Diagnostic accuracy and receiver-operating characteristics curve analysis in surgical research and decision making.

PubMed

Søreide, Kjetil; Kørner, Hartwig; Søreide, Jon Arne

2011-01-01

In surgical research, the ability to correctly classify one type of condition or specific outcome from another is of great importance for variables influencing clinical decision making. Receiver-operating characteristic (ROC) curve analysis is a useful tool in assessing the diagnostic accuracy of any variable with a continuous spectrum of results. In order to rule a disease state in or out with a given test, the test results are usually binary, with arbitrarily chosen cut-offs for defining disease versus health, or for grading of disease severity. In the postgenomic era, the translation from bench-to-bedside of biomarkers in various tissues and body fluids requires appropriate tools for analysis. In contrast to predetermining a cut-off value to define disease, the advantages of applying ROC analysis include the ability to test diagnostic accuracy across the entire range of variable scores and test outcomes. In addition, ROC analysis can easily examine visual and statistical comparisons across tests or scores. ROC is also favored because it is thought to be independent from the prevalence of the condition under investigation. ROC analysis is used in various surgical settings and across disciplines, including cancer research, biomarker assessment, imaging evaluation, and assessment of risk scores.With appropriate use, ROC curves may help identify the most appropriate cutoff value for clinical and surgical decision making and avoid confounding effects seen with subjective ratings. ROC curve results should always be put in perspective, because a good classifier does not guarantee the expected clinical outcome. In this review, we discuss the fundamental roles, suggested presentation, potential biases, and interpretation of ROC analysis in surgical research.

Receiver operating characteristic (ROC) curves: review of methods with applications in diagnostic medicine

NASA Astrophysics Data System (ADS)

Obuchowski, Nancy A.; Bullen, Jennifer A.

2018-04-01

Receiver operating characteristic (ROC) analysis is a tool used to describe the discrimination accuracy of a diagnostic test or prediction model. While sensitivity and specificity are the basic metrics of accuracy, they have many limitations when characterizing test accuracy, particularly when comparing the accuracies of competing tests. In this article we review the basic study design features of ROC studies, illustrate sample size calculations, present statistical methods for measuring and comparing accuracy, and highlight commonly used ROC software. We include descriptions of multi-reader ROC study design and analysis, address frequently seen problems of verification and location bias, discuss clustered data, and provide strategies for testing endpoints in ROC studies. The methods are illustrated with a study of transmission ultrasound for diagnosing breast lesions.

Modeling of recovery profiles in mentally disabled and intact patients after sevoflurane anesthesia; a pharmacodynamic analysis.

PubMed

Shin, Teo Jeon; Noh, Gyu-Jeong; Koo, Yong-Seo; Han, Dong Woo

2014-11-01

Mentally disabled patients show different recovery profiles compared to normal patients after general anesthesia. However, the relationship of dose-recovery profiles of mentally disabled patients has never been compared to that of normal patients. Twenty patients (10 mentally disabled patients and 10 mentally intact patients) scheduled to dental surgery under general anesthesia was recruited. Sevoflurane was administered to maintain anesthesia during dental treatment. At the end of the surgery, sevoflurane was discontinued. End-tidal sevoflurane and recovery of consciousness (ROC) were recorded after sevoflurane discontinuation. The pharmacodynamic relation between the probability of ROC and end-tidal sevoflurane concentration was analyzed using NONMEM software (version VII). End-tidal sevoflurane concentration associated with 50% probability of ROC (C₅₀) and γ value were lower in the mentally disabled patients (C₅₀=0.37 vol %, γ=16.5 in mentally intact patients, C₅₀=0.19 vol %, γ=4.58 in mentally disabled patients). Mentality was a significant covariate of C₅₀ for ROC and γ value to pharmacodynamic model. A sigmoid Emanx model explains the pharmacodynamic relationship between end-tidal sevoflurane concentration and ROC. Mentally disabled patients may recover slower from anesthesia at lower sevoflurane concentration at ROC an compared to normal patients.

Modeling of Recovery Profiles in Mentally Disabled and Intact Patients after Sevoflurane Anesthesia; A Pharmacodynamic Analysis

PubMed Central

Shin, Teo Jeon; Noh, Gyu-Jeong; Koo, Yong-Seo

2014-01-01

Purpose Mentally disabled patients show different recovery profiles compared to normal patients after general anesthesia. However, the relationship of dose-recovery profiles of mentally disabled patients has never been compared to that of normal patients. Materials and Methods Twenty patients (10 mentally disabled patients and 10 mentally intact patients) scheduled to dental surgery under general anesthesia was recruited. Sevoflurane was administered to maintain anesthesia during dental treatment. At the end of the surgery, sevoflurane was discontinued. End-tidal sevoflurane and recovery of consciousness (ROC) were recorded after sevoflurane discontinuation. The pharmacodynamic relation between the probability of ROC and end-tidal sevoflurane concentration was analyzed using NONMEM software (version VII). Results End-tidal sevoflurane concentration associated with 50% probability of ROC (C50) and γ value were lower in the mentally disabled patients (C50=0.37 vol %, γ=16.5 in mentally intact patients, C50=0.19 vol %, γ=4.58 in mentally disabled patients). Mentality was a significant covariate of C50 for ROC and γ value to pharmacodynamic model. Conclusion A sigmoid Emanx model explains the pharmacodynamic relationship between end-tidal sevoflurane concentration and ROC. Mentally disabled patients may recover slower from anesthesia at lower sevoflurane concentration at ROC an compared to normal patients. PMID:25323901

The three-class ideal observer for univariate normal data: Decision variable and ROC surface properties

PubMed Central

Edwards, Darrin C.; Metz, Charles E.

2012-01-01

Although a fully general extension of ROC analysis to classification tasks with more than two classes has yet to be developed, the potential benefits to be gained from a practical performance evaluation methodology for classification tasks with three classes have motivated a number of research groups to propose methods based on constrained or simplified observer or data models. Here we consider an ideal observer in a task with underlying data drawn from three univariate normal distributions. We investigate the behavior of the resulting ideal observer’s decision variables and ROC surface. In particular, we show that the pair of ideal observer decision variables is constrained to a parametric curve in two-dimensional likelihood ratio space, and that the decision boundary line segments used by the ideal observer can intersect this curve in at most six places. From this, we further show that the resulting ROC surface has at most four degrees of freedom at any point, and not the five that would be required, in general, for a surface in a six-dimensional space to be non-degenerate. In light of the difficulties we have previously pointed out in generalizing the well-known area under the ROC curve performance metric to tasks with three or more classes, the problem of developing a suitable and fully general performance metric for classification tasks with three or more classes remains unsolved. PMID:23162165

Laser confocal measurement system for curvature radius of lenses based on grating ruler

NASA Astrophysics Data System (ADS)

Tian, Jiwei; Wang, Yun; Zhou, Nan; Zhao, Weirui; Zhao, Weiqian

2015-02-01

In the modern optical measurement field, the radius of curvature (ROC) is one of the fundamental parameters of optical lens. Its measurement accuracy directly affects the other optical parameters, such as focal length, aberration and so on, which significantly affect the overall performance of the optical system. To meet the demand of measurement instruments for radius of curvature (ROC) with high accuracy in the market, we develop a laser confocal radius measurement system with grating ruler. The system uses the peak point of the confocal intensity curve to precisely identify the cat-eye and confocal positions and then measure the distance between these two positions by using the grating ruler, thereby achieving the high-precision measurement for the ROC. The system has advantages of high focusing sensitivity and anti-environment disturbance ability. And the preliminary theoretical analysis and experiments show that the measuring repeatability can be up to 0.8 um, which can provide an effective way for the accurate measurement of ROC.

Exploring the clonal evolution of CD133/aldehyde-dehydrogenase-1 (ALDH1)-positive cancer stem-like cells from primary to recurrent high-grade serous ovarian cancer (HGSOC). A study of the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) Consortium.

PubMed

Ruscito, Ilary; Cacsire Castillo-Tong, Dan; Vergote, Ignace; Ignat, Iulia; Stanske, Mandy; Vanderstichele, Adriaan; Ganapathi, Ram N; Glajzer, Jacek; Kulbe, Hagen; Trillsch, Fabian; Mustea, Alexander; Kreuzinger, Caroline; Benedetti Panici, Pierluigi; Gourley, Charlie; Gabra, Hani; Kessler, Mirjana; Sehouli, Jalid; Darb-Esfahani, Silvia; Braicu, Elena Ioana

2017-07-01

High-grade serous ovarian cancer (HGSOC) causes 80% of all ovarian cancer (OC) deaths. In this setting, the role of cancer stem-like cells (CSCs) is still unclear. In particular, the evolution of CSC biomarkers from primary (pOC) to recurrent (rOC) HGSOCs is unknown. Aim of this study was to investigate changes in CD133 and aldehyde dehydrogenase-1 (ALDH1) CSC biomarker expression in pOC and rOC HGSOCs. Two-hundred and twenty-four pOC and rOC intrapatient paired tissue samples derived from 112 HGSOC patients were evaluated for CD133 and ALDH1 expression using immunohistochemistry (IHC); pOCs and rOCs were compared for CD133 and/or ALDH1 levels. Expression profiles were also correlated with patients' clinicopathological and survival data. Some 49.1% of the patient population (55/112) and 37.5% (42/112) pOCs were CD133+ and ALDH1+ respectively. CD133+ and ALDH1+ samples were detected in 33.9% (38/112) and 36.6% (41/112) rOCs. CD133/ALDH1 coexpression was observed in 23.2% (26/112) and 15.2% (17/112) of pOCs and rOCs respectively. Pairwise analysis showed a significant shift of CD133 staining from higher (pOCs) to lower expression levels (rOCs) (p < 0.0001). Furthermore, all CD133 + pOC patients were International Federation of Gynaecology and Obstetrics (FIGO)-stage III/IV (p < 0.0001) and had significantly worse progression-free interval (PFI) (p = 0.04) and overall survival (OS) (p = 0.02). On multivariate analysis, CD133/ALDH1 coexpression in pOCs was identified as independent prognostic factor for PFI (HR: 1.64; 95% CI: 1.03-2.60; p = 0.036) and OS (HR: 1.71; 95% CI: 1.01-2.88; p = 0.045). Analysis on 52 pts patients with known somatic BRCA status revealed that BRCA mutations did not influence CSC biomarker expression. The study showed that CD133/ALDH1 expression impacts HGSOC patients' survival and first suggests that CSCs might undergo phenotypic change during the disease course similarly to non stem-like cancer cells, providing also a first evidence that there is no correlation between CSCs and BRCA status. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of ROC on chest direct digital radiography (DR) after image processing in diagnosis of SARS

NASA Astrophysics Data System (ADS)

Lv, Guozheng; Lan, Rihui; Zeng, Qingsi; Zheng, Zhong

2004-05-01

The Severe Acute Respiratory Syndrome (SARS, also called Infectious Atypical Pneumonia), which initially broke out in late 2002, has threatened the public"s health seriously. How to confirm the patients contracting SARS becomes an urgent issue in diagnosis. This paper intends to evaluate the importance of Image Processing in the diagnosis on SARS at the early stage. Receiver Operating Characteristics (ROC) analysis has been employed in this study to compare the value of DR images in the diagnosis of SARS patients before and after image processing by Symphony Software supplied by E-Com Technology Ltd., and DR image study of 72 confirmed or suspected SARS patients were reviewed respectively. All the images taken from the studied patients were processed by Symphony. Both the original and processed images were taken into ROC analysis, based on which the ROC graph for each group of images has been produced as described below: For processed images: a = 1.9745, b = 1.4275, SA = 0.8714; For original images: a = 0.9066, b = 0.8310, SA = 0.7572; (a - intercept, b - slop, SA - Area below the curve). The result shows significant difference between the original images and processed images (P<0.01). In summary, the images processed by Symphony are superior to the original ones in detecting the opacity lesion, and increases the accuracy of SARS diagnosis.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Receiver operating characteristic analysis. Application to the study of quantum fluctuation effects in optic nerve of Rana pipiens

PubMed Central

1975-01-01

Receiver operating characteristic (ROC) analysis of nerve messages is described. The hypothesis that quantum fluctuations provide the only limit to the ability of frog ganglion cells to signal luminance change information is examined using ROC analysis. In the context of ROC analysis, the quantum fluctuation hypothesis predicts (a) the detectability of a luminance change signal should rise proportionally to the size of the change, (b) detectability should decrease as the square root of background, an implication of which is the deVries-Rose law, and (c) ROC curves should exhibit a shape particular to underlying Poisson distributions. Each of these predictions is confirmed for the responses of dimming ganglion cells to brief luminance decrements at scotopic levels, but none could have been tested using classical nerve message analysis procedures. PMID:172597

Asymptotic Properties of the Sequential Empirical ROC, PPV and NPV Curves Under Case-Control Sampling.

PubMed

Koopmeiners, Joseph S; Feng, Ziding

2011-01-01

The receiver operating characteristic (ROC) curve, the positive predictive value (PPV) curve and the negative predictive value (NPV) curve are three measures of performance for a continuous diagnostic biomarker. The ROC, PPV and NPV curves are often estimated empirically to avoid assumptions about the distributional form of the biomarkers. Recently, there has been a push to incorporate group sequential methods into the design of diagnostic biomarker studies. A thorough understanding of the asymptotic properties of the sequential empirical ROC, PPV and NPV curves will provide more flexibility when designing group sequential diagnostic biomarker studies. In this paper we derive asymptotic theory for the sequential empirical ROC, PPV and NPV curves under case-control sampling using sequential empirical process theory. We show that the sequential empirical ROC, PPV and NPV curves converge to the sum of independent Kiefer processes and show how these results can be used to derive asymptotic results for summaries of the sequential empirical ROC, PPV and NPV curves.

Asymptotic Properties of the Sequential Empirical ROC, PPV and NPV Curves Under Case-Control Sampling

PubMed Central

Koopmeiners, Joseph S.; Feng, Ziding

2013-01-01

The receiver operating characteristic (ROC) curve, the positive predictive value (PPV) curve and the negative predictive value (NPV) curve are three measures of performance for a continuous diagnostic biomarker. The ROC, PPV and NPV curves are often estimated empirically to avoid assumptions about the distributional form of the biomarkers. Recently, there has been a push to incorporate group sequential methods into the design of diagnostic biomarker studies. A thorough understanding of the asymptotic properties of the sequential empirical ROC, PPV and NPV curves will provide more flexibility when designing group sequential diagnostic biomarker studies. In this paper we derive asymptotic theory for the sequential empirical ROC, PPV and NPV curves under case-control sampling using sequential empirical process theory. We show that the sequential empirical ROC, PPV and NPV curves converge to the sum of independent Kiefer processes and show how these results can be used to derive asymptotic results for summaries of the sequential empirical ROC, PPV and NPV curves. PMID:24039313

Setting Cut Scores on an EFL Placement Test Using the Prototype Group Method: A Receiver Operating Characteristic (ROC) Analysis

ERIC Educational Resources Information Center

Eckes, Thomas

2017-01-01

This paper presents an approach to standard setting that combines the prototype group method (PGM; Eckes, 2012) with a receiver operating characteristic (ROC) analysis. The combined PGM-ROC approach is applied to setting cut scores on a placement test of English as a foreign language (EFL). To implement the PGM, experts first named learners whom…

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

Objective: In multireader, multicase (MRMC) receiver operating characteristic (ROC) studies for evaluating medical imaging systems, the area under the ROC curve (AUC) is often used as a summary metric. Owing to the limitations of AUC, plotting the average ROC curve to accompany the rigorous statistical inference on AUC is recommended. The objective of this article is to investigate methods for generating the average ROC curve from ROC curves of individual readers. Methods: We present both a non-parametric method and a parametric method for averaging ROC curves that produce a ROC curve, the area under which is equal to the average AUC of individual readers (a property we call area preserving). We use hypothetical examples, simulated data and a real-world imaging data set to illustrate these methods and their properties. Results: We show that our proposed methods are area preserving. We also show that the method of averaging the ROC parameters, either the conventional bi-normal parameters (a, b) or the proper bi-normal parameters (c, da), is generally not area preserving and may produce a ROC curve that is intuitively not an average of multiple curves. Conclusion: Our proposed methods are useful for making plots of average ROC curves in MRMC studies as a companion to the rigorous statistical inference on the AUC end point. The software implementing these methods is freely available from the authors. Advances in knowledge: Methods for generating the average ROC curve in MRMC ROC studies are formally investigated. The area-preserving criterion we defined is useful to evaluate such methods. PMID:24884728

The receiver operational characteristic for binary classification with multiple indices and its application to the neuroimaging study of Alzheimer's disease.

PubMed

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2013-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis.

The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer’s Disease

PubMed Central

Wu, Xia; Li, Juan; Ayutyanont, Napatkamon; Protas, Hillary; Jagust, William; Fleisher, Adam; Reiman, Eric; Yao, Li; Chen, Kewei

2014-01-01

Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer’s disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as “AND,” “OR,” and “at least n” (where n is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the “leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis. PMID:23702553

Recollection is a continuous process: Evidence from plurality memory receiver operating characteristics.

PubMed

Slotnick, Scott D; Jeye, Brittany M; Dodson, Chad S

2016-01-01

Is recollection a continuous/graded process or a threshold/all-or-none process? Receiver operating characteristic (ROC) analysis can answer this question as the continuous model and the threshold model predict curved and linear recollection ROCs, respectively. As memory for plurality, an item's previous singular or plural form, is assumed to rely on recollection, the nature of recollection can be investigated by evaluating plurality memory ROCs. The present study consisted of four experiments. During encoding, words (singular or plural) or objects (single/singular or duplicate/plural) were presented. During retrieval, old items with the same plurality or different plurality were presented. For each item, participants made a confidence rating ranging from "very sure old", which was correct for same plurality items, to "very sure new", which was correct for different plurality items. Each plurality memory ROC was the proportion of same versus different plurality items classified as "old" (i.e., hits versus false alarms). Chi-squared analysis revealed that all of the plurality memory ROCs were adequately fit by the continuous unequal variance model, whereas none of the ROCs were adequately fit by the two-high threshold model. These plurality memory ROC results indicate recollection is a continuous process, which complements previous source memory and associative memory ROC findings.

On the convexity of ROC curves estimated from radiological test results.

PubMed

Pesce, Lorenzo L; Metz, Charles E; Berbaum, Kevin S

2010-08-01

Although an ideal observer's receiver operating characteristic (ROC) curve must be convex-ie, its slope must decrease monotonically-published fits to empirical data often display "hooks." Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This article aims to identify the practical implications of nonconvex ROC curves and the conditions that can lead to empirical or fitted ROC curves that are not convex. This article views nonconvex ROC curves from historical, theoretical, and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve does not cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any nonconvex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. In general, ROC curve fits that show hooks should be looked on with suspicion unless other arguments justify their presence. 2010 AUR. Published by Elsevier Inc. All rights reserved.

On the convexity of ROC curves estimated from radiological test results

PubMed Central

Pesce, Lorenzo L.; Metz, Charles E.; Berbaum, Kevin S.

2010-01-01

Rationale and Objectives Although an ideal observer’s receiver operating characteristic (ROC) curve must be convex — i.e., its slope must decrease monotonically — published fits to empirical data often display “hooks.” Such fits sometimes are accepted on the basis of an argument that experiments are done with real, rather than ideal, observers. However, the fact that ideal observers must produce convex curves does not imply that convex curves describe only ideal observers. This paper aims to identify the practical implications of non-convex ROC curves and the conditions that can lead to empirical and/or fitted ROC curves that are not convex. Materials and Methods This paper views non-convex ROC curves from historical, theoretical and statistical perspectives, which we describe briefly. We then consider population ROC curves with various shapes and analyze the types of medical decisions that they imply. Finally, we describe how sampling variability and curve-fitting algorithms can produce ROC curve estimates that include hooks. Results We show that hooks in population ROC curves imply the use of an irrational decision strategy, even when the curve doesn’t cross the chance line, and therefore usually are untenable in medical settings. Moreover, we sketch a simple approach to improve any non-convex ROC curve by adding statistical variation to the decision process. Finally, we sketch how to test whether hooks present in ROC data are likely to have been caused by chance alone and how some hooked ROCs found in the literature can be easily explained as fitting artifacts or modeling issues. Conclusion In general, ROC curve fits that show hooks should be looked upon with suspicion unless other arguments justify their presence. PMID:20599155

To t-Test or Not to t-Test? A p-Values-Based Point of View in the Receiver Operating Characteristic Curve Framework.

PubMed

Vexler, Albert; Yu, Jihnhee

2018-04-13

A common statistical doctrine supported by many introductory courses and textbooks is that t-test type procedures based on normally distributed data points are anticipated to provide a standard in decision-making. In order to motivate scholars to examine this convention, we introduce a simple approach based on graphical tools of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. In this context, we propose employing a p-values-based method, taking into account the stochastic nature of p-values. We focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we extend the EPV concept to be considered in terms of the ROC curve technique. This provides expressive evaluations and visualizations of a wide spectrum of testing mechanisms' properties. We show that the conventional power characterization of tests is a partial aspect of the presented EPV/ROC technique. We desire that this explanation of the EPV/ROC approach convinces researchers of the usefulness of the EPV/ROC approach for depicting different characteristics of decision-making procedures, in light of the growing interest regarding correct p-values-based applications.

Some interesting examples of binormal degeneracy and analysis using a contaminated binormal ROC model

NASA Astrophysics Data System (ADS)

Berbaum, Kevin S.; Dorfman, Donald D.

2001-06-01

Receiver operating characteristic (ROC) data with false positive fractions of zero are often difficult to fit with standard ROC methodology, and are sometimes discarded. Some extreme examples of such data were analyzed. A new ROC model is proposed that assumes that for a proportion of abnormalities, no signal information is captured and that those abnormalities have the same distribution as noise along the latent decision axis. Rating reports of fracture for single view ankle radiographs were also analyzed with the binormal ROC model and two proper ROC models. The conventional models gave ROC area close to one, implying a true positive fraction close to one. The data contained no such fractions. When all false positive fractions were zero, conventional ROC areas gave little or no hint of unmistakable differences in true positive fractions. In contrast, the new model can fit ROC data in which some or all of the ROC points have false positive fractions of zero and true positive fractions less than one without concluding perfect performance. These data challenge the validity and robustness of conventional ROC models, but the contaminated binormal model accounts for these data. This research has been published for a different audience.

Exploratory Use of Decision Tree Analysis in Classification of Outcome in Hypoxic-Ischemic Brain Injury.

PubMed

Phan, Thanh G; Chen, Jian; Singhal, Shaloo; Ma, Henry; Clissold, Benjamin B; Ly, John; Beare, Richard

2018-01-01

Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.

THE VALIDITY OF USING ROC SOFTWARE FOR ANALYSING VISUAL GRADING CHARACTERISTICS DATA: AN INVESTIGATION BASED ON THE NOVEL SOFTWARE VGC ANALYZER.

PubMed

Hansson, Jonny; Månsson, Lars Gunnar; Båth, Magnus

2016-06-01

The purpose of the present work was to investigate the validity of using single-reader-adapted receiver operating characteristics (ROC) software for analysis of visual grading characteristics (VGC) data. VGC data from four published VGC studies on optimisation of X-ray examinations, previously analysed using ROCFIT, were reanalysed using a recently developed software dedicated to VGC analysis (VGC Analyzer), and the outcomes [the mean and 95 % confidence interval (CI) of the area under the VGC curve (AUCVGC) and the p-value] were compared. The studies included both paired and non-paired data and were reanalysed both for the fixed-reader and the random-reader situations. The results showed good agreement between the softwares for the mean AUCVGC For non-paired data, wider CIs were obtained with VGC Analyzer than previously reported, whereas for paired data, the previously reported CIs were similar or even broader. Similar observations were made for the p-values. The results indicate that the use of single-reader-adapted ROC software such as ROCFIT for analysing non-paired VGC data may lead to an increased risk of committing Type I errors, especially in the random-reader situation. On the other hand, the use of ROC software for analysis of paired VGC data may lead to an increased risk of committing Type II errors, especially in the fixed-reader situation. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity

PubMed Central

Wittenberg, Leah A.; Jonsson, Nina J.; Chan, RV Paul; Chiang, Michael F.

2014-01-01

Presence of plus disease in retinopathy of prematurity (ROP) is an important criterion for identifying treatment-requiring ROP. Plus disease is defined by a standard published photograph selected over 20 years ago by expert consensus. However, diagnosis of plus disease has been shown to be subjective and qualitative. Computer-based image analysis, using quantitative methods, has potential to improve the objectivity of plus disease diagnosis. The objective was to review the published literature involving computer-based image analysis for ROP diagnosis. The PubMed and Cochrane library databases were searched for the keywords “retinopathy of prematurity” AND “image analysis” AND/OR “plus disease.” Reference lists of retrieved articles were searched to identify additional relevant studies. All relevant English-language studies were reviewed. There are four main computer-based systems, ROPtool (AU ROC curve, plus tortuosity 0.95, plus dilation 0.87), RISA (AU ROC curve, arteriolar TI 0.71, venular diameter 0.82), Vessel Map (AU ROC curve, arteriolar dilation 0.75, venular dilation 0.96), and CAIAR (AU ROC curve, arteriole tortuosity 0.92, venular dilation 0.91), attempting to objectively analyze vessel tortuosity and dilation in plus disease in ROP. Some of them show promise for identification of plus disease using quantitative methods. This has potential to improve the diagnosis of plus disease, and may contribute to the management of ROP using both traditional binocular indirect ophthalmoscopy and image-based telemedicine approaches. PMID:21366159

A tutorial on the use of ROC analysis for computer-aided diagnostic systems.

PubMed

Scheipers, Ulrich; Perrey, Christian; Siebers, Stefan; Hansen, Christian; Ermert, Helmut

2005-07-01

The application of the receiver operating characteristic (ROC) curve for computer-aided diagnostic systems is reviewed. A statistical framework is presented and different methods of evaluating the classification performance of computer-aided diagnostic systems, and, in particular, systems for ultrasonic tissue characterization, are derived. Most classifiers that are used today are dependent on a separation threshold, which can be chosen freely in many cases. The separation threshold separates the range of output values of the classification system into different target groups, thus conducting the actual classification process. In the first part of this paper, threshold specific performance measures, e.g., sensitivity and specificity, are presented. In the second part, a threshold-independent performance measure, the area under the ROC curve, is reviewed. Only the use of separation threshold-independent performance measures provides classification results that are overall representative for computer-aided diagnostic systems. The following text was motivated by the lack of a complete and definite discussion of the underlying subject in available textbooks, references and publications. Most manuscripts published so far address the theme of performance evaluation using ROC analysis in a manner too general to be practical for everyday use in the development of computer-aided diagnostic systems. Nowadays, the user of computer-aided diagnostic systems typically handles huge amounts of numerical data, not always distributed normally. Many assumptions made in more or less theoretical works on ROC analysis are no longer valid for real-life data. The paper aims at closing the gap between theoretical works and real-life data. The review provides the interested scientist with information needed to conduct ROC analysis and to integrate algorithms performing ROC analysis into classification systems while understanding the basic principles of classification.

Psychometric properties of the Medical Student Well-Being Index among medical students in a Malaysian medical school.

PubMed

Yusoff, Muhamad Saiful Bahri; Yaacob, Mohd Jamil; Naing, Nyi Nyi; Esa, Ab Rahman

2013-02-01

This study evaluated the convergent, discriminant, construct, concurrent and discriminative validity of the Medical Student Wellbeing Index (MSWBI) as well as to evaluate its internal consistency and optimal cut-off total scores to detect at least moderate levels of general psychological distress, stress, anxiety and depression symptoms. A cross sectional study was done on 171 medical students. The MSWBI and DASS-21 were administered and returned immediately upon completion. Confirmatory factor analysis, reliability analysis, ROC analysis and Pearson correlation test were applied to assess psychometric properties of the MSWBI. A total of 168 (98.2%) medical students responded. The goodness of fit indices showed the MSWBI had a good construct (χ(2)=6.14, p=0.803, RMSEA<0.001, RMR=0.004, GFI=0.99, AGFI=0.97, CFI=1.00, IFI=1.02, TLI=1.04). The Cronbach's alpha value was 0.69 indicating an acceptable level of internal consistency. Pearson correlation coefficients and ROC analysis suggested each MSWBI's item showed adequate convergent and discriminant validity. Its optimal cut-off scores to detect at least moderate levels of general psychological distress, stress, anxiety, and depression were 1.5, 2.5, 1.5 and 2.5 respectively with sensitivity and specificity ranged from 62 to 80% and the areas under ROC curve ranged from 0.71 to 0.83. This study showed that the MSWBI had good level of psychometric properties. The MSWBI score more than 2 can be considered as having significant psychological distress. The MSWBI is a valid and reliable screening instrument to assess psychological distress of medical students. Copyright © 2012 Elsevier B.V. All rights reserved.

Improving fMRI reliability in presurgical mapping for brain tumours.

PubMed

Stevens, M Tynan R; Clarke, David B; Stroink, Gerhard; Beyea, Steven D; D'Arcy, Ryan Cn

2016-03-01

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps. Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel. The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively). We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Analysis of confidence level scores from an ROC study: comparison of three mammographic systems for detection of simulated calcifications

NASA Astrophysics Data System (ADS)

Lai, Chao-Jen; Shaw, Chris C.; Whitman, Gary J.; Yang, Wei T.; Dempsey, Peter J.

2005-04-01

The purpose of this study is to compare the detection performance of three different mammography systems: screen/film (SF) combination, a-Si/CsI flat-panel (FP-), and charge-coupled device (CCD-) based systems. A 5-cm thick 50% adipose/50% glandular breast tissue equivalent slab phantom was used to provide an uniform background. Calcium carbonate grains of three different size groups were used to simulate microcalcifications (MCs): 112-125, 125-140, and 140-150 μm overlapping with the uniform background. Calcification images were acquired with the three mammography systems. Digital images were printed on hardcopy films. All film images were displayed on a mammographic viewer and reviewed by 5 mammographers. The visibility of the MC was rated with a 5-point confidence rating scale for each detection task, including the negative controls. Scores were averaged over all readers for various detectors and size groups. Receiver operating characteristic (ROC) analysis was performed and the areas under the ROC curves (Az"s) were computed for various imaging conditions. The results shows that (1) the FP-based system performed significantly better than the SF and CCD-based systems for individual size groups using ROC analysis (2) the FP-based system also performed significantly better than the SF and CCD-based systems for individual size groups using averaged confidence scale, and (3) the results obtained from the Az"s were largely correlated with these from confidence level scores. However, the correlation varied slightly among different imaging conditions.

Compare diagnostic tests using transformation-invariant smoothed ROC curves⋆

PubMed Central

Tang, Liansheng; Du, Pang; Wu, Chengqing

2012-01-01

Receiver operating characteristic (ROC) curve, plotting true positive rates against false positive rates as threshold varies, is an important tool for evaluating biomarkers in diagnostic medicine studies. By definition, ROC curve is monotone increasing from 0 to 1 and is invariant to any monotone transformation of test results. And it is often a curve with certain level of smoothness when test results from the diseased and non-diseased subjects follow continuous distributions. Most existing ROC curve estimation methods do not guarantee all of these properties. One of the exceptions is Du and Tang (2009) which applies certain monotone spline regression procedure to empirical ROC estimates. However, their method does not consider the inherent correlations between empirical ROC estimates. This makes the derivation of the asymptotic properties very difficult. In this paper we propose a penalized weighted least square estimation method, which incorporates the covariance between empirical ROC estimates as a weight matrix. The resulting estimator satisfies all the aforementioned properties, and we show that it is also consistent. Then a resampling approach is used to extend our method for comparisons of two or more diagnostic tests. Our simulations show a significantly improved performance over the existing method, especially for steep ROC curves. We then apply the proposed method to a cancer diagnostic study that compares several newly developed diagnostic biomarkers to a traditional one. PMID:22639484

Adaptive histogram equalization in digital radiography of destructive skeletal lesions.

PubMed

Braunstein, E M; Capek, P; Buckwalter, K; Bland, P; Meyer, C R

1988-03-01

Adaptive histogram equalization, an image-processing technique that distributes pixel values of an image uniformly throughout the gray scale, was applied to 28 plain radiographs of bone lesions, after they had been digitized. The non-equalized and equalized digital images were compared by two skeletal radiologists with respect to lesion margins, internal matrix, soft-tissue mass, cortical breakthrough, and periosteal reaction. Receiver operating characteristic (ROC) curves were constructed on the basis of the responses. Equalized images were superior to nonequalized images in determination of cortical breakthrough and presence or absence of periosteal reaction. ROC analysis showed no significant difference in determination of margins, matrix, or soft-tissue masses.

[Comparative Study of Patient Identifications for Conventional and Portable Chest Radiographs Utilizing ROC Analysis].

PubMed

Kawashima, Hiroki; Hayashi, Norio; Ohno, Naoki; Matsuura, Yukihiro; Sanada, Shigeru

2015-08-01

To evaluate the patient identification ability of radiographers, previous and current chest radiographs were assessed with observer study utilizing a receiver operating characteristics (ROCs) analysis. This study included portable and conventional chest radiographs from 43 same and 43 different patients. The dataset used in this study was divided into the three following groups: (1) a pair of portable radiographs, (2) a pair of conventional radiographs, and (3) a combination of each type of radiograph. Seven observers participated in this ROC study, which aimed to identify same or different patients, using these datasets. ROC analysis was conducted to calculate the average area under ROC curve obtained by each observer (AUCave), and a statistical test was performed using the multi-reader multi-case method. Comparable results were obtained with pairs of portable (AUCave: 0.949) and conventional radiographs (AUCave: 0.951). In a comparison between the same modality, there were no significant differences. In contrast, the ability to identify patients by comparing a portable and conventional radiograph (AUCave: 0.873) was lower than with the matching datasets (p=0.002 and p=0.004, respectively). In conclusion, the use of different imaging modalities reduces radiographers' ability to identify their patients.

Determination of glucose-6-phosphate dehydrogenase cut-off values in a Tunisian population.

PubMed

Laouini, Naouel; Sahli, Chaima Abdelhafidh; Jouini, Latifa; Haloui, Sabrine; Fredj, Sondes Hadj; Daboubi, Rym; Siala, Hajer; Ouali, Faida; Becher, Meriam; Toumi, Nourelhouda; Bibi, Amina; Messsaoud, Taieb

2017-07-26

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the commonest enzymopathy worldwide. The incidence depends essentially on the methods used for the assessment. In this respect, we attempted in this study to set cut-off values of G6PD activity to discriminate among normal, heterozygous, and deficient individuals using the World Health Organization (WHO) classification and the receiver operating characteristics (ROC) curve analysis. Blood samples from 250 female and 302 male subjects were enrolled in this study. The G6PD activity was determined using a quantitative assay. The common G6PD mutations in Tunisia were determined using the amplification refractory mutation system (ARMS-PCR) method. The ROC curve was used to choice the best cut-off. Normal G6PD values were 7.69±2.37, 7.86±2.39, and 7.51±2.35 U/g Hb for the entire, male, and female groups, respectively. Cut-off values for the total, male, and female were determined using the WHO classification and ROC curves analysis. In the male population, both cut-offs established using ROC curve analysis (4.00 U/g Hb) and the 60% level (3.82 U/g Hb), respectively are sensitive and specific resulting in a good efficiency of discrimination between deficient and normal males. For the female group the ROC cut-off (5.84 U/g Hb) seems better than the 60% level cut-off (3.88 U/g Hb) to discriminate between normal and heterozygote or homozygote women with higher Youden Index. The establishment of the normal values for a population is important for a better evaluation of the assay result. The ROC curve analysis is an alternative method to determine the status of patients since it correlates DNA analysis and G6PD activity.

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

CombiROC: an interactive web tool for selecting accurate marker combinations of omics data.

PubMed

Mazzara, Saveria; Rossi, Riccardo L; Grifantini, Renata; Donizetti, Simone; Abrignani, Sergio; Bombaci, Mauro

2017-03-30

Diagnostic accuracy can be improved considerably by combining multiple markers, whose performance in identifying diseased subjects is usually assessed via receiver operating characteristic (ROC) curves. The selection of multimarker signatures is a complicated process that requires integration of data signatures with sophisticated statistical methods. We developed a user-friendly tool, called CombiROC, to help researchers accurately determine optimal markers combinations from diverse omics methods. With CombiROC data from different domains, such as proteomics and transcriptomics, can be analyzed using sensitivity/specificity filters: the number of candidate marker panels rising from combinatorial analysis is easily optimized bypassing limitations imposed by the nature of different experimental approaches. Leaving to the user full control on initial selection stringency, CombiROC computes sensitivity and specificity for all markers combinations, performances of best combinations and ROC curves for automatic comparisons, all visualized in a graphic interface. CombiROC was designed without hard-coded thresholds, allowing a custom fit to each specific data: this dramatically reduces the computational burden and lowers the false negative rates given by fixed thresholds. The application was validated with published data, confirming the marker combination already originally described or even finding new ones. CombiROC is a novel tool for the scientific community freely available at http://CombiROC.eu.

