and attitudes that might potentially drive engagement. These were then analyzed by univariate and multivariate analysis.ResultsEight percent of participants were involved with a lung cancer organization and 12% chose it among cancers to receive more support. Most participants felt that lung cancer was principally caused by external factors, that it could be cured if caught early, and that lung cancer patients were at least partly to blame for their illness. In multivariate analysis, participants who were supportive in some way of efforts against lung cancer were more likely to be employed, live in suburbia, and to be unsure of the cause of lung cancer. Potential supporters were more likely to be employed, female, younger, have higher income, to believe that genetics is the primary cause of lung cancer, and to believe that lung cancer can be cured when caught early. Participants frequently noted that they supported a particular cancer because of knowing someone affected by that cancer.ConclusionAs the lung cancer movement attempts to grow and increase its impact, the most successful recruitment efforts will be targeted to these groups.