Incidental venous thromboembolism in cancer patients: prevalence and consequence

Introduction: Careful re-evaluation of CT-scans for cancer staging frequently reveals unsuspected venous thromboembolism (VTE) on CT-scans. However, it is unknown how often these findings lead to anticoagulant treatment in daily clinical practice. Methods: Reports from thoracic and/or abdominal CT-scans performed in a consecutive series of patients to stage cancer were retrospectively evaluated to determine the prevalence of incidental venous thromboembolism (iVTE). Presence of pre-existing signs of VTE, anticoagulant treatment and 3-month follow-up were analysed in patients with iVTE. Results: A total of 1466 staging scans (838 patients) from the year 2006 were included in the analysis. The prevalence of VTE in patients was 2.5% (21/838 patients, 95% confidence interval 1.6-3.8%); the prevalence of VTE on scans was 1.4% (21/1466 scans, 95% CI 0.9-2.2%). Incidental PE or deep vein thrombosis (DVT) was observed in 11 (1.3%, 0.7-2.3%) and abdominal vein thrombosis in 9 patients (1.1%, 0.6-2.0%; in the portal (5), mesenteric (3) and renal vein (1), respectively). Nine out of eleven patients with PE/DVT were treated with anticoagulants, while none of the patients with thrombosis in other locations received anticoagulants. One of these patients developed symptomatic PE one month later; otherwise, follow up was uneventful in the untreated patients. Conclusion: The prevalence of iVTE in patients with cancer in clinical practice is relatively low and most patients with PE or DVT are treated with anticoagulants. For patients with thrombi in other locations, further research is necessary to understand the natural history of these thrombi in order to develop adequate guidelines. © 2010 Elsevier Ltd. All rights reserved

Practical data handling pipeline improves performance of qPCR-based circulating miRNA measurements

Since numerous miRNAs have been shown to be present in circulation, these so-called circulating miRNAs have emerged as potential biomarkers for disease. However, results of qPCR studies on circulating miRNA biomarkers vary greatly and many experiments cannot be reproduced. Missing data in qPCR experiments often occur due to off-target amplification, nonanalyzable qPCR curves and discordance between replicates. The low concentration of most miRNAs leads to most, but not all missing data. Therefore, failure to distinguish between missing data due to a low concentration and missing data due to a randomly occurring technical errors partly explains the variation within and between otherwise similar studies. Based on qPCR kinetics, an analysis pipeline was developed to distinguish missing data due to technical errors from missing data due to a low concentration of the miRNA-equivalent cDNA in the PCR reaction. Furthermore, this pipeline incorporates a method to statistically decide whether concentrations from replicates are sufficiently concordant, which improves stability of results and avoids unnecessary data loss. By going through the pipeline's steps, the result of each measurement is categorized as "valid, invalid, or undetectable." Together with a set of imputation rules, the pipeline leads to more robust and reproducible data as was confirmed experimentally. Using two validation approaches, in two cohorts totaling 2214 heart failure patients, we showed that this pipeline increases both the accuracy and precision of qPCR measurements. In conclusion, this statistical data handling pipeline improves the performance of qPCR studies on low-expressed targets such as circulating miRNAs. $x 1469-900

Practical data handling pipeline improves performance of qPCR-based circulating miRNA measurements

Since numerous miRNAs have been shown to be present in circulation, these so-called circulating miRNAs have emerged as potential biomarkers for disease. However, results of qPCR studies on circulating miRNA biomarkers vary greatly and many experiments cannot be reproduced. Missing data in qPCR experiments often occur due to off-target amplification, nonanalyzable qPCR curves and discordance between replicates. The low concentration of most miRNAs leads to most, but not all missing data. Therefore, failure to distinguish between missing data due to a low concentration and missing data due to randomly occurring technical errors partly explains the variation within and between otherwise similar studies. Based on qPCR kinetics, an analysis pipeline was developed to distinguish missing data due to technical errors from missing data due to a low concentration of the miRNA-equivalent cDNA in the PCR reaction. Furthermore, this pipeline incorporates a method to statistically decide whether concentrations from replicates are sufficiently concordant, which improves stability of results and avoids unnecessary data loss. By going through the pipeline's steps, the result of each measurement is categorized as "valid, invalid, or undetectable." Together with a set of imputation rules, the pipeline leads to more robust and reproducible data as was confirmed experimentally. Using two validation approaches, in two cohorts totaling 2214 heart failure patients, we showed that this pipeline increases both the accuracy and precision of qPCR measurements. In conclusion, this statistical data handling pipeline improves the performance of qPCR studies on low-expressed targets such as circulating miRNA