MYC and Human Telomerase Gene (TERC) Copy Number Gain in Early-stage Non–small Cell Lung Cancer

PubMed Central

Flacco, Antonella; Ludovini, Vienna; Bianconi, Fortunato; Ragusa, Mark; Bellezza, Guido; Tofanetti, Francesca R.; Pistola, Lorenza; Siggillino, Annamaria; Vannucci, Jacopo; Cagini, Lucio; Sidoni, Angelo; Puma, Francesco; Varella-Garcia, Marileila; Crinò, Lucio

2015-01-01

Objectives We investigated the frequency of MYC and TERC increased gene copy number (GCN) in early-stage non–small cell lung cancer (NSCLC) and evaluated the correlation of these genomic imbalances with clinicopathologic parameters and outcome. Materials and Methods Tumor tissues were obtained from 113 resected NSCLCs. MYC and TERC GCNs were tested by fluorescence in situ hybridization (FISH) according to the University of Colorado Cancer Center (UCCC) criteria and based on the receiver operating characteristic (ROC) classification. Results When UCCC criteria were applied, 41 (36%) cases for MYC and 41 (36%) cases for TERC were considered FISH-positive. MYC and TERC concurrent FISH-positive was observed in 12 cases (11%): 2 (17%) cases with gene amplification and 10 (83%) with high polysomy. By using the ROC analysis, high MYC (mean ≥2.83 copies/cell) and TERC (mean ≥2.65 copies/cell) GCNs were observed in 60 (53.1%) cases and 58 (51.3%) cases, respectively. High TERC GCN was associated with squamous cell carcinoma (SCC) histology (P = 0.001). In univariate analysis, increased MYC GCN was associated with shorter overall survival (P = 0.032 [UCCC criteria] or P = 0.02 [ROC classification]), whereas high TERC GCN showed no association. In multivariate analysis including stage and age, high MYC GCN remained significantly associated with worse overall survival using both the UCCC criteria (P = 0.02) and the ROC classification (P = 0.008). Conclusions Our results confirm MYC as frequently amplified in early-stage NSCLC and increased MYC GCN as a strong predictor of worse survival. Increased TERC GCN does not have prognostic impact but has strong association with squamous histology. PMID:25806711

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

PubMed

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

A comparison of ROC inferred from FROC and conventional ROC

NASA Astrophysics Data System (ADS)

McEntee, Mark F.; Littlefair, Stephen; Pietrzyk, Mariusz W.

2014-03-01

This study aims to determine whether receiver operating characteristic (ROC) scores inferred from free-response receiver operating characteristic (FROC) were equivalent to conventional ROC scores for the same readers and cases. Forty-five examining radiologists of the American Board of Radiology independently reviewed 47 PA chest radiographs under at least two conditions. Thirty-seven cases had abnormal findings and 10 cases had normal findings. Half the readers were asked to first locate any visualized lung nodules, mark them and assign a level of confidence [the FROC mark-rating pair] and second give an overall to the entire image on the same scale [the ROC score]. The second half of readers gave the ROC rating first followed by the FROC mark-rating pairs. A normal image was represented with number 1 and malignant lesions with numbers 2-5. A jackknife free-response receiver operating characteristic (JAFROC), and inferred ROC (infROC) was calculated from the mark-rating pairs using JAFROC V4.1 software. ROC based on the overall rating of the image calculated using DBM MRMC software, which was also used to compare infROC and ROC AUCs treating the methods as modalities. Pearson's correlations coefficient and linear regression were used to examine their relationship using SPSS, version 21.0; (SPSS, Chicago, IL). The results of this study showed no significant difference between the ROC and Inferred ROC AUCs (p≤0.25). While Pearson's correlation coefficient was 0.7 (p≤0.01). Inter-reader correlation calculated from Obuchowski- Rockette covariance's ranged from 0.43-0.86 while intra-reader agreement was greater than previously reported ranging from 0.68-0.82.

Magnetic Resonance Lymphography Findings in Patients With Biochemical Recurrence After Prostatectomy and the Relation With the Stephenson Nomogram

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meijer, Hanneke J.M., E-mail: H.Meijer@rther.umcn.nl; Debats, Oscar A.; Roach, Mack

2012-12-01

Purpose: To estimate the occurrence of positive lymph nodes on magnetic resonance lymphography (MRL) in patients with a prostate-specific antigen (PSA) recurrence after prostatectomy and to investigate the relation between score on the Stephenson nomogram and lymph node involvement on MRL. Methods and Materials: Sixty-five candidates for salvage radiation therapy were referred for an MRL to determine their lymph node status. Clinical and histopathologic features were recorded. For 49 patients, data were complete to calculate the Stephenson nomogram score. Receiver operating characteristic (ROC) analysis was performed to determine how well this nomogram related to the MRL result. Analysis was donemore » for the whole group and separately for patients with a PSA <1.0 ng/mL to determine the situation in candidates for early salvage radiation therapy, and for patients without pathologic lymph nodes at initial lymph node dissection. Results: MRL detected positive lymph nodes in 47 patients. ROC analysis for the Stephenson nomogram yielded an area under the curve (AUC) of 0.78 (95% confidence interval, 0.61-0.93). Of 29 patients with a PSA <1.0 ng/mL, 18 had a positive MRL. Of 37 patients without lymph node involvement at initial lymph node dissection, 25 had a positive MRL. ROC analysis for the Stephenson nomogram showed AUCs of 0.84 and 0.74, respectively, for these latter groups. Conclusion: MRL detected positive lymph nodes in 72% of candidates for salvage radiation therapy, in 62% of candidates for early salvage radiation therapy, and in 68% of initially node-negative patients. The Stephenson nomogram showed a good correlation with the MRL result and may thus be useful for identifying patients with a PSA recurrence who are at high risk for lymph node involvement.« less

Combining fibre optic Raman spectroscopy and tactile resonance measurement for tissue characterization

NASA Astrophysics Data System (ADS)

Candefjord, Stefan; Nyberg, Morgan; Jalkanen, Ville; Ramser, Kerstin; Lindahl, Olof A.

2010-12-01

Tissue characterization is fundamental for identification of pathological conditions. Raman spectroscopy (RS) and tactile resonance measurement (TRM) are two promising techniques that measure biochemical content and stiffness, respectively. They have potential to complement the golden standard--histological analysis. By combining RS and TRM, complementary information about tissue content can be obtained and specific drawbacks can be avoided. The aim of this study was to develop a multivariate approach to compare RS and TRM information. The approach was evaluated on measurements at the same points on porcine abdominal tissue. The measurement points were divided into five groups by multivariate analysis of the RS data. A regression analysis was performed and receiver operating characteristic (ROC) curves were used to compare the RS and TRM data. TRM identified one group efficiently (area under ROC curve 0.99). The RS data showed that the proportion of saturated fat was high in this group. The regression analysis showed that stiffness was mainly determined by the amount of fat and its composition. We concluded that RS provided additional, important information for tissue identification that was not provided by TRM alone. The results are promising for development of a method combining RS and TRM for intraoperative tissue characterization.

Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization.

PubMed

Lätti, Sakari; Niinivehmas, Sanna; Pentikäinen, Olli T

2016-01-01

Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also includes an automatic calculation of the AUC for the ROC curve and Boltzmann-enhanced discrimination of ROC (BEDROC). Furthermore, in virtual screening campaigns it is often important to understand the early enrichment of active ligand identification, for this Rocker offers automated calculation routine. To enable further development of Rocker, it is freely available (MIT-GPL license) for use and modifications from our web-site (http://www.jyu.fi/rocker).

Three-class ROC analysis--the equal error utility assumption and the optimality of three-class ROC surface using the ideal observer.

PubMed

He, Xin; Frey, Eric C

2006-08-01

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.

Experimental Design and Data Analysis in Receiver Operating Characteristic Studies: Lessons Learned from Reports in Radiology from 1997 to 20061

PubMed Central

Shiraishi, Junji; Pesce, Lorenzo L.; Metz, Charles E.; Doi, Kunio

2009-01-01

Purpose: To provide a broad perspective concerning the recent use of receiver operating characteristic (ROC) analysis in medical imaging by reviewing ROC studies published in Radiology between 1997 and 2006 for experimental design, imaging modality, medical condition, and ROC paradigm. Materials and Methods: Two hundred ninety-five studies were obtained by conducting a literature search with PubMed with two criteria: publication in Radiology between 1997 and 2006 and occurrence of the phrase “receiver operating characteristic.” Studies returned by the query that were not diagnostic imaging procedure performance evaluations were excluded. Characteristics of the remaining studies were tabulated. Results: Two hundred thirty-three (79.0%) of the 295 studies reported findings based on observers' diagnostic judgments or objective measurements. Forty-three (14.6%) did not include human observers, with most of these reporting an evaluation of a computer-aided diagnosis system or functional data obtained with computed tomography (CT) or magnetic resonance (MR) imaging. The remaining 19 (6.4%) studies were classified as reviews or meta-analyses and were excluded from our subsequent analysis. Among the various imaging modalities, MR imaging (46.0%) and CT (25.7%) were investigated most frequently. Approximately 60% (144 of 233) of ROC studies with human observers published in Radiology included three or fewer observers. Conclusion: ROC analysis is widely used in radiologic research, confirming its fundamental role in assessing diagnostic performance. However, the ROC studies reported in Radiology were not always adequate to support clear and clinically relevant conclusions. © RSNA, 2009 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.2533081632/-/DC1 PMID:19864510

Design of a receiver operating characteristic (ROC) study of 10:1 lossy image compression

NASA Astrophysics Data System (ADS)

Collins, Cary A.; Lane, David; Frank, Mark S.; Hardy, Michael E.; Haynor, David R.; Smith, Donald V.; Parker, James E.; Bender, Gregory N.; Kim, Yongmin

1994-04-01

The digital archiving system at Madigan Army Medical Center (MAMC) uses a 10:1 lossy data compression algorithm for most forms of computed radiography. A systematic study on the potential effect of lossy image compression on patient care has been initiated with a series of studies focused on specific diagnostic tasks. The studies are based upon the receiver operating characteristic (ROC) method of analysis for diagnostic systems. The null hypothesis is that observer performance with approximately 10:1 compressed and decompressed images is not different from using original, uncompressed images for detecting subtle pathologic findings seen on computed radiographs of bone, chest, or abdomen, when viewed on a high-resolution monitor. Our design involves collecting cases from eight pathologic categories. Truth is determined by committee using confirmatory studies performed during routine clinical practice whenever possible. Software has been developed to aid in case collection and to allow reading of the cases for the study using stand-alone Siemens Litebox workstations. Data analysis uses two methods, ROC analysis and free-response ROC (FROC) methods. This study will be one of the largest ROC/FROC studies of its kind and could benefit clinical radiology practice using PACS technology. The study design and results from a pilot FROC study are presented.

Anxiety and Depression Screening for Youth in a Primary Care Population

PubMed Central

Katon, Wayne; Joan, Russo; Richardson, Laura; McCauley, Elizabeth; Lozano, Paula

2008-01-01

Objective Prior studies have shown a low rate of accurate identification by primary care physicians of mental health disorders in youth. This study tested the psychometric properties of two brief mental health screening questionnaires, the Mood and Feelings Questionnaire – Short Form (MFQ-SF) and Childhood Anxiety Sensitivity Index (ASI), in a large sample of youth. Methods In a sample of 1375 youth age 11 to 17 (779 with asthma, 596 randomly selected controls) enrolled in an HMO, the psychometric properties (optimum cutoffs on Receiver Operating Curve (ROC) curves, sensitivity, specificity, positive and negative predictive values) of two brief anxiety and depression screens were examined versus a “gold standard” structured psychiatric interview. Results Both the MFQ-SF and ASI performed well on ROC analysis for screening youth for one or more DSM-IV anxiety or depressive disorders. The MFQ-SF performed better on ROC analysis than the ASI for youth with major depression (area under the curve of 0.84 vs 0.77). For screening youth with anxiety disorders ROC curves showed that both the MFQ-SF and ASI only performed in the fair range (area under the curve of 0.76). Conclusion The MFQ-SF and ASI are two relatively brief questionnaires that performed well for screening youth for one or more DSM-IV anxiety or depressive disorders. The MFQ-SF performed better than the ASI for screening youth with major depression. Use of these instruments could increase the accuracy of identification of mental health disorders in youth by primary care physicians. PMID:18501865

Validating the Injury Severity Score (ISS) in different populations: ISS predicts mortality better among Hispanics and females.

PubMed

Bolorunduro, O B; Villegas, C; Oyetunji, T A; Haut, E R; Stevens, K A; Chang, D C; Cornwell, E E; Efron, D T; Haider, A H

2011-03-01

The Injury Severity Score (ISS) is the most commonly used measure of injury severity. The score has been shown to have excellent predictive capability for trauma mortality and has been validated in multiple data sets. However, the score has never been tested to see if its discriminatory ability is affected by differences in race and gender. This study is aimed at validating the ISS in men and women and in three different race/ethnic groups using a nationwide database. Retrospective analysis of patients age 18-64 y in the National Trauma Data Bank 7.0 with blunt trauma was performed. ISS was categorized as mild (<9,) moderate (9-15), severe (16-25), and profound (>25). Logistic regression was done to measure the relative odds of mortality associated with a change in ISS categories. The discriminatory ability was compared using the receiver operating characteristics curves (ROC). A P value testing the equality of the ROC curves was calculated. Age stratified analyses were also conducted. A total of 872,102 patients had complete data for the analysis on ethnicity, while 763,549 patients were included in the gender analysis. The overall mortality rate was 3.7%. ROC in Whites was 0.8617, in Blacks 0.8586, and in Hispanics 0.8869. Hispanics have a statistically significant higher ROC (P value < 0.001). Similar results were observed within each age category. ROC curves were also significantly higher in females than in males. The ISS possesses excellent discriminatory ability in all populations as indicated by the high ROCs. Copyright © 2011 Elsevier Inc. All rights reserved.

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change.

PubMed

Cappon, Giacomo; Marturano, Francesca; Vettoretti, Martina; Facchinetti, Andrea; Sparacino, Giovanni

2018-05-01

The standard formula (SF) used in bolus calculators (BCs) determines meal insulin bolus using "static" measurement of blood glucose concentration (BG) obtained by self-monitoring of blood glucose (SMBG) fingerprick device. Some methods have been proposed to improve efficacy of SF using "dynamic" information provided by continuous glucose monitoring (CGM), and, in particular, glucose rate of change (ROC). This article compares, in silico and in an ideal framework limiting the exposition to possibly confounding factors (such as CGM noise), the performance of three popular techniques devised for such a scope, that is, the methods of Buckingham et al (BU), Scheiner (SC), and Pettus and Edelman (PE). Using the UVa/Padova Type 1 diabetes simulator we generated data of 100 virtual subjects in noise-free, single-meal scenarios having different preprandial BG and ROC values. Meal insulin bolus was computed using SF, BU, SC, and PE. Performance was assessed with the blood glucose risk index (BGRI) on the 9 hours after meal. On average, BU, SC, and PE improve BGRI compared to SF. When BG is rapidly decreasing, PE obtains the best performance. In the other ROC scenarios, none of the considered methods prevails in all the preprandial BG conditions tested. Our study showed that, at least in the considered ideal framework, none of the methods to correct SF according to ROC is globally better than the others. Critical analysis of the results also suggests that further investigations are needed to develop more effective formulas to account for ROC information in BCs.

Turbidity of mouthrinsed water as a screening index for oral malodor.

PubMed

Ueno, Masayuki; Takeuchi, Susumu; Samnieng, Patcharaphol; Morishima, Seiji; Shinada, Kayoko; Kawaguchi, Yoko

2013-08-01

The objectives of this research were to examine the relationship between turbidity of mouthrinsed water and oral malodor, and to evaluate whether the turbidity could be used to screen oral malodor. The subjects were 165 oral malodor patients. Gas chromatography and organoleptic test (OT) were used for oral malodor measurement. Oral examination along with collection of saliva and quantification of bacteria was conducted. Turbidity of mouthrinsed water was measured with turbidimeter. Logistic regression with oral malodor status by OT as the dependent variable and receiver operating characteristic (ROC) analysis were performed. Turbidity had a significant association with oral malodor status. In addition, ROC analysis showed that the turbidity had an ability to screen for presence or absence of oral malodor. Turbidity could reflect or represent other influential variables of oral malodor and may be useful as a screening method for oral malodor. Copyright © 2013 Elsevier Inc. All rights reserved.

bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests.

PubMed

To Duc, Khanh

2017-11-18

Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias-corrected inference tools are required. This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias-corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. bcROCsurface may become an important tool for the statistical evaluation of three-class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .

Simultaneous detection of antibodies to five Actinobacillus pleuropneumoniae serovars using bead-based multiplex analysis.

PubMed

Berger, Sanne Schou; Lauritsen, Klara Tølbøll; Boas, Ulrik; Lind, Peter; Andresen, Lars Ole

2017-11-01

We developed and made a preliminary validation of a bead-based multiplexed immunoassay for simultaneous detection of porcine serum antibodies to Actinobacillus pleuropneumoniae serovars 1, 2, 6, 7, and 12. Magnetic fluorescent beads were coupled with A. pleuropneumoniae antigens and tested with a panel of serum samples from experimentally infected pigs and with serum samples from uninfected and naturally infected pigs. The multiplex assay was compared to in-house ELISAs and complement fixation (CF) tests, which have been used for decades as tools for herd classification in the Danish Specific Pathogen Free system. Assay specificities and sensitivities as well as the corresponding cutoff values were determined using receiver operating characteristic (ROC) curve analysis, and the A. pleuropneumoniae multiplex assay showed good correlation with the in-house ELISAs and CF tests with areas under ROC curves ≥ 0.988. Benefits of multiplexed assays compared to ELISAs and CF tests include reduced serum sample volumes needed for analysis, less labor, and shorter assay time.

Initial Validation of a Comprehensive Assessment Instrument for Bereavement-Related Grief Symptoms and Risk of Complications: The Indicator of Bereavement Adaptation—Cruse Scotland (IBACS)

PubMed Central

Schut, Henk; Stroebe, Margaret S.; Wilson, Stewart; Birrell, John

2016-01-01

Objective This study assessed the validity of the Indicator of Bereavement Adaptation Cruse Scotland (IBACS). Designed for use in clinical and non-clinical settings, the IBACS measures severity of grief symptoms and risk of developing complications. Method N = 196 (44 male, 152 female) help-seeking, bereaved Scottish adults participated at two timepoints: T1 (baseline) and T2 (after 18 months). Four validated assessment instruments were administered: CORE-R, ICG-R, IES-R, SCL-90-R. Discriminative ability was assessed using ROC curve analysis. Concurrent validity was tested through correlation analysis at T1. Predictive validity was assessed using correlation analyses and ROC curve analysis. Optimal IBACS cutoff values were obtained by calculating a maximal Youden index J in ROC curve analysis. Clinical implications were compared across instruments. Results ROC curve analysis results (AUC = .84, p < .01, 95% CI between .77 and .90) indicated the IBACS is a good diagnostic instrument for assessing complicated grief. Positive correlations (p < .01, 2-tailed) with all four instruments at T1 demonstrated the IBACS' concurrent validity, strongest with complicated grief measures (r = .82). Predictive validity was shown to be fair in T2 ROC curve analysis results (n = 67, AUC = .78, 95% CI between .65 and .92; p < .01). Predictive validity was also supported by stable positive correlations between IBACS and other instruments at T2. Clinical indications were found not to differ across instruments. Conclusions The IBACS offers effective grief symptom and risk assessment for use by non-clinicians. Indications are sufficient to support intake assessment for a stepped model of bereavement intervention. PMID:27741246

Impact of FIB-4 index on hepatocellular carcinoma incidence during nucleos(t)ide analogue therapy in patients with chronic hepatitis B: An analysis using time-dependent receiver operating characteristic.

PubMed

Tada, Toshifumi; Kumada, Takashi; Toyoda, Hidenori; Tsuji, Kunihiko; Hiraoka, Atsushi; Tanaka, Junko

2017-02-01

Nucleos(t)ide analogue (NA) therapy has been reported to reduce the risk of hepatocellular carcinoma (HCC) development in patients with chronic hepatitis B (CHB). However, even during NA therapy, development of HCC has been observed in patients with CHB. Therefore, we clarified the predictive power of clinical factors for HCC incidence using receiver operating characteristic (ROC) analysis that takes time dependence into account. A total of 539 patients with CHB treated with NAs were enrolled. Univariate, multivariate, and time-dependent ROC curves for clinical factors associated with the development of HCC were analyzed. Eighty-one patients developed HCC during the follow-up period (median duration, 5.9 years). α-fetoprotein (AFP) and FIB-4 index at 24 weeks from the initiation of treatment and sex were significantly associated with HCC incidence according to the log-rank test. Cox proportional hazards models including the covariates of sex, hepatitis B genotype, basal core promoter mutations, AFP at 24 weeks, and FIB-4 index at 24 weeks showed that FIB-4 index >2.65 (HR, 5.03; 95% CI, 3.06-8.26; P < 0.001) and male sex were independently associated with HCC incidence. In addition, time-dependent ROC analysis showed that compared with AFP at 24 weeks, FIB-4 index at 24 weeks had higher predictive power for HCC incidence throughout the follow-up period. Elevated FIB-4 index at 24 weeks in patients with CHB receiving NA therapy is a risk factor for developing HCC. The FIB-4 index is an excellent predictor of HCC development. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Voice-onset time and buzz-onset time identification: A ROC analysis

NASA Astrophysics Data System (ADS)

Lopez-Bascuas, Luis E.; Rosner, Burton S.; Garcia-Albea, Jose E.

2004-05-01

Previous studies have employed signal detection theory to analyze data from speech and nonspeech experiments. Typically, signal distributions were assumed to be Gaussian. Schouten and van Hessen [J. Acoust. Soc. Am. 104, 2980-2990 (1998)] explicitly tested this assumption for an intensity continuum and a speech continuum. They measured response distributions directly and, assuming an interval scale, concluded that the Gaussian assumption held for both continua. However, Pastore and Macmillan [J. Acoust. Soc. Am. 111, 2432 (2002)] applied ROC analysis to Schouten and van Hessen's data, assuming only an ordinal scale. Their ROC curves suppported the Gaussian assumption for the nonspeech signals only. Previously, Lopez-Bascuas [Proc. Audit. Bas. Speech Percept., 158-161 (1997)] found evidence with a rating scale procedure that the Gaussian model was inadequate for a voice-onset time continuum but not for a noise-buzz continuum. Both continua contained ten stimuli with asynchronies ranging from -35 ms to +55 ms. ROC curves (double-probability plots) are now reported for each pair of adjacent stimuli on the two continua. Both speech and nonspeech ROCs often appeared nonlinear, indicating non-Gaussian signal distributions under the usual zero-variance assumption for response criteria.

Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models

PubMed Central

Hillis, Stephen L.

2015-01-01

A basic assumption for a meaningful diagnostic decision variable is that there is a monotone relationship between it and its likelihood ratio. This relationship, however, generally does not hold for a decision variable that results in a binormal ROC curve. As a result, receiver operating characteristic (ROC) curve estimation based on the assumption of a binormal ROC-curve model produces improper ROC curves that have “hooks,” are not concave over the entire domain, and cross the chance line. Although in practice this “improperness” is usually not noticeable, sometimes it is evident and problematic. To avoid this problem, Metz and Pan proposed basing ROC-curve estimation on the assumption of a binormal likelihood-ratio (binormal-LR) model, which states that the decision variable is an increasing transformation of the likelihood-ratio function of a random variable having normal conditional diseased and nondiseased distributions. However, their development is not easy to follow. I show that the binormal-LR model is equivalent to a bi-chi-squared model in the sense that the families of corresponding ROC curves are the same. The bi-chi-squared formulation provides an easier-to-follow development of the binormal-LR ROC curve and its properties in terms of well-known distributions. PMID:26608405

Recent developments in imaging system assessment methodology, FROC analysis and the search model.

PubMed

Chakraborty, Dev P

2011-08-21

A frequent problem in imaging is assessing whether a new imaging system is an improvement over an existing standard. Observer performance methods, in particular the receiver operating characteristic (ROC) paradigm, are widely used in this context. In ROC analysis lesion location information is not used and consequently scoring ambiguities can arise in tasks, such as nodule detection, involving finding localized lesions. This paper reviews progress in the free-response ROC (FROC) paradigm in which the observer marks and rates suspicious regions and the location information is used to determine whether lesions were correctly localized. Reviewed are FROC data analysis, a search-model for simulating FROC data, predictions of the model and a method for estimating the parameters. The search model parameters are physically meaningful quantities that can guide system optimization.

Mycobacterium tuberculosis Is a Natural Ornithine Aminotransferase (rocD) Mutant and Depends on Rv2323c for Growth on Arginine

PubMed Central

Hampel, Annegret; Huber, Claudia; Geffers, Robert; Spona-Friedl, Marina; Eisenreich, Wolfgang; Bange, Franz-Christoph

2015-01-01

Mycobacterium tuberculosis (Mtb) possesses a genetic repertoire for metabolic pathways, which are specific and fit to its intracellular life style. Under in vitro conditions, Mtb is known to use arginine as a nitrogen source, but the metabolic pathways for arginine utilization have not been identified. Here we show that, in the presence of arginine, Mtb upregulates a gene cluster which includes an ornithine aminotransferase (rocD) and Rv2323c, a gene of unknown function. Isotopologue analysis by using 13C- or 15N-arginine revealed that in Mtb arginine is not only used as nitrogen source but also as carbon source for the formation of amino acids, in particular of proline. Surprisingly, rocD, which is widespread in other bacteria and is part of the classical arginase pathway turned out to be naturally deleted in Mtb, but not in non-tuberculous mycobacteria. Mtb lacking Rv2323c showed a growth defect on arginine, did not produce proline from arginine, and incorporated less nitrogen derived from arginine in its core nitrogen metabolism. We conclude that the highly induced pathway for arginine utilization in Mtb differs from that of other bacteria including non-tuberculous mycobacteria, probably reflecting a specific metabolic feature of intracellular Mtb. PMID:26368558

Corneal Structural Changes in Nonneoplastic and Neoplastic Monoclonal Gammopathies.

PubMed

Aragona, Pasquale; Allegra, Alessandro; Postorino, Elisa Imelde; Rania, Laura; Innao, Vanessa; Wylegala, Edward; Nowinska, Anna; Ieni, Antonio; Pisani, Antonina; Musolino, Caterina; Puzzolo, Domenico; Micali, Antonio

2016-05-01

To investigate corneal confocal microscopic changes in nonneoplastic and neoplastic monoclonal gammopathies. Three groups of subjects were considered: group 1, twenty normal subjects; group 2, fifteen patients with monoclonal gammopathy of undetermined significance (MGUS); group 3, eight patients with smoldering multiple myeloma and eight patients with untreated multiple myeloma. After hematologic diagnosis, patients underwent ophthalmologic exam and in vivo confocal microscopic study. The statistical analysis was performed using ANOVA and Student-Newman-Keuls tests and receiver operating characteristic (ROC) curve analysis. Epithelial cells of gammopathic patients showed significantly higher reflectivity than controls, demonstrated by optical density (P < 0.001). Subbasal nerve density, branching, and beading were significantly altered in gammopathic patients (P = 0.01, P = 0.02, P = 0.02, respectively). The number of keratocytes was significantly reduced in neoplastic patients (P < 0.001 versus both normal and MGUS) in the anterior, medium, and posterior stroma. The ROC curve analysis showed good sensitivity and specificity for this parameter. Group 2 and 3 keratocytes showed higher nuclear and cytoplasmatic reflectivity in the medium and posterior stroma. Endothelial cells were not affected. Patients with neoplastic gammopathies showed peculiar alterations of the keratocyte number, which appeared significantly reduced. A follow-up with corneal confocal microscopy of patients with MGUS is suggested as a useful tool to identify peripheral tissue alterations linked to possible neoplastic disease development.

Rollover Car Crashes with Ejection: A Deadly Combination—An Analysis of 719 Patients

PubMed Central

Latifi, Rifat; El-Menyar, Ayman; El-Hennawy, Hany; Al-Thani, Hassan

2014-01-01

Rollover car crashes (ROCs) are serious public safety concerns worldwide. Objective. To determine the incidence and outcomes of ROCs with or without ejection of occupants in the State of Qatar. Methods. A retrospective study of all patients involved in ROCs admitted to Level I trauma center in Qatar (2011-2012). Patients were divided into Group I (ROC with ejection) and Group II (ROC without ejection). Results. A total of 719 patients were evaluated (237 in Group I and 482 in Group II). The mean age in Group I was lower than in Group II (24.3 ± 10.3 versus 29 ± 12.2; P = 0.001). Group I had higher injury severity score and sustained significantly more head, chest, and abdominal injuries in comparison to Group II. The mortality rate was higher in Group I (25% versus 7%; P = 0.001). Group I patients required higher ICU admission rate (P = 0.001). Patients in Group I had a 5-fold increased risk for age-adjusted mortality (OR 5.43; 95% CI 3.11–9.49), P = 0.001). Conclusion. ROCs with ejection are associated with higher rate of morbidity and mortality compared to ROCs without ejection. As an increased number of young Qatari males sustain ROCs with ejection, these findings highlight the need for research-based injury prevention initiatives in the country. PMID:24693231

Ultra-short screening instruments for major depressive episode and generalized anxiety disorder in epilepsy: The NDDIE-2 and the GAD-SI.

PubMed

Micoulaud-Franchi, Jean-Arthur; Bartolomei, Fabrice; McGonigal, Aileen

2017-03-01

Systematic screening is recommended for major depressive episode (MDE) with the Neurological Disorders Depression Inventory for Epilepsy NDDI-E, 6 items and generalized anxiety disorder (GAD) with the GAD 7 items in patients with epilepsy (PWE). Shorter versions of the NDDI-E and the GAD-7 could facilitate increased screening by busy clinicians and be more accessible to patients with mild cognitive and/or language impairments. The effectiveness of ultra-short versions of the NDDI-E (2 items) and the GAD-7 (the GAD-2, 2 items, and the GAD-SI with a single item) in comparison with the original versions were statistically tested using ROC analysis. ROC analysis of the NDDIE-2 showed an AUC of 0.926 (p<0.001), a sensitivity of 81.82% and a specificity of 89.16%, without significant difference with the NDDI-E (z=1.582, p=0.11). ROC analysis of the GAD-SI showed an AUC of 0.872 (p<0.001), a sensitivity of 83.67% and a specificity of 82.29%, without significant difference with the GAD-7 (z=1.281, p=0.2). The GAD-2 showed poorer psychometric properties. The limitation is the use of data from previously reported subjects in a single language version, the NDDIE-2 that lacks detection of dysphoric symptoms in comparison with the NDDIE-6 and the GAD-SI that exhibited a more than 10% lower sensitivity than the GAD-7. This study highlights the potential utility of the NDDIE-2 and the GAD-SI as ultra-short screening tools for MDE and GAD respectively in PWE. Further studies in a larger population, including multi-lingual versions, could be a valuable next step. However, the brevity and simplicity of this tool could be an advantage in PWE who present cognitive difficulties, especially attentional or language deficits. Copyright © 2017 Elsevier B.V. All rights reserved.

Corrected ROC analysis for misclassified binary outcomes.

PubMed

Zawistowski, Matthew; Sussman, Jeremy B; Hofer, Timothy P; Bentley, Douglas; Hayward, Rodney A; Wiitala, Wyndy L

2017-06-15

Creating accurate risk prediction models from Big Data resources such as Electronic Health Records (EHRs) is a critical step toward achieving precision medicine. A major challenge in developing these tools is accounting for imperfect aspects of EHR data, particularly the potential for misclassified outcomes. Misclassification, the swapping of case and control outcome labels, is well known to bias effect size estimates for regression prediction models. In this paper, we study the effect of misclassification on accuracy assessment for risk prediction models and find that it leads to bias in the area under the curve (AUC) metric from standard ROC analysis. The extent of the bias is determined by the false positive and false negative misclassification rates as well as disease prevalence. Notably, we show that simply correcting for misclassification while building the prediction model is not sufficient to remove the bias in AUC. We therefore introduce an intuitive misclassification-adjusted ROC procedure that accounts for uncertainty in observed outcomes and produces bias-corrected estimates of the true AUC. The method requires that misclassification rates are either known or can be estimated, quantities typically required for the modeling step. The computational simplicity of our method is a key advantage, making it ideal for efficiently comparing multiple prediction models on very large datasets. Finally, we apply the correction method to a hospitalization prediction model from a cohort of over 1 million patients from the Veterans Health Administrations EHR. Implementations of the ROC correction are provided for Stata and R. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Detection of common carotid artery stenosis using duplex ultrasonography: a validation study with computed tomographic angiography.

PubMed

Slovut, David P; Romero, Javier M; Hannon, Kathleen M; Dick, James; Jaff, Michael R

2010-01-01

Severe stenosis of the common carotid artery (CCA), while uncommon, is associated with increased risk of transient ischemic attack and stroke. To date, no validated duplex ultrasound criteria have been established for grading the severity of CCA stenosis. The goal of this study was to use receiver-operating curve (ROC) analysis with computed tomographic angiography as the reference standard to establish duplex ultrasound criteria for diagnosing >or=50% CCA stenosis. The study cohort included 64 patients (42 men, 22 women) with a mean age of 65 +/- 12 years (range, 16-89 years) who had CCA peak systolic velocity (PSV) >or=150 cm/sec and underwent computed tomographic angiography (CTA) of the cervical and intracerebral vessels within 1 month of the duplex examination. One study was excluded because the CTA was technically inadequate, whereas another was excluded because the patient underwent bilateral CCA stenting. The CCA ipsilateral to any of the following was excluded from the analysis: innominate artery occlusion (n = 1), previous stenting of the ICA or CCA (n = 7), carotid endarterectomy (n = 1), or carotid-to-carotid bypass (n = 1). Thus, the data set included 62 patients and 115 vessels. Bland-Altman analysis was used to examine the agreement between two measures of luminal reduction measured by CTA: percent diameter stenosis and percent area stenosis. Receiver operating characteristic (ROC) analysis was used to determine optimal PSV and EDV thresholds for diagnosing >or=50% CCA stenosis. Severity of CCA stenosis was <50% in 76 vessels, 50%-59% in eight, 60%-69% in eight, 70%-79% in nine, 80%-89% in three, 90%-99% in five, and occluded in six. Duplex ultrasonography identified six of six (100%) patients with 100% CCA occlusion by CTA. Bland-Altman analysis showed poor agreement between percent stenosis determined by vessel diameter compared with percent stenosis determined by reduction in lumen area. Therefore, subsequent analysis was performed using percent stenosis by area. ROC analysis of different PSV thresholds for detecting stenosis >or=50% showed that >182 cm/sec was the most accurate with a sensitivity of 64% and specificity of 88% (P < .0001). Sensitivity, specificity, and accuracy of carotid duplex were higher when the stenosis was located in the mid or distal aspects of the CCA (sensitivity 76%, specificity 89%, area under curve 0.84, P < .001) than in the intrathoracic and proximal segment of the artery (P = NS). ROC analysis of different EDV thresholds for detecting CCA stenosis >or=50% showed that >30 cm/sec was the most accurate with a sensitivity of 54% and a specificity of 74% (P < .0239). Duplex ultrasonography is highly sensitive, specific, and accurate for detecting CCA lesions in the mid and distal CCA. Use of peak systolic velocity may lead to improved detection of CCA disease and initiation of appropriate therapy to reduce the risk of stroke. Copyright 2010 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.

2014-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.1 PMID:25395692

Optimizing area under the ROC curve using semi-supervised learning.

PubMed

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Clinical diagnostic accuracy of acute colonic diverticulitis in patients admitted with acute abdominal pain, a receiver operating characteristic curve analysis.

PubMed

Jamal Talabani, A; Endreseth, B H; Lydersen, S; Edna, T-H

2017-01-01

The study investigated the capability of clinical findings, temperature, C-reactive protein (CRP), and white blood cell (WBC) count to discern patients with acute colonic diverticulitis from all other patients admitted with acute abdominal pain. The probability of acute diverticulitis was assessed by the examining doctor, using a scale from 0 (zero probability) to 10 (100 % probability). Receiver operating characteristic (ROC) curves were used to assess the clinical diagnostic accuracy of acute colonic diverticulitis in patients admitted with acute abdominal pain. Of 833 patients admitted with acute abdominal pain, 95 had acute colonic diverticulitis. ROC curve analysis gave an area under the ROC curve (AUC) of 0.95 (CI 0.92 to 0.97) for ages <65 years, AUC = 0.86 (CI 0.78 to 0.93) in older patients. Separate analysis showed an AUC = 0.83 (CI 0.80 to 0.86) of CRP alone. White blood cell count and temperature were almost useless to discriminate acute colonic diverticulitis from other types of acute abdominal pain, AUC = 0.59 (CI 0.53 to 0.65) for white blood cell count and AUC = 0.57 (0.50 to 0.63) for temperature, respectively. This prospective study demonstrates that standard clinical evaluation by non-specialist doctors based on history, physical examination, and initial blood tests on admission provides a high degree of diagnostic precision in patients with acute colonic diverticulitis.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PubMed

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

Analytical and clinical performance of thyroglobulin autoantibody assays in thyroid cancer follow-up.

