Risk factors for and estimated incidence of community-associated Clostridium difficile infection, North Carolina, USA.

We determined estimated incidence of and risk factors for community-associated Clostridium difficile infection (CA-CDI) among patients treated at 6 North Carolina hospitals. CA-CDI case-patients were defined as adults (>18 years of age) with a positive stool test result for C. difficile toxin and no hospitalization within the prior 8 weeks. CA-CDI incidence was 21 and 46 per 100,000 person-years in Veterans Affairs (VA) outpatients and Durham County populations, respectively. VA case-patients were more likely than controls to have received antimicrobial drugs (adjusted odds ratio [aOR] 17.8, 95% confidence interval [CI] 6.6-48] and to have had a recent outpatient visit (aOR 5.1, 95% CI 1.5-17.9). County case-patients were more likely than controls to have received antimicrobial drugs (aOR 9.1, 95% CI 2.9-28.9), to have gastroesophageal reflux disease (aOR 11.2, 95% CI 1.9-64.2), and to have cardiac failure (aOR 3.8, 95% CI 1.1-13.7). Risk factors for CA-CDI overlap with those for healthcare-associated infection.

HPV16 antibodies as risk factors for oropharyngeal cancer and their association with tumor HPV and smoking status.

BACKGROUND: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC. METHODS: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC. RESULTS: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively). CONCLUSIONS: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.