Prostate functional magnetic resonance image analysis using multivariate curve resolution methods

This paper discusses the potential of Multivariate Curve Resolution (MCR) models to extract physiological dynamics behaviors from Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) Imaging prostate perfusion studies for cancer diagnosis. A relationship with biomarkers ( hidden parameters for assessing the possible existence of a tumor) from pharmacokinetic models is also studied.This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2011-28112-C04-02.Prats-Montalbán, JM.; Sanz Requena, R.; Marti Bonmati, L.; Ferrer, A. (2014). Prostate functional magnetic resonance image analysis using multivariate curve resolution methods. Journal of Chemometrics. 28(8):672-680. https://doi.org/10.1002/cem.2585S672680288Collins, D. J., & Padhani, A. R. (2004). Dynamic magnetic resonance imaging of tumor perfusion. IEEE Engineering in Medicine and Biology Magazine, 23(5), 65-83. doi:10.1109/memb.2004.1360410JACKSON, A. S. N., REINSBERG, S. A., SOHAIB, S. A., CHARLES-EDWARDS, E. M., JHAVAR, S., CHRISTMAS, T. J., … DEARNALEY, D. P. (2009). Dynamic contrast-enhanced MRI for prostate cancer localization. The British Journal of Radiology, 82(974), 148-156. doi:10.1259/bjr/89518905Leach, M. O., Brindle, K. M., Evelhoch, J. L., Griffiths, J. R., Horsman, M. R., Jackson, A., … Workman, P. (2005). The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations. British Journal of Cancer, 92(9), 1599-1610. doi:10.1038/sj.bjc.6602550Tofts, P. S., Brix, G., Buckley, D. L., Evelhoch, J. L., Henderson, E., Knopp, M. V., … Weisskoff, R. M. (1999). Estimating kinetic parameters from dynamic contrast-enhanced t1-weighted MRI of a diffusable tracer: Standardized quantities and symbols. Journal of Magnetic Resonance Imaging, 10(3), 223-232. doi:10.1002/(sici)1522-2586(199909)10:33.0.co;2-sPort, R. E., Knopp, M. V., & Brix, G. (2001). Dynamic contrast-enhanced MRI using Gd-DTPA: Interindividual variability of the arterial input function and consequences for the assessment of kinetics in tumors. Magnetic Resonance in Medicine, 45(6), 1030-1038. doi:10.1002/mrm.1137McGrath, D. M., Bradley, D. P., Tessier, J. L., Lacey, T., Taylor, C. J., & Parker, G. J. M. (2009). Comparison of model-based arterial input functions for dynamic contrast-enhanced MRI in tumor bearing rats. Magnetic Resonance in Medicine, 61(5), 1173-1184. doi:10.1002/mrm.21959Yang, C., Karczmar, G. S., Medved, M., Oto, A., Zamora, M., & Stadler, W. M. (2009). Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced-MRI analysis. Magnetic Resonance in Medicine, 61(4), 851-859. doi:10.1002/mrm.21912Meng, R., Chang, S. D., Jones, E. C., Goldenberg, S. L., & Kozlowski, P. (2010). 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Simple and objective prediction of survival in patients with lung cancer: staging the host systemic inflammatory response

Background. Prediction of survival in patients diagnosed with lung cancer remains problematical. The aim of the present study was to examine the clinical utility of an established objective marker of the systemic inflammatory response, the Glasgow Prognostic Score, as the basis of risk stratification in patients with lung cancer. Methods. Between 2005 and 2008 all newly diagnosed lung cancer patients coming through the multidisciplinary meetings (MDTs) of four Scottish centres were included in the study. The details of 882 patients with a confirmed new diagnosis of any subtype or stage of lung cancer were collected prospectively. Results. The median survival was 5.6 months (IQR 4.8–6.5). Survival analysis was undertaken in three separate groups based on mGPS score. In the mGPS 0 group the most highly predictive factors were performance status, weight loss, stage of NSCLC, and palliative treatment offered. In the mGPS 1 group performance status, stage of NSCLC, and radical treatment offered were significant. In the mGPS 2 group only performance status and weight loss were statistically significant. Discussion. This present study confirms previous work supporting the use of mGPS in predicting cancer survival; however, it goes further by showing how it might be used to provide more objective risk stratification in patients diagnosed with lung cancer