PubMed

Katrangi, Waddah; Grebe, Stephan K G; Algeciras-Schimnich, Alicia

2017-10-26

While thyroglobulin autoantibodies (TgAb) can result in false low serum thyroglobulin (Tg) immunoassay (IA) measurements, they might also be indicators of disease persistence/recurrence. Hence, accurate TgAb measurement, in addition to Tg quantification, is crucial for thyroid cancer monitoring. We compared the analytical and clinical performance of four commonly used TgAb IAs. We measured Tg by mass spectrometry (Tg-MS) and by four pairs of Tg and TgAb IAs (Beckman, Roche, Siemens, Thermo) in 576 samples. Limit of quantitation (LOQ) and manufacturers' upper reference interval cut-off (URI) were used for comparisons. Clinical performance was assessed by receiving operator characteristics (ROC) curve analysis. Quantitative and qualitative agreement between TgAb-IAs was moderate with R2 of 0.20-0.70 and κ from 0.41-0.66 using LOQ and 0.47-0.71 using URI. In samples with TgAb interference, detection rates of TgAb were similar using LOQ and URI for Beckman, Siemens, and Thermo, but much lower for the Roche TgAb-IA when the URI was used. In TgAb positive cases, the ROC areas under the curve (AUC) for the TgAb-IAs were 0.59 (Beckman), 0.62 (Siemens), 0.59 (Roche), and 0.59 (Thermo), similar to ROC AUCs achieved with Tg. Combining Tg and TgAb measurements improved the ROC AUCs compared to Tg or TgAb alone. TgAb-IAs show significant qualitative and quantitative differences. For 2 of the 4 TgAb-IAs, using the LOQ improves the detection of interfering TgAbs. All assays showed suboptimal clinical performance when used as surrogate markers of disease, with modest improvements when Tg and TgAb were combined.

Do We Know Who Will Drop out?: A Review of the Predictors of Dropping out of High School--Precision, Sensitivity, and Specificity

ERIC Educational Resources Information Center

Bowers, Alex J.; Sprott, Ryan; Taff, Sherry A.

2013-01-01

The purpose of this study is to review the literature on the most accurate indicators of students at risk of dropping out of high school. We used Relative Operating Characteristic (ROC) analysis to compare the sensitivity and specificity of 110 dropout flags across 36 studies. Our results indicate that 1) ROC analysis provides a means to compare…

Wavelet and receiver operating characteristic analysis of heart rate variability

NASA Astrophysics Data System (ADS)

McCaffery, G.; Griffith, T. M.; Naka, K.; Frennaux, M. P.; Matthai, C. C.

2002-02-01

Multiresolution wavelet analysis has been used to study the heart rate variability in two classes of patients with different pathological conditions. The scale dependent measure of Thurner et al. was found to be statistically significant in discriminating patients suffering from hypercardiomyopathy from a control set of normal subjects. We have performed Receiver Operating Characteristc (ROC) analysis and found the ROC area to be a useful measure by which to label the significance of the discrimination, as well as to describe the severity of heart dysfunction.

Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results.

PubMed

Sagiyama, Koji; Watanabe, Yuji; Kamei, Ryotaro; Hong, Sungtak; Kawanami, Satoshi; Matsumoto, Yoshihiro; Honda, Hiroshi

2017-12-01

To investigate the usefulness of voxel-based analysis of standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs) for evaluating soft-tissue tumour malignancy with a PET/MR system. Thirty-five subjects with either ten low/intermediate-grade tumours or 25 high-grade tumours were prospectively enrolled. Zoomed diffusion-weighted and fluorodeoxyglucose ( 18 FDG)-PET images were acquired along with fat-suppressed T2-weighted images (FST2WIs). Regions of interest (ROIs) were drawn on FST2WIs including the tumour in all slices. ROIs were pasted onto PET and ADC-maps to measure SUVs and ADCs within tumour ROIs. Tumour volume, SUVmax, ADCminimum, the heterogeneity and the correlation coefficients of SUV and ADC were recorded. The parameters of high- and low/intermediate-grade groups were compared, and receiver operating characteristic (ROC) analysis was also performed. The mean correlation coefficient for SUV and ADC in high-grade sarcomas was lower than that of low/intermediate-grade tumours (-0.41 ± 0.25 vs. -0.08 ± 0.34, P < 0.01). Other parameters did not differ significantly. ROC analysis demonstrated that correlation coefficient showed the best diagnostic performance for differentiating the two groups (AUC 0.79, sensitivity 96.0%, specificity 60%, accuracy 85.7%). SUV and ADC determined via PET/MR may be useful for differentiating between high-grade and low/intermediate-grade soft tissue tumours. • PET/MR allows voxel-based comparison of SUVs and ADCs in soft-tissue tumours. • A comprehensive assessment of internal heterogeneity was performed with scatter plots. • SUVmax or ADCminimum could not differentiate high-grade sarcoma from low/intermediate-grade tumours. • Only the correlation coefficient between SUV and ADC differentiated the two groups. • The correlation coefficient showed the best diagnostic performance by ROC analysis.

Ratio of urine and blood urea nitrogen concentration predicts the response of tolvaptan in congestive heart failure.

PubMed

Shimizu, Keisuke; Doi, Kent; Imamura, Teruhiko; Noiri, Eisei; Yahagi, Naoki; Nangaku, Masaomi; Kinugawa, Koichiro

2015-06-01

This study was conducted to evaluate the performance of the ratio of urine and blood urea nitrogen concentration (UUN/BUN) as a new predictive factor for the response of an arginine vasopressin receptor 2 antagonist tolvaptan (TLV) in decompensated heart failure patients. This study enrolled 70 decompensated heart failure patients who were administered TLV at University of Tokyo Hospital. We collected the data of clinical parameters including UUN/BUN before administering TLV. Two different outcomes were defined as follows: having over 300 mL increase in urine volume on the first day (immediate urine output response) and having any decrease in body weight within one week after starting TLV treatment (subsequent clinical response). Among the 70 enrolled patients, 37 patients (52.9%) showed immediate urine output response; 51 patients (72.9%) showed a subsequent clinical response of body weight decrease. Receiver operating characteristics (ROC) analysis showed good prediction by UUN/BUN for the immediate response (AUC-ROC 0.86 [0.75-0.93]) and a significantly better prediction by UUN/BUN for the subsequent clinical response compared with urinary osmolality (AUC-ROC 0.78 [0.63-0.88] vs. 0.68 [0.52-0.80], P < 0.05). We demonstrated that a clinical parameter of UUN/BUN can predict the response of TLV even when measured before TLV administration. UUN/BUN might enable identification of good responders for this new drug. © 2015 Asian Pacific Society of Nephrology.

Development and testing of new candidate psoriatic arthritis screening questionnaires combining optimal questions from existing tools.

PubMed

Coates, Laura C; Walsh, Jessica; Haroon, Muhammad; FitzGerald, Oliver; Aslam, Tariq; Al Balushi, Farida; Burden, A D; Burden-Teh, Esther; Caperon, Anna R; Cerio, Rino; Chattopadhyay, Chandrabhusan; Chinoy, Hector; Goodfield, Mark J D; Kay, Lesley; Kelly, Stephen; Kirkham, Bruce W; Lovell, Christopher R; Marzo-Ortega, Helena; McHugh, Neil; Murphy, Ruth; Reynolds, Nick J; Smith, Catherine H; Stewart, Elizabeth J C; Warren, Richard B; Waxman, Robin; Wilson, Hilary E; Helliwell, Philip S

2014-09-01

Several questionnaires have been developed to screen for psoriatic arthritis (PsA), but head-to-head studies have found limitations. This study aimed to develop new questionnaires encompassing the most discriminative questions from existing instruments. Data from the CONTEST study, a head-to-head comparison of 3 existing questionnaires, were used to identify items with a Youden index score of ≥0.1. These were combined using 4 approaches: CONTEST (simple additions of questions), CONTESTw (weighting using logistic regression), CONTESTjt (addition of a joint manikin), and CONTESTtree (additional questions identified by classification and regression tree [CART] analysis). These candidate questionnaires were tested in independent data sets. Twelve individual questions with a Youden index score of ≥0.1 were identified, but 4 of these were excluded due to duplication and redundancy. Weighting for 2 of these questions was included in CONTESTw. Receiver operating characteristic (ROC) curve analysis showed that involvement in 6 joint areas on the manikin was predictive of PsA for inclusion in CONTESTjt. CART analysis identified a further 5 questions for inclusion in CONTESTtree. CONTESTtree was not significant on ROC curve analysis and discarded. The other 3 questionnaires were significant in all data sets, although CONTESTw was slightly inferior to the others in the validation data sets. Potential cut points for referral were also discussed. Of 4 candidate questionnaires combining existing discriminatory items to identify PsA in people with psoriasis, 3 were found to be significant on ROC curve analysis. Testing in independent data sets identified 2 questionnaires (CONTEST and CONTESTjt) that should be pursued for further prospective testing. Copyright © 2014 by the American College of Rheumatology.

Effect of Combined 68Ga-PSMAHBED-CC Uptake Pattern and Multiparametric MRI Derived With Simultaneous PET/MRI in the Diagnosis of Primary Prostate Cancer: Initial Experience.

PubMed

Taneja, Sangeeta; Jena, Amarnath; Taneja, Rajesh; Singh, Aru; Ahuja, Aashim

2018-06-01

The purpose of this study is to assess whether temporal changes in 68 Ga-prostate-specific membrane antigen (PSMA)-HBED-CC uptake and multiparametric MRI parameters derived using PET/MRI can aid in characterization of benign and malignant prostate lesions. Thirty-five men with 29 malignant and six benign prostate lesions undergoing complete clinical workup including histologic analysis were enrolled for this retrospective study. All had undergone simultaneous whole-body 68 Ga-PSMAHBED-CC PET/MRI. Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) assessment was made using a 5-point scale showing the likelihood of cancer with the combination of multiparametric MRI findings. Gallium-68-PSMA uptake was recorded at two time points: early (7 minutes) and delayed (54 minutes), adopting a copy-and-paste function of the ROI defined on MR images. ROC curve analysis was performed to test the diagnostic accuracy of early versus delayed PSMA uptake (measured as maximum standardized uptake value [SUV]). A multiple-ROI analysis was done to obtain ROCs for combined PET SUV and multiparametric MRI datasets. Spearman analysis was performed to assess the correlations. There was a significant difference between early and delayed PSMA uptake in malignant prostatic lesions (p < 0.01), which was able to characterize prostate lesions with an AUC of 0.83 and 0.94. Combined ROC analysis of PI-RADSv2 category derived from multiparametric MRI and differential PSMA uptake in characterizing prostatic lesions improved the AUC to 0.99. Dual-phase PSMA uptake improves accuracy of classifying malignant versus benign prostate lesions and complements multiparametric MRI in the diagnosis of prostate cancer.

Revisiting the Roco G-protein cycle.

PubMed

Terheyden, Susanne; Ho, Franz Y; Gilsbach, Bernd K; Wittinghofer, Alfred; Kortholt, Arjan

2015-01-01

Mutations in leucine-rich-repeat kinase 2 (LRRK2) are the most frequent cause of late-onset Parkinson's disease (PD). LRRK2 belongs to the Roco family of proteins which share a conserved Ras-like G-domain (Roc) and a C-terminal of Roc (COR) domain tandem. The nucleotide state of small G-proteins is strictly controlled by guanine-nucleotide-exchange factors (GEFs) and GTPase-activating proteins (GAPs). Because of contradictory structural and biochemical data, the regulatory mechanism of the LRRK2 Roc G-domain and the RocCOR tandem is still under debate. In the present study, we solved the first nucleotide-bound Roc structure and used LRRK2 and bacterial Roco proteins to characterize the RocCOR function in more detail. Nucleotide binding induces a drastic structural change in the Roc/COR domain interface, a region strongly implicated in patients with an LRRK2 mutation. Our data confirm previous assumptions that the C-terminal subdomain of COR functions as a dimerization device. We show that the dimer formation is independent of nucleotide. The affinity for GDP/GTP is in the micromolar range, the result of which is high dissociation rates in the s-1 range. Thus Roco proteins are unlikely to need GEFs to achieve activation. Monomeric LRRK2 and Roco G-domains have a similar low GTPase activity to small G-proteins. We show that GTPase activity in bacterial Roco is stimulated by the nucleotide-dependent dimerization of the G-domain within the complex. We thus propose that the Roco proteins do not require GAPs to stimulate GTP hydrolysis but stimulate each other by one monomer completing the catalytic machinery of the other.

Identification of benign and malignant thyroid nodules by in vivo iodine concentration measurement using single-source dual energy CT

PubMed Central

Gao, Shun-Yu; Zhang, Xiao-Yan; Wei, Wei; Li, Xiao-Ting; Li, Yan-Ling; Xu, Min; Sun, Ying-Shi; Zhang, Xiao-Peng

2016-01-01

Abstract This study proposed to determine whether in vivo iodine concentration measurement by single-source dual energy (SSDE) CT can improve differentiation between benign and malignant thyroid nodules. In total, 53 patients presenting with thyroid nodules underwent SSDE CT scanning. Iodine concentrations were measured for each nodule and normal thyroid tissue using the GSI-viewer image analysis software. A total of 26 thyroid nodules were malignant in 26 patients and confirmed by surgery; 33 nodules from 27 patients were benign, with 10 confirmed by surgery and others after follow-up. Iodine concentrations with plain CT were significantly lower in malignant than benign nodules (0.47 ± 0.20 vs 1.17 ± 0.38 mg/mL, P = 0.00). Receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.93; with a cutoff of 0.67, iodine concentration showed 92.3% sensitivity and 88.5% specificity in diagnosing malignancy. Iodine concentration obtained by enhanced and plain CT were significantly higher in malignant than benign nodules (9.05 ± 3.35 vs 3.46 ± 2.24 mg/mL, P = 0.00). ROC curve analysis showed an AUC of 0.93; with a cutoff value of 3.37, iodine concentration displayed 78% sensitivity, 95% specificity in diagnosing malignancy. Combining unenhanced with enhanced iodine concentrations, the diagnostic equation was: Y = –8.641 × unenhanced iodine concentration + 0.663 × iodine concentration. ROC curve showed an AUC of 0.98 (95% CI, 0.94, 1.00). With Y ≥ –2 considered malignancy, diagnostic sensitivity and specificity were 96%, 96.3%, respectively. This study concluded that SSDE CT can detect the differences in iodine uptake and blood supply between benign and malignant thyroid lesions. PMID:27684811

Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia.

PubMed

Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

2016-09-24

The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box-Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9-17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia.

Electrochemical Skin Conductance May Be Used to Screen for Diabetic Cardiac Autonomic Neuropathy in a Chinese Population with Diabetes

PubMed Central

He, Tianyi; Wang, Chuan; Zuo, Anju; Liu, Pan; Li, Wenjuan

2017-01-01

Aims. This study aimed to assess whether the electrochemical skin conductance (ESC) could be used to screen for diabetic cardiac autonomic neuropathy (DCAN) in a Chinese population with diabetes. Methods. We recruited 75 patients with type 2 diabetes mellitus (T2DM) and 45 controls without diabetes. DCAN was diagnosed by the cardiovascular autonomic reflex tests (CARTs) as gold standard. In all subjects ESCs of hands and feet were also detected by SUDOSCAN™ as a new screening method. The efficacy was assessed by receiver operating characteristic (ROC) curve analysis. Results. The ESCs of both hands and feet were significantly lower in T2DM patients with DCAN than those without DCAN (67.33 ± 15.37 versus 78.03 ± 13.73, P = 0.002, and 57.77 ± 20.99 versus 75.03 ± 11.41, P < 0.001). The ROC curve analysis showed the areas under the ROC curve were both 0.75 for ESCs of hands and feet in screening DCAN. And the optimal cut-off values of ESCs, sensitivities, and specificities were 76 μS, 76.7%, and 75.6% for hands and 75 μS, 80.0%, and 60.0% for feet, respectively. Conclusions. ESC measurement is a reliable and feasible method to screen DCAN in the Chinese population with diabetes before further diagnosis with CARTs. PMID:28280746

A Primer on Receiver Operating Characteristic Analysis and Diagnostic Efficiency Statistics for Pediatric Psychology: We Are Ready to ROC

PubMed Central

2014-01-01

Objective To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Method Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Results Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. Conclusions This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses. PMID:23965298

A primer on receiver operating characteristic analysis and diagnostic efficiency statistics for pediatric psychology: we are ready to ROC.

PubMed

Youngstrom, Eric A

2014-03-01

To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.

Combining classifiers using their receiver operating characteristics and maximum likelihood estimation.

PubMed

Haker, Steven; Wells, William M; Warfield, Simon K; Talos, Ion-Florin; Bhagwat, Jui G; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H

2005-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging.

Combining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation*

PubMed Central

Haker, Steven; Wells, William M.; Warfield, Simon K.; Talos, Ion-Florin; Bhagwat, Jui G.; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H.

2010-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging. PMID:16685884

Impact of Wisteria floribunda Agglutinin-Positive Mac-2-Binding Protein in Patients with Hepatitis C Virus-Related Compensated Liver Cirrhosis.

PubMed

Hasegawa, Kunihiro; Takata, Ryo; Nishikawa, Hiroki; Enomoto, Hirayuki; Ishii, Akio; Iwata, Yoshinori; Miyamoto, Yuho; Ishii, Noriko; Yuri, Yukihisa; Nakano, Chikage; Nishimura, Takashi; Yoh, Kazunori; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

2016-09-12

We aimed to examine the effect of Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA⁺-M2BP) level on survival comparing with other laboratory liver fibrosis markers in hepatitis C virus (HCV)-related compensated liver cirrhosis (LC) (n = 165). For assessing prognostic performance of continuous fibrosis markers, we adapted time-dependent receiver operating characteristics (ROC) curves for clinical outcome. In time-dependent ROC analysis, annual area under the ROCs (AUROCs) were plotted. We also calculated the total sum of AUROCs in all time-points (TAAT score) in each fibrosis marker. WFA⁺-M2BP value ranged from 0.66 cutoff index (COI) to 19.95 COI (median value, 5.29 COI). Using ROC analysis for survival, the optimal cutoff point for WFA⁺-M2BP was 6.15 COI (AUROC = 0.79348, sensitivity = 80.0%, specificity = 74.78%). The cumulative five-year survival rate in patients with WFA⁺-M2BP ≥ 6.15 COI (n = 69) was 43.99%, while that in patients with WFA⁺-M2BP < 6.15 COI (n = 96) was 88.40% (p < 0.0001). In the multivariate analysis, absence of hepatocellular carcinoma (p = 0.0008), WFA⁺-M2BP < 6.15 COI (p = 0.0132), achievement of sustained virological response (p < 0.0001) and des-γ-carboxy prothrombin < 41 mAU/mL (p = 0.0018) were significant favorable predictors linked to survival. In time-dependent ROC analysis in all cases, WFA⁺-M2BP had the highest TAAT score among liver fibrosis markers. In conclusion, WFA⁺-M2BP can be a useful predictor in HCV-related compensated LC.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome.

PubMed

Lalonde, Michel; Wells, R Glenn; Birnie, David; Ruddy, Terrence D; Wassenaar, Richard

2014-07-01

Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard; Wells, R. Glenn

2014-07-15

Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: Aboutmore » 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.« less

Spinal Cord Injury Pain Instrument and painDETECT questionnaire: Convergent construct validity in individuals with Spinal Cord Injury.

PubMed

Franz, S; Schuld, C; Wilder-Smith, E P; Heutehaus, L; Lang, S; Gantz, S; Schuh-Hofer, S; Treede, R-D; Bryce, T N; Wang, H; Weidner, N

2017-11-01

Neuropathic pain (NeuP) is a frequent sequel of spinal cord injury (SCI). The SCI Pain Instrument (SCIPI) was developed as a SCI-specific NeuP screening tool. A preliminary validation reported encouraging results requiring further evaluation in terms of psychometric properties. The painDETECT questionnaire (PDQ), a commonly applied NeuP assessment tool, was primarily validated in German, but not specifically developed for SCI and not yet validated according to current diagnostic guidelines. We aimed to provide convergent construct validity and to identify the optimal item combination for the SCIPI. The PDQ was re-evaluated according to current guidelines with respect to SCI-related NeuP. Prospective monocentric study. Subjects received a neurological examination according to the International Standards for Neurological Classification of SCI. After linguistic validation of the SCIPI, the IASP-grading system served as reference to diagnose NeuP, accompanied by the PDQ after its re-evaluation as binary classifier. Statistics were evaluated through ROC-analysis, with the area under the ROC curve (AUROC) as optimality criterion. The SCIPI was refined by systematic item permutation. Eighty-eight individuals were assessed with the German SCIPI. Of 127 possible combinations, a 4-item-SCIPI (cut-off-score = 1.5/sensitivity = 0.864/specificity = 0.839) was identified as most reasonable. The SCIPI showed a strong correlation (r sp  = 0.76) with PDQ. ROC-analysis of SCIPI/PDQ (AUROC = 0.877) revealed comparable results to SCIPI/IASP (AUROC = 0.916). ROC-analysis of PDQ/IASP delivered a score threshold of 10.5 (sensitivity = 0.727/specificity = 0.903). The SCIPI is a valid easy-to-apply NeuP screening tool in SCI. The PDQ is recommended as complementary NeuP assessment tool in SCI, e.g. to monitor pain severity and/or its time-dependent course. In SCI-related pain, both SCIPI and PainDETECT show strong convergent construct validity versus the current IASP-grading system. SCIPI is now optimized from a 7-item to an easy-to-apply 4-item screening tool in German and English. We provided evidence that the scope for PainDETECT can be expanded to individuals with SCI. © 2017 European Pain Federation - EFIC®.

Increased Levels of Circulating Anti-ANXA1 IgG Antibody in Patients with Non-Small Cell Lung Cancer.

PubMed

Liang, Tingting; Han, Zhifeng; Zhao, Huan; Zhang, Xuan; Wang, Yao

2018-06-01

Our previous studies revealed that concentrations of circulating antibodies to annexin A1 (ANXA1) were increased in non-small lung cancer (NSCLC). This study was thus designed to replicate this initial finding with an independent sample set. An enzyme-linked immunosorbent assay (ELISA) was developed in-house to examine plasma antiANXA1 IgG levels in 220 patients with NSCLC and 200 control subjects. Mann-Whitney U test showed that patients with NSCLC had significantly higher anti-ANXA1 IgG levels than control subjects (Z = -4.02, p < 0.001); male patients appeared to mainly contribute to the increased antibody level (Z = -3.09, p = 0.002). Receiver operating characteristic (ROC) curve analysis showed an overall area under the ROC curve (AUC) of 0.61 (95% CI: 0.56 - 0.67), with sensitivity of 8% against a specificity of 95.0%. Spearman's correlation analysis failed to show a significant correlation between the anti-ANXA1 IgG levels and the expression of three tumor-associated antigens including p53 (r = 0.156, p = 0.027), Ki67 (r = -0.048, p = 0.489), and EGFR (r = 0.02, p = 0.782). Increased levels of circulating anti-ANXA1 IgG antibody may have a prognostic value for NSCLC.

Glutamate Dehydrogenase Affects Resistance to Cell Wall Antibiotics in Bacillus subtilis

PubMed Central

Lee, Yong Heon; Kingston, Anthony W.

2012-01-01

The glutamate dehydrogenase RocG of Bacillus subtilis is a bifunctional protein with both enzymatic and regulatory functions. Here we show that the rocG null mutant is sensitive to β-lactams, including cefuroxime (CEF), and to fosfomycin but that resistant mutants arise due to gain-of-function mutations in gudB, which encodes an otherwise inactive glutamate dehydrogenase. In the presence of CEF, ΔrocG ΔgudB mutant cells exhibit growth arrest when they reach mid-exponential phase. Using microarray-based transcriptional profiling, we found that the σW regulon was downregulated in the ΔrocG ΔgudB null mutant. A survey of σW-controlled genes for effects on CEF resistance identified both the NfeD protein YuaF and the flotillin homologue YuaG (FloT). Notably, overexpression of yuaFG in the rocG null mutant prevents the growth arrest induced by CEF. The YuaG flotillin has been shown previously to localize to defined lipid microdomains, and we show here that the yuaFGI operon contributes to a σW-dependent decrease in membrane fluidity. We conclude that glutamate dehydrogenase activity affects the expression of the σW regulon, by pathways that are yet unclear, and thereby influences resistance to CEF and other antibiotics. PMID:22178969

Glutamate dehydrogenase affects resistance to cell wall antibiotics in Bacillus subtilis.

PubMed

Lee, Yong Heon; Kingston, Anthony W; Helmann, John D

2012-03-01

The glutamate dehydrogenase RocG of Bacillus subtilis is a bifunctional protein with both enzymatic and regulatory functions. Here we show that the rocG null mutant is sensitive to β-lactams, including cefuroxime (CEF), and to fosfomycin but that resistant mutants arise due to gain-of-function mutations in gudB, which encodes an otherwise inactive glutamate dehydrogenase. In the presence of CEF, ΔrocG ΔgudB mutant cells exhibit growth arrest when they reach mid-exponential phase. Using microarray-based transcriptional profiling, we found that the σ(W) regulon was downregulated in the ΔrocG ΔgudB null mutant. A survey of σ(W)-controlled genes for effects on CEF resistance identified both the NfeD protein YuaF and the flotillin homologue YuaG (FloT). Notably, overexpression of yuaFG in the rocG null mutant prevents the growth arrest induced by CEF. The YuaG flotillin has been shown previously to localize to defined lipid microdomains, and we show here that the yuaFGI operon contributes to a σ(W)-dependent decrease in membrane fluidity. We conclude that glutamate dehydrogenase activity affects the expression of the σ(W) regulon, by pathways that are yet unclear, and thereby influences resistance to CEF and other antibiotics.

A principled approach to setting optimal diagnostic thresholds: where ROC and indifference curves meet.

PubMed

Irwin, R John; Irwin, Timothy C

2011-06-01

Making clinical decisions on the basis of diagnostic tests is an essential feature of medical practice and the choice of the decision threshold is therefore crucial. A test's optimal diagnostic threshold is the threshold that maximizes expected utility. It is given by the product of the prior odds of a disease and a measure of the importance of the diagnostic test's sensitivity relative to its specificity. Choosing this threshold is the same as choosing the point on the Receiver Operating Characteristic (ROC) curve whose slope equals this product. We contend that a test's likelihood ratio is the canonical decision variable and contrast diagnostic thresholds based on likelihood ratio with two popular rules of thumb for choosing a threshold. The two rules are appealing because they have clear graphical interpretations, but they yield optimal thresholds only in special cases. The optimal rule can be given similar appeal by presenting indifference curves, each of which shows a set of equally good combinations of sensitivity and specificity. The indifference curve is tangent to the ROC curve at the optimal threshold. Whereas ROC curves show what is feasible, indifference curves show what is desirable. Together they show what should be chosen. Copyright © 2010 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

The ROC Toolbox: A toolbox for analyzing receiver-operating characteristics derived from confidence ratings.

PubMed

Koen, Joshua D; Barrett, Frederick S; Harlow, Iain M; Yonelinas, Andrew P

2017-08-01

Signal-detection theory, and the analysis of receiver-operating characteristics (ROCs), has played a critical role in the development of theories of episodic memory and perception. The purpose of the current paper is to present the ROC Toolbox. This toolbox is a set of functions written in the Matlab programming language that can be used to fit various common signal detection models to ROC data obtained from confidence rating experiments. The goals for developing the ROC Toolbox were to create a tool (1) that is easy to use and easy for researchers to implement with their own data, (2) that can flexibly define models based on varying study parameters, such as the number of response options (e.g., confidence ratings) and experimental conditions, and (3) that provides optimal routines (e.g., Maximum Likelihood estimation) to obtain parameter estimates and numerous goodness-of-fit measures.The ROC toolbox allows for various different confidence scales and currently includes the models commonly used in recognition memory and perception: (1) the unequal variance signal detection (UVSD) model, (2) the dual process signal detection (DPSD) model, and (3) the mixture signal detection (MSD) model. For each model fit to a given data set the ROC toolbox plots summary information about the best fitting model parameters and various goodness-of-fit measures. Here, we present an overview of the ROC Toolbox, illustrate how it can be used to input and analyse real data, and finish with a brief discussion on features that can be added to the toolbox.

The use of intraoperative triggered electromyography to detect misplaced pedicle screws: a systematic review and meta-analysis.

PubMed

Mikula, Anthony L; Williams, Seth K; Anderson, Paul A

2016-04-01

Insertion of instruments or implants into the spine carries a risk for injury to neural tissue. Triggered electromyography (tEMG) is an intraoperative neuromonitoring technique that involves electrical stimulation of a tool or screw and subsequent measurement of muscle action potentials from myotomes innervated by nerve roots near the stimulated instrument. The authors of this study sought to determine the ability of tEMG to detect misplaced pedicle screws (PSs). The authors searched the U.S. National Library of Medicine, the Web of Science Core Collection database, and the Cochrane Central Register of Controlled Trials for PS studies. A meta-analysis of these studies was performed on a per-screw basis to determine the ability of tEMG to detect misplaced PSs. Sensitivity, specificity, and receiver operating characteristic (ROC) area under the curve (AUC) were calculated overall and in subgroups. Twenty-six studies were included in the systematic review. The authors analyzed 18 studies in which tEMG was used during PS placement in the meta-analysis, representing data from 2932 patients and 15,065 screws. The overall sensitivity of tEMG for detecting misplaced PSs was 0.78, and the specificity was 0.94. The overall ROC AUC was 0.96. A tEMG current threshold of 10-12 mA (ROC AUC 0.99) and a pulse duration of 300 µsec (ROC AUC 0.97) provided the most accurate testing parameters for detecting misplaced screws. Screws most accurately conducted EMG signals (ROC AUC 0.98). Triggered electromyography has very high specificity but only fair sensitivity for detecting malpositioned PSs.

DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans.

PubMed

Main, Keith L; Soman, Salil; Pestilli, Franco; Furst, Ansgar; Noda, Art; Hernandez, Beatriz; Kong, Jennifer; Cheng, Jauhtai; Fairchild, Jennifer K; Taylor, Joy; Yesavage, Jerome; Wesson Ashford, J; Kraemer, Helena; Adamson, Maheen M

2017-01-01

Standard MRI methods are often inadequate for identifying mild traumatic brain injury (TBI). Advances in diffusion tensor imaging now provide potential biomarkers of TBI among white matter fascicles (tracts). However, it is still unclear which tracts are most pertinent to TBI diagnosis. This study ranked fiber tracts on their ability to discriminate patients with and without TBI. We acquired diffusion tensor imaging data from military veterans admitted to a polytrauma clinic (Overall n  = 109; Age: M  = 47.2, SD  = 11.3; Male: 88%; TBI: 67%). TBI diagnosis was based on self-report and neurological examination. Fiber tractography analysis produced 20 fiber tracts per patient. Each tract yielded four clinically relevant measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity). We applied receiver operating characteristic (ROC) analyses to identify the most diagnostic tract for each measure. The analyses produced an optimal cutpoint for each tract. We then used kappa coefficients to rate the agreement of each cutpoint with the neurologist's diagnosis. The tract with the highest kappa was most diagnostic. As a check on the ROC results, we performed a stepwise logistic regression on each measure using all 20 tracts as predictors. We also bootstrapped the ROC analyses to compute the 95% confidence intervals for sensitivity, specificity, and the highest kappa coefficients. The ROC analyses identified two fiber tracts as most diagnostic of TBI: the left cingulum (LCG) and the left inferior fronto-occipital fasciculus (LIF). Like ROC, logistic regression identified LCG as most predictive for the FA measure but identified the right anterior thalamic tract (RAT) for the MD, RD, and AD measures. These findings are potentially relevant to the development of TBI biomarkers. Our methods also demonstrate how ROC analysis may be used to identify clinically relevant variables in the TBI population.

Effectiveness of computer aided detection for solitary pulmonary nodules

NASA Astrophysics Data System (ADS)

Yan, Jiayong; Li, Wenjie; Du, Xiangying; Lu, Huihai; Xu, Jianrong; Xu, Mantao; Rong, Dongdong

2009-02-01

This study is to investigate the incremental effect of using a high performance computer-aided detection (CAD) system in detection of solitary pulmonary nodules in chest radiographs. The Kodak Chest CAD system was evaluated by a panel of six radiologists at different levels of experience. The observer study consisted of two independent phases: readings without CAD and readings with assistance of CAD. The study was conducted over a set of chest radiographs comprising 150 cancer cases and 150 cancer-free cases. The actual sensitivity of the CAD system is 72% with 3.7 false positives per case. Receiver operating characteristic (ROC) analysis was used to assess the overall observer performance. The AUZ (area under ROC curve) showed a significantly improvement (P=0.0001) from 0.844 to 0.884 after using CAD. The ROC analysis was also applied for observer performances on nodules in different sizes and visibilities. The average AUZs are improved from 0.798 to 0.835 (P=0.0003) for 5-10mm nodules, 0.853 to 0.907 (P=0.001) for 10-15mm nodules, 0.864 to 0.897 (P=0.051) for 15-20 mm nodules and 0.859 to 0.896 (P=0.0342) for 20-30mm nodules, respectively. For different visibilities, the average AUZs are improved from 0.886 to 0.915 (P=0.0337), 0.803 to 0.840 (P=0.063), 0.830 to 0.893 (P=0.0001), and 0.813 to 0.847 (P=0.152), for nodules clearly visible, hidden by ribs, partially overlap with ribs, and overlap with other structures, respectively. These results showed that observer performance could be greatly improved when the CAD system is employed as a second reader, especially for small nodules and nodules occluded by ribs.

Discrimination of dementia with Lewy bodies from Alzheimer's disease using voxel-based morphometry of white matter by statistical parametric mapping 8 plus diffeomorphic anatomic registration through exponentiated Lie algebra.

PubMed

Nakatsuka, Tomoya; Imabayashi, Etsuko; Matsuda, Hiroshi; Sakakibara, Ryuji; Inaoka, Tsutomu; Terada, Hitoshi

2013-05-01

The purpose of this study was to identify brain atrophy specific for dementia with Lewy bodies (DLB) and to evaluate the discriminatory performance of this specific atrophy between DLB and Alzheimer's disease (AD). We retrospectively reviewed 60 DLB and 30 AD patients who had undergone 3D T1-weighted MRI. We randomly divided the DLB patients into two equal groups (A and B). First, we obtained a target volume of interest (VOI) for DLB-specific atrophy using correlation analysis of the percentage rate of significant whole white matter (WM) atrophy calculated using the Voxel-based Specific Regional Analysis System for Alzheimer's Disease (VSRAD) based on statistical parametric mapping 8 (SPM8) plus diffeomorphic anatomic registration through exponentiated Lie algebra, with segmented WM images in group A. We then evaluated the usefulness of this target VOI for discriminating the remaining 30 DLB patients in group B from the 30 AD patients. Z score values in this target VOI obtained from VSRAD were used as the determinant in receiver operating characteristic (ROC) analysis. Specific target VOIs for DLB were determined in the right-side dominant dorsal midbrain, right-side dominant dorsal pons, and bilateral cerebellum. ROC analysis revealed that the target VOI limited to the midbrain exhibited the highest area under the ROC curves of 0.75. DLB patients showed specific atrophy in the midbrain, pons, and cerebellum. Midbrain atrophy demonstrated the highest power for discriminating DLB and AD. This approach may be useful for determining the contributions of DLB and AD pathologies to the dementia syndrome.

[Resistant Obsessive Compulsive disorder (ROC): clinical picture, predictive factors and influence of affective temperaments].

PubMed

Hantouche, E G; Demonfaucon, C

2008-12-01

Despite significant advances in clinical research, Obsessive Compulsive Disorder, OCD represents a difficult to treat condition. The French Association of patients suffering from OCD, "AFTOC" is highly concerned by this issue. A new survey was implemented with the aim of exploring Resistant Obsessive Compulsive disorder "ROC". Patients with OCD and members of the "AFTOC" were included in the survey. A self-rated file was elaborated in order to get the maximum of information on the clinical and therapeutic aspects and conditions of OCD. The full version of "TEMPS-A" was also included for assessment of affective temperaments. Statistical analyses were performed for inter-group comparison between "ROC" (resistant OCD) and good responders. Logistic regression analyses with "ROC" method were used to search for independent predictive factors to "ROC". The new survey of "AFTOC", "TOC & ROC" selected a sample of 360 patients, who are members of the association. The rate of "ROC" was 44.2%, 25.3% of Good Responders (GR), and 30.5% in between. Inter-group comparisons ("ROC" versus GR) showed significant higher rates of psychiatric admissions (49% versus 28%), and suicide attempts (26% versus 13%), greater numbers of doctors consulted (5.5 versus. 3.2), compulsions (4.6 versus 3.4), and psychiatric comorbidity (2.8 disorders versus. 2.0; notably agoraphobia, social anxiety and worry about appearance) in the "ROC" group. Assessment by full "TEMPS-A" scale revealed, significantly higher rates of Cyclothymic Temperament (63% versus 43%; p: 0.0003), Depressive Temperament (72% versus 53%; p: 0.004), and Irritable Temperament (21% versus 9%; p: 0.02) in the ROC group. Moreover, the mean global score on each of these temperaments was significantly higher in the "ROC" group. No difference was obtained in the rate or the mean score on the hyperthymic temperament scale. The most predictive factors of "ROC" were represented by "slow continuous course", "worsening under SRI", "worry about appearance", current age above 40 years and psychiatric admission. Our data provides a more precise clinical picture of "ROC", which should be initially explored through baseline severity, compulsive dominance, hoarding, special comorbidity such as recurrent depression, obsession of appearance, agoraphobia, social anxiety, and complex mixture of unstable affective temperament (cyclothymic, irritable, and depressive), and course of illness. Furthermore, vigilance towards the notion of worsening linked to drug therapy, and the increased suicide risk is warranted in the clinical management of "ROC".

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis

PubMed Central

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

Background The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. Methods and finding We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755–0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691–0.783) and 0.742 (0.698–0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. Conclusions According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction. PMID:28060903

Receiver operating characteristic analysis of eyewitness memory: comparing the diagnostic accuracy of simultaneous versus sequential lineups.

PubMed

Mickes, Laura; Flowe, Heather D; Wixted, John T

2012-12-01

A police lineup presents a real-world signal-detection problem because there are two possible states of the world (the suspect is either innocent or guilty), some degree of information about the true state of the world is available (the eyewitness has some degree of memory for the perpetrator), and a decision is made (identifying the suspect or not). A similar state of affairs applies to diagnostic tests in medicine because, in a patient, the disease is either present or absent, a diagnostic test yields some degree of information about the true state of affairs, and a decision is made about the presence or absence of the disease. In medicine, receiver operating characteristic (ROC) analysis is the standard method for assessing diagnostic accuracy. By contrast, in the eyewitness memory literature, this powerful technique has never been used. Instead, researchers have attempted to assess the diagnostic performance of different lineup procedures using methods that cannot identify the better procedure (e.g., by computing a diagnosticity ratio). Here, we describe the basics of ROC analysis, explaining why it is needed and showing how to use it to measure the performance of different lineup procedures. To illustrate the unique advantages of this technique, we also report 3 ROC experiments that were designed to investigate the diagnostic accuracy of simultaneous versus sequential lineups. According to our findings, the sequential procedure appears to be inferior to the simultaneous procedure in discriminating between the presence versus absence of a guilty suspect in a lineup.

How Does One Assess the Accuracy of Academic Success Predictors? ROC Analysis Applied to University Entrance Factors

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

This article attempts to present a novel application of a method of measuring accuracy for academic success predictors that could be used as a standard. This procedure is known as the receiver operating characteristic (ROC) curve, which comes from statistical decision techniques. The statistical prediction techniques provide predictor models and…

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

C-Reactive Protein on Postoperative Day 1 Is a Reliable Predictor of Pancreas-Specific Complications After Pancreaticoduodenectomy.

PubMed

Guilbaud, Théophile; Birnbaum, David Jérémie; Lemoine, Coralie; Chirica, Mircea; Risse, Olivier; Berdah, Stéphane; Girard, Edouard; Moutardier, Vincent

2018-05-01

Postoperative pancreatic fistula and pancreas-specific complications have a significant influence on patient management and outcomes after pancreatoduodenectomy. The aim of the study was to assess the value of serum C-reactive protein on the postoperative day 1 as early predictor of pancreatic fistula and pancreas-specific complications. Between 2013 and 2016, 110 patients underwent pancreaticoduodenectomy. Clinical, biological, intraoperative, and pathological characteristics were prospectively recorded. Pancreatic fistula was graded according to the International Study Group on Pancreatic Fistula classification. A composite endpoint was defined as pancreas-specific complications including pancreatic fistula, intra-abdominal abscess, postoperative hemorrhage, and bile leak. The diagnostic accuracy of serum C-reactive protein on postoperative day 1 in predicting adverse postoperative outcomes was assessed by ROC curve analysis. Six patients (5%) died and 87 (79%) experienced postoperative complications (pancreatic-specific complications: n = 58 (53%); pancreatic fistula: n = 48 (44%)). A soft pancreatic gland texture, a main pancreatic duct diameter < 3 mm and serum C-reactive protein ≥ 100 mg/L on postoperative day 1 were independent predictors of pancreas-specific complications (p < 0.01) and pancreatic fistula (p < 0.01). ROC analysis showed that serum C-reactive protein ≥ 100 mg/L on postoperative day 1 was a significant predictor of pancreatic fistula (AUC: 0.70; 95%CI: 0.60-0.79, p < 0.01) and pancreas-specific complications (AUC: 0.72; 95%CI: 0.62-0.82, p < 0.01). ROC analysis showed that serum C-reactive protein ≥ 50 mg/L at discharge was a significant predictor of 90-day hospital readmission (AUC: 0.70; 95%CI: 0.60-0.79, p < 0.01). C-reactive protein levels reliably predict risks of pancreatic fistula, pancreas-specific complications, and hospital readmission, and should be inserted in risk-stratified management algorithms after pancreaticoduodenectomy.

A virtual clinical trial comparing static versus dynamic PET imaging in measuring response to breast cancer therapy

NASA Astrophysics Data System (ADS)

Wangerin, Kristen A.; Muzi, Mark; Peterson, Lanell M.; Linden, Hannah M.; Novakova, Alena; Mankoff, David A.; E Kinahan, Paul

2017-05-01

We developed a method to evaluate variations in the PET imaging process in order to characterize the relative ability of static and dynamic metrics to measure breast cancer response to therapy in a clinical trial setting. We performed a virtual clinical trial by generating 540 independent and identically distributed PET imaging study realizations for each of 22 original dynamic fluorodeoxyglucose (18F-FDG) breast cancer patient studies pre- and post-therapy. Each noise realization accounted for known sources of uncertainty in the imaging process, such as biological variability and SUV uptake time. Four definitions of SUV were analyzed, which were SUVmax, SUVmean, SUVpeak, and SUV50%. We performed a ROC analysis on the resulting SUV and kinetic parameter uncertainty distributions to assess the impact of the variability on the measurement capabilities of each metric. The kinetic macro parameter, K i , showed more variability than SUV (mean CV K i   =  17%, SUV  =  13%), but K i pre- and post-therapy distributions also showed increased separation compared to the SUV pre- and post-therapy distributions (mean normalized difference K i   =  0.54, SUV  =  0.27). For the patients who did not show perfect separation between the pre- and post-therapy parameter uncertainty distributions (ROC AUC  <  1), dynamic imaging outperformed SUV in distinguishing metabolic change in response to therapy, ranging from 12 to 14 of 16 patients over all SUV definitions and uptake time scenarios (p  <  0.05). For the patient cohort in this study, which is comprised of non-high-grade ER+  tumors, K i outperformed SUV in an ROC analysis of the parameter uncertainty distributions pre- and post-therapy. This methodology can be applied to different scenarios with the ability to inform the design of clinical trials using PET imaging.

Experimental Demonstration of Observability and Operability of Robustness of Coherence

NASA Astrophysics Data System (ADS)

Zheng, Wenqiang; Ma, Zhihao; Wang, Hengyan; Fei, Shao-Ming; Peng, Xinhua

2018-06-01

Quantum coherence is an invaluable physical resource for various quantum technologies. As a bona fide measure in quantifying coherence, the robustness of coherence (ROC) is not only mathematically rigorous, but also physically meaningful. We experimentally demonstrate the witness-observable and operational feature of the ROC in a multiqubit nuclear magnetic resonance system. We realize witness measurements by detecting the populations of quantum systems in one trial. The approach may also apply to physical systems compatible with ensemble or nondemolition measurements. Moreover, we experimentally show that the ROC quantifies the advantage enabled by a quantum state in a phase discrimination task.

Face recognition in schizophrenia: do individual and average ROCs tell the same story?

PubMed

Tiberghien, Guy; Martin, Clara; Baudouin, Jean-Yves; Franck, Nicolas; Guillaume, Fabrice; Huron, Caroline

2015-01-01

Many studies have shown that recollection process is impaired in patients with schizophrenia, whereas familiarity is generally spared. However, in these studies, the Receiver Operating Characteristic (ROC) presented is average ROC likely to mask individual differences. In the present study using a face-recognition task, we computed the individual ROC of patients with schizophrenia and control participants. Each group was divided into two subgroups on the basis of the type of recognition processes implemented: recognition based on familiarity only and recognition based on familiarity and recollection. The recognition performance of the schizophrenia patients was below that of the control participants only when recognition was based solely on familiarity. For the familiarity-alone patients, the score obtained on the Scale for the Assessment of Positive Symptoms (SAPS) was correlated with the variance of the old-face familiarity. For the familiarity-recollection patients, the score obtained on the Scale for the Assessment of Negative Symptoms (SANS) was correlated with the decision criterion and with the old-face recollection probability. These results show that one cannot ascribe the impaired recognition observed in patients with schizophrenia to a recollection deficit alone. These results show that individual ROC can be used to distinguish between subtypes of schizophrenia and could serve as a basis for setting up specific cognitive remediation therapy for individuals with schizophrenia.

Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia

PubMed Central

Ramírez-Vélez, Robinson; López-Cifuentes, Mario Ferney; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; González-Jiménez, Emilio; Córdoba-Rodríguez, Diana Paola; Vivas, Andrés; Triana-Reina, Hector Reynaldo; Schmidt-RioValle, Jacqueline

2016-01-01

The assessment of skinfold thickness is an objective measure of adiposity. The aims of this study were to establish Colombian smoothed centile charts and LMS L (Box–Cox transformation), M (median), and S (coefficient of variation) tables for triceps, subscapular, and triceps + subscapular skinfolds; appropriate cut-offs were selected using receiver operating characteristic (ROC) analysis based on a population-based sample of children and adolescents in Bogotá, Colombia. A cross-sectional study was conducted in 9618 children and adolescents (55.7% girls; age range of 9–17.9 years). Triceps and subscapular skinfold measurements were obtained using standardized methods. We calculated the triceps + subscapular skinfold (T + SS) sum. Smoothed percentile curves for triceps and subscapular skinfold thickness were derived using the LMS method. ROC curve analyses were used to evaluate the optimal cut-off point of skinfold thickness for overweight and obesity, based on the International Obesity Task Force definitions. Subscapular and triceps skinfolds and T + SS were significantly higher in girls than in boys (p < 0.001). The ROC analysis showed that subscapular and triceps skinfolds and T + SS have a high discriminatory power in the identification of overweight and obesity in the sample population in this study. Our results provide sex- and age-specific normative reference standards for skinfold thickness values from a population from Bogotá, Colombia. PMID:27669294

ROC analysis of diagnostic performance in liver scintigraphy.

PubMed

Fritz, S L; Preston, D F; Gallagher, J H

1981-02-01

Studies on the accuracy of liver scintigraphy for the detection of metastases were assembled from 38 sources in the medical literature. An ROC curve was fitted to the observed values of sensitivity and specificity using an algorithm developed by Ogilvie and Creelman. This ROC curve fitted the data better than average sensitivity and specificity values in each of four subsets of the data. For the subset dealing with Tc-99m sulfur colloid scintigraphy, performed for detection of suspected metastases and containing data on 2800 scans from 17 independent series, it was not possible to reject the hypothesis that interobserver variation was entirely due to the use of different decision thresholds by the reporting clinicians. Thus the ROC curve obtained is a reasonable baseline estimate of the performance potentially achievable in today's clinical setting. Comparison of new reports with these data is possible, but is limited by the small sample sizes in most reported series.

Inflammatory Asthma Phenotype Discrimination Using an Electronic Nose Breath Analyzer.

PubMed

Plaza, V; Crespo, A; Giner, J; Merino, J L; Ramos-Barbón, D; Mateus, E F; Torrego, A; Cosio, B G; Agustí, A; Sibila, O

2015-01-01

Patients with persistent asthma have different inflammatory phenotypes. The electronic nose is a new technology capable of distinguishing volatile organic compound (VOC) breath-prints in exhaled breath. The aim of the study was to investigate the capacity of electronic nose breath-print analysis to discriminate between different inflammatory asthma phenotypes (eosinophilic, neutrophilic, paucigranulocytic) determined by induced sputum in patients with persistent asthma. Fifty-two patients with persistent asthma were consecutively included in a cross-sectional proof-of-concept study. Inflammatory asthma phenotypes (eosinophilic, neutrophilic and paucigranulocytic) were recognized by inflammatory cell counts in induced sputum. VOC breath-prints were analyzed using the electronic nose Cyranose 320 and assessed by discriminant analysis on principal component reduction, resulting in cross-validated accuracy values. Receiver operating characteristic (ROC) curves were calculated. VOC breath-prints were different in eosinophilic asthmatics compared with both neutrophilic asthmatics (accuracy 73%; P=.008; area under ROC, 0.92) and paucigranulocytic asthmatics (accuracy 74%; P=.004; area under ROC, 0.79). Likewise, neutrophilic and paucigranulocytic breath-prints were also different (accuracy 89%; P=.001; area under ROC, 0.88). An electronic nose can discriminate inflammatory phenotypes in patients with persistent asthma in a regular clinical setting. ClinicalTrials.gov identifier: NCT02026336.

Is ozonation environmentally benign for reverse osmosis concentrate treatment? Four-level analysis on toxicity reduction based on organic matter fractionation.

PubMed

Weng, Jingxia; Jia, Huichao; Wu, Bing; Pan, Bingcai

2018-01-01

Ozonation is a promising option to treat reverse osmosis concentrate (ROC). However, a systematic understanding and assessment of ozonation on toxicity reduction is insufficient. In this study, ROC sampled from a typical industrial park wastewater treatment plant of China was fractionated into hydrophobic acid (HOA), hydrophobic base (HOB), hydrophobic neutral (HON), and hydrophilic fraction (HI). Systematic bioassays covering bacteria, algae, fish, and human cell lines were conducted to reveal the role of ozonation in toxicity variation of the four ROC fractions. HOA in the raw ROC exhibited the highest toxicity, followed by HON and HI. Ozonation significantly reduced total organic carbon (TOC) and UV 254 values in HOA, HON, and HI and their toxicity except in HOB. Correlation analysis indicated that chemical data (TOC and UV 254 ) of HOA and HON correlated well with their toxicities; however, poor correlations were observed for HOB and HI, suggesting that a battery of toxicity assays is necessary. This study indicates that TOC reduction during ozonation could not fully reflect the toxicity issue, and toxicity assessment is required in conjunction with the chemical data to evaluate the effectiveness of ozonation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating risk assessments using receiver operating characteristic analysis: rationale, advantages, insights, and limitations.

PubMed

Mossman, Douglas

2013-01-01

The last two decades have witnessed major changes in the way that mental health professionals assess, describe, and think about persons' risk for future violence. Psychiatrists and psychologists have gone from believing that they could not predict violence to feeling certain they can assess violence risk with well-above-chance accuracy. Receiver operating characteristic (ROC) analysis has played a central role in changing this view. This article reviews the key concepts underlying ROC methods, the meaning of the area under the ROC curve (AUC), the relationship between AUC and effect size d, and what these two indices tell us about evaluations of violence risk. The area under the ROC curve and d provide succinct but incomplete descriptions of discrimination capacity. These indices do not provide details about sensitivity-specificity trade-offs; they do not tell us how to balance false-positive and false-negative errors; and they do not determine whether a diagnostic system is accurate enough to make practically useful distinctions between violent and non-violent subject groups. Justifying choices or clinical practices requires a contextual investigation of outcomes, a process that takes us beyond simply knowing global indices of accuracy. Copyright © 2013 John Wiley & Sons, Ltd.

Application of impulse oscillometry and bronchial dilation test for analysis in patients with asthma and chronic obstructive pulmonary disease

PubMed Central

Li, Yueyue; Chen, Yang; Wang, Ping

2015-01-01

Impulse oscillometry (IOS) is a good method for measuring airway resistance. The aim of this study was to assess the diagnostic contribution of IOS combined with bronchial dilation test (BDT) when distinguishing between patients with asthma and those with chronic obstructive pulmonary disease (COPD). 870 were enrolled in the study including 561 patients with asthma, 100 patients with COPD and 209 patients with chronic coughing or normal subjects. All the participants underwent routine pulmonary function tests, IOS and BDT examination. And IOS examination was before and after BDT. IOS parameters (R5, R20, R25, R35, X5, X20, X25, X35, Fres, Zrs & RP) and forced expiratory volume in one second (FEV1) were recorded. Receiver operating characteristics (ROC) curve analysis was performed to evaluate the diagnostic ability to differentiate asthma and COPD. The discriminative power of the various parameters studied was determined by means of ROC curves: the area under the curve (AUC), sensitivity and specificity. The X5, X20, X25, X35, Fres, Zrs and Rp correlated better with COPD. In particular, X5, Fres and X25 have been found to be significantly correlated with COPD. The diagnostic efficiency of X5, Fres and X25 when diagnosis COPD, expressed by ROC curve parameters, was as follows: AUC (0.725, 0.730, 0.724), sensitivity (67%, 77%, 83%) and specificity (68%, 65%, 58%), respectively. The diagnostic efficiency of Zrs, R5 and X35 when diagnosis asthma, expressed by ROC curve parameters, was as follows: AUC (0.721, 0.710, 0.695), sensitivity (62%, 72%, 53%) and specificity (72%, 61%, 76%), respectively. Our findings show, that X5, X25 and Fres may be useful for predictions and evaluations for COPD. And R5, X35 and Zrs may provide useful IOS parameters for asthma. IOS combined BDT could be useful diagnostic and differential diagnosis between asthma and COPD. PMID:25785124

Application of impulse oscillometry and bronchial dilation test for analysis in patients with asthma and chronic obstructive pulmonary disease.

PubMed

Li, Yueyue; Chen, Yang; Wang, Ping

2015-01-01

Impulse oscillometry (IOS) is a good method for measuring airway resistance. The aim of this study was to assess the diagnostic contribution of IOS combined with bronchial dilation test (BDT) when distinguishing between patients with asthma and those with chronic obstructive pulmonary disease (COPD). 870 were enrolled in the study including 561 patients with asthma, 100 patients with COPD and 209 patients with chronic coughing or normal subjects. All the participants underwent routine pulmonary function tests, IOS and BDT examination. And IOS examination was before and after BDT. IOS parameters (R5, R20, R25, R35, X5, X20, X25, X35, Fres, Zrs & RP) and forced expiratory volume in one second (FEV1) were recorded. Receiver operating characteristics (ROC) curve analysis was performed to evaluate the diagnostic ability to differentiate asthma and COPD. The discriminative power of the various parameters studied was determined by means of ROC curves: the area under the curve (AUC), sensitivity and specificity. The X5, X20, X25, X35, Fres, Zrs and Rp correlated better with COPD. In particular, X5, Fres and X25 have been found to be significantly correlated with COPD. The diagnostic efficiency of X5, Fres and X25 when diagnosis COPD, expressed by ROC curve parameters, was as follows: AUC (0.725, 0.730, 0.724), sensitivity (67%, 77%, 83%) and specificity (68%, 65%, 58%), respectively. The diagnostic efficiency of Zrs, R5 and X35 when diagnosis asthma, expressed by ROC curve parameters, was as follows: AUC (0.721, 0.710, 0.695), sensitivity (62%, 72%, 53%) and specificity (72%, 61%, 76%), respectively. Our findings show, that X5, X25 and Fres may be useful for predictions and evaluations for COPD. And R5, X35 and Zrs may provide useful IOS parameters for asthma. IOS combined BDT could be useful diagnostic and differential diagnosis between asthma and COPD.

Impact of signal scattering and parametric uncertainties on receiver operating characteristics

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Breton, Daniel J.; Hart, Carl R.; Pettit, Chris L.

2017-05-01

The receiver operating characteristic (ROC curve), which is a plot of the probability of detection as a function of the probability of false alarm, plays a key role in the classical analysis of detector performance. However, meaningful characterization of the ROC curve is challenging when practically important complications such as variations in source emissions, environmental impacts on the signal propagation, uncertainties in the sensor response, and multiple sources of interference are considered. In this paper, a relatively simple but realistic model for scattered signals is employed to explore how parametric uncertainties impact the ROC curve. In particular, we show that parametric uncertainties in the mean signal and noise power substantially raise the tails of the distributions; since receiver operation with a very low probability of false alarm and a high probability of detection is normally desired, these tails lead to severely degraded performance. Because full a priori knowledge of such parametric uncertainties is rarely available in practice, analyses must typically be based on a finite sample of environmental states, which only partially characterize the range of parameter variations. We show how this effect can lead to misleading assessments of system performance. For the cases considered, approximately 64 or more statistically independent samples of the uncertain parameters are needed to accurately predict the probabilities of detection and false alarm. A connection is also described between selection of suitable distributions for the uncertain parameters, and Bayesian adaptive methods for inferring the parameters.

The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets.

PubMed

Saito, Takaya; Rehmsmeier, Marc

2015-01-01

Binary classifiers are routinely evaluated with performance measures such as sensitivity and specificity, and performance is frequently illustrated with Receiver Operating Characteristics (ROC) plots. Alternative measures such as positive predictive value (PPV) and the associated Precision/Recall (PRC) plots are used less frequently. Many bioinformatics studies develop and evaluate classifiers that are to be applied to strongly imbalanced datasets in which the number of negatives outweighs the number of positives significantly. While ROC plots are visually appealing and provide an overview of a classifier's performance across a wide range of specificities, one can ask whether ROC plots could be misleading when applied in imbalanced classification scenarios. We show here that the visual interpretability of ROC plots in the context of imbalanced datasets can be deceptive with respect to conclusions about the reliability of classification performance, owing to an intuitive but wrong interpretation of specificity. PRC plots, on the other hand, can provide the viewer with an accurate prediction of future classification performance due to the fact that they evaluate the fraction of true positives among positive predictions. Our findings have potential implications for the interpretation of a large number of studies that use ROC plots on imbalanced datasets.

The SLCO1A2 -189_-188InsA polymorphism reduces clearance of rocuronium in patients submitted to elective surgeries.

PubMed

Costa, A C C; Coelho, E B; Lanchote, V L; Correia, B V; Abumansur, J T; Lauretti, G R; de Moraes, N V

2017-08-01

Rocuronium (ROC) is a neuromuscular blocker mainly eliminated by biliary excretion dependent on organic anion transporting polypeptide 1A2 (OATP1A2) hepatocellular uptake. However, the influence of SLCO1A2 (gene encoding OATP1A2) genetic polymorphism on ROC pharmacokinetics was never described before. The objective of this work was to evaluate the influence of genetic polymorphisms of SLCO1A2 on the pharmacokinetics of rocuronium (ROC). Patients undergoing elective surgeries under general anesthesia using rocuronium as a neuromuscular blocker were genotyped for SLCO1A2 polymorphisms in the coding region (41A>G, 382A>T, 404A>T, 502C>T, 516A>C, 559G>A, 830C>A, and 833delA) and in the promoter region (-1105G>A, -1032G>A, -715T>C, -361G>A, and -189_-188insA). Rocuronium pharmacokinetic parameters were estimated by non-compartmental analysis. None of the patients had heterozygous or homozygous variant of 404A>T, 382A>T, 502C>T, 833delA, 830C>A, 41A>G, and -715T>C. A linkage disequilibrium was found between -1105G>A and -1032G>A genotypes. Patients genotyped as -A or AA (n = 17) for SLCO1A2 -189_-188InsA showed reduced total clearance of ROC compared to patients genotyped as -/- (n = 13) (151.6 vs 207.1 mL/min, p ≤ 0.05). The pharmacokinetics parameters of ROC were not significantly different between other SLCO1A2 genotypes. SLCO1A2 -189_-188InsA polymorphism is related to the reduced clearance of rocuronium in patients submitted to elective surgeries under general anesthesia. NCT 02399397 ( ClinicalTrials.gov ).

Glutamate dehydrogenase (RocG) in Bacillus licheniformis WX-02: Enzymatic properties and specific functions in glutamic acid synthesis for poly-γ-glutamic acid production.

PubMed

Tian, Guangming; Wang, Qin; Wei, Xuetuan; Ma, Xin; Chen, Shouwen

2017-04-01

Poly-γ-glutamic acid (γ-PGA), a natural biopolymer, is widely used in cosmetics, medicine, food, water treatment, and agriculture owing to its features of moisture sequestration, cation chelation, non-toxicity and biodegradability. Intracellular glutamic acid, the substrate of γ-PGA, is a limiting factor for high yield in γ-PGA production. Bacillus subtilis and Bacillus licheniformis are both important γ-PGA producing strains, and B. subtilis synthesizes glutamic acid in vivo using the unique GOGAT/GS pathway. However, little is known about the glutamate synthesis pathway in B. licheniformis. The aim of this work was to characterize the glutamate dehydrogenase (RocG) in glutamic acid synthesis from B. licheniformis with both in vivo and in vitro experiments. By re-directing the carbon flux distribution, the rocG gene deletion mutant WX-02ΔrocG produced intracellular glutamic acid with a concentration of 90ng/log(CFU), which was only 23.7% that of the wild-type WX-02 (380ng/log(CFU)). Furthermore, the γ-PGA yield of mutant WX-02ΔrocG was 5.37g/L, a decrease of 45.3% compared to the wild type (9.82g/L). In vitro enzymatic assays of RocG showed that RocG has higher affinity for 2-oxoglutarate than glutamate, and the glutamate synthesis rate was far above degradation. This is probably the first study to reveal the glutamic acid synthesis pathway and the specific functions of RocG in B. licheniformis. The results indicate that γ-PGA production can be enhanced through improving intracellular glutamic acid synthesis. Copyright © 2017 Elsevier Inc. All rights reserved.

The anticancer phytochemical rocaglamide inhibits Rho GTPase activity and cancer cell migration

PubMed Central

Becker, Michael S.; Müller, Paul M.; Bajorat, Jörg; Schroeder, Anne; Giaisi, Marco; Amin, Ehsan; Ahmadian, Mohammad R.; Rocks, Oliver; Köhler, Rebecca; Krammer, Peter H.; Li-Weber, Min

2016-01-01

Chemotherapy is one of the pillars of anti-cancer therapy. Although chemotherapeutics cause regression of the primary tumor, many chemotherapeutics are often shown to induce or accelerate metastasis formation. Moreover, metastatic tumors are largely resistant against chemotherapy. As more than 90% of cancer patients die due to metastases and not due to primary tumor formation, novel drugs are needed to overcome these shortcomings. In this study, we identified the anticancer phytochemical Rocaglamide (Roc-A) to be an inhibitor of cancer cell migration, a crucial event in metastasis formation. We show that Roc-A inhibits cellular migration and invasion independently of its anti-proliferative and cytotoxic effects in different types of human cancer cells. Mechanistically, Roc-A treatment induces F-actin-based morphological changes in membrane protrusions. Further investigation of the molecular mechanisms revealed that Roc-A inhibits the activities of the small GTPases RhoA, Rac1 and Cdc42, the master regulators of cellular migration. Taken together, our results provide evidence that Roc-A may be a lead candidate for a new class of anticancer drugs that inhibit metastasis formation. PMID:27340868

Differences in the associations of anthropometric measures with insulin resistance and type 2 diabetes mellitus between Korean and US populations: Comparisons of representative nationwide sample data.

PubMed

Yoon, Yeong Sook; Choi, Han Seok; Kim, Jin Kuk; Kim, Yu Il; Oh, Sang Woo

Variation among ethnic groups in the association between obesity and insulin resistance (IR)/diabetes has been suggested, but studies reported inconsistent results. We evaluated ethnic differences in the association between obesity and insulin resistance (IR)/diabetes. We conducted a cross-sectional analysis using Korea (n=18,845) and the USA (n=4657) National Health and Nutrition Examination Survey(NHANES) 2007-2010. We performed statistical comparisons of AUC-ROC (area under the curve in a receiver operating characteristic curve) values for body mass index (BMI), waist circumference (WC) and homeostasis model assessment of insulin resistance (HOMA-IR) to predict IR or diabetes among different ethnic groups. AUC-ROC values for BMI and WC for predicting IR were highest in Whites (0.8324 and 0.8468) and lowest in Koreans (0.7422 and 0.7367). Whites showed the highest AUC-ROC values for BMI (0.6869) and WC (0.7421) for predicting diabetes, while the AUC-ROC for HOMA-IR was highest in Koreans (0.8861). Linear regression showed significant interactions between ethnicity and the main effects (all P<0.0001). Increases in BMI were associated with a larger increase in HOMA-IR in Whites (β=0.0719) and WC in Hispanics (β=0.0324), while BMI was associated with a larger increase in fasting glucose in Koreans (β=0.8279) and WC in Blacks (β=0.4037). In addition, the slope for fasting glucose with increasing HOMA-IR was steeper in Koreans (β=16.5952, P<0.001) than in other groups. The ability of BMI and WC to predict IR and diabetes was highest in Whites, while the ability of HOMA-IR to predict diabetes was highest in Koreans. Copyright © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Three regularities of recognition memory: the role of bias.

PubMed

Hilford, Andrew; Maloney, Laurence T; Glanzer, Murray; Kim, Kisok

2015-12-01

A basic assumption of Signal Detection Theory is that decisions are made on the basis of likelihood ratios. In a preceding paper, Glanzer, Hilford, and Maloney (Psychonomic Bulletin & Review, 16, 431-455, 2009) showed that the likelihood ratio assumption implies that three regularities will occur in recognition memory: (1) the Mirror Effect, (2) the Variance Effect, (3) the normalized Receiver Operating Characteristic (z-ROC) Length Effect. The paper offered formal proofs and computational demonstrations that decisions based on likelihood ratios produce the three regularities. A survey of data based on group ROCs from 36 studies validated the likelihood ratio assumption by showing that its three implied regularities are ubiquitous. The study noted, however, that bias, another basic factor in Signal Detection Theory, can obscure the Mirror Effect. In this paper we examine how bias affects the regularities at the theoretical level. The theoretical analysis shows: (1) how bias obscures the Mirror Effect, not the other two regularities, and (2) four ways to counter that obscuring. We then report the results of five experiments that support the theoretical analysis. The analyses and the experimental results also demonstrate: (1) that the three regularities govern individual, as well as group, performance, (2) alternative explanations of the regularities are ruled out, and (3) that Signal Detection Theory, correctly applied, gives a simple and unified explanation of recognition memory data.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve

NASA Astrophysics Data System (ADS)

Xu, Lili; Luo, Shuqian

2010-11-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve.

PubMed

Xu, Lili; Luo, Shuqian

2010-01-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Contrast-Enhanced Ultrasound in the Diagnosis of Gallbladder Diseases: A Multi-Center Experience

PubMed Central

Liu, Lin-Na; Xu, Hui-Xiong; Lu, Ming-De; Xie, Xiao-Yan; Wang, Wen-Ping; Hu, Bing; Yan, Kun; Ding, Hong; Tang, Shao-Shan; Qian, Lin-Xue; Luo, Bao-Ming; Wen, Yan-Ling

2012-01-01

Objective To assess the usefulness of contrast–enhanced ultrasound (CEUS) in differentiating malignant from benign gallbladder (GB) diseases. Methods This study had institutional review board approval. 192 patients with GB diseases from 9 university hospitals were studied. After intravenous bonus injection of a phospholipid-stabilized shell microbubble contrast agent, lesions were scanned with low acoustic power CEUS. A multiple logistic regression analysis was performed to identify diagnostic clues from 17 independent variables that enabled differentiation between malignant and benign GB diseases. Receiver operating characteristic (ROC) curve analysis was performed. Results Among the 17 independent variables, multiple logistic regression analysis showed that the following 4 independent variables were associated with the benign nature of the GB diseases, including the patient age, intralesional blood vessel depicted on CEUS, contrast washout time, and wall intactness depicted on CEUS (all P<0.05). ROC analysis showed that the patient age, intralesional vessels on CEUS, and the intactness of the GB wall depicted on CEUS yielded an area under the ROC curve (Az) greater than 0.8 in each and Az for the combination of the 4 significant independent variables was 0.915 [95% confidence interval (CI): 0.857–0.974]. The corresponding Az, sensitivity, and specificity for the age were 0.805 (95% CI: 0.746–0.863), 92.2%%, and 59.6%; for the intralesional vessels on CEUS were 0.813 (95% CI: 0.751–0.875), 59.8%, and 98.0%; and for the GB wall intactness were 0.857 (95% CI: 0.786–0.928), 78.4%, and 92.9%. The cut-off values for benign GB diseases were patient age <53.5 yrs, dotted intralesional vessels on CEUS and intact GB wall on CEUS. Conclusion CEUS is valuable in differentiating malignant from benign GB diseases. Branched or linear intralesional vessels and destruction of GB wall on CEUS are the CEUS features highly suggestive of GB malignancy and the patient age >53.5 yrs is also a clue for GB malignancy. PMID:23118996

Anti-A2 and anti-A1 domain antibodies are potential predictors of immune tolerance induction outcome in children with hemophilia A.

PubMed

Lapalud, P; Rothschild, C; Mathieu-Dupas, E; Balicchi, J; Gruel, Y; Laune, D; Molina, F; Schved, J F; Granier, C; Lavigne-Lissalde, G

2015-04-01

Hemophilia A (HA) is a congenital bleeding disorder resulting from factor VIII deficiency. The most serious complication of HA management is the appearance of inhibitory antibodies (Abs) against injected FVIII concentrates. To eradicate inhibitors, immune tolerance induction (ITI) is usually attempted, but it fails in up to 30% of cases. Currently, no undisputed predictive marker of ITI outcome is available to facilitate the clinical decision. To identify predictive markers of ITI efficacy. The isotypic and epitopic repertoires of inhibitory Abs were analyzed in plasma samples collected before ITI initiation from 15 children with severe HA and high-titer inhibitors, and their levels were compared in the two outcome groups (ITI success [n = 7] and ITI failure [n = 8]). The predictive value of these candidate biomarkers and of the currently used indicators (inhibitor titer and age at ITI initiation, highest inhibitor titer before ITI, and interval between inhibitor diagnosis and ITI initiation) was then compared by statistical analysis (Wilcoxon test and receiver receiver operating characteristic [ROC] curve analysis). Whereas current indicators seemed to fail in discriminating patients in the two outcome groups (ITI success or failure), anti-A1 and anti-A2 Ab levels before ITI initiation appeared to be good potential predictive markers of ITI outcome (P < 0.018). ROC analysis showed that anti-A1 and anti-A2 Abs were the best at discriminating between outcome groups (area under the ROC curve of > 0.875). Anti-A1 and anti-A2 Abs could represent new promising tools for the development of ITI outcome prediction tests for children with severe HA. © 2015 International Society on Thrombosis and Haemostasis.

Comparison of conventional and automated breast volume ultrasound in the description and characterization of solid breast masses based on BI-RADS features.

PubMed

Kim, Hyunji; Cha, Joo Hee; Oh, Ha-Yeun; Kim, Hak Hee; Shin, Hee Jung; Chae, Eun Young

2014-07-01

To compare the performance of radiologists in the use of conventional ultrasound (US) and automated breast volume ultrasound (ABVU) for the characterization of benign and malignant solid breast masses based on breast imaging and reporting data system (BI-RADS) criteria. Conventional US and ABVU images were obtained in 87 patients with 106 solid breast masses (52 cancers, 54 benign lesions). Three experienced radiologists who were blinded to all examination results independently characterized the lesions and reported a BI-RADS assessment category and a level of suspicion of malignancy. The results were analyzed by calculation of Cohen's κ coefficient and by receiver operating characteristic (ROC) analysis. Assessment of the agreement of conventional US and ABVU indicated that the posterior echo feature was the most discordant feature of seven features (κ = 0.371 ± 0.225) and that orientation had the greatest agreement (κ = 0.608 ± 0.210). The final assessment showed substantial agreement (κ = 0.773 ± 0.104). The areas under the ROC curves (Az) for conventional US and ABVU were not statistically significant for each reader, but the mean Az values of conventional US and ABVU by multi-reader multi-case analysis were significantly different (conventional US 0.991, ABVU 0.963; 95 % CI -0.0471 to -0.0097). The means for sensitivity, specificity, positive predictive value, and negative predictive value of conventional US and ABVU did not differ significantly. There was substantial inter-observer agreement in the final assessment of solid breast masses by conventional US and ABVU. ROC analysis comparing the performance of conventional US and ABVU indicated a marginally significant difference in mean Az, but not in mean sensitivity, specificity, positive predictive value, or negative predictive value.

