4 resultados para Automated Hazard Analysis


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The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.

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Advances in clinical virology for detecting respiratory viruses have been focused on nucleic acids amplification techniques, which have converted in the reference method for the diagnosis of acute respiratory infections of viral aetiology. Improvements of current commercial molecular assays to reduce hands-on-time rely on two strategies, a stepwise automation (semi-automation) and the complete automation of the whole procedure. Contributions to the former strategy have been the use of automated nucleic acids extractors, multiplex PCR, real-time PCR and/or DNA arrays for detection of amplicons. Commercial fully-automated molecular systems are now available for the detection of respiratory viruses. Some of them could convert in point-of-care methods substituting antigen tests for detection of respiratory syncytial virus and influenza A and B viruses. This article describes laboratory methods for detection of respiratory viruses. A cost-effective and rational diagnostic algorithm is proposed, considering technical aspects of the available assays, infrastructure possibilities of each laboratory and clinic-epidemiologic factors of the infection.

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Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infections pose major public health problems because of their prevalence worldwide. Consequently, screening for these infections is an important part of routine laboratory activity. Serological and molecular markers are key elements in diagnosis, prognosis and treatment monitoring for HBV and HCV infections. Today, automated chemiluminescence immunoassay (CLIA) analyzers are widely used for virological diagnosis, particularly in high-volume clinical laboratories. Molecular biology techniques are routinely used to detect and quantify viral genomes as well as to analyze their sequence; in order to determine their genotype and detect resistance to antiviral drugs. Real-time PCR, which provides high sensitivity and a broad dynamic range, has gradually replaced other signal and target amplification technologies for the quantification and detection of nucleic acid. The next-generation DNA sequencing techniques are still restricted to research laboratories.The serological and molecular marker methods available for HBV and HCV are discussed in this article, along with their utility and limitations for use in Chronic Hepatitis B (CHB) diagnosis and monitoring.

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INTRODUCTION Obesity is an unfavorable prognostic factor in breast cancer (BC) patients regardless of menopausal status and treatment received. However, the association between obesity and survival outcome by pathological subtype requires further clarification. METHODS We performed a retrospective analysis including 5,683 operable BC patients enrolled in four randomized clinical trials (GEICAM/9906, GEICAM/9805, GEICAM/2003-02, and BCIRG 001) evaluating anthracyclines and taxanes as adjuvant treatments. Our primary aim was to assess the prognostic effect of body mass index (BMI) on disease recurrence, breast cancer mortality (BCM), and overall mortality (OM). A secondary aim was to detect differences of such prognostic effects by subtype. RESULTS Multivariate survival analyses adjusting for age, tumor size, nodal status, menopausal status, surgery type, histological grade, hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, chemotherapy regimen, and under-treatment showed that obese patients (BMI 30.0 to 34.9) had similar prognoses to that of patients with a BMI < 25 (reference group) in terms of recurrence (Hazard Ratio [HR] = 1.08, 95% Confidence Interval [CI] = 0.90 to 1.30), BCM (HR = 1.02, 0.81 to 1.29), and OM (HR = 0.97, 0.78 to 1.19). Patients with severe obesity (BMI ≥ 35) had a significantly increased risk of recurrence (HR = 1.26, 1.00 to 1.59, P = 0.048), BCM (HR = 1.32, 1.00 to 1.74, P = 0.050), and OM (HR = 1.35, 1.06 to 1.71, P = 0.016) compared to our reference group. The prognostic effect of severe obesity did not vary by subtype. CONCLUSIONS Severely obese patients treated with anthracyclines and taxanes present a worse prognosis regarding recurrence, BCM, and OM than patients with BMI < 25. The magnitude of the harmful effect of BMI on survival-related outcomes was similar across subtypes.