Trends in self-reported past alcoholic beverage consumption and ethanol intake from 1950 to 1995 observed in eight European countries participating in the European Investigation into Cancer and Nutrition (EPIC).

OBJECTIVE To describe the trends of self-reported past consumption of alcoholic beverages and ethanol intake from 1950 to 1995 within the European Prospective Investigation into Cancer and Nutrition (EPIC). DESIGN Data on consumption of beer/cider, wine and liqueur/spirits were obtained retrospectively at age 20, 30 and 40 years to calculate average consumption and ethanol intake for the time periods 1950-1975 (at age 20), 1960-1985 (at age 30) and 1970-1995 (at age 40). Regression analysis was conducted with the time period data to assess trends in past alcoholic beverage consumption and ethanol intake with time. SETTING The EPIC project. SUBJECTS In total, 392 064 EPIC participants (275 249 women and 116 815 men) from 21 study centres in eight European countries. RESULTS Generally, increases in beer/cider consumption were observed for most EPIC centres for 1950-1975, 1960-1985 and 1970-1995. Trends in wine consumption differed according to geographical location: downward trends with time were observed for men in southern European EPIC centres, upward trends for those in middle/northern European study centres. For women, similar but less pronounced trends were observed. Because wine consumption was the major contributor to ethanol intake for both men and women in most study centres, time trends for ethanol intake showed a similar geographical pattern to that of wine consumption. CONCLUSION The different trends in alcoholic beverage consumption and ethanol intake suggest that information depicting lifetime history of ethanol intake should be included in analyses of the relationship between ethanol and chronic diseases, particularly in multi-centre studies such as EPIC.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Expression profiling of rectal tumors defines response to neoadjuvant treatment related genes.

To date, no effective method exists that predicts the response to preoperative chemoradiation (CRT) in locally advanced rectal cancer (LARC). Nevertheless, identification of patients who have a higher likelihood of responding to preoperative CRT could be crucial in decreasing treatment morbidity and avoiding expensive and time-consuming treatments. The aim of this study was to identify signatures or molecular markers related to response to pre-operative CRT in LARC. We analyzed the gene expression profiles of 26 pre-treatment biopsies of LARC (10 responders and 16 non-responders) without metastasis using Human WG CodeLink microarray platform. Two hundred and fifty seven genes were differentially over-expressed in the responder patient subgroup. Ingenuity Pathway Analysis revealed a significant ratio of differentially expressed genes related to cancer, cellular growth and proliferation pathways, and c-Myc network. We demonstrated that high Gng4, c-Myc, Pola1, and Rrm1 mRNA expression levels was a significant prognostic factor for response to treatment in LARC patients (p<0.05). Using this gene set, we were able to establish a new model for predicting the response to CRT in rectal cancer with a sensitivity of 60% and 100% specificity. Our results reflect the value of gene expression profiling to gain insight about the molecular pathways involved in the response to treatment of LARC patients. These findings could be clinically relevant and support the use of mRNA levels when aiming to identify patients who respond to CRT therapy.

Acute abdomen secondary to complete tubular colonic duplication.

We report the case of a 6-month-old infant who presented with a complete duplication of the large intestine, debuting clinically with acute abdomen and severe metabolic disorders. We discuss the pathogenesis and morphology of the lesions, diagnostic difficulties and peculiarities of surgical treatment.

A Clinical Decision Support using a Terminology Server to improve Patient Safety.

Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.