[Correlation between percentage of body fat and simple anthropometric parameters in children aged 6-9 years in Guangzhou].

PubMed

Yan, H C; Hao, Y T; Guo, Y F; Wei, Y H; Zhang, J H; Huang, G P; Mao, L M; Zhang, Z Q

2017-11-10

Objective: To evaluate the accuracy of simple anthropometric parameters in diagnosing obesity in children in Guangzhou. Methods: A cross-sectional study, including 465 children aged 6-9 years, was carried out in Guangzhou. Their body height and weight, waist circumference (WC) and hip circumference were measured according to standard procedure. Body mass index (BMI), waist to hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BF%) was determined by dual-energy X-ray absorptiometry. Multiple regression analysis was applied to evaluate the correlations between age-adjusted physical indicators and BF%, after the adjustment for age. Obesity was defined by BF%. Receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic accuracy of the indicators for childhood obesity. Area under-ROC curves (AUCs) were calculated and the best cut-off point that maximizing 'sensitivity + specificity-1' was determined. Results: BMI showed the strongest association with BF% through multiple regression analysis. For 'per-standard deviation increase' of BMI, BF% increased by 5.3% ( t =23.1, P <0.01) in boys and 4.6% ( t =17.5, P <0.01) in girls, respectively. The ROC curve analysis indicated that BMI exhibited the largest AUC in both boys (AUC=0.908) and girls (AUC=0.895). The sensitivity was 80.8% in boys and 81.8% in girls, and the specificity was 88.2% in boys and 87.1% in girls. Both the AUCs for WHtR and WC were less than 0.8 in boys and girls. WHR had the smallest AUCs (<0.8) in both boys and girls. Conclusion: BMI appeared to be a good predicator for BF% in children aged 6-9 years in Guangzhou.

Utility of Shear Wave Elastography for Differentiating Biliary Atresia From Infantile Hepatitis Syndrome.

PubMed

Wang, Xiaoman; Qian, Linxue; Jia, Liqun; Bellah, Richard; Wang, Ning; Xin, Yue; Liu, Qinglin

2016-07-01

The purpose of this study was to investigate the potential utility of shear wave elastography (SWE) for diagnosis of biliary atresia and for differentiating biliary atresia from infantile hepatitis syndrome by measuring liver stiffness. Thirty-eight patients with biliary atresia and 17 patients with infantile hepatitis syndrome were included, along with 31 healthy control infants. The 3 groups underwent SWE. The hepatic tissue of each patient with biliary atresia had been surgically biopsied. Statistical analyses for mean values of the 3 groups were performed. Optimum cutoff values using SWE for differentiation between the biliary atresia and control groups were calculated by a receiver operating characteristic (ROC) analysis. The mean SWE values ± SD for the 3 groups were as follows: biliary atresia group, 20.46 ± 10.19 kPa; infantile hepatitis syndrome group, 6.29 ± 0.99 kPa; and control group, 6.41 ± 1.08 kPa. The mean SWE value for the biliary atresia group was higher than the values for the control and infantile hepatitis syndrome groups (P < .01). The mean SWE values between the control and infantile hepatitis syndrome groups were not statistically different. The ROC analysis showed a cutoff value of 8.68 kPa for differentiation between the biliary atresia and control groups. The area under the ROC curve was 0.997, with sensitivity of 97.4%, specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 96.9%. Correlation analysis suggested a positive correlation between SWE values and age for patients with biliary atresia, with a Pearson correlation coefficient of 0.463 (P < .05). The significant increase in liver SWE values in neonates and infants with biliary atresia supports their application for differentiating biliary atresia from infantile hepatitis syndrome.

Dual-time point scanning of integrated FDG PET/CT for the evaluation of mediastinal and hilar lymph nodes in non-small cell lung cancer diagnosed as operable by contrast-enhanced CT.

PubMed

Kasai, Takami; Motoori, Ken; Horikoshi, Takuro; Uchiyama, Katsuhiro; Yasufuku, Kazuhiro; Takiguchi, Yuichi; Takahashi, Fumiaki; Kuniyasu, Yoshio; Ito, Hisao

2010-08-01

To evaluate whether dual-time point scanning with integrated fluorine-18 fluorodeoxyglucose ((18)F-FDG) positron emission tomography and computed tomography (PET/CT) is useful for evaluation of mediastinal and hilar lymph nodes in non-small cell lung cancer diagnosed as operable by contrast-enhanced CT. PET/CT data and pathological findings of 560 nodal stations in 129 patients with pathologically proven non-small cell lung cancer diagnosed as operable by contrast-enhanced CT were reviewed retrospectively. Standardized uptake values (SUVs) on early scans (SUVe) 1h, and on delayed scans (SUVd) 2h after FDG injection of each nodal station were measured. Retention index (RI) (%) was calculated by subtracting SUVe from SUVd and dividing by SUVe. Logistic regression analysis was performed with seven kinds of models, consisting of (1) SUVe, (2) SUVd, (3) RI, (4) SUVe and SUVd, (5) SUVe and RI, (6) SUVd and RI, and (7) SUVe, SUVd and RI. The seven derived models were compared by receiver-operating characteristic (ROC) analysis. k-Fold cross-validation was performed with k values of 5 and 10. p<0.05 was considered statistically significant. Model (1) including the term of SUVe showed the largest area under the ROC curve among the seven models. The cut-off probability of metastasis of 3.5% with SUVe of 2.5 revealed a sensitivity of 78% and a specificity of 81% on ROC analysis, and approximately 60% and 80% on k-fold cross-validation. Single scanning of PET/CT is sufficiently useful for evaluating mediastinal and hilar nodes for metastasis. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

On the form of ROCs constructed from confidence ratings.

PubMed

Malmberg, Kenneth J

2002-03-01

A classical question for memory researchers is whether memories vary in an all-or-nothing, discrete manner (e.g., stored vs. not stored, recalled vs. not recalled), or whether they vary along a continuous dimension (e.g., strength, similarity, or familiarity). For yes-no classification tasks, continuous- and discrete-state models predict nonlinear and linear receiver operating characteristics (ROCs), respectively (D. M. Green & J. A. Swets, 1966; N. A. Macmillan & C. D. Creelman, 1991). Recently, several authors have assumed that these predictions are generalizable to confidence ratings tasks (J. Qin, C. L. Raye, M. K. Johnson, & K. J. Mitchell, 2001; S. D. Slotnick, S. A. Klein, C. S. Dodson, & A. P. Shimamura, 2000, and A. P. Yonelinas, 1999). This assumption is shown to be unwarranted by showing that discrete-state ratings models predict both linear and nonlinear ROCs. The critical factor determining the form of the discrete-state ROC is the response strategy adopted by the classifier.

Iodine concentration: a new, important characteristic of the spot sign that predicts haematoma expansion.

PubMed

Fu, Fan; Sun, Shengjun; Liu, Liping; Li, Jianying; Su, Yaping; Li, Yingying

2018-04-19

The computed tomography angiography (CTA) spot sign is a validated predictor of haematoma expansion (HE) in spontaneous intracerebral haemorrhage (SICH). We investigated whether defining the iodine concentration (IC) inside the spot sign and the haematoma on Gemstone spectral imaging (GSI) would improve its sensitivity and specificity for predicting HE. From 2014 to 2016, we prospectively enrolled 65 SICH patients who underwent single-phase spectral CTA within 6 h. Logistic regression was performed to assess the risk factors for HE. The predictive performance of individual spot sign characteristics was examined via receiver operating characteristic (ROC) analysis. The spot sign was detected in 46.1% (30/65) of patients. ROC analysis indicated that IC inside the spot sign had the greatest area under the ROC curve for HE (0.858; 95% confidence interval, 0.727-0.989; p = 0.003). Multivariate analysis found that spot sign with higher IC (i.e. IC > 7.82 100 μg/ml) was an independent predictor of HE (odds ratio = 34.27; 95% confidence interval, 5.608-209.41; p < 0.001) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.81, 0.75, 0.90 and 0.60, respectively; while the spot sign showed sensitivity, specificity, PPV and NPV of 0.81, 0.79, 0.73 and 0.86. Logistic regression analysis indicated that the IC in haematomas was independently associated with HE (odds ratio = 1.525; 95% confidence interval, 1.041-2.235; p = 0.030). ICs in haematoma and in spot sign were all independently associated with HE. IC analysis in spectral imaging may help to identify SICH patients for targeted haemostatic therapy. • Iodine concentration in spot sign and haematoma can predict haematoma expansion • Spectral imaging could measure the IC inside the spot sign and haematoma • IC in spot sign improved the positive predictive value (PPV) cf. CTA.

What is an ROC curve?

PubMed

Hoo, Zhe Hui; Candlish, Jane; Teare, Dawn

2017-06-01

The paper by Body et al is concerned with the evaluation of decision aids, which can be used to identify potential acute coronary syndromes (ACS) in the ED. The authors previously developed the Manchester Acute Coronary Syndromes model (MACS) decision aid, which uses several clinical variables and two biomarkers to 'rule in' and 'rule out' ACS. However, one of the two biomarkers (heart-type fatty acid bindingprotein, H-FABP) is not widely used so a revised decision aid has been developed (Troponin-only Manchester Acute Coronary Syndromes, T-MACS), which include a single biomarker hs-cTnT. In this issue, the authors show how they derive a revised decision aid and describe its performance in a number of independent diagnostic cohort studies. Decision aids (as well as other types of 'diagnostic tests') are often evaluated in terms of diagnostic testing parameters such as the area under the receiver operating characteristic (ROC) curve, sensitivity and specificity. In this article, we explain how the ROC analysis is conducted and why it is an essential step towards developing a test with the desirable levels of sensitivity and specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Regional homogeneity of resting-state brain abnormalities in bipolar and unipolar depression.

PubMed

Liu, Chun-Hong; Ma, Xin; Wu, Xia; Zhang, Yu; Zhou, Fu-Chun; Li, Feng; Tie, Chang-Le; Dong, Jie; Wang, Yong-Jun; Yang, Zhi; Wang, Chuan-Yue

2013-03-05

Bipolar disorder patients experiencing a depressive episode (BD-dep) without an observed history of mania are often misdiagnosed and are consequently treated as having unipolar depression (UD), leading to inadequate treatment and poor outcomes. An essential solution to this problem is to identify objective biological markers that distinguish BD-dep and UD patients at an early stage. However, studies directly comparing the brain dysfunctions associated with BD-dep and UD are rare. More importantly, the specificity of the differences in brain activity between these mental disorders has not been examined. With whole-brain regional homogeneity analysis and region-of-interest (ROI) based receiver operating characteristic (ROC) analysis, we aimed to compare the resting-state brain activity of BD-dep and UD patients. Furthermore, we examined the specific differences and whether these differences were attributed to the brain abnormality caused by BD-dep, UD, or both. Twenty-one bipolar and 21 unipolar depressed patients, as well as 26 healthy subjects matched for gender, age, and educational levels, participated in the study. We compared the differences in the regional homogeneity (ReHo) of the BD-dep and UD groups and further identified their pathophysiological abnormality. In the brain regions showing a difference between the BD-dep and UD groups, we further conducted receptive operation characteristic (ROC) analyses to confirm the effectiveness of the identified difference in classifying the patients. We observed ReHo differences between the BD-dep and UD groups in the right ventrolateral middle frontal gyrus, right dorsal anterior insular, right ventral anterior insular, right cerebellum posterior gyrus, right posterior cingulate cortex, right parahippocampal gyrus, and left cerebellum anterior gyrus. Further ROI comparisons and ROC analysis on these ROIs showed that the right parahippocampal gyrus reflected abnormality specific to the BD-dep group, while the right middle frontal gyrus, the right dorsal anterior insular, the right cerebellum posterior gyrus, and the right posterior cingulate cortex showed abnormality specific to the UD group. We found brain regions showing resting state ReHo differences and examined their sensitivity and specificity, suggesting a potential neuroimaging biomarker to distinguish between BD-dep and UD patients. We further clarified the pathophysiological abnormality of these regions for each of the two patient populations. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantitative evaluation of the memory bias effect in ROC studies with PET/CT

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Pianou, Nicoletta; Georgakopoulos, Alexandros; Kafiri, Georgia; Pavlou, Spiros; Chatziioannou, Sofia

2012-02-01

PURPOSE. The purpose of the study was to evaluate the memory bias effect in ROC experiments with tomographic data and, specifically, in the evaluation of two different PET/CT protocols for the detection and diagnosis of recurrent thyroid cancer. MATERIALS AND METHODS. Two readers participated in an ROC experiment that evaluated tomographic images from 43 patients followed up for thyroid cancer recurrence. Readers evaluated first whole body PET/CT scans of the patients and then a combination of whole body and high-resolution head and neck scans of the same patients. The second set was read twice. Once within 48 hours of the first set and the second time at least a month later. The detection and diagnostic performances of the readers in the three reading sessions were assessed with the DBMMRMC and LABMRMC software using the area under the ROC curve as a performance index. Performances were also evaluated by comparing the number and the size of the detected abnormal foci among the three readings. RESULTS. There was no performance difference between first and second treatments. There were statistically significant differences between first and third, and second and third treatments showing that memory can seriously affect the outcome of ROC studies. CONCLUSION. Despite the fact that tomographic data involve numerous image slices per patient, the memory bias effect is present and substantial and should be carefully eliminated from analogous ROC experiments.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion.

PubMed

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F

2017-01-01

The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure's ability to predict A&E mortality and need for hospital admission to the ward or theatre. A total of 1053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κ lin =0.47), and maximum (κ max =0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66-0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69-0.79) was significantly greater than SATS (ROC 0.57; 0.53-0.60) with regard to need for admission. KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diagnostic accuracy of the Kampala Trauma Score using estimated Abbreviated Injury Scale scores and physician opinion

PubMed Central

Gardner, Andrew; Forson, Paa Kobina; Oduro, George; Stewart, Barclay; Dike, Nkechi; Glover, Paul; Maio, Ronald F.

2016-01-01

Background The Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores. Methods This was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure’s ability to predict A&E mortality and need for hospital admission to the ward or theatre. Results A total of 1,053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κlin=0.47), and maximum (κmax=0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66–0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69–0.79) was significantly greater than SATS (ROC 0.57; 0.53–0.60) with regard to need for admission. Conclusions KTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs. PMID:27908493

Target Detection and Identification Using Canonical Correlations Analysis and Subspace Partitioning

DTIC Science & Technology

2008-04-01

Fig. 2. ROCs for DCC, DCC-P, NNLS, and NNLSP (Present chemical=t1, background= t56 , SNR= 5 dB) alarm, or 1−specificity, and PD is the probability of...discrimination values are given in each ROC plot. In Fig. 2, we use t56 as the background, and t1 as the target chemical. The SNR is 5 dB. For each

Magnetic Resonance Imaging of Intracranial Hypotension: Diagnostic Value of Combined Qualitative Signs and Quantitative Metrics.

PubMed

Aslan, Kerim; Gunbey, Hediye Pinar; Tomak, Leman; Ozmen, Zafer; Incesu, Lutfi

The aim of this study was to investigate whether the use of combination quantitative metrics (mamillopontine distance [MPD], pontomesencephalic angle, and mesencephalon anterior-posterior/medial-lateral diameter ratios) with qualitative signs (dural enhancement, subdural collections/hematoma, venous engorgement, pituitary gland enlargements, and tonsillar herniations) provides a more accurate diagnosis of intracranial hypotension (IH). The quantitative metrics and qualitative signs of 34 patients and 34 control subjects were assessed by 2 independent observers. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative metrics and qualitative signs, and for the diagnosis of IH, optimum cutoff values of quantitative metrics were found with ROC analysis. Combined ROC curve was measured for the quantitative metrics, and qualitative signs combinations in determining diagnostic accuracy and sensitivity, specificity, and positive and negative predictive values were found, and the best model combination was formed. Whereas MPD and pontomesencephalic angle were significantly lower in patients with IH when compared with the control group (P < 0.001), mesencephalon anterior-posterior/medial-lateral diameter ratio was significantly higher (P < 0.001). For qualitative signs, the highest individual distinctive power was dural enhancement with area under the ROC curve (AUC) of 0.838. For quantitative metrics, the highest individual distinctive power was MPD with AUC of 0.947. The best accuracy in the diagnosis of IH was obtained by combination of dural enhancement, venous engorgement, and MPD with an AUC of 1.00. This study showed that the combined use of dural enhancement, venous engorgement, and MPD had diagnostic accuracy of 100 % for the diagnosis of IH. Therefore, a more accurate IH diagnosis can be provided with combination of quantitative metrics with qualitative signs.

Pulse Oximetry for the Detection of Obstructive Sleep Apnea Syndrome: Can the Memory Capacity of Oxygen Saturation Influence Their Diagnostic Accuracy?

PubMed Central

Nigro, Carlos A.; Dibur, Eduardo; Rhodius, Edgardo

2011-01-01

Objective. To assess the diagnostic ability of WristOx 3100 using its three different recording settings in patients with suspected obstructive sleep apnea syndrome (OSAS). Methods. All participants (135) performed the oximetry (three oximeters WristOx 3100) and polysomnography (PSG) simultaneously in the sleep laboratory. Both recordings were interpreted blindly. Each oximeter was set to one of three different recording settings (memory capabilities 0.25, 0.5, and 1 Hz). The software (nVision 5.1) calculated the adjusted O2 desaturation index-mean number of O2 desaturation per hour of analyzed recording ≥2, 3, and 4% (ADI2, 3, and 4). The ADI2, 3, and 4 cutoff points that better discriminated between subjects with or without OSAS arose from the receiver-operator characteristics (ROCs) curve analysis. OSAS was defined as a respiratory disturbance index (RDI) ≥ 5. Results. 101 patients were included (77 men, mean age 52, median RDI 22.6, median BMI 27.4 kg/m2). The area under the ROCs curves (AUC-ROCs) of ADI2, 3, and 4 with different data storage rates were similar (AUC-ROCs with data storage rates of 0.25/0.5/1 Hz: ADI2: 0.958/0.948/0.965, ADI3: 0.961/0.95/0.966, and ADI4: 0.957/0.949/0.963, P NS). Conclusions. The ability of WristOx 3100 to detect patients with OSAS was not affected by the data storage rate of the oxygen saturation signal. Both memory capacity of 0.25, 0.5, or 1 Hz showed a similar performance for the diagnosis of OSAS. PMID:23471171

The ROC Curves of Fused Independent Classification Systems

DTIC Science & Technology

2008-09-01

spectral settings arises in many fields of study; in medicine, the detection of a cancer; in marketing , the detection of the best customer base; in the...p ≤ 0.4 p/3 + 2/3, 0.4 ≤ p ≤ 1.0 fB(p) = tanh( 4p ) fC(p) = p1/3 The following plots will show how these ROC curves combine, and how the optimal

Measurements of diagnostic examination performance and correlation analysis using microvascular leakage, cerebral blood volume, and blood flow derived from 3T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in glial tumor grading.

PubMed

Server, Andrés; Graff, Bjørn A; Orheim, Tone E Døli; Schellhorn, Till; Josefsen, Roger; Gadmar, Øystein B; Nakstad, Per H

2011-06-01

To assess the diagnostic accuracy of microvascular leakage (MVL), cerebral blood volume (CBV) and blood flow (CBF) values derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC-MR imaging) for grading of cerebral glial tumors, and to estimate the correlation between vascular permeability/perfusion parameters and tumor grades. A prospective study of 79 patients with cerebral glial tumors underwent DSC-MR imaging. Normalized relative CBV (rCBV) and relative CBF (rCBF) from tumoral (rCBVt and rCBFt), peri-enhancing region (rCBVe and rCBFe), and the value in the tumor divided by the value in the peri-enhancing region (rCBVt/e and rCBFt/e), as well as MVL, expressed as the leakage coefficient K(2) were calculated. Hemodynamic variables and tumor grades were analyzed statistically and with Pearson correlations. Receiver operating characteristic (ROC) curve analyses were also performed for each of the variables. The differences in rCBVt and the maximum MVL (MVL(max)) values were statistically significant among all tumor grades. Correlation analysis using Pearson was as follows: rCBVt and tumor grade, r = 0.774; rCBFt and tumor grade, r = 0.417; MVL(max) and tumor grade, r = 0.559; MVL(max) and rCBVt, r = 0.440; MVL(max) and rCBFt, r = 0.192; and rCBVt and rCBFt, r = 0.605. According to ROC analyses for distinguishing tumor grade, rCBVt showed the largest areas under ROC curve (AUC), except for grade III from IV. Both rCBVt and MVL(max) showed good discriminative power in distinguishing all tumor grades. rCBVt correlated strongly with tumor grade; the correlation between MVL(max) and tumor grade was moderate.

Bioimpedance spectroscopy can precisely discriminate human breast carcinoma from benign tumors.

PubMed

Du, Zhenggui; Wan, Hangyu; Chen, Yu; Pu, Yang; Wang, Xiaodong

2017-01-01

Intraoperative frozen pathology is critical when a breast tumor is not diagnosed before surgery. However, frozen tumor tissues always present various microscopic morphologies, leading to a high misdiagnose rate from frozen section examination. Thus, we aimed to identify breast tumors using bioimpedance spectroscopy (BIS), a technology that measures the tissues' impedance. We collected and measured 976 specimens from breast patients during surgery, including 581 breast cancers, 190 benign tumors, and 205 normal mammary gland tissues. After measurement, Cole-Cole curves were generated by a bioimpedance analyzer and parameters R0/R∞, fc, and α were calculated from the curve. The Cole-Cole curves showed a trend to differentiate mammary gland, benign tumors, and cancer. However, there were some curves overlapped with other groups, showing that it is not an ideal model. Subsequent univariate analysis of R0/R∞, fc, and α showed significant differences between benign tumor and cancer. However, receiver operating characteristic (ROC) analysis indicated the diagnostic value of fc and R0/R∞ were not superior to frozen sections (area under curve [AUC] = 0.836 and 0.849, respectively), and α was useless in diagnosis (AUC = 0.596). After further research, we found a scatter diagram that showed a synergistic effect of the R0/R∞ and fc, in discriminating cancer from benign tumors. Thus, we used multivariate analysis, which revealed that these two parameters were independent predictors, to combine them. A simplified equation, RF = 0.2fc + 3.6R0/R∞, based on multivariate analysis was developed. The ROC curve for RF' showed an AUC = 0.939, and the sensitivity and specificity were 82.62% and 95.79%, respectively. To match a clinical setting, the diagnostic criteria were set at 6.91 and 12.9 for negative and positive diagnosis, respectively. In conclusion, RF' derived from BIS can discriminate benign tumor and cancers, and integrated criteria were developed for diagnosis.

Bioimpedance spectroscopy can precisely discriminate human breast carcinoma from benign tumors

PubMed Central

Du, Zhenggui; Wan, Hangyu; Chen, Yu; Pu, Yang; Wang, Xiaodong

2017-01-01

Abstract Intraoperative frozen pathology is critical when a breast tumor is not diagnosed before surgery. However, frozen tumor tissues always present various microscopic morphologies, leading to a high misdiagnose rate from frozen section examination. Thus, we aimed to identify breast tumors using bioimpedance spectroscopy (BIS), a technology that measures the tissues’ impedance. We collected and measured 976 specimens from breast patients during surgery, including 581 breast cancers, 190 benign tumors, and 205 normal mammary gland tissues. After measurement, Cole-Cole curves were generated by a bioimpedance analyzer and parameters R0/R∞, fc, and α were calculated from the curve. The Cole-Cole curves showed a trend to differentiate mammary gland, benign tumors, and cancer. However, there were some curves overlapped with other groups, showing that it is not an ideal model. Subsequent univariate analysis of R0/R∞, fc, and α showed significant differences between benign tumor and cancer. However, receiver operating characteristic (ROC) analysis indicated the diagnostic value of fc and R0/R∞ were not superior to frozen sections (area under curve [AUC] = 0.836 and 0.849, respectively), and α was useless in diagnosis (AUC = 0.596). After further research, we found a scatter diagram that showed a synergistic effect of the R0/R∞ and fc, in discriminating cancer from benign tumors. Thus, we used multivariate analysis, which revealed that these two parameters were independent predictors, to combine them. A simplified equation, RF′ = 0.2fc + 3.6R0/R∞, based on multivariate analysis was developed. The ROC curve for RF′ showed an AUC = 0.939, and the sensitivity and specificity were 82.62% and 95.79%, respectively. To match a clinical setting, the diagnostic criteria were set at 6.91 and 12.9 for negative and positive diagnosis, respectively. In conclusion, RF′ derived from BIS can discriminate benign tumor and cancers, and integrated criteria were developed for diagnosis. PMID:28121948

Sensitivity and specificity of machine learning classifiers and spectral domain OCT for the diagnosis of glaucoma.

PubMed

Vidotti, Vanessa G; Costa, Vital P; Silva, Fabrício R; Resende, Graziela M; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S

2012-06-15

Purpose. To investigate the sensitivity and specificity of machine learning classifiers (MLC) and spectral domain optical coherence tomography (SD-OCT) for the diagnosis of glaucoma. Methods. Sixty-two patients with early to moderate glaucomatous visual field damage and 48 healthy individuals were included. All subjects underwent a complete ophthalmologic examination, achromatic standard automated perimetry, and RNFL imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, California, USA). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters. Subsequently, the following MLCs were tested: Classification Tree (CTREE), Random Forest (RAN), Bagging (BAG), AdaBoost M1 (ADA), Ensemble Selection (ENS), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Naive-Bayes (NB), and Support Vector Machine (SVM). Areas under the ROC curves (aROCs) obtained for each parameter and each MLC were compared. Results. The mean age was 57.0±9.2 years for healthy individuals and 59.9±9.0 years for glaucoma patients (p=0.103). Mean deviation values were -4.1±2.4 dB for glaucoma patients and -1.5±1.6 dB for healthy individuals (p<0.001). The SD-OCT parameters with the greater aROCs were inferior quadrant (0.813), average thickness (0.807), 7 o'clock position (0.765), and 6 o'clock position (0.754). The aROCs from classifiers varied from 0.785 (ADA) to 0.818 (BAG). The aROC obtained with BAG was not significantly different from the aROC obtained with the best single SD-OCT parameter (p=0.93). Conclusions. The SD-OCT showed good diagnostic accuracy in a group of patients with early glaucoma. In this series, MLCs did not improve the sensitivity and specificity of SD-OCT for the diagnosis of glaucoma.

Evaluation of computer-aided detection of lesions in mammograms obtained with a digital phase-contrast mammography system.

PubMed

Tanaka, Toyohiko; Nitta, Norihisa; Ohta, Shinichi; Kobayashi, Tsuyoshi; Kano, Akiko; Tsuchiya, Keiko; Murakami, Yoko; Kitahara, Sawako; Wakamiya, Makoto; Furukawa, Akira; Takahashi, Masashi; Murata, Kiyoshi

2009-12-01

A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P = 0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P = 0.034) and from 0.947 to 0.962 for masses (P = 0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.

Memorial familiarity remains intact for pictures but not for words in patients with amnestic mild cognitive impairment.

PubMed

Embree, Lindsay M; Budson, Andrew E; Ally, Brandon A

2012-07-01

Understanding how memory breaks down in the earliest stages of Alzheimer's disease (AD) process has significant implications, both clinically and with respect to intervention development. Previous work has highlighted a robust picture superiority effect in patients with amnestic mild cognitive impairment (aMCI). However, it remains unclear as to how pictures improve memory compared to words in this patient population. In the current study, we utilized receiver operating characteristic (ROC) curves to obtain estimates of familiarity and recollection for pictures and words in patients with aMCI and healthy older controls. Analysis of accuracy shows that even when performance is matched between pictures and words in the healthy control group, patients with aMCI continue to show a significant picture superiority effect. The results of the ROC analysis showed that patients demonstrated significantly impaired recollection and familiarity for words compared controls. In contrast, patients with aMCI demonstrated impaired recollection, but intact familiarity for pictures, compared to controls. Based on previous work from our lab, we speculate that patients can utilize the rich conceptual information provided by pictures to enhance familiarity, and perceptual information may allow for post-retrieval monitoring or verification of the enhanced sense of familiarity. Alternatively, the combination of enhanced conceptual and perceptual fluency of the test item might drive a stronger or more robust sense of familiarity that can be accurately attributed to a studied item. Copyright © 2012 Elsevier Ltd. All rights reserved.

Memorial familiarity remains intact for pictures but not for words in patients with amnestic mild cognitive impairment

PubMed Central

Embree, Lindsay M.; Budson, Andrew E.; Ally, Brandon A.

2012-01-01

Understanding how memory breaks down in the earliest stages of the Alzheimer’s disease (AD) process has significant implications, both clinically and with respect to intervention development. Previous work has highlighted a robust picture superiority effect in patients with amnestic mild cognitive impairment (aMCI). However, it remains unclear as to how pictures improve memory compared to words in this patient population. In the current study, we utilized receiver operating characteristic (ROC) curves to obtain estimates of familiarity and recollection for pictures and words in patients with aMCI and healthy older controls. Analysis of accuracy shows that even when performance is matched between pictures and words in the healthy control group, patients with aMCI continue to show a significant picture superiority effect. The results of the ROC analysis showed that patients demonstrated significantly impaired recollection and familiarity for words compared controls. In contrast, patients with aMCI demonstrated impaired recollection, but intact familiarity for pictures, compared to controls. Based on previous work from our lab, we speculate that patients can utilize the rich conceptual information provided by pictures to enhance familiarity, and perceptual information may allow for post-retrieval monitoring or verification of the enhanced sense of familiarity. Alternatively, the combination of enhanced conceptual and perceptual fluency of the test item might drive a stronger or more robust sense of familiarity that can be accurately attributed to a studied item. PMID:22705441

Contrast-enhanced spectral mammography improves diagnostic accuracy in the symptomatic setting.

PubMed

Tennant, S L; James, J J; Cornford, E J; Chen, Y; Burrell, H C; Hamilton, L J; Girio-Fragkoulakis, C

2016-11-01

To assess the diagnostic accuracy of contrast-enhanced spectral mammography (CESM), and gauge its "added value" in the symptomatic setting. A retrospective multi-reader review of 100 consecutive CESM examinations was performed. Anonymised low-energy (LE) images were reviewed and given a score for malignancy. At least 3 weeks later, the entire examination (LE and recombined images) was reviewed. Histopathology data were obtained for all cases. Differences in performance were assessed using receiver operator characteristic (ROC) analysis. Sensitivity, specificity, and lesion size (versus MRI or histopathology) differences were calculated. Seventy-three percent of cases were malignant at final histology, 27% were benign following standard triple assessment. ROC analysis showed improved overall performance of CESM over LE alone, with area under the curve of 0.93 versus 0.83 (p<0.025). CESM showed increased sensitivity (95% versus 84%, p<0.025) and specificity (81% versus 63%, p<0.025) compared to LE alone, with all five readers showing improved accuracy. Tumour size estimation at CESM was significantly more accurate than LE alone, the latter tending to undersize lesions. In 75% of cases, CESM was deemed a useful or significant aid to diagnosis. CESM provides immediately available, clinically useful information in the symptomatic clinic in patients with suspicious palpable abnormalities. Radiologist sensitivity, specificity, and size accuracy for breast cancer detection and staging are all improved using CESM as the primary mammographic investigation. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Mixing Strong and Weak Targets Provides No Evidence against the Unequal-Variance Explanation of zRoc Slope: A Comment on Koen and Yonelinas (2010)

ERIC Educational Resources Information Center

Starns, Jeffrey J.; Rotello, Caren M.; Ratcliff, Roger

2012-01-01

Koen and Yonelinas (2010; K&Y) reported that mixing classes of targets that had short (weak) or long (strong) study times had no impact on zROC slope, contradicting the predictions of the encoding variability hypothesis. We show that they actually derived their predictions from a mixture unequal-variance signal detection (UVSD) model, which…

On the meaning of the weighted alternative free-response operating characteristic figure of merit.

PubMed

Chakraborty, Dev P; Zhai, Xuetong

2016-05-01

The free-response receiver operating characteristic (FROC) method is being increasingly used to evaluate observer performance in search tasks. Data analysis requires definition of a figure of merit (FOM) quantifying performance. While a number of FOMs have been proposed, the recommended one, namely, the weighted alternative FROC (wAFROC) FOM, is not well understood. The aim of this work is to clarify the meaning of this FOM by relating it to the empirical area under a proposed wAFROC curve. The weighted wAFROC FOM is defined in terms of a quasi-Wilcoxon statistic that involves weights, coding the clinical importance, assigned to each lesion. A new wAFROC curve is proposed, the y-axis of which incorporates the weights, giving more credit for marking clinically important lesions, while the x-axis is identical to that of the AFROC curve. An expression is derived relating the area under the empirical wAFROC curve to the wAFROC FOM. Examples are presented with small numbers of cases showing how AFROC and wAFROC curves are affected by correct and incorrect decisions and how the corresponding FOMs credit or penalize these decisions. The wAFROC, AFROC, and inferred ROC FOMs were applied to three clinical data sets involving multiple reader FROC interpretations in different modalities. It is shown analytically that the area under the empirical wAFROC curve equals the wAFROC FOM. This theorem is the FROC analog of a well-known theorem developed in 1975 for ROC analysis, which gave meaning to a Wilcoxon statistic based ROC FOM. A similar equivalence applies between the area under the empirical AFROC curve and the AFROC FOM. The examples show explicitly that the wAFROC FOM gives equal importance to all diseased cases, regardless of the number of lesions, a desirable statistical property not shared by the AFROC FOM. Applications to the clinical data sets show that the wAFROC FOM yields results comparable to that using the AFROC FOM. The equivalence theorem gives meaning to the weighted AFROC FOM, namely, it is identical to the empirical area under weighted AFROC curve.

A new method to predict anatomical outcome after idiopathic macular hole surgery.

PubMed

Liu, Peipei; Sun, Yaoyao; Dong, Chongya; Song, Dan; Jiang, Yanrong; Liang, Jianhong; Yin, Hong; Li, Xiaoxin; Zhao, Mingwei

2016-04-01

To investigate whether a new macular hole closure index (MHCI) could predict anatomic outcome of macular hole surgery. A vitrectomy with internal limiting membrane peeling, air-fluid exchange, and gas tamponade were performed on all patients. The postoperative anatomic status of the macular hole was defined by spectral-domain OCT. MHCI was calculated as (M+N)/BASE based on the preoperative OCT status. M and N were the curve lengths of the detached photoreceptor arms, and BASE was the length of the retinal pigment epithelial layer (RPE layer) detaching from the photoreceptors. Postoperative anatomical outcomes were divided into three grades: A (bridge-like closure), B (good closure), and C (poor closure or no closure). Correlation analysis was performed between anatomical outcomes and MHCI. Receiver operating characteristic (ROC) curves were derived for MHCI, indicating good model discrimination. ROC curves were also assessed by the area under the curve, and cut-offs were calculated. Other predictive parameters reported previously, which included the MH minimum, the MH height, the macular hole index (MHI), the diameter hole index (DHI), and the tractional hole index (THI) had been compared as well. MHCI correlated significantly with postoperative anatomical outcomes (r = 0.543, p = 0.000), but other predictive parameters did not. The areas under the curves indicated that MHCI could be used as an effective predictor of anatomical outcome. Cut-off values of 0.7 and 1.0 were obtained for MHCI from ROC curve analysis. MHCI demonstrated a better predictive effect than other parameters, both in the correlation analysis and ROC analysis. MHCI could be an easily measured and accurate predictive index for postoperative anatomical outcomes.

A better way to evaluate remote monitoring programs in chronic disease care: receiver operating characteristic analysis.

PubMed

Brown Connolly, Nancy E

2014-12-01

This foundational study applies the process of receiver operating characteristic (ROC) analysis to evaluate utility and predictive value of a disease management (DM) model that uses RM devices for chronic obstructive pulmonary disease (COPD). The literature identifies a need for a more rigorous method to validate and quantify evidence-based value for remote monitoring (RM) systems being used to monitor persons with a chronic disease. ROC analysis is an engineering approach widely applied in medical testing, but that has not been evaluated for its utility in RM. Classifiers (saturated peripheral oxygen [SPO2], blood pressure [BP], and pulse), optimum threshold, and predictive accuracy are evaluated based on patient outcomes. Parametric and nonparametric methods were used. Event-based patient outcomes included inpatient hospitalization, accident and emergency, and home health visits. Statistical analysis tools included Microsoft (Redmond, WA) Excel(®) and MedCalc(®) (MedCalc Software, Ostend, Belgium) version 12 © 1993-2013 to generate ROC curves and statistics. Persons with COPD were monitored a minimum of 183 days, with at least one inpatient hospitalization within 12 months prior to monitoring. Retrospective, de-identified patient data from a United Kingdom National Health System COPD program were used. Datasets included biometric readings, alerts, and resource utilization. SPO2 was identified as a predictive classifier, with an optimal average threshold setting of 85-86%. BP and pulse were failed classifiers, and areas of design were identified that may improve utility and predictive capacity. Cost avoidance methodology was developed. RESULTS can be applied to health services planning decisions. Methods can be applied to system design and evaluation based on patient outcomes. This study validated the use of ROC in RM program evaluation.