Prognostic Impact of miR-224 and RAS Mutations in Medullary Thyroid Carcinoma

Little is known about the function of microRNA-224 (miR-224) in medullary thyroid cancer (MTC). This study investigated the role of miR-224 expression in MTC and correlated it with mutation status in sporadic MTCs. A consecutive series of 134 MTCs were considered. Patients had a sporadic form in 80% of cases (107/134). In this group, REarranged during transfection (RET) and rat sarcoma (RAS) mutation status were assessed by direct sequencing in the tumor tissues. Quantitative real-time polymerase chain reaction was used to quantify mature hsa-miR-224 in tumor tissue. RAS (10/107 cases, 9%) and RET (39/107 cases, 36%) mutations were mutually exclusive in sporadic cases. miR-224 expression was significantly downregulated in patients with the following: high calcitonin levels at diagnosis (p=0.03, r=−0.3); advanced stage (p=0.001); persistent disease (p=0.001); progressive disease (p=0.002); and disease-related death (p=0.0001). We found a significant positive correlation between miR-224 expression and somatic RAS mutations (p=0.007). Patients whose MTCs had a low miR-224 expression tended to have a shorter overall survival (log-rank test p=0.005). On multivariate analysis, miR-224 represented an independent prognostic marker. Our data indicate that miR-224 is upregulated in RAS-mutated MTCs and in patients with a better prognosis and could represent an independent prognostic marker in MTC patients

A New SVDD-Based Multivariate Non-parametric Process Capability Index

Process capability index (PCI) is a commonly used statistic to measure ability of a process to operate within the given specifications or to produce products which meet the required quality specifications. PCI can be univariate or multivariate depending upon the number of process specifications or quality characteristics of interest. Most PCIs make distributional assumptions which are often unrealistic in practice. This paper proposes a new multivariate non-parametric process capability index. This index can be used when distribution of the process or quality parameters is either unknown or does not follow commonly used distributions such as multivariate normal

Relationship of hyperglycaemia, hypoglycaemia, and glucose variability to atherosclerotic disease in type 2 diabetes

Objective: Type 2 diabetes mellitus (T2DM) is known to be associated with increased cardiovascular risk. The aim of this study was therefore to investigate the independent effects of hyperglycaemia, hypoglycaemia, and glucose variability on microvascular and macrovascular disease in T2DM. Methods. Subjects with T2DM of 7.8mmol/L (β=15.83, p=0005) was the sole independent predictor of albuminuria in generalised linear regression. Conclusions. This study demonstrates that hypoglycaemia is associated with the occurrence of atherosclerotic disease while hyperglycaemia is associated with microvascular disease in a Caucasian population with T2DM of recent duration.peer-reviewe

A cross-sectional study on prevalence and predictors of burnout among a sample of pharmacists employed in pharmacies in Central Italy

Burnout is defined as an occupational phenomenon linked to chronic workplace stress that has not been successfully managed and included among the factors influencing health status or contact with health services. Although several studies were performed for assessing this phenomenon, there is a lack of data on the prevalence of burnout and associated predictors, due to different definitions of the syndrome and heterogeneity of assessment methods. One of the well-known evidences on burnout is related to the highest risk professions, which include policemen, firemen, teachers, psychologists, medical students, nurses, physicians, and other health professionals, such as pharmacists. Objective. The aims of the present study were to (1) assess the occurrence of burnout syndrome among a sample of pharmacists employed in public and private pharmacies located in Rome province (Latium Region; central Italy); (2) evaluate the role of some potential predictors for the development of the syndrome. Materials and Methods. A questionnaire elaborated ad hoc was administered online to 2,000 members of the Association of Professional Pharmacists of Rome and its province and employed in public or private pharmacies. The questionnaire included the 14-item Shirom-Melamed Burnout Measure (SMBM) tool and questions on demographic characteristics and working conditions. Results. Physical exhaustion was the burnout dimension with the highest score; besides, approximately 11% of the studied pharmacists were categorized as having clinically relevant burnout levels (≥4.40). Several of the investigated variables significantly influenced the single burnout dimensions at the univariate analyses; multivariate analyses demonstrated that alcohol consumption and workplace location have a significant independent role on the overall SMBM index, while working time significantly influences clinically relevant burnout level. Conclusions. The results revealed that pharmacists are at risk of burnout, and thus, it is necessary to perform specific preventive intervention for managing this occupational threat

Volatility forecasting

Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly. JEL Klassifikation: C10, C53, G1

Generalized Multivariate Extreme Value Models for Explicit Route Choice Sets

This paper analyses a class of route choice models with closed-form probability expressions, namely, Generalized Multivariate Extreme Value (GMEV) models. A large group of these models emerge from different utility formulas that combine systematic utility and random error terms. Twelve models are captured in a single discrete choice framework. The additive utility formula leads to the known logit family, being multinomial, path-size, paired combinatorial and link-nested. For the multiplicative formulation only the multinomial and path-size weibit models have been identified; this study also identifies the paired combinatorial and link-nested variations, and generalizes the path-size variant. Furthermore, a new traveller's decision rule based on the multiplicative utility formula with a reference route is presented. Here the traveller chooses exclusively based on the differences between routes. This leads to four new GMEV models. We assess the models qualitatively based on a generic structure of route utility with random foreseen travel times, for which we empirically identify that the variance of utility should be different from thus far assumed for multinomial probit and logit-kernel models. The expected travellers' behaviour and model-behaviour under simple network changes are analysed. Furthermore, all models are estimated and validated on an illustrative network example with long distance and short distance origin-destination pairs. The new multiplicative models based on differences outperform the additive models in both tests