Hair analysis for detection of triptans occasionally used or overused by migraine patients-a pilot study.

PubMed

Ferrari, Anna; Baraldi, Carlo; Licata, Manuela; Vandelli, Daniele; Marchesi, Filippo; Palazzoli, Federica; Verri, Patrizia; Rustichelli, Cecilia; Giuliani, Enrico; Silingardi, Enrico

2016-09-01

The aim of this study is to evaluate the detection rate of almotriptan, eletriptan, frovatriptan, sumatriptan, rizatriptan, and zolmitriptan in the hair of migraineurs taking these drugs; the degree of agreement between type of self-reported triptan and triptan found in hair; if the concentrations in hair were related to the reported cumulative doses of triptans; and whether hair analysis was able to distinguish occasional use from the overuse of these drugs. Out of 300 headache patients consecutively enrolled, we included 147 migraine patients who reported to have taken at least one dose of one triptan in the previous 3 months; 51 % of the patients overused triptans. A detailed pharmacological history and a sample of hair were collected for each patient. Hair samples were analyzed by liquid chromatography-electrospray tandem mass spectrometry (LC-MS/MS) by a method that we developed. All the triptans could be detected in the hair of the patients. The agreement between type of self-reported triptan and type of triptan found in hair was from fair to good for frovatriptan and zolmitriptan and excellent for almotriptan, eletriptan, sumatriptan, and rizatriptan (P < 0.01, Cohen's kappa). The correlation between the reported quantities of triptan and hair concentrations was statistically significant for almotriptan, eletriptan, rizatriptan, and sumatriptan (P < 0.01, Spearman's rank correlation coefficient). The accuracy of hair analysis in distinguishing occasionally users from overusers was high for almotriptan (ROC AUC = 0.9092), eletriptan (ROC AUC = 0.8721), rizatriptan (ROC AUC = 0.9724), and sumatriptan (ROC AUC = 0.9583). Hair analysis can be a valuable system to discriminate occasional use from triptan overuse.

Predictive value of pulse pressure variation for fluid responsiveness in septic patients using lung-protective ventilation strategies.

PubMed

Freitas, F G R; Bafi, A T; Nascente, A P M; Assunção, M; Mazza, B; Azevedo, L C P; Machado, F R

2013-03-01

The applicability of pulse pressure variation (ΔPP) to predict fluid responsiveness using lung-protective ventilation strategies is uncertain in clinical practice. We designed this study to evaluate the accuracy of this parameter in predicting the fluid responsiveness of septic patients ventilated with low tidal volumes (TV) (6 ml kg(-1)). Forty patients after the resuscitation phase of severe sepsis and septic shock who were mechanically ventilated with 6 ml kg(-1) were included. The ΔPP was obtained automatically at baseline and after a standardized fluid challenge (7 ml kg(-1)). Patients whose cardiac output increased by more than 15% were considered fluid responders. The predictive values of ΔPP and static variables [right atrial pressure (RAP) and pulmonary artery occlusion pressure (PAOP)] were evaluated through a receiver operating characteristic (ROC) curve analysis. Thirty-four patients had characteristics consistent with acute lung injury or acute respiratory distress syndrome and were ventilated with high levels of PEEP [median (inter-quartile range) 10.0 (10.0-13.5)]. Nineteen patients were considered fluid responders. The RAP and PAOP significantly increased, and ΔPP significantly decreased after volume expansion. The ΔPP performance [ROC curve area: 0.91 (0.82-1.0)] was better than that of the RAP [ROC curve area: 0.73 (0.59-0.90)] and pulmonary artery occlusion pressure [ROC curve area: 0.58 (0.40-0.76)]. The ROC curve analysis revealed that the best cut-off for ΔPP was 6.5%, with a sensitivity of 0.89, specificity of 0.90, positive predictive value of 0.89, and negative predictive value of 0.90. Automatized ΔPP accurately predicted fluid responsiveness in septic patients ventilated with low TV.

[Relationships between soil and rocky desertification in typical karst mountain area based on redundancy analysis].

PubMed

Long, Jian; Liao, Hong-Kai; Li, Juan; Chen, Cai-Yun

2012-06-01

Redundancy analysis (RDA) was employed to reveal the relationships between soil and rocky desertification through vegetation investigation and analysis of soil samples collected in typical karst mountain area of southwest Guizhou Province. The results showed that except TP, TK and ACa, all other variables including SOC, TN, MBC, ROC, DOC, available nutrients and basal respiration showed significant downward trends during the rocky desertification process. RDA results showed significant correlations between different types of desertification and soil variables, described as non-degraded > potential desertification > light desertification > moderate desertification > severe desertification. Moreover, RDA showed that using SOC, TN, AN, and BD as soil indicators, 74.4% of the variance information on soil and rocky desertification could be explained. Furthermore, the results of correlation analysis showed that soil variables were significantly affected by surface vegetation. Considering the ecological function of the aboveground vegetation and the soil quality, Zanthoxylum would be a good choice for restoration of local vegetation in karst mountain area.

Modification and Validation of the Triglyceride-to-HDL Cholesterol Ratio as a Surrogate of Insulin Sensitivity in White Juveniles and Adults without Diabetes Mellitus: The Single Point Insulin Sensitivity Estimator (SPISE).

PubMed

Paulmichl, Katharina; Hatunic, Mensud; Højlund, Kurt; Jotic, Aleksandra; Krebs, Michael; Mitrakou, Asimina; Porcellati, Francesca; Tura, Andrea; Bergsten, Peter; Forslund, Anders; Manell, Hannes; Widhalm, Kurt; Weghuber, Daniel; Anderwald, Christian-Heinz

2016-09-01

The triglyceride-to-HDL cholesterol (TG/HDL-C) ratio was introduced as a tool to estimate insulin resistance, because circulating lipid measurements are available in routine settings. Insulin, C-peptide, and free fatty acids are components of other insulin-sensitivity indices but their measurement is expensive. Easier and more affordable tools are of interest for both pediatric and adult patients. Study participants from the Relationship Between Insulin Sensitivity and Cardiovascular Disease [43.9 (8.3) years, n = 1260] as well as the Beta-Cell Function in Juvenile Diabetes and Obesity study cohorts [15 (1.9) years, n = 29] underwent oral-glucose-tolerance tests and euglycemic clamp tests for estimation of whole-body insulin sensitivity and calculation of insulin sensitivity indices. To refine the TG/HDL ratio, mathematical modeling was applied including body mass index (BMI), fasting TG, and HDL cholesterol and compared to the clamp-derived M-value as an estimate of insulin sensitivity. Each modeling result was scored by identifying insulin resistance and correlation coefficient. The Single Point Insulin Sensitivity Estimator (SPISE) was compared to traditional insulin sensitivity indices using area under the ROC curve (aROC) analysis and χ(2) test. The novel formula for SPISE was computed as follows: SPISE = 600 × HDL-C(0.185)/(TG(0.2) × BMI(1.338)), with fasting HDL-C (mg/dL), fasting TG concentrations (mg/dL), and BMI (kg/m(2)). A cutoff value of 6.61 corresponds to an M-value smaller than 4.7 mg · kg(-1) · min(-1) (aROC, M:0.797). SPISE showed a significantly better aROC than the TG/HDL-C ratio. SPISE aROC was comparable to the Matsuda ISI (insulin sensitivity index) and equal to the QUICKI (quantitative insulin sensitivity check index) and HOMA-IR (homeostasis model assessment-insulin resistance) when calculated with M-values. The SPISE seems well suited to surrogate whole-body insulin sensitivity from inexpensive fasting single-point blood draw and BMI in white adolescents and adults. © 2016 American Association for Clinical Chemistry.

[Mobbing, organizational dysfunction and bio-psycho-social effects: an integrated assessment. Preliminary data for the validation of the Questionnaire in the Neapoletan dialect on Distress at Work(Qn-DL)].

PubMed

Nolfe, Giovanni; Petrella, Claudio; Triassi, Maria; Zontini, Gemma; Uttieri, Simona; Pagliaro, Alessia; Blasi, Francesco; Cappuccio, Antonella; Nolfe, Giuseppe

2013-01-01

The aim of this study is to produce preliminary data about the validation of the "Naples-Questionnaire of Distress at Work" (nQ.DW). This inventory is a new assessment tool in order to evaluate the distress perceived in the working environment by means of the differentiation of the conditions linked to the mobbing from which related to organizational disfunction. The nQ-DW also measures the bio-psycho-social global effects of these two phenomena. The questionnaire has been administered to workers suffering of a psychopathological disturbance related to work distress and to a control group matched for the sociodemographic and working variables. The statistical analysis demonstrated a significant validity and reliability. The degree of internal coherence was satisfactory. The ROC curves allow the determination of a threshold value which allows to separate the workers subjected to mobbing and/or organizational stress from control-workers with an optimal reliability degree. The values of the area under the ROC curves show that the inventory has a high discriminating capacity. Future studies, based on a greater sample size, will be oriented to the analysis of the questionnaire by means of multivariate techniques like the factorial analysis.

Development and Validation Study of the Internet Overuse Screening Questionnaire

PubMed Central

Lee, Han-Kyeong; Lee, Hae-Woo; Han, Joo Hyun; Park, Subin; Ju, Seok-Jin; Choi, Kwanwoo; Lee, Ji Hyeon; Jeon, Hong Jin

2018-01-01

Objective Concerns over behavioral and emotional problems caused by excessive internet usage have been developed. This study intended to develop and a standardize questionnaire that can efficiently identify at-risk internet users through their internet usage habits. Methods Participants (n=158) were recruited at six I-will-centers located in Seoul, South Korea. From the initial 36 questionnaire item pool, 28 preliminary items were selected through expert evaluation and panel discussions. The construct validity, internal consistency, and concurrent validity were examined. We also conducted Receiver Operating Curve (ROC) analysis to assess diagnostic ability of the Internet Overuse Screening-Questionnaire (IOS-Q). Results The exploratory factor analysis yielded a five factor structure. Four factors with 17 items remained after items that had unclear factor loading were removed. The Cronbach’s alpha for the IOS-Q total score was 0.91, and test-retest reliability was 0.72. The correlation between Young’s internet addiction scale and K-scale supported concurrent validity. ROC analysis showed that the IOS-Q has superior diagnostic ability with the Area Under the Curve of 0.87. At the cut-off point of 25.5, the sensitivity was 0.93 and specificity was 0.86. Conclusion Overall, this study supports the use of IOS-Q for internet addiction research and for screening high-risk individuals. PMID:29669406

FIESTA ROC: A new finite element analysis program for solar cell simulation

NASA Technical Reports Server (NTRS)

Clark, Ralph O.

1991-01-01

The Finite Element Semiconductor Three-dimensional Analyzer by Ralph O. Clark (FIESTA ROC) is a computational tool for investigating in detail the performance of arbitrary solar cell structures. As its name indicates, it uses the finite element technique to solve the fundamental semiconductor equations in the cell. It may be used for predicting the performance (thereby dictating the design parameters) of a proposed cell or for investigating the limiting factors in an established design.

Diagnostic accuracy of presepsin (sCD14-ST) as a biomarker of infection and sepsis in the emergency department.

PubMed

de Guadiana Romualdo, Luis García; Torrella, Patricia Esteban; Acebes, Sergio Rebollo; Otón, María Dolores Albaladejo; Sánchez, Roberto Jiménez; Holgado, Ana Hernando; Santos, Enrique Jiménez; Freire, Alejandro Ortín

2017-01-01

Presepsin is a promising biomarker for the diagnosis and prognosis of sepsis. However, results reported about its value to diagnose sepsis in an emergency department (ED) are controversial, probably due to differences in the design of the studies. We have evaluated the diagnostic accuracy of presepsin for infection and sepsis, compared with procalcitonin (PCT) and C-reactive protein (CRP), in patients presenting to the emergency department (ED) with suspected infection. 223 patients with suspected infection were enrolled for the study. Blood samples were collected on admission for measurement of biomarkers. Definitive diagnosis was obtained afterwards by analysis of digital medical records. Receiver operating characteristic (ROC) curve analysis was conducted to determine the diagnostic accuracy. Infection was confirmed in 200 patients, including 130 with non-complicated infection and 70 with sepsis. Median CRP, PCT and presepsin levels were significantly higher in patients with infection and sepsis. PCT was the biomarker with the highest performance for infection (ROC AUC: 0.910); for sepsis, PCT (ROC AUC: 0.815) and presepsin (ROC AUC: 0.775) shown a similar performance. Although presepsin is a valuable biomarker for diagnosis of infection and sepsis, its diagnostic accuracy in our study does not improve that of PCT. Its introduction in clinical practice is not justified. Copyright © 2016 Elsevier B.V. All rights reserved.

[Establish Assessment Model of 18 Years of Age in Chinese Han Population by Mandibular Third Molar].

PubMed

Fan, Fei; Dai, Xin-hua; Wang, Liang; Li, Yuan; Zhang, Kui; Deng, Zhen-hua

2016-02-01

To explore the value of estimating chronologic age based on the grades of mandibular third molar development. To evaluate whether mandibular third molar could be used as an indicator for estimating the age under or over 18 years. The mineralization status of mandibular third molar of 1 845 individuals aged 10 - 30 was graded and marked based on Demirjian's classification of grades reformed by Orhan. Gender difference was examined by t-test. A cubic regression model was established to analyze the correlation between third molar and chronologic age. Each grade of age cumulative distribution diagram and ROC curve was respectively performed to evaluate the relationship between third molar and the age of 18. Using Bayes discriminant analysis, an equation was established for estimating the age of 18. The inner-rater reliability was 0.903. Statistical analysis showed a moderate correlation between age and grade. Significant differences of both genders were found only in grade D and H (P < 0.05). Males at the grades from 1 to D and females at the grades from 1 to C were under 18 years old, and both males and females at grade H were over 18 years old. The area under the ROC curve was 0.797 (P < 0.05). Third molar development shows a high correlation with age, and combined with other indicators, it can be used to estimate the age of 18.

Versican and its associated molecules: potential diagnostic markers for multiple myeloma.

PubMed

Gupta, Nidhi; Khan, Rehan; Kumar, Raman; Kumar, Lalit; Sharma, Alpana

2015-03-10

Multiple myeloma (MM) represents a malignancy of B-cells characterized by proliferation of malignant plasma cells in the bone marrow (BM). Versican (VCAN), an extracellular matrix (ECM) protein, appears to be involved in multiple processes in several cancers. Identifying optimum diagnostic markers and delineating its association with disease severity might be important for controlling MM. Expression of VCAN and its associated molecules (β-catenin, β1 integrin and FAK) were investigated in 60 subjects to evaluate their usefulness as diagnostic marker. Circulatory and molecular levels of above molecules were analyzed in their BM and Blood using ELISA, Q-PCR and western blotting along with their ROC curve analysis. Circulatory levels of VCAN, β-catenin and FAK were significantly higher in patients with varying significance in each stage. β-Catenin and FAK intracellular levels were significantly elevated in patients. mRNA levels of all molecules were significantly higher in BMMNCs while VCAN and β-catenin also showed increase in PBMCs. Upregulation of these molecules was also observed at protein level. ROC curve analysis for VCAN showed absolute combination of sensitivity and specificity for diagnosis in serum. Significant elevation of VCAN and its associated molecules imply their role in MM. Optimal sensitivity and specificity of VCAN might utilize its importance as potential marker for active disease. Copyright © 2015 Elsevier B.V. All rights reserved.

Diagnostic depressive symptoms of the mixed bipolar episode.

PubMed

Cassidy, F; Ahearn, E; Murry, E; Forest, K; Carroll, B J

2000-03-01

There is not yet consensus on the best diagnostic definition of mixed bipolar episodes. Many have suggested the DSM-III-R/-IV definition is too rigid. We propose alternative criteria using data from a large patient cohort. We evaluated 237 manic in-patients using DSM-III-R criteria and the Scale for Manic States (SMS). A bimodally distributed factor of dysphoric mood has been reported from the SMS data. We used both the factor and the DSM-III-R classifications to identify candidate depressive symptoms and then developed three candidate depressive symptom sets. Using ROC analysis we determined the optimal threshold number of symptoms in each set and compared the three ROC solutions. The optimal solution was tested against the DSM-III-R classification for crossvalidation. The optimal ROC solution was a set, derived from both the DSM-III-R and the SMS, and the optimal threshold for diagnosis was two or more symptoms. Applying this set iteratively to the DSM-III-R classification produced the identical ROC solution. The prevalence of mixed episodes in the cohort was 13.9% by DSM-III-R, 20.2% by the dysphoria factor and 27.4% by the new ROC solution. A diagnostic set of six dysphoric symptoms (depressed mood, anhedonia, guilt, suicide, fatigue and anxiety), with a threshold of two symptoms, is proposed for a mixed episode. This new definition has a foundation in clinical data, in the proved diagnostic performance of the qualifying symptoms, and in ROC validation against two previous definitions that each have face validity.

Factors related to clinical pregnancy after vitrified-warmed embryo transfer: a retrospective and multivariate logistic regression analysis of 2313 transfer cycles.

PubMed

Shi, Wenhao; Zhang, Silin; Zhao, Wanqiu; Xia, Xue; Wang, Min; Wang, Hui; Bai, Haiyan; Shi, Juanzi

2013-07-01

What factors does multivariate logistic regression show to be significantly associated with the likelihood of clinical pregnancy in vitrified-warmed embryo transfer (VET) cycles? Assisted hatching (AH) and if the reason to freeze embryos was to avoid the risk of ovarian hyperstimulation syndrome (OHSS) were significantly positively associated with a greater likelihood of clinical pregnancy. Single factor analysis has shown AH, number of embryos transferred and the reason of freezing for OHSS to be positively and damaged blastomere to be negatively significantly associated with the chance of clinical pregnancy after VET. It remains unclear what factors would be significant after multivariate analysis. The study was a retrospective analysis of 2313 VET cycles from 1481 patients performed between January 2008 and April 2012. A multivariate logistic regression analysis was performed to identify the factors to affect clinical pregnancy outcome of VET. There were 22 candidate variables selected based on clinical experiences and the literature. With the thresholds of α entry = α removal= 0.05 for both variable entry and variable removal, eight variables were chosen to contribute the multivariable model by the bootstrap stepwise variable selection algorithm (n = 1000). Eight variables were age at controlled ovarian hyperstimulation (COH), reason for freezing, AH, endometrial thickness, damaged blastomere, number of embryos transferred, number of good-quality embryos, and blood presence on transfer catheter. A descriptive comparison of the relative importance was accomplished by the proportion of explained variation (PEV). Among the reasons for freezing, the OHSS group showed a higher OR than the surplus embryo group when compared with other reasons for VET groups (OHSS versus Other, OR: 2.145; CI: 1.4-3.286; Surplus embryos versus Other, OR: 1.152; CI: 0.761-1.743) and high PEV (marginal 2.77%, P = 0.2911; partial 1.68%; CI of area under receptor operator characteristic curve (ROC): 0.5576-0.6000). AH also showed a high OR (OR: 2.105, CI: 1.554-2.85) and high PEV (marginal 1.97%; partial 1.02%; CI of area under ROC: 0.5344-0.5647). The number of good-quality embryos showed the highest marginal PEV and partial PEV (marginal 3.91%, partial 2.28%; CI of area under ROC: 0.5886-0.6343). This was a retrospective multivariate analysis of the data obtained in 5 years from a single IVF center. Repeated cycles in the same woman were treated as independent observations, which could introduce bias. Results are based on clinical pregnancy and not live births. Prospective analysis of a larger data set from a multicenter study based on live births is necessary to confirm the findings. Paying attention to the quality of embryos, the number of good embryos, AH and the reasons for freezing that are associated with clinical pregnancy after VET will assist the improvement of success rates.

Significance of MPEG-7 textural features for improved mass detection in mammography.

PubMed

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Effect of Edge-Preserving Adaptive Image Filter on Low-Contrast Detectability in CT Systems: Application of ROC Analysis

PubMed Central

Okumura, Miwa; Ota, Takamasa; Kainuma, Kazuhisa; Sayre, James W.; McNitt-Gray, Michael; Katada, Kazuhiro

2008-01-01

Objective. For the multislice CT (MSCT) systems with a larger number of detector rows, it is essential to employ dose-reduction techniques. As reported in previous studies, edge-preserving adaptive image filters, which selectively eliminate only the noise elements that are increased when the radiation dose is reduced without affecting the sharpness of images, have been developed. In the present study, we employed receiver operating characteristic (ROC) analysis to assess the effects of the quantum denoising system (QDS), which is an edge-preserving adaptive filter that we have developed, on low-contrast resolution, and to evaluate to what degree the radiation dose can be reduced while maintaining acceptable low-contrast resolution. Materials and Methods. The low-contrast phantoms (Catphan 412) were scanned at various tube current settings, and ROC analysis was then performed for the groups of images obtained with/without the use of QDS at each tube current to determine whether or not a target could be identified. The tube current settings for which the area under the ROC curve (Az value) was approximately 0.7 were determined for both groups of images with/without the use of QDS. Then, the radiation dose reduction ratio when QDS was used was calculated by converting the determined tube current to the radiation dose. Results. The use of the QDS edge-preserving adaptive image filter allowed the radiation dose to be reduced by up to 38%. Conclusion. The QDS was found to be useful for reducing the radiation dose without affecting the low-contrast resolution in MSCT studies. PMID:19043565

Wavelets analysis for differentiating solid, non-macroscopic fat containing, enhancing renal masses: a pilot study

NASA Astrophysics Data System (ADS)

Varghese, Bino; Hwang, Darryl; Mohamed, Passant; Cen, Steven; Deng, Christopher; Chang, Michael; Duddalwar, Vinay

2017-11-01

Purpose: To evaluate potential use of wavelets analysis in discriminating benign and malignant renal masses (RM) Materials and Methods: Regions of interest of the whole lesion were manually segmented and co-registered from multiphase CT acquisitions of 144 patients (98 malignant RM: renal cell carcinoma (RCC) and 46 benign RM: oncocytoma, lipid-poor angiomyolipoma). Here, the Haar wavelet was used to analyze the grayscale images of the largest segmented tumor in the axial direction. Six metrics (energy, entropy, homogeneity, contrast, standard deviation (SD) and variance) derived from 3-levels of image decomposition in 3 directions (horizontal, vertical and diagonal) respectively, were used to quantify tumor texture. Independent t-test or Wilcoxon rank sum test depending on data normality were used as exploratory univariate analysis. Stepwise logistic regression and receiver operator characteristics (ROC) curve analysis were used to select predictors and assess prediction accuracy, respectively. Results: Consistently, 5 out of 6 wavelet-based texture measures (except homogeneity) were higher for malignant tumors compared to benign, when accounting for individual texture direction. Homogeneity was consistently lower in malignant than benign tumors irrespective of direction. SD and variance measured in the diagonal direction on the corticomedullary phase showed significant (p<0.05) difference between benign versus malignant tumors. The multivariate model with variance (3 directions) and SD (vertical direction) extracted from the excretory and pre-contrast phase, respectively showed an area under the ROC curve (AUC) of 0.78 (p < 0.05) in discriminating malignant from benign. Conclusion: Wavelet analysis is a valuable texture evaluation tool to add to a radiomics platforms geared at reliably characterizing and stratifying renal masses.

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot.

PubMed

Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Kikuchi, Kazufumi; Yoshimoto, Koji; Mizoguchi, Masahiro; Suzuki, Satoshi O; Yoshiura, Takashi; Honda, Hiroshi

2016-07-01

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas. This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis. Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529). CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The value of "liver windows" settings in the detection of small renal cell carcinomas on unenhanced computed tomography.

PubMed

Sahi, Kamal; Jackson, Stuart; Wiebe, Edward; Armstrong, Gavin; Winters, Sean; Moore, Ronald; Low, Gavin

2014-02-01

To assess if "liver window" settings improve the conspicuity of small renal cell carcinomas (RCC). Patients were analysed from our institution's pathology-confirmed RCC database that included the following: (1) stage T1a RCCs, (2) an unenhanced computed tomography (CT) abdomen performed ≤ 6 months before histologic diagnosis, and (3) age ≥ 17 years. Patients with multiple tumours, prior nephrectomy, von Hippel-Lindau disease, and polycystic kidney disease were excluded. The unenhanced CT was analysed, and the tumour locations were confirmed by using corresponding contrast-enhanced CT or magnetic resonance imaging studies. Representative single-slice axial, coronal, and sagittal unenhanced CT images were acquired in "soft tissue windows" (width, 400 Hounsfield unit (HU); level, 40 HU) and liver windows (width, 150 HU; level, 88 HU). In addition, single-slice axial, coronal, and sagittal unenhanced CT images of nontumourous renal tissue (obtained from the same cases) were acquired in soft tissue windows and liver windows. These data sets were randomized, unpaired, and were presented independently to 3 blinded radiologists for analysis. The presence or absence of suspicious findings for tumour was scored on a 5-point confidence scale. Eighty-three of 415 patients met the study criteria. Receiver operating characteristics (ROC) analysis, t test analysis, and kappa analysis were used. ROC analysis showed statistically superior diagnostic performance for liver windows compared with soft tissue windows (area under the curve of 0.923 vs 0.879; P = .0002). Kappa statistics showed "good" vs "moderate" agreement between readers for liver windows compared with soft tissue windows. Use of liver windows settings improves the detection of small RCCs on the unenhanced CT. Copyright © 2014 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

Diagnosis of insomnia sleep disorder using short time frequency analysis of PSD approach applied on EEG signal using channel ROC-LOC.

PubMed

Siddiqui, Mohd Maroof; Srivastava, Geetika; Saeed, Syed Hasan

2016-01-01

Insomnia is a sleep disorder in which the subject encounters problems in sleeping. The aim of this study is to identify insomnia events from normal or effected person using time frequency analysis of PSD approach applied on EEG signals using channel ROC-LOC. In this research article, attributes and waveform of EEG signals of Human being are examined. The aim of this study is to draw the result in the form of signal spectral analysis of the changes in the domain of different stages of sleep. The analysis and calculation is performed in all stages of sleep of PSD of each EEG segment. Results indicate the possibility of recognizing insomnia events based on delta, theta, alpha and beta segments of EEG signals.

On analyzing free-response data on location level

NASA Astrophysics Data System (ADS)

Bandos, Andriy I.; Obuchowski, Nancy A.

2017-03-01

Free-response ROC (FROC) data are typically collected when primary question of interest is focused on the proportions of the correct detection-localization of known targets and frequencies of false positive responses, which can be multiple per subject (image). These studies are particularly relevant for CAD and related applications. The fundamental tool of the location-level FROC analysis is the FROC curve. Although there are many methods of FROC analysis, as we describe in this work, some of the standard and popular approaches, while important, are not suitable for analyzing specifically the location-level FROC performance as summarized by the FROC curve. Analysis of the FROC curve, on the other hand, might not be straightforward. Recently we developed an approach for the location-level analysis of the FROC data using the well-known tools for clustered ROC analysis. In the current work, based on previously developed concepts, and using specific examples, we demonstrate the key reasons why specifically location-level FROC performance cannot be fully addressed by the common approaches as well as illustrate the proposed solution. Specifically, we consider the two most salient FROC approaches, namely JAFROC and the area under the exponentially transformed FROC curve (AFE) and show that clearly superior FROC curves can have lower values for these indices. We describe the specific features that make these approaches inconsistent with FROC curves. This work illustrates some caveats for using the common approaches for location-level FROC analysis and provides guidelines for the appropriate assessment or comparison of FROC systems.

Investigating strength and frequency effects in recognition memory using type-2 signal detection theory.

PubMed

Higham, Philip A; Perfect, Timothy J; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower false alarm rate, for low frequency words compared with high frequency words. In Experiment 2, the authors manipulated item strength with repetition, which showed an increased hit rate but no effect on the false alarm rate. Whereas Type-1 indices were ambiguous as to whether these effects were based on a criterion- or distribution-shift model, the two models predict opposite effects on Type-2 distractor monitoring under some assumptions. Hence, Type-2 ROC analysis discriminated between potential models of recognition that could not be discriminated using Type-1 indices alone. In Experiment 3, the authors manipulated Type-1 response bias by varying the number of old versus new response categories to confirm the assumptions made in Experiments 1 and 2. The authors conclude that Type-2 analyses are a useful tool for investigating recognition memory when used in conjunction with more traditional Type-1 analyses.

On determining the most appropriate test cut-off value: the case of tests with continuous results

PubMed Central

Habibzadeh, Parham; Yadollahie, Mahboobeh

2016-01-01

There are several criteria for determination of the most appropriate cut-off value in a diagnostic test with continuous results. Mostly based on receiver operating characteristic (ROC) analysis, there are various methods to determine the test cut-off value. The most common criteria are the point on ROC curve where the sensitivity and specificity of the test are equal; the point on the curve with minimum distance from the left-upper corner of the unit square; and the point where the Youden’s index is maximum. There are also methods mainly based on Bayesian decision analysis. Herein, we show that a proposed method that maximizes the weighted number needed to misdiagnose, an index of diagnostic test effectiveness we previously proposed, is the most appropriate technique compared to the aforementioned ones. For determination of the cut-off value, we need to know the pretest probability of the disease of interest as well as the costs incurred by misdiagnosis. This means that even for a certain diagnostic test, the cut-off value is not universal and should be determined for each region and for each disease condition. PMID:27812299

Lipid accumulation product is related to metabolic syndrome in women with polycystic ovary syndrome.

PubMed

Xiang, S; Hua, F; Chen, L; Tang, Y; Jiang, X; Liu, Z

2013-02-01

Metabolic disturbances are common features of polycystic ovary syndrome (PCOS), which possibly enhance the risk of diabetes and cardiovascular disease. Lipid accumulation product (LAP) is an emerging cardiovascular risk factor. The aim of this study was to explore the ability of LAP to identify metabolic syndrome (MS) in PCOS women. In a cross-sectional study, anthropometric, biochemical and clinical parameters were measured in 105 PCOS women. Receiver operating characteristic (ROC) analysis was used to find out the cut-off points of LAP to predict MS. MS was categorized according to International Diabetes Federation (IDF) criteria. The prevalence of MS was 43.8% in this study. PCOS women with MS had significantly higher LAP levels compared to those without MS. LAP was highly correlated with components of MS. ROC analysis showed that LAP was a significant discriminator for MS in PCOS women, and the optimal cutoff point of LAP to predict MS was 54.2 (93.3% sensitivity, 96.7% specificity). LAP seems to be associated with MS and has a strong and reliable diagnostic accuracy for MS in PCOS women. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

A comparison of the validity of GHQ-12 and CHQ-12 in Chinese primary care patients in Manchester.

PubMed

Pan, P C; Goldberg, D P

1990-11-01

The present study compares the efficacy of the GHQ-12 and the Chinese Health Questionnaire (CHQ-12) in Cantonese speaking Chinese primary-care patients living in Greater Manchester, using relative operating characteristic (ROC) analysis. We did not find that the Chinese version offered any advantage over the conventional version of the GHQ in this population. Stepwise discriminant analysis however confirmed the value of individual items in the former pertaining to specific somatic symptoms and interpersonal relationships in differentiating cases from non-cases. Information biases, arising from the lack of a reliability study on the second-stage case identifying interview and the unique linguistic characteristics of the Chinese language may have affected the overall validity indices of the questionnaires. The study also examines the effects of using different criteria to define a case, and shows that with increasing levels of severity, there is an improvement in the diagnostic performance of the two questionnaires as reflected by areas under ROC curves and traditional validity indices. Possible explanations of these findings are discussed. The scoring method proposed by Goodchild & Duncan-Jones (1985) when used on these questionnaires had no demonstrable advantage over the conventional scoring method.

Recollection, not familiarity, decreases in healthy aging: Converging evidence from four estimation methods

PubMed Central

Koen, Joshua D.; Yonelinas, Andrew P.

2014-01-01

Although it is generally accepted that aging is associated with recollection impairments, there is considerable disagreement surrounding how healthy aging influences familiarity-based recognition. One factor that might contribute to the mixed findings regarding age differences in familiarity is the estimation method used to quantify the two mnemonic processes. Here, this issue is examined by having a group of older adults (N = 39) between 40 and 81 years of age complete Remember/Know (RK), receiver operating characteristic (ROC), and process dissociation (PD) recognition tests. Estimates of recollection, but not familiarity, showed a significant negative correlation with chronological age. Inconsistent with previous findings, the estimation method did not moderate the relationship between age and estimations of recollection and familiarity. In a final analysis, recollection and familiarity were estimated as latent factors in a confirmatory factor analysis (CFA) that modeled the covariance between measures of free recall and recognition, and the results converged with the results from the RK, PD, and ROC tasks. These results are consistent with the hypothesis that episodic memory declines in older adults are primary driven by recollection deficits, and also suggest that the estimation method plays little to no role in age-related decreases in familiarity. PMID:25485974

Evaluation and simplification of the occupational slip, trip and fall risk-assessment test

PubMed Central

NAKAMURA, Takehiro; OYAMA, Ichiro; FUJINO, Yoshihisa; KUBO, Tatsuhiko; KADOWAKI, Koji; KUNIMOTO, Masamizu; ODOI, Haruka; TABATA, Hidetoshi; MATSUDA, Shinya

2016-01-01

Objective: The purpose of this investigation is to evaluate the efficacy of the occupational slip, trip and fall (STF) risk assessment test developed by the Japan Industrial Safety and Health Association (JISHA). We further intended to simplify the test to improve efficiency. Methods: A previous cohort study was performed using 540 employees aged ≥50 years who took the JISHA’s STF risk assessment test. We conducted multivariate analysis using these previous results as baseline values and answers to questionnaire items or score on physical fitness tests as variables. The screening efficiency of each model was evaluated based on the obtained receiver operating characteristic (ROC) curve. Results: The area under the ROC obtained in multivariate analysis was 0.79 when using all items. Six of the 25 questionnaire items were selected for stepwise analysis, giving an area under the ROC curve of 0.77. Conclusion: Based on the results of follow-up performed one year after the initial examination, we successfully determined the usefulness of the STF risk assessment test. Administering a questionnaire alone is sufficient for screening subjects at risk of STF during the subsequent one-year period. PMID:27021057

Receiver operating characteristic analysis of age-related changes in lineup performance.

PubMed

Humphries, Joyce E; Flowe, Heather D

2015-04-01

In the basic face memory literature, support has been found for the late maturation hypothesis, which holds that face recognition ability is not fully developed until at least adolescence. Support for the late maturation hypothesis in the criminal lineup identification literature, however, has been equivocal because of the analytic approach that has been used to examine age-related changes in identification performance. Recently, receiver operator characteristic (ROC) analysis was applied for the first time in the adult eyewitness memory literature to examine whether memory sensitivity differs across different types of lineup tests. ROC analysis allows for the separation of memory sensitivity from response bias in the analysis of recognition data. Here, we have made the first ROC-based comparison of adults' and children's (5- and 6-year-olds and 9- and 10-year-olds) memory performance on lineups by reanalyzing data from Humphries, Holliday, and Flowe (2012). In line with the late maturation hypothesis, memory sensitivity was significantly greater for adults compared with young children. Memory sensitivity for older children was similar to that for adults. The results indicate that the late maturation hypothesis can be generalized to account for age-related performance differences on an eyewitness memory task. The implications for developmental eyewitness memory research are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluation of Screening for Retinopathy of Prematurity by ROPtool or a Lay Reader.

PubMed

Abbey, Ashkan M; Besirli, Cagri G; Musch, David C; Andrews, Chris A; Capone, Antonio; Drenser, Kimberly A; Wallace, David K; Ostmo, Susan; Chiang, Michael; Lee, Paul P; Trese, Michael T

2016-02-01

To determine if (1) tortuosity assessment by a computer program (ROPtool, developed at the University of North Carolina, Chapel Hill, and Duke University, and licensed by FocusROP) that traces retinal blood vessels and (2) assessment by a lay reader are comparable with assessment by a panel of 3 retinopathy of prematurity (ROP) experts for remote clinical grading of vascular abnormalities such as plus disease. Validity and reliability analysis of diagnostic tools. Three hundred thirty-five fundus images of prematurely born infants. Three hundred thirty-five fundus images of prematurely born infants were obtained by neonatal intensive care unit nurses. A panel of 3 ROP experts graded 84 images showing vascular dilatation, tortuosity, or both and 251 images showing no evidence of vascular abnormalities. These images were sent electronically to an experienced lay reader who independently graded them for vascular abnormalities. The images also were analyzed using the ROPtool, which assigns a numerical value to the level of vascular abnormality and tortuosity present in each of 4 quadrants or sectors. The ROPtool measurements of vascular abnormalities were graded and compared with expert panel grades with a receiver operating characteristic (ROC) curve. Grades between human readers were cross-tabulated. The area under the ROC curve was calculated for the ROPtool, and sensitivity and specificity were computed for the lay reader. Measurements of vascular abnormalities by ROPtool and grading of vascular abnormalities by 3 ROP experts and 1 experienced lay reader. The ROC curve for ROPtool's tortuosity assessment had an area under the ROC curve of 0.917. Using a threshold value of 4.97 for the second most tortuous quadrant, ROPtool's sensitivity was 91% and its specificity was 82%. Lay reader sensitivity and specificity were 99% and 73%, respectively, and had high reliability (κ, 0.87) in repeated measurements. ROPtool had very good accuracy for detection of vascular abnormalities suggestive of plus disease when compared with expert physician graders. The lay reader's results showed excellent sensitivity and good specificity when compared with those of the expert graders. These options for remote reading of images to detect vascular abnormalities deserve consideration in the quest to use telemedicine with remote reading for efficient delivery of high-quality care and to detect infants requiring bedside examination. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Estimating the Area Under ROC Curve When the Fitted Binormal Curves Demonstrate Improper Shape.

PubMed

Bandos, Andriy I; Guo, Ben; Gur, David

2017-02-01

The "binormal" model is the most frequently used tool for parametric receiver operating characteristic (ROC) analysis. The binormal ROC curves can have "improper" (non-concave) shapes that are unrealistic in many practical applications, and several tools (eg, PROPROC) have been developed to address this problem. However, due to the general robustness of binormal ROCs, the improperness of the fitted curves might carry little consequence for inferences about global summary indices, such as the area under the ROC curve (AUC). In this work, we investigate the effect of severe improperness of fitted binormal ROC curves on the reliability of AUC estimates when the data arise from an actually proper curve. We designed theoretically proper ROC scenarios that induce severely improper shape of fitted binormal curves in the presence of well-distributed empirical ROC points. The binormal curves were fitted using maximum likelihood approach. Using simulations, we estimated the frequency of severely improper fitted curves, bias of the estimated AUC, and coverage of 95% confidence intervals (CIs). In Appendix S1, we provide additional information on percentiles of the distribution of AUC estimates and bias when estimating partial AUCs. We also compared the results to a reference standard provided by empirical estimates obtained from continuous data. We observed up to 96% of severely improper curves depending on the scenario in question. The bias in the binormal AUC estimates was very small and the coverage of the CIs was close to nominal, whereas the estimates of partial AUC were biased upward in the high specificity range and downward in the low specificity range. Compared to a non-parametric approach, the binormal model led to slightly more variable AUC estimates, but at the same time to CIs with more appropriate coverage. The improper shape of the fitted binormal curve, by itself, ie, in the presence of a sufficient number of well-distributed points, does not imply unreliable AUC-based inferences. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Diagnostic yield of ink-jet prints from digital radiographs for the assessment of approximal carious lesions: ROC-analysis.

PubMed

Schulze, Ralf K W; Grimm, Stefanie; Schulze, Dirk; Voss, Kai; Keller, Hans-Peter; Wedel, Matthias

2011-08-01

To investigate the diagnostic quality of different quality, individually calibrated ink-jet printers for the very challenging dental radiographic task of approximal carious lesion detection. A test-pattern evaluating resolution, contrast and homogeneity of the ink-jet prints was developed. 50 standardized dental radiographs each showing two neighbouring teeth in natural contact were printed on glossy paper with calibrated, randomly selected ink-jet printers (Canon S520 and iP4500, Epson Stylus Photo R2400). Printing size equalled the viewing size on a 17″ cathode-ray-tube monitor daily quality-tested according to German regulations. The true caries status was determined from serial sectioning and microscopic evaluation. 16 experienced observers evaluated the radiographs on a five-point confidence scale on all prints plus the viewing monitor with respect to the visibility of a carious lesion. A non-parametric Receiver-Operating Characteristics (ROC-) analysis was performed explicitly designed for the evaluation of readings stemming from identical samples but different modality. Significant differences are expressed by a critical ratio z exceeding ±2. Diagnostic accuracy was determined by the area (Az) underneath the ROC-curves. Average Az-values ranged between 0.62 (S520 and R2400) and 0.64 (monitor, iP4500), with no significant difference between modalities (P=0.172). Neither significant (range mean z: -0.40 (S520) and -0.11 (iP4500)) nor clinically relevant differences were found between printers and viewing monitor. Our results for a challenging task in dental radiography indicate that calibrated, off-the-shelf ink-jet printers are able to reproduce (dental) radiographs at quality levels sufficient for radiographic diagnosis in a typical dental working environment. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Preoperative vitamin D deficiency and postoperative hypocalcemia in thyroid cancer patients undergoing total thyroidectomy plus central compartment neck dissection

PubMed Central

Wang, Xiaofei; Zhu, Jingqiang; Liu, Feng; Gong, Yanping; Li, Zhihui

2017-01-01

Background There appears to be a lack of consensus whether preoperative vitamin D deficiency (VDD) increases the risk of postoperative hypocalcemia and decreases the accuracy of postoperative parathyroid hormone (PTH) in predicting hypocalcemia in thyroid cancer patients undergoing total thyroidectomy (TT) plus central compartment neck dissection (CCND). This study aims to address these issues. Method All consecutive thyroid cancer patients who underwent TT plus CCND were retrospectively reviewed through a prospectively collected database between October 2015 and April 2016 in a tertiary referral hospital. The multivariate analysis was performed to identify the significant predictors for hypocalcemia. Receiver operator characteristic curve (ROC) was created and the area under the ROC was used to evaluate the predictive accuracy of postoperative PTH and compared between patients with or without VDD. Results A total of 186 patients were included. The incidence of VDD was 73.7% (137 patients). The incidence of biochemical and symptomatic hypocalcemia was similar in patients with or without VDD (P = 0.304 and 0.657, respectively). Multivariate analysis showed that only postoperative PTH was an independent predictor of symptomatic hypocalcemia (OR = 8.05, 95%CI = 3.99-16.22; P = 0.000). The area under the ROC was similar between patients with preoperative vitamin D level < 20 and ≥20 ng/mL (0.809 versus 0.845, P = 0.592). Conclusion VDD was not a significant risk factor for hypocalcemia following TT+CCND, and did not affect the accuracy of postoperative PTH as a predictor of postoperative hypocalcemia. Thus, routine preoperative screening for vitamin D seems to be unnecessary. PMID:29100453

Usefulness of Tc-99m MDP spine SPECT imaging in differentiating malignant from benign lesions in cancer patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryu, J.S.; Moon, D.H.; Shin, M.J.

1994-05-01

Solitary or a few spinal abnormalities on planar bone scan pose a dilemma in cancer patients. The purpose of this study was to evaluate the usefulness of spine SPECT imaging in differential diagnosis of malignant and benign lesion. Subjects were 54 adult patients with solitary or a few equivocal vertebral lesions on planar bone scan. Spine SPECT imaging was obtained by a triple head SPECT system (TRIAD, Trionix). The final diagnoses were based on data from biopsy, other imaging studies, or minimum 1 year of follow up. Two blind observers reviewed the planar image first, then both planar and SPECTmore » images. The uptake patterns on SPECT images were analyzed, and the diagnostic performance was evaluated by the ROC analysis. Thirty three lesions of 22 patients were malignant, and 60 lesions of 32 patients were benign. Common characteristic patterns of malignant lesions were focal or segmental hot uptake in the body, hot uptake in the body and pedicle, and cold defect with surrounding hot uptake in the vertebra. Whereas marginal protruding hot uptakes in endplate, and hot uptakes in facet joints were benign. The ROC analysis showed that SPECT improved the diagnostic performance (the area under the ROC curve of two observers for planar image 0.903 and 0.791, for the combination of planar and SPECT : 0.950 and 0.976). In conclusion, the uptake pattern recognition in spine SPECT provides useful information for differential diagnosis of malignant and benign lesions in vertebra. Spine SPECT is a valuable complement in cancer patients with inconclusive findings on planar bone scan.« less

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

NASA Astrophysics Data System (ADS)

Daye, Dania; Bobo, Ezra; Baumann, Bethany; Ioannou, Antonios; Conant, Emily F.; Maidment, Andrew D. A.; Kontos, Despina

2011-03-01

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Non-invasive detection of the freezing of gait in Parkinson's disease using spectral and wavelet features.

PubMed

Nazarzadeh, Kimia; Arjunan, Sridhar P; Kumar, Dinesh K; Das, Debi Prasad

2016-08-01

In this study, we have analyzed the accelerometer data recorded during gait analysis of Parkinson disease patients for detecting freezing of gait (FOG) episodes. The proposed method filters the recordings for noise reduction of the leg movement changes and computes the wavelet coefficients to detect FOG events. Publicly available FOG database was used and the technique was evaluated using receiver operating characteristic (ROC) analysis. Results show a higher performance of the wavelet feature in discrimination of the FOG events from the background activity when compared with the existing technique.

Clinical value of serum anti-mullerian hormone and inhibin B in prediction of ovarian response in patients with polycystic ovary syndrome.

PubMed

Zhang, Fan; Liu, Xiao-Ling; Rong, Nan; Huang, Xiao-Wen

2017-02-01

The present study aimed to investigate the clinical value of serum anti-mullerian hormone (AMH) and inhibin B (INHB) in predicting the ovarian response of patients with polycystic ovary syndrome (PCOS). A total of 120 PCOS patients were enrolled and divided into three groups in terms of the ovarian response: a low-response group (n=36), a normal-response group (n=44), and a high-response group (n=40). The serum AMH and INHB levels were measured by enzyme-linked immunosorbent assay (ELISA). The follicle stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E2) levels were determined by chemiluminescence microparticle immunoassay. The correlation of the serum AMH and INHB levels with other indicators was analyzed. A receiver operating characteristic (ROC) curve was established to analyze the prediction of ovarian response by AMH and INHB. The results showed that there were significant differences in age, body mass index (BMI), FSH, total gonadotropin-releasing hormone (GnRH), LH, E2, and antral follicle counts (AFCs) between the groups (P<0.05). The serum AMH and INHB levels were increased significantly with the ovarian response of PCOS patients increasing (P<0.05). The serum AMH and INHB levels were negatively correlated with the age, BMI, FSH level, Gn, and E2 levels (P<0.05). They were positively correlated with the LH levels and AFCs (P<0.05). ROC curve analysis of serum AMH and INHB in prediction of a low ovarian response showed that the area under the ROC curve (AUC) value of the serum AMH level was 0.817, with a cut-off value of 1.29 ng/mL. The sensitivity and specificity were 71.2% and 79.6%, respectively. The AUC value of serum INHB was 0.674, with a cut-off value of 38.65 ng/mL, and the sensitivity and specificity were 50.7% and 74.5%, respectively. ROC curve analysis showed when the serum AMH and INHB levels were used to predict a high ovarian response, the AUC value of the serum AMH level was 0.742, with a cut-off value of 2.84 ng/mL, and the sensitivity and specificity were 72.7% and 65.9%, respectively; the AUC value of the serum INHB level was 0.551 with a cut-off of 45.76 ng/mL, and the sensitivity and specificity were 76.3% and 40.2%, respectively. It was suggested the serum AMH and INHB levels have high clinical value in predicting the ovarian response of PCOS patients.

iPads and LCDs show similar performance in the detection of pulmonary nodules

NASA Astrophysics Data System (ADS)

McEntee, Mark F.; Lowe, Joanna; Butler, Marie Louise; Pietrzyk, Mariusz; Evanoff, Michael G.; Ryan, John; Brennan, Patrick C.; Rainford, Louise A.

2012-02-01

In February 2011 the University of Chicago Medical School distributed iPads to its trainee doctors for use when reviewing clinical information and images on the ward or clinics. The use of tablet computing devices is becoming widespread in medicine with Apple™ heralding them as "revolutionary" in medicine. The question arises, just because it is technical achievable to use iPads for clinical evaluation of images, should we do so? The current work assesses the diagnostic efficacy of iPads when compared with LCD secondary display monitors for identifying lung nodules on chest x-rays. Eight examining radiologists of the American Board of Radiology were involved in the assessment, reading chest images on both the iPad and the an off-the-shelf LCD monitor. Thirty chest images were shown to each observer, of which 15 had one or more lung nodules. Radiologists were asked to locate the nodules and score how confident they were with their decision on a scale of 1-5. An ROC and JAFROC analysis was performed and modalities were compared using DBM MRMC. The results demonstrate no significant differences in performance between the iPad and the LCD for the ROC AUC (p<0.075) or JAFROC FOM (p<0.059) for random readers and random cases. Sample size estimation showed that this result is significant at a power of 0.8 and an effect size of 0.05 for ROC and 0.07 for JAFROC. This work demonstrates that for the task of identifying pulmonary nodules, the use of the iPad does not significantly change performance compared to an off-the-shelf LCD.

Plasma long non-coding RNA BACE1 as a novel biomarker for diagnosis of Alzheimer disease.

PubMed

Feng, Liang; Liao, Yu-Ting; He, Jin-Cai; Xie, Cheng-Long; Chen, Si-Yan; Fan, Hui-Hui; Su, Zhi-Peng; Wang, Zhen

2018-01-09

Long non-coding RNA (LncRNA) have been reported to be involved in the pathogenesis of neurodegenerative diseases, but whether it can serve as a biomarker for Alzheimer disease (AD) is not yet known. The present study selected four specific LncRNA (17A, 51A, BACE1 and BC200) as possible AD biomarker. RT-qPCR was performed to validate the LncRNA. Receiver operating characteristic curve (ROC) and area under the ROC curve (AUC) were applied to study the potential of LncRNA as a biomarker in a population of 88 AD patients and 72 control individuals. We found that the plasma LncRNA BACE1 level of AD patients was significantly higher than that of healthy controls (p = 0.006). Plasma level of LncRNA 17A, 51A and BC200 did not show a significant difference between two groups (p = 0.098, p = 0.204 and p = 0.232, respectively). ROC curve analysis showed that LncRNA BACE1 was the best candidate of these LncRNA (95% CI: 0.553-0.781, p = 0.003). In addition, no correlation was found for expression of these LncRNA in both control and AD groups with age or MMSE scale (p > 0.05). Our present study compared the plasma level of four LncRNA between AD and non-AD patients, and found that the level of the BACE1 is increased in the plasma of AD patients and have a high specificity (88%) for AD, indicating BACE1 may be a potential candidate biomarker to predict AD.

Predisposing factors for postoperative nausea and vomiting in gynecologic tumor patients.

PubMed

de Souza, Daiane Spitz; Costa, Amine Farias; Chaves, Gabriela Villaça

2016-11-01

To evaluate the predictors of postoperative nausea and vomiting (PONV) in women with gynecologic tumor. The analysis was based on prospectively collected data of 82 adult patients with gynecologic tumor, who were submitted to open surgical treatment and undergoing general anesthesia. The predictors included were age ≥50 years, non-smoker, use of postoperative opioids, mechanical bowel preparation, intraoperative intravenous hydration (IH) ≥10 mL/kg/h, and IH in the immediate postoperative, first and second postoperative days (PO1 and PO2) ≥30 mL/kg. A score with predictor variables was built. A multiple logistic regression was fitted. To estimate the discriminating power of the chosen model, a receiver operating characteristic (ROC) curve was plotted and the area under the ROC curve (AUC) was calculated. Statistical significance was set at p value <0.05 and the confidence interval at 95 %. The incidence (%) of nausea, vomiting and both, in the general population, was 36.6, 28.1, 22.0, respectively. The highest incidences of PONV were found in non-smokers and in patients who received >30 mL/kg of IH in the PO2. The results of the adjusted model showed an increased risk of PONV for each 1-point increase in the score punctuation. The relative risk was higher than 2.0 for vomiting in all period and in the PO1. The ROC curve showed great discrimination of postoperative nausea and vomiting from the proposed score (AUC >0.75). The study population was at high risk of PONV. Therefore, institutional guidelines abolishing modificable variables following temporal evaluation of the effectiveness should be undertaken.

LIDAR Metrology for Prescription Characterization and Alignment of Large Mirrors

NASA Technical Reports Server (NTRS)

Eegholm, B.; Eichhorn, W.; von Handorf, R.; Hayden, J.; Ohl, R.; Wenzel, G.

2011-01-01

We describe the use of LIDAR, or "laser radar," (LR) as a fast, accurate, and non-contact tool for the measurement of the radius of curvature (RoC) of large mirrors. We report the results of a demonstration of this concept using a commercial laser radar system. We measured the RoC of a 1.4m x 1m spherical mirror with a nominal RoC of 4.6 m with a manufacturing tolerance of 4600mm +/- 6mm. The prescription of the mirror is related to its role as ground support equipment used in the test of part of the James Webb Space Telescope (JWST). The RoC of such a large mirror is not easily measured without contacting the surface. From a position near the center of curvature of the mirror, the LIDAR scanned the mirror surface, sampling it with 1 point per 3.5 sq cm. The measurement consisted of 3983 points and lasted only a few minutes. The laser radar uses the LIDAR signal to provide range, and encoder information from angular azimuth and elevation rotation stages provide the spherical coordinates of a given point. A best-fit to a sphere of the measured points was performed. The resulting RoC was within 20 ppm of the nominal RoC, also showing good agreement with the results of a laser tracker-based, contact metrology. This paper also discusses parameters such as test alignment, scan density, and optical surface type, as well as future possible application for full prescription characterization of aspherical mirrors, including radius, conic, off-axis distance, and aperture.

Wet Deposition Flux of Reactive Organic Carbon

NASA Astrophysics Data System (ADS)

Safieddine, S.; Heald, C. L.

2016-12-01

Reactive organic carbon (ROC) is the sum of non-methane volatile organic compounds (NMVOCs) and primary and secondary organic aerosols (OA). ROC plays a key role in driving the chemistry of the atmosphere, affecting the hydroxyl radical concentrations, methane lifetime, ozone formation, heterogeneous chemical reactions, and cloud formation, thereby impacting human health and climate. Uncertainties on the lifecycle of ROC in the atmosphere remain large. In part this can be attributed to the large uncertainties associated with the wet deposition fluxes. Little is known about the global magnitude of wet deposition as a sink of both gas and particle phase organic carbon, making this an important area for research and sensitivity testing in order to better understand the global ROC budget. In this study, we simulate the wet deposition fluxes of the reactive organic carbon of the troposphere using a global chemistry transport model, GEOS-Chem. We start by showing the current modeled global distribution of ROC wet deposition fluxes and investigate the sensitivity of these fluxes to variability in Henry's law solubility constants and spatial resolution. The average carbon oxidation state (OSc) is a useful metric that depicts the degree of oxidation of atmospheric reactive carbon. Here, we present for the first time the simulated gas and particle phase OSc of the global troposphere. We compare the OSc in the wet deposited reactive carbon flux and the dry deposited reactive carbon flux to the OSc of atmospheric ROC to gain insight into the degree of oxidation in deposited material and, more generally, the aging of organic material in the troposphere.

Software for illustrative presentation of basic clinical characteristics of laboratory tests--GraphROC for Windows.

PubMed

Kairisto, V; Poola, A

1995-01-01

GraphROC for Windows is a program for clinical test evaluation. It was designed for the handling of large datasets obtained from clinical laboratory databases. In the user interface, graphical and numerical presentations are combined. For simplicity, numerical data is not shown unless requested. Relevant numbers can be "picked up" from the graph by simple mouse operations. Reference distributions can be displayed by using automatically optimized bin widths. Any percentile of the distribution with corresponding confidence limits can be chosen for display. In sensitivity-specificity analysis, both illness- and health-related distributions are shown in the same graph. The following data for any cutoff limit can be shown in a separate click window: clinical sensitivity and specificity with corresponding confidence limits, positive and negative likelihood ratios, positive and negative predictive values and efficiency. Predictive values and clinical efficiency of the cutoff limit can be updated for any prior probability of disease. Receiver Operating Characteristics (ROC) curves can be generated and combined into the same graph for comparison of several different tests. The area under the curve with corresponding confidence interval is calculated for each ROC curve. Numerical results of analyses and graphs can be printed or exported to other Microsoft Windows programs. GraphROC for Windows also employs a new method, developed by us, for the indirect estimation of health-related limits and change limits from mixed distributions of clinical laboratory data.

Receiver-operating-characteristic analysis of an automated program for analyzing striatal uptake of 123I-ioflupane SPECT images: calibration using visual reads.

PubMed

Kuo, Phillip Hsin; Avery, Ryan; Krupinski, Elizabeth; Lei, Hong; Bauer, Adam; Sherman, Scott; McMillan, Natalie; Seibyl, John; Zubal, George

2013-03-01

A fully automated objective striatal analysis (OSA) program that quantitates dopamine transporter uptake in subjects with suspected Parkinson's disease was applied to images from clinical (123)I-ioflupane studies. The striatal binding ratios or alternatively the specific binding ratio (SBR) of the lowest putamen uptake was computed, and receiver-operating-characteristic (ROC) analysis was applied to 94 subjects to determine the best discriminator using this quantitative method. Ninety-four (123)I-ioflupane SPECT scans were analyzed from patients referred to our clinical imaging department and were reconstructed using the manufacturer-supplied reconstruction and filtering parameters for the radiotracer. Three trained readers conducted independent visual interpretations and reported each case as either normal or showing dopaminergic deficit (abnormal). The same images were analyzed using the OSA software, which locates the striatal and occipital structures and places regions of interest on the caudate and putamen. Additionally, the OSA places a region of interest on the occipital region that is used to calculate the background-subtracted SBR. The lower SBR of the 2 putamen regions was taken as the quantitative report. The 33 normal (bilateral comma-shaped striata) and 61 abnormal (unilateral or bilateral dopaminergic deficit) studies were analyzed to generate ROC curves. Twenty-nine of the scans were interpreted as normal and 59 as abnormal by all 3 readers. For 12 scans, the 3 readers did not unanimously agree in their interpretations (discordant). The ROC analysis, which used the visual-majority-consensus interpretation from the readers as the gold standard, yielded an area under the curve of 0.958 when using 1.08 as the threshold SBR for the lowest putamen. The sensitivity and specificity of the automated quantitative analysis were 95% and 89%, respectively. The OSA program delivers SBR quantitative values that have a high sensitivity and specificity, compared with visual interpretations by trained nuclear medicine readers. Such a program could be a helpful aid for readers not yet experienced with (123)I-ioflupane SPECT images and if further adapted and validated may be useful to assess disease progression during pharmaceutical testing of therapies.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

PubMed

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Value of semen parameters, with special reference to TNF-α, in predicting the quality of boar semen after short-term storage.

PubMed

Mrkun, Janko; Kosec, Marjan; Zrimšek, Petra

2013-06-01

The aim of this study was to address the question whether changes in boar semen quality after short-term storage could be predicted on the basis of standard semen parameters and TNF-α level determined on the day of semen collection under commercial conditions. Progressive motility showed the highest positive correlation with morphology on day 0 of collection, and progressive motility on day 3 (P < 0.05) showed a negative correlation with acrosome abnormalities (P < 0.05). According to the area under receiver operating characteristics (ROC) curves (AUCs), progressive motility could also be used in predicting semen quality after 3 days of storage (AUC > 0.5; P < 0.05). TNF-α in seminal plasma is the only parameter measured on day 0 to show a significant correlation with the percentage of viable spermatozoa after 3 days of semen storage (r = 0.495, P < 0.05). ROC analysis shows that TNF-α level is helpful in discriminating viability outcome after semen storage (AUC = 0.94, P < 0.001). We can predict with 92.35% certainty that fresh semen samples with more than 150 pg/ml of TNF-α in the seminal plasma will retain more than 85% of viable spermatozoa after 3 days of storage. Thus, TNF-α can contribute to predicting the quality of short-term stored semen.

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

PubMed

Du, Pang; Tang, Liansheng

2009-01-30

When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

Validity of the posttraumatic stress disorders (PTSD) checklist in pregnant women.

PubMed

Gelaye, Bizu; Zheng, Yinnan; Medina-Mora, Maria Elena; Rondon, Marta B; Sánchez, Sixto E; Williams, Michelle A

2017-05-12

The PTSD Checklist-civilian (PCL-C) is one of the most commonly used self-report measures of PTSD symptoms, however, little is known about its validity when used in pregnancy. This study aims to evaluate the reliability and validity of the PCL-C as a screen for detecting PTSD symptoms among pregnant women. A total of 3372 pregnant women who attended their first prenatal care visit in Lima, Peru participated in the study. We assessed the reliability of the PCL-C items using Cronbach's alpha. Criterion validity and performance characteristics of PCL-C were assessed against an independent, blinded Clinician-Administered PTSD Scale (CAPS) interview using measures of sensitivity, specificity and receiver operating characteristics (ROC) curves. We tested construct validity using exploratory and confirmatory factor analytic approaches. The reliability of the PCL-C was excellent (Cronbach's alpha =0.90). ROC analysis showed that a cut-off score of 26 offered optimal discriminatory power, with a sensitivity of 0.86 (95% CI: 0.78-0.92) and a specificity of 0.63 (95% CI: 0.62-0.65). The area under the ROC curve was 0.75 (95% CI: 0.71-0.78). A three-factor solution was extracted using exploratory factor analysis and was further complemented with three other models using confirmatory factor analysis (CFA). In a CFA, a three-factor model based on DSM-IV symptom structure had reasonable fit statistics with comparative fit index of 0.86 and root mean square error of approximation of 0.09. The Spanish-language version of the PCL-C may be used as a screening tool for pregnant women. The PCL-C has good reliability, criterion validity and factorial validity. The optimal cut-off score obtained by maximizing the sensitivity and specificity should be considered cautiously; women who screened positive may require further investigation to confirm PTSD diagnosis.

Protective effects of a standardised red orange extract on air pollution-induced oxidative damage in traffic police officers.

PubMed

Bonina, Francesco P; Puglia, Carmelo; Frasca, Giuseppina; Cimino, Francesco; Trombetta, Domenico; Tringali, Giovanni; Roccazzello, Annamaria; Insiriello, Elio; Rapisarda, Paolo; Saija, Antonella

2008-01-01

Several pathological conditions have all been associated with a higher release of atmospheric pollutants. There is growing evidence that oxidative stress may represent one of the agents involved in the initiation and/or progression of many of these pathologies. The aim of the present study was to evaluate the effects of short-term dietary supplementation with a standardised red orange extract (ROC) on a group of traffic police officers exposed to traffic exhaust pollution and cigarette smoking, by measuring some noninvasive biomarkers of oxidative stress. At the beginning of the study, all the groups showed similar serum lipid hydroperoxide levels, but traffic officers showed lower serum concentrations of thiol (SH) groups; furthermore, the frequency of spontaneous sister chromatide exchanges (SCEs) in peripheral lymphocytes was increased by smoking (but not by pollution exposure alone) at a higher degree in subjects exposed to traffic pollution. After 1 month of ROC administration, serum lipid hydroperoxide levels decreased only in all non-smoking subjects; furthermore, SH group levels measured in traffic officers appeared restored to normal values observed in the respective controls. Finally, the increase in SCE frequency induced by smoking was reduced by treatment with ROC especially in traffic officers. Our study suggests that ROC supplementation could be useful to minimise the detrimental effects caused by exposure to air pollution and smoking.

Association between Platelet Counts before and during Pharmacological Therapy for Patent Ductus Arteriosus and Treatment Failure in Preterm Infants.

PubMed

Sallmon, Hannes; Weber, Sven C; Dirks, Juliane; Schiffer, Tamara; Klippstein, Tamara; Stein, Anja; Felderhoff-Müser, Ursula; Metze, Boris; Hansmann, Georg; Bührer, Christoph; Cremer, Malte; Koehne, Petra

2018-01-01

The role of platelets for mediating closure of the ductus arteriosus in human preterm infants is controversial. Especially, the effect of low platelet counts on pharmacological treatment failure is still unclear. In this retrospective study of 471 preterm infants [<1,500 g birth weight (BW)], who were treated for a patent ductus arteriosus (PDA) with indomethacin or ibuprofen, we investigated whether platelet counts before or during pharmacological treatment had an impact on the successful closure of a hemodynamically significant PDA. The effects of other factors, such as sepsis, preeclampsia, gestational age, BW, and gender, were also evaluated. Platelet counts before initiation of pharmacological PDA treatment did not differ between infants with later treatment success or failure. However, we found significant associations between low platelet counts during pharmacological PDA therapy and treatment failure ( p  < 0.05). Receiver operating characteristic (ROC) curve analysis showed that platelet counts after the first, and before and after the second cyclooxygenase inhibitor (COXI) cycle were significantly associated with treatment failure (area under the curve of >0.6). However, ROC curve analysis did not reveal a specific platelet cutoff-value that could predict PDA treatment failure. Multivariate logistic regression analysis showed that lower platelet counts, a lower BW, and preeclampsia were independently associated with COXI treatment failure. We provide further evidence for an association between low platelet counts during pharmacological therapy for symptomatic PDA and treatment failure, while platelet counts before initiation of therapy did not affect treatment outcome.

Signal detection in animal psychoacoustics: Analysis and simulation of sensory and decision-related influences

PubMed Central

Alves-Pinto, A.; Sollini, J.; Sumner, C.J.

2012-01-01

Signal detection theory (SDT) provides a framework for interpreting psychophysical experiments, separating the putative internal sensory representation and the decision process. SDT was used to analyse ferret behavioural responses in a (yes–no) tone-in-noise detection task. Instead of measuring the receiver-operating characteristic (ROC), we tested SDT by comparing responses collected using two common psychophysical data collection methods. These (Constant Stimuli, Limits) differ in the set of signal levels presented within and across behavioural sessions. The results support the use of SDT as a method of analysis: SDT sensory component was unchanged between the two methods, even though decisions depended on the stimuli presented within a behavioural session. Decision criterion varied trial-by-trial: a ‘yes’ response was more likely after a correct rejection trial than a hit trial. Simulation using an SDT model with several decision components reproduced the experimental observations accurately, leaving only ∼10% of the variance unaccounted for. The model also showed that trial-by-trial dependencies were unlikely to influence measured psychometric functions or thresholds. An additional model component suggested that inattention did not contribute substantially. Further analysis showed that ferrets were changing their decision criteria, almost optimally, to maximise the reward obtained in a session. The data suggest trial-by-trial reward-driven optimization of the decision process. Understanding the factors determining behavioural responses is important for correlating neural activity and behaviour. SDT provides a good account of animal psychoacoustics, and can be validated using standard psychophysical methods and computer simulations, without recourse to ROC measurements. PMID:22698686

A comparison of logistic regression analysis and an artificial neural network using the BI-RADS lexicon for ultrasonography in conjunction with introbserver variability.

PubMed

Kim, Sun Mi; Han, Heon; Park, Jeong Mi; Choi, Yoon Jung; Yoon, Hoi Soo; Sohn, Jung Hee; Baek, Moon Hee; Kim, Yoon Nam; Chae, Young Moon; June, Jeon Jong; Lee, Jiwon; Jeon, Yong Hwan

2012-10-01

To determine which Breast Imaging Reporting and Data System (BI-RADS) descriptors for ultrasound are predictors for breast cancer using logistic regression (LR) analysis in conjunction with interobserver variability between breast radiologists, and to compare the performance of artificial neural network (ANN) and LR models in differentiation of benign and malignant breast masses. Five breast radiologists retrospectively reviewed 140 breast masses and described each lesion using BI-RADS lexicon and categorized final assessments. Interobserver agreements between the observers were measured by kappa statistics. The radiologists' responses for BI-RADS were pooled. The data were divided randomly into train (n = 70) and test sets (n = 70). Using train set, optimal independent variables were determined by using LR analysis with forward stepwise selection. The LR and ANN models were constructed with the optimal independent variables and the biopsy results as dependent variable. Performances of the models and radiologists were evaluated on the test set using receiver-operating characteristic (ROC) analysis. Among BI-RADS descriptors, margin and boundary were determined as the predictors according to stepwise LR showing moderate interobserver agreement. Area under the ROC curves (AUC) for both of LR and ANN were 0.87 (95% CI, 0.77-0.94). AUCs for the five radiologists ranged 0.79-0.91. There was no significant difference in AUC values among the LR, ANN, and radiologists (p > 0.05). Margin and boundary were found as statistically significant predictors with good interobserver agreement. Use of the LR and ANN showed similar performance to that of the radiologists for differentiation of benign and malignant breast masses.

The role of stenosis ratio as a predictor of surgical satisfaction in patients with lumbar spinal canal stenosis: a receiver-operator characteristic (ROC) curve analysis.

PubMed

Mohammadi, Hassanreza R; Azimi, Parisa; Benzel, Edward C; Shahzadi, Sohrab; Azhari, Shirzad

2016-09-01

The aim of this study was to elucidate independent factors that predict surgical satisfaction in lumbar spinal canal stenosis (LSCS) patients. Patients who underwent surgery were grouped based on the age, gender, duration of symptoms, walking distance, Neurogenic Claudication Outcome Score (NCOS) and the stenosis ratio (SR) described by Lurencin. We recorded on 2-year patient satisfaction using standardized measure. The optimal cut-off points in SR, NCOS and walking distance for predicting surgical satisfaction were estimated from sensitivity and specificity calculations and receiver operator characteristic (ROC) curves. One hundred fifty consecutive patients (51 male, 99 female, mean age 62.4±10.9 years) were followed up for 34±13 months (range 24-49). One, two, three and four level stenosis was observed in 10.7%, 39.3%, 36.0 % and 14.0% of patients, respectively. Post-surgical satisfaction was 78.5% at the 2 years follow up. In ROC curve analysis, the asymptotic significance is less than 0.05 in SR and the optimal cut-off value of SR to predict worsening surgical satisfaction was measured as more than 0.52, with 85.4% sensitivity and 77.4% specificity (AUC 0.798, 95% CI 0.73-0.90; P<0.01). The present study suggests that the SR, with a cut-off set a 0.52 cross-sectional area, may be superior to walking distance and NCOS in patients with degenerative lumbar stenosis considered for surgical treatment. Using a ROC curve analysis, a radiological feature, the SR, demonstrated superiority in predicting patient satisfaction, compared to functional and clinical characteristics such as walking distance and NCOS.

Comparison of FIB-4 index and aspartate aminotransferase to platelet ratio index on carcinogenesis in chronic hepatitis B treated with entecavir

PubMed Central

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

Aims: We sought to compare the effects of FIB-4 index and aspartate aminotransferase to platelet ratio index (APRI) on hepatocellular carcinoma (HCC) incidence in chronic hepatitis B (CHB) patients undergoing entecavir (ETV) therapy. Patient and methods: A total of 338 nucleosides analogue therapy naïve CHB patients initially treated with ETV were analyzed. The optimal cutoff points in each continuous variable were determined by receiver operating curve (ROC) analysis. The effects of FIB-4 index and APRI on HCC incidence were compared using time-dependent ROC analysis and factors linked to HCC incidence were also examined using univariate and multivariate analyses. Results: There were 215 males and 123 females with the median age of 52 years and the median baseline HBV-DNA level of 6.6 log copies/ml. The median follow-up interval after the initiation of ETV therapy was 4.99 years. During the follow-up period, 33 patients (9.8%) developed HCC. The 3-, 5- 7-year cumulative HCC incidence rates in all cases were 4.4%, 9.2% and 13.5%, respectively. In the multivariate analysis, FIB-4 index revealed to be an independent predictor associated with HCC incidence, while APRI was not. In the time-dependent ROC analyses for all cases and for all subgroups analyses stratified by viral status or cirrhosis status, all area under the ROCs in each time point (2-, 3-, 4-, 5-, 6-, and 7-year) of FIB-4 index were higher than those of APRI. Conclusion: FIB-4 index rather than APRI can be a useful predictor associated with HCC development for CHB patients undergoing ETV therapy. PMID:28243319

Comparison of FIB-4 index and aspartate aminotransferase to platelet ratio index on carcinogenesis in chronic hepatitis B treated with entecavir.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

We sought to compare the effects of FIB-4 index and aspartate aminotransferase to platelet ratio index (APRI) on hepatocellular carcinoma (HCC) incidence in chronic hepatitis B (CHB) patients undergoing entecavir (ETV) therapy. A total of 338 nucleosides analogue therapy naïve CHB patients initially treated with ETV were analyzed. The optimal cutoff points in each continuous variable were determined by receiver operating curve (ROC) analysis. The effects of FIB-4 index and APRI on HCC incidence were compared using time-dependent ROC analysis and factors linked to HCC incidence were also examined using univariate and multivariate analyses. There were 215 males and 123 females with the median age of 52 years and the median baseline HBV-DNA level of 6.6 log copies/ml. The median follow-up interval after the initiation of ETV therapy was 4.99 years. During the follow-up period, 33 patients (9.8%) developed HCC. The 3-, 5- 7-year cumulative HCC incidence rates in all cases were 4.4%, 9.2% and 13.5%, respectively. In the multivariate analysis, FIB-4 index revealed to be an independent predictor associated with HCC incidence, while APRI was not. In the time-dependent ROC analyses for all cases and for all subgroups analyses stratified by viral status or cirrhosis status, all area under the ROCs in each time point (2-, 3-, 4-, 5-, 6-, and 7-year) of FIB-4 index were higher than those of APRI. FIB-4 index rather than APRI can be a useful predictor associated with HCC development for CHB patients undergoing ETV therapy.

Expected p-values in light of an ROC curve analysis applied to optimal multiple testing procedures.

PubMed

Vexler, Albert; Yu, Jihnhee; Zhao, Yang; Hutson, Alan D; Gurevich, Gregory

2017-01-01

Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures or associations between investigated factors to be difficult. We turn our focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we prove that the EPV can be considered in the context of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. The ROC-based framework provides a new and efficient methodology for investigating and constructing statistical decision-making procedures, including: (1) evaluation and visualization of properties of the testing mechanisms, considering, e.g. partial EPVs; (2) developing optimal tests via the minimization of EPVs; (3) creation of novel methods for optimally combining multiple test statistics. We demonstrate that the proposed EPV-based approach allows us to maximize the integrated power of testing algorithms with respect to various significance levels. In an application, we use the proposed method to construct the optimal test and analyze a myocardial infarction disease dataset. We outline the usefulness of the "EPV/ROC" technique for evaluating different decision-making procedures, their constructions and properties with an eye towards practical applications.

Clinical evaluation of JPEG2000 compression for digital mammography

NASA Astrophysics Data System (ADS)

Sung, Min-Mo; Kim, Hee-Joung; Kim, Eun-Kyung; Kwak, Jin-Young; Yoo, Jae-Kyung; Yoo, Hyung-Sik

2002-06-01

Medical images, such as computed radiography (CR), and digital mammographic images will require large storage facilities and long transmission times for picture archiving and communications system (PACS) implementation. American College of Radiology and National Equipment Manufacturers Association (ACR/NEMA) group is planning to adopt a JPEG2000 compression algorithm in digital imaging and communications in medicine (DICOM) standard to better utilize medical images. The purpose of the study was to evaluate the compression ratios of JPEG2000 for digital mammographic images using peak signal-to-noise ratio (PSNR), receiver operating characteristic (ROC) analysis, and the t-test. The traditional statistical quality measures such as PSNR, which is a commonly used measure for the evaluation of reconstructed images, measures how the reconstructed image differs from the original by making pixel-by-pixel comparisons. The ability to accurately discriminate diseased cases from normal cases is evaluated using ROC curve analysis. ROC curves can be used to compare the diagnostic performance of two or more reconstructed images. The t test can be also used to evaluate the subjective image quality of reconstructed images. The results of the t test suggested that the possible compression ratios using JPEG2000 for digital mammographic images may be as much as 15:1 without visual loss or with preserving significant medical information at a confidence level of 99%, although both PSNR and ROC analyses suggest as much as 80:1 compression ratio can be achieved without affecting clinical diagnostic performance.

Developing a new diagnostic algorithm for human papilloma virus associated oropharyngeal carcinoma: an investigation of HPV DNA assays.

PubMed

Cohen, Natasha; Gupta, Michael; Doerwald-Munoz, Lilian; Jang, Dan; Young, James Edward Massey; Archibald, Stuart; Jackson, Bernard; Lee, Jenny; Chernesky, Max

2017-02-13

Human papilloma virus (HPV) has been implicated in the development of a large proportion of oropharyngeal squamous cell carcinoma (OPSCC). Current techniques used to diagnose HPV etiology require histopathologic analysis. We aim to investigate the diagnostic accuracy of a new application non-histopathologic diagnostic tests to help assist diagnosis of HPV-related oropharyngeal tumors. Patients with OPSCC with nodal metastasis were consecutively recruited from a multidisciplinary cancer clinic. Appropriate samples were collected and analyzed. The various tests examined included COBAS® 4800, Cervista® HR and Genotyping. These tests were compared to p16 staining, which was used as the diagnostic standard. StataIC 14.2 was used to perform analysis, including sensitivity, specificity and receiver operator characteristic [ROC] curves. The COBAS® FNA (area under ROC 0.863) and saliva (area under ROC 0.847) samples performed well in diagnosing HPV positive and negative tumors. Samples tested with Cervista® did not corroborate p16 status reliably. We were able to increase the diagnostic yield of the COBAS® FNA samples by applying the results of the saliva test to negative FNA samples which correctly identified 11 additional p16 positive tumors (area under ROC 0.915). Surrogate testing for HPV using alternate methods is feasible and closely predicts the results of standard diagnostic methods. In the future, these could minimize invasive procedures for diagnosing HPV-related oropharyngeal cancer, but also help to diagnose and treat patients with unknown primaries.

[The role of preoperative (18)F-FDG PET-CT in lymphatic metastasis diagnosis of cutaneous malignant melanoma on extremities and trunk].

PubMed

Zhang, X X; Fang, Y; Xu, L B; Xu, S F; Zhao, Z G; Sun, C; Ma, P Q; Liu, T; Yu, S J; Zhang, W J

2018-05-23

Objective: To evaluate the clinical value of preoperative (18)F-Fludeoxyglucose ((18)F-FDG PET-CT) in lymphatic metastasis diagnosis of cutaneous melanoma on extremities and trunk. Methods: 112 patients with cutaneous melanoma pathologically of extremities and trunk from January 2006 to December 2016, who received (18)F-FDG PET-CT examination preoperatively, were retrospectively reviewed. The correlations between the maximal diameters of lymph nodes, the maximal standard uptake value (SUV) and the diagnostic impression grades of PET-CT examination, and the final pathological diagnosis were analyzed. The correlations between Breslow thickness of primary lesions and the diagnostic impression of PET-CT examination were also analyzed. All the above were analyzed with Receiver Operating Characteristic (ROC) curve to get the cut-off value. Based on the final results of pathological diagnosis of lymph nodes as the golden standard, the statistically significant indicators of ROC curve analysis were used to evaluate the diagnostic effect, as well as to calculate the sensitivity, specificity and accuracy. With gender, age, maximal diameter of lymph nodes, maximal SUV, diagnosis impressions, and Breslow thickness as the independent variables and pathological diagnosis results of lymph nodes as the dependent variable, two-class stepwise Logistic regression analysis was used to determine the independence of diagnostic indicators. ROC curve analysis and log rank test were used to analyze the relationship between Breslow thickness and patient survival. Results: To evaluate melanoma patients' lymph node status, the results of ROC curve analysis showed that the area under the curve of lymph node maximal diameter, maximal SUV, diagnosis impression of PET-CT examinations were 0.789, 0.786 and 0.816, respectively (all P <0.05). The cut-off values were 0.85 cm, 1.45 and 2.5, respectively. The sensitivity of the cut-off values to determine the status of lymph nodes in melanoma patients were 71.4%, 64.9% and 72.1% respectively, and the specificities were 85.2%, 88.7% and 87.0% respectively. Multivariate Logistic regression analysis showed that PET-CT diagnosis impressions had independent diagnostic significance for the lymph node status of melanoma patients ( OR =11.296, 95% CI : 2.550~50.033). The area under the curve of Breslow thickness evaluating PET-CT diagnostic impression is 0.664 ( P =0.042) and the cut-off value was 4.25 mm. The survival rate of the patients with Breslow thickness ≥ 4.25 mm was lower than that in the group <4.25 mm ( P =0.006). Conclusions: (18)F-FDG PET-CT can help to evaluate metastases and make treatment decisions for cutaneous melanoma of extremities and trunk, especially for patients whose primary lesion's Breslow thickness has reached more than 4.25 mm. For the patients whose maximal SUV of regional lymph node is higher than 1.45 and short diameter of the largest lymph node is larger than 0.85cm, the possibility of metastases should be considered.

A Quantitative Approach to Distinguish Pneumonia From Atelectasis Using Computed Tomography Attenuation.

PubMed

Edwards, Rachael M; Godwin, J David; Hippe, Dan S; Kicska, Gregory

2016-01-01

It is known that atelectasis demonstrates greater contrast enhancement than pneumonia on computed tomography (CT). However, the effectiveness of using a Hounsfield unit (HU) threshold to distinguish pneumonia from atelectasis has never been shown. The objective of the study is to demonstrate that an HU threshold can be quantitatively used to effectively distinguish pneumonia from atelectasis. Retrospectively identified CT pulmonary angiogram examinations that did not show pulmonary embolism but contained nonaerated lungs were classified as atelectasis or pneumonia based on established clinical criteria. The HU attenuation was measured in these nonaerated lungs. Receiver operating characteristic (ROC) analysis was performed to determine the area under the ROC curve, sensitivity, and specificity of using the attenuation to distinguish pneumonia from atelectasis. Sixty-eight nonaerated lungs were measured in 55 patients. The mean (SD) enhancement was 62 (18) HU in pneumonia and 119 (24) HU in atelectasis (P < 0.001). A threshold of 92 HU diagnosed pneumonia with 97% sensitivity (confidence interval [CI], 80%-99%) and 85% specificity (CI, 70-93). Accuracy, measured as area under the ROC curve, was 0.97 (CI, 0.89-0.99). We have established that a threshold HU value can be used to confidently distinguish pneumonia from atelectasis with our standard CT pulmonary angiogram imaging protocol and patient population. This suggests that a similar threshold HU value may be determined for other scanning protocols, and application of this threshold may facilitate a more confident diagnosis of pneumonia and thus speed treatment.

Utility of the Military Acute Concussion Evaluation as a screening tool for mild traumatic brain injury in a civilian trauma population.

PubMed

Stone, Melvin E; Safadjou, Saman; Farber, Benjamin; Velazco, Nerissa; Man, Jianliang; Reddy, Srinivas H; Todor, Roxanne; Teperman, Sheldon

2015-07-01

Mild traumatic brain injury (mTBI) constitutes 75% of more than 1.5 million traumatic brain injuries annually. There exists no consensus on point-of-care screening for mTBI. The Military Acute Concussion Evaluation (MACE) is a quick and easy test used by the US Army to screen for mTBI; however, its utility in civilian trauma is unclear. It has two parts: a history section and the Standardized Assessment of Concussion (SAC) score (0-30) previously validated in sports injury. As a performance improvement project, our institution sought to evaluate the MACE as a concussion screening tool that could be used by housestaff in a general civilian trauma population. From June 2013 to May 2014, patients 18 years to 65 years old with suspected concussion were given the MACE within 72 hours of admission to our urban Level I trauma center. Patients with a positive head computed tomography were excluded. Demographic data and MACE scores were recorded in prospect. Concussion was defined as loss of consciousness and/or posttraumatic amnesia; concussed patients were compared with those nonconcussed. Sensitivity and specificity for each respective MACE score were used to plot a receiver operating characteristic (ROC) curve. An ROC curve area of 0.8 was set as the benchmark for a good screening test to distinguish concussion from nonconcussion. There were 84 concussions and 30 nonconcussed patients. Both groups were similar; however, the concussion group had a lower mean MACE score than the nonconcussed patients. Data analysis demonstrated the sensitivity and specificity of a range of MACE scores used to generate an ROC curve area of only 0.65. The MACE showed a lower mean score for individuals with concussion, defined by loss of consciousness and/or posttraumatic amnesia. However, the ROC curve area of 0.65 highly suggests that MACE alone would be a poor screening test for mTBI in a general civilian trauma population. Diagnostic study, level II.

Development and prospective multicenter evaluation of the long noncoding RNA MALAT-1 as a diagnostic urinary biomarker for prostate cancer

PubMed Central

Lu, Ji; Shi, Xiaolei; Zhu, Yasheng; Zhang, Wei; Jing, Taile; Zhang, Chao; Shen, Jian; Xu, Chuanliang; Wang, Huiqing; Wang, Haifeng; Wang, Yang; Liu, Bin; Li, Yaoming; Fang, Ziyu; Guo, Fei; Qiao, Meng; Wu, Chengyao; Wei, Qiang; Xu, Danfeng; Shen, Dan; Lu, Xin; Gao, Xu; Hou, Jianguo; Sun, Yinghao

2014-01-01

The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), a long noncoding RNA, for predicting the risk of PCa before biopsy. The MALAT-1 score was tested in a discovery phase and a multi-center validation phase. The predictive power of the MALAT-1 score was evaluated by the area under receiver operating characteristic (ROC) curve (AUC) and by decision curve analysis. As an independent predictor of PCa, the MALAT-1 score was significantly higher in men with a positive biopsy than in those with a negative biopsy. The ROC analysis showed a higher AUC for the MALAT-1 score (0.670 and 0.742) vs. the total PSA (0.545 and 0.601) and percent free PSA (0.622 and 0.627) in patients with PSA values of 4.0-10 ng/ml. According to the decision curve analysis, using a probability threshold of 25%, the MALAT-1 model would prevent 30.2%-46.5% of unnecessary biopsies in PSA 4–10 ng/ml cohorts, without missing any high-grade cancers. Our results demonstrate that urine MALAT-1 is a promising biomarker for predicting prostate cancer risk. PMID:25526029

Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2018-01-01

Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d' or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

PubMed

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

A comparative study of quantitative immunohistochemistry and quantum dot immunohistochemistry for mutation carrier identification in Lynch syndrome.

PubMed

Barrow, Emma; Evans, D Gareth; McMahon, Ray; Hill, James; Byers, Richard

2011-03-01

Lynch Syndrome is caused by mutations in DNA mismatch repair (MMR) genes. Mutation carrier identification is facilitated by immunohistochemical detection of the MMR proteins MHL1 and MSH2 in tumour tissue and is desirable as colonoscopic screening reduces mortality. However, protein detection by conventional immunohistochemistry (IHC) is subjective, and quantitative techniques are required. Quantum dots (QDs) are novel fluorescent labels that enable quantitative multiplex staining. This study compared their use with quantitative 3,3'-diaminobenzidine (DAB) IHC for the diagnosis of Lynch Syndrome. Tumour sections from 36 mutation carriers and six controls were obtained. These were stained with DAB on an automated platform using antibodies against MLH1 and MSH2. Multiplex QD immunofluorescent staining of the sections was performed using antibodies against MLH1, MSH2 and smooth muscle actin (SMA). Multispectral analysis of the slides was performed. The staining intensity of DAB and QDs was measured in multiple colonic crypts, and the mean intensity scores calculated. Receiver operating characteristic (ROC) curves of staining performance for the identification of mutation carriers were evaluated. For quantitative DAB IHC, the area under the MLH1 ROC curve was 0.872 (95% CI 0.763 to 0.981), and the area under the MSH2 ROC curve was 0.832 (95% CI 0.704 to 0.960). For quantitative QD IHC, the area under the MLH1 ROC curve was 0.812 (95% CI 0.681 to 0.943), and the area under the MSH2 ROC curve was 0.598 (95% CI 0.418 to 0.777). Despite the advantage of QD staining to enable several markers to be measured simultaneously, it is of lower utility than DAB IHC for the identification of MMR mutation carriers. Automated DAB IHC staining and quantitative slide analysis may enable high-throughput IHC.

Discriminability of Personality Profiles in Isolated and Co-Morbid Marijuana and Nicotine Users

PubMed Central

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L.; Filbey, Francesca M

2016-01-01

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co-morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana + nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. PMID:27086256

A COMPARATIVE STUDY OF REAL-TIME AND STATIC ULTRASONOGRAPHY DIAGNOSES FOR THE INCIDENTAL DETECTION OF DIFFUSE THYROID DISEASE.

PubMed

Kim, Dong Wook

2015-08-01

The aim of this study was to compare the diagnostic accuracy of real-time and static ultrasonography (US) for the incidental detection of diffuse thyroid disease (DTD). In 118 consecutive patients, a single radiologist performed real-time US before thyroidectomy. For static US, the same radiologist retrospectively investigated the sonographic findings on a picture-archiving and communication system after 3 months. The diagnostic categories of both real-time and static US diagnoses were determined based on the number of abnormal findings, and the diagnostic indices were calculated by a receiver operating characteristic (ROC) curve analysis using the histopathologic results as the reference standard. Histopathologic results included normal thyroid (n = 77), Hashimoto thyroiditis (n = 11), non-Hashimoto lymphocytic thyroiditis (n = 29), and diffuse hyperplasia (n = 1). Normal thyroid and DTD showed significant differences in echogenicity, echotexture, glandular margin, and vascularity on both real-time and static US. There was a positive correlation between US categories and histopathologic results in both real-time and static US. The highest diagnostic indices were obtained when the cutoff criteria of real-time and static US diagnoses were chosen as indeterminate and suspicious for DTD, respectively. The ROC curve analysis showed that real-time US was superior to static US in diagnostic accuracy. Both real-time and static US may be helpful for the detection of incidental DTD, but real-time US is superior to static US for detecting incidental DTD.

Development and Validation of a Disease Severity Scoring Model for Pediatric Sepsis.

PubMed

Hu, Li; Zhu, Yimin; Chen, Mengshi; Li, Xun; Lu, Xiulan; Liang, Ying; Tan, Hongzhuan

2016-07-01

Multiple severity scoring systems have been devised and evaluated in adult sepsis, but a simplified scoring model for pediatric sepsis has not yet been developed. This study aimed to develop and validate a new scoring model to stratify the severity of pediatric sepsis, thus assisting the treatment of sepsis in children. Data from 634 consecutive patients who presented with sepsis at Children's hospital of Hunan province in China in 2011-2013 were analyzed, with 476 patients placed in training group and 158 patients in validation group. Stepwise discriminant analysis was used to develop the accurate discriminate model. A simplified scoring model was generated using weightings defined by the discriminate coefficients. The discriminant ability of the model was tested by receiver operating characteristic curves (ROC). The discriminant analysis showed that prothrombin time, D-dimer, total bilirubin, serum total protein, uric acid, PaO2/FiO2 ratio, myoglobin were associated with severity of sepsis. These seven variables were assigned with values of 4, 3, 3, 4, 3, 3, 3 respectively based on the standardized discriminant coefficients. Patients with higher scores had higher risk of severe sepsis. The areas under ROC (AROC) were 0.836 for accurate discriminate model, and 0.825 for simplified scoring model in validation group. The proposed disease severity scoring model for pediatric sepsis showed adequate discriminatory capacity and sufficient accuracy, which has important clinical significance in evaluating the severity of pediatric sepsis and predicting its progress.

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Quantitative contrast-enhanced ultrasound evaluation of pathological complete response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy.

PubMed

Wan, Cai-Feng; Liu, Xue-Song; Wang, Lin; Zhang, Jie; Lu, Jin-Song; Li, Feng-Hua

2018-06-01

To clarify whether the quantitative parameters of contrast-enhanced ultrasound (CEUS) can be used to predict pathological complete response (pCR) in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC). Fifty-one patients with histologically proved locally advanced breast cancer scheduled for NAC were enrolled. The quantitative data for CEUS and the tumor diameter were collected at baseline and before surgery, and compared with the pathological response. Multiple logistic regression analysis was performed to examine quantitative parameters at CEUS and the tumor diameter to predict the pCR, and receiver operating characteristic (ROC) curve analysis was used as a summary statistic. Multiple logistic regression analysis revealed that PEAK (the maximum intensity of the time-intensity curve during bolus transit), PEAK%, TTP% (time to peak), and diameter% were significant independent predictors of pCR, and the area under the ROC curve was 0.932(Az 1 ), and the sensitivity and specificity to predict pCR were 93.7% and 80.0%. The area under the ROC curve for the quantitative parameters was 0.927(Az 2 ), and the sensitivity and specificity to predict pCR were 81.2% and 94.3%. For diameter%, the area under the ROC curve was 0.786 (Az 3 ), and the sensitivity and specificity to predict pCR were 93.8% and 54.3%. The values of Az 1 and Az 2 were significantly higher than that of Az 3 (P = 0.027 and P = 0.034, respectively). However, there was no significant difference between the values of Az 1 and Az 2 (P = 0.825). Quantitative analysis of tumor blood perfusion with CEUS is superior to diameter% to predict pCR, and can be used as a functional technique to evaluate tumor response to NAC. Copyright © 2018. Published by Elsevier B.V.

A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

PubMed

Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

2018-04-30

Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

Wavelet coherence analysis: A new approach to distinguish organic and functional tremor types.

PubMed

Kramer, G; Van der Stouwe, A M M; Maurits, N M; Tijssen, M A J; Elting, J W J

2018-01-01

To distinguish tremor subtypes using wavelet coherence analysis (WCA). WCA enables to detect variations in coherence and phase difference between two signals over time and might be especially useful in distinguishing functional from organic tremor. In this pilot study, polymyography recordings were studied retrospectively of 26 Parkinsonian (PT), 26 functional (FT), 26 essential (ET), and 20 enhanced physiological (EPT) tremor patients. Per patient one segment of 20 s in duration, in which tremor was present continuously in the same posture, was selected. We studied several coherence and phase related parameters, and analysed all possible muscle combinations of the flexor and extensor muscles of the upper and fore arm. The area under the receiver operating characteristic curve (AUC-ROC) was applied to compare WCA and standard coherence analysis to distinguish tremor subtypes. The percentage of time with significant coherence (PTSC) and the number of periods without significant coherence (NOV) proved the most discriminative parameters. FT could be discriminated from organic (PT, ET, EPT) tremor by high NOV (31.88 vs 21.58, 23.12 and 10.20 respectively) with an AUC-ROC of 0.809, while standard coherence analysis resulted in an AUC-ROC of 0.552. EMG-EMG WCA analysis might provide additional variables to distinguish functional from organic tremor. WCA might prove to be of additional value to discriminate between tremor types. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Investigation of Three-Group Classifiers to Fully Automate Detection and Classification of Breast Lesions in an Intelligent CAD Mammography Workstation

DTIC Science & Technology

2007-05-01

evaluation of approximations,” tech. rep., Dep. Sistemes Informàtics i Computació, Univ. Politècnica de València (Spain), 2003. [7] D. C. Edwards, C. E...Maryellen L. Giger, scientific collaborator • Lorenzo Pesce, computer programmer 16 C The Hypervolume under the ROC Hypersurface of “Near-Guessing...the simple model we have just described corresponds in the two-class classification task to ROC analysis performed ‘‘per ARTICLE IN PRESS

Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma.

PubMed

Guo, Jin-Cheng; Wu, Yang; Chen, Yang; Pan, Feng; Wu, Zhi-Yong; Zhang, Jia-Sheng; Wu, Jian-Yi; Xu, Xiu-E; Zhao, Jian-Mei; Li, En-Min; Zhao, Yi; Xu, Li-Yan

2018-04-09

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC. Using Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset. Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients. The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

Diagnosis of tuberculous pleurisy with combination of adenosine deaminase and interferon-γ immunospot assay in a tuberculosis-endemic population: A prospective cohort study.

PubMed

Xu, Han-Yan; Li, Cheng-Ye; Su, Shan-Shan; Yang, Li; Ye, Min; Ye, Jun-Ru; Ke, Pei-Pei; Chen, Cheng-Shui; Xie, Yu-Peng; Li, Yu-Ping

2017-11-01

The aim of this study was to identify the optimal cut-off value of T cell enzyme-linked immunospot assay for tuberculosis (T-SPOT.TB) and evaluate its diagnostic performance alone (in the peripheral blood) or in combination with the adenosine deaminase (ADA) activity test (in peripheral blood and the pleural fluid) in patients with tuberculous pleurisy.Adult patients presenting with pleural effusion were included in this prospective cohort study. Tuberculous pleurisy was diagnosed by T-SPOT.TB in peripheral blood and a combination of T-SPOT.TB and ADA activity test in pleural fluid and peripheral blood. Receiver operating characteristic (ROC) curve in combination with multivariate logistic regression was used to evaluate the diagnostic performance of the assays.Among a total of 189 patients with suspected tuberculous pleurisy who were prospectively enrolled in this study, 177 patients were validated for inclusion in the final analysis. ROC analysis revealed that the area under the ROC curve (AUC) for T-SPOT.TB in pleural fluid and peripheral blood was 0.918 and 0.881, respectively, and for the ADA activity test in pleural fluid was 0.944. In addition, 95.5 spot-forming cells (SFCs)/2.5 × 10 cells were determined as the optimal cut-off value for T-SPOT.TB in pleural fluid. Parallel combination of T-SPOT.TB and ADA activity test in pleural fluid showed increased sensitivity (96.9%) and specificity (87.5%), whereas serial combination showed increased specificity (97.5%). The combination of 3 assays had the highest sensitivity at 97.9%, with an AUC value of 0.964.T-SPOT.TB in pleural fluid performed better than that in peripheral blood and the ADA activity test in pleural fluid for tuberculous pleurisy diagnosis. The optimal cut-off value of T-SPOT.TB in pleural fluid was 95.5 SFCs/2.5 × 10 cells. Combination of 3 assays might be a promising approach for tuberculous pleurisy diagnosis. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Diagnosis of tuberculous pleurisy with combination of adenosine deaminase and interferon-γ immunospot assay in a tuberculosis-endemic population

PubMed Central

Xu, Han-Yan; Li, Cheng-Ye; Su, Shan-Shan; Yang, Li; Ye, Min; Ye, Jun-Ru; Ke, Pei-Pei; Chen, Cheng-Shui; Xie, Yu-Peng; Li, Yu-Ping

2017-01-01

Abstract The aim of this study was to identify the optimal cut-off value of T cell enzyme-linked immunospot assay for tuberculosis (T-SPOT.TB) and evaluate its diagnostic performance alone (in the peripheral blood) or in combination with the adenosine deaminase (ADA) activity test (in peripheral blood and the pleural fluid) in patients with tuberculous pleurisy. Adult patients presenting with pleural effusion were included in this prospective cohort study. Tuberculous pleurisy was diagnosed by T-SPOT.TB in peripheral blood and a combination of T-SPOT.TB and ADA activity test in pleural fluid and peripheral blood. Receiver operating characteristic (ROC) curve in combination with multivariate logistic regression was used to evaluate the diagnostic performance of the assays. Among a total of 189 patients with suspected tuberculous pleurisy who were prospectively enrolled in this study, 177 patients were validated for inclusion in the final analysis. ROC analysis revealed that the area under the ROC curve (AUC) for T-SPOT.TB in pleural fluid and peripheral blood was 0.918 and 0.881, respectively, and for the ADA activity test in pleural fluid was 0.944. In addition, 95.5 spot-forming cells (SFCs)/2.5 × 105 cells were determined as the optimal cut-off value for T-SPOT.TB in pleural fluid. Parallel combination of T-SPOT.TB and ADA activity test in pleural fluid showed increased sensitivity (96.9%) and specificity (87.5%), whereas serial combination showed increased specificity (97.5%). The combination of 3 assays had the highest sensitivity at 97.9%, with an AUC value of 0.964. T-SPOT.TB in pleural fluid performed better than that in peripheral blood and the ADA activity test in pleural fluid for tuberculous pleurisy diagnosis. The optimal cut-off value of T-SPOT.TB in pleural fluid was 95.5 SFCs/2.5 × 105 cells. Combination of 3 assays might be a promising approach for tuberculous pleurisy diagnosis. PMID:29381918

Usefulness of CA125 and their kinetic parameters and positron emission tomography/computed tomography (PET/CT) with fluorodeoxyglucose ([18F] FDG) in the detection of recurrent ovarian cancer levels.

PubMed

Palomar Muñoz, Azahara; Cordero García, José Manuel; Talavera Rubio, Prado; García Vicente, Ana M; González García, Beatriz; Bellón Guardia, María Emiliana; Soriano Castrejón, Ángel; Aranda Aguilar, Enrique

2017-12-21

To assess the usefulness of cancer antigen 125 (CA125) serum levels and kinetic values, velocity (CA125vel) and doubling time (CA125dt), as well as fluorodeoxyglucose ([ 18 F]FDG) positron emission tomography/computed tomography (PET/CT), in the detection of ovarian cancer recurrence. To assess the optimal cut-off for CA125, CA125vel and CA125dt to detect relapse with [ 18 F]FDG-PET/CT. A retrospective analysis was performed of 59 [ 18 F]FDG-PET/CT (48 patients) for suspected recurrence of ovarian cancer. Receiver operating characteristic (ROC) curves were plotted and area-under-the curve (AUC) statistics were computed for CA125, CA125vel and CA125dt. The results obtained in the group with normal and high (>35U/ml) CA125 levels were compared. Forty-four cases of recurrence were diagnosed (7 had CA125 ≤35U/ml), whereas 15 showed no disease. All of them were correctly catalogued by PET/CT. In ROC analysis, the discriminatory power of CA125 was relatively high (AUC 0.835) and the optimal cut-off point to reflect active disease was 23.9U/ml. The ROC analyses for the CA125vel and CA125dt showed an AUC of 0.849 and 0.728, respectively, with an optimal cut-off point of 1.96U/ml/month and 0.76 months, respectively. In patients with normal CA125 and recurrence of ovarian cancer, the CA125vel was significantly higher than in patients without recurrence (p=0.029). [ 18 F]FDG-PET/CT is more accurate than CA125 parameters in the detection of ovarian cancer recurrence. CA125 serum levels are essential; nevertheless, CA125 kinetic values must be considered to detect relapse. Particularly in patients with CA125 within normal values, in which a higher CA125vel is indicative of recurrence. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Time-varying surface electromyography topography as a prognostic tool for chronic low back pain rehabilitation.

PubMed

Hu, Yong; Kwok, Jerry Weilun; Tse, Jessica Yuk-Hang; Luk, Keith Dip-Kei

2014-06-01

Nonsurgical rehabilitation therapy is a commonly used strategy to treat chronic low back pain (LBP). The selection of the most appropriate therapeutic options is still a big challenge in clinical practices. Surface electromyography (sEMG) topography has been proposed to be an objective assessment of LBP rehabilitation. The quantitative analysis of dynamic sEMG would provide an objective tool of prognosis for LBP rehabilitation. To evaluate the prognostic value of quantitative sEMG topographic analysis and to verify the accuracy of the performance of proposed time-varying topographic parameters for identifying the patients who have better response toward the rehabilitation program. A retrospective study of consecutive patients. Thirty-eight patients with chronic nonspecific LBP and 43 healthy subjects. The accuracy of the time-varying quantitative sEMG topographic analysis for monitoring LBP rehabilitation progress was determined by calculating the corresponding receiver-operating characteristic (ROC) curves. Physiologic measure was the sEMG during lumbar flexion and extension. Patients who suffered from chronic nonspecific LBP without the history of back surgery and any medical conditions causing acute exacerbation of LBP during the clinical test were enlisted to perform the clinical test during the 12-week physiotherapy (PT) treatment. Low back pain patients were classified into two groups: "responding" and "nonresponding" based on the clinical assessment. The responding group referred to the LBP patients who began to recover after the PT treatment, whereas the nonresponding group referred to some LBP patients who did not recover or got worse after the treatment. The results of the time-varying analysis in the responding group were compared with those in the nonresponding group. In addition, the accuracy of the analysis was analyzed through ROC curves. The time-varying analysis showed discrepancies in the root-mean-square difference (RMSD) parameters between the responding and nonresponding groups. The relative area (RA) and relative width (RW) of RMSD at flexion and extension in the responding group were significantly lower than those in the nonresponding group (p<.05). The areas under the ROC curve of RA and RW of RMSD at flexion and extension were greater than 0.7 and were statistically significant. The quantitative time-varying analysis of sEMG topography showed significant difference between the healthy and LBP groups. The discrepancies in quantitative dynamic sEMG topography of LBP group from normal group, in terms of RA and RW of RMSD at flexion and extension, were able to identify those LBP subjects who would respond to a conservative rehabilitation program focused on functional restoration of lumbar muscle. Copyright © 2014 Elsevier Inc. All rights reserved.

Can unaided non-linguistic measures predict cochlear implant candidacy?

PubMed Central

Shim, Hyun Joon; Won, Jong Ho; Moon, Il Joon; Anderson, Elizabeth S.; Drennan, Ward R.; McIntosh, Nancy E.; Weaver, Edward M.; Rubinstein, Jay T.

2014-01-01

Objective To determine if unaided, non-linguistic psychoacoustic measures can be effective in evaluating cochlear implant (CI) candidacy. Study Design Prospective split-cohort study including predictor development subgroup and independent predictor validation subgroup. Setting Tertiary referral center. Subjects Fifteen subjects (28 ears) with hearing loss were recruited from patients visiting the University of Washington Medical Center for CI evaluation. Methods Spectral-ripple discrimination (using a 13-dB modulation depth) and temporal modulation detection using 10- and 100-Hz modulation frequencies were assessed with stimuli presented through insert earphones. Correlations between performance for psychoacoustic tasks and speech perception tasks were assessed. Receiver operating characteristic (ROC) curve analysis was performed to estimate the optimal psychoacoustic score for CI candidacy evaluation in the development subgroup and then tested in an independent sample. Results Strong correlations were observed between spectral-ripple thresholds and both aided sentence recognition and unaided word recognition. Weaker relationships were found between temporal modulation detection and speech tests. ROC curve analysis demonstrated that the unaided spectral ripple discrimination shows a good sensitivity, specificity, positive predictive value, and negative predictive value compared to the current gold standard, aided sentence recognition. Conclusions Results demonstrated that the unaided spectral-ripple discrimination test could be a promising tool for evaluating CI candidacy. PMID:24901669

A diagnostic model for the detection of sensitization to wheat allergens was developed and validated in bakery workers.

PubMed

Suarthana, Eva; Vergouwe, Yvonne; Moons, Karel G; de Monchy, Jan; Grobbee, Diederick; Heederik, Dick; Meijer, Evert

2010-09-01

To develop and validate a prediction model to detect sensitization to wheat allergens in bakery workers. The prediction model was developed in 867 Dutch bakery workers (development set, prevalence of sensitization 13%) and included questionnaire items (candidate predictors). First, principal component analysis was used to reduce the number of candidate predictors. Then, multivariable logistic regression analysis was used to develop the model. Internal validation and extent of optimism was assessed with bootstrapping. External validation was studied in 390 independent Dutch bakery workers (validation set, prevalence of sensitization 20%). The prediction model contained the predictors nasoconjunctival symptoms, asthma symptoms, shortness of breath and wheeze, work-related upper and lower respiratory symptoms, and traditional bakery. The model showed good discrimination with an area under the receiver operating characteristic (ROC) curve area of 0.76 (and 0.75 after internal validation). Application of the model in the validation set gave a reasonable discrimination (ROC area=0.69) and good calibration after a small adjustment of the model intercept. A simple model with questionnaire items only can be used to stratify bakers according to their risk of sensitization to wheat allergens. Its use may increase the cost-effectiveness of (subsequent) medical surveillance.

Comparison of Paired ROC Curves through a Two-Stage Test.

PubMed

Yu, Wenbao; Park, Eunsik; Chang, Yuan-Chin Ivan

2015-01-01

The area under the receiver operating characteristic (ROC) curve (AUC) is a popularly used index when comparing two ROC curves. Statistical tests based on it for analyzing the difference have been well developed. However, this index is less informative when two ROC curves cross and have similar AUCs. In order to detect differences between ROC curves in such situations, a two-stage nonparametric test that uses a shifted area under the ROC curve (sAUC), along with AUCs, is proposed for paired designs. The new procedure is shown, numerically, to be effective in terms of power under a wide range of scenarios; additionally, it outperforms two conventional ROC-type tests, especially when two ROC curves cross each other and have similar AUCs. Larger sAUC implies larger partial AUC at the range of low false-positive rates in this case. Because high specificity is important in many classification tasks, such as medical diagnosis, this is an appealing characteristic. The test also implicitly analyzes the equality of two commonly used binormal ROC curves at every operating point. We also apply the proposed method to synthesized data and two real examples to illustrate its usefulness in practice.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Marghany, Maged

2016-10-01

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study

PubMed Central

Hartwig, Saskia; Kluttig, Alexander; Tiller, Daniel; Fricke, Julia; Müller, Grit; Schipf, Sabine; Völzke, Henry; Schunk, Michaela; Meisinger, Christa; Schienkiewitz, Anja; Heidemann, Christin; Moebus, Susanne; Pechlivanis, Sonali; Werdan, Karl; Kuss, Oliver; Tamayo, Teresa; Haerting, Johannes; Greiser, Karin Halina

2016-01-01

Objective To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Methods Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Results Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥65 years). Conclusions We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged. PMID:26792214

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study.

PubMed

Hartwig, Saskia; Kluttig, Alexander; Tiller, Daniel; Fricke, Julia; Müller, Grit; Schipf, Sabine; Völzke, Henry; Schunk, Michaela; Meisinger, Christa; Schienkiewitz, Anja; Heidemann, Christin; Moebus, Susanne; Pechlivanis, Sonali; Werdan, Karl; Kuss, Oliver; Tamayo, Teresa; Haerting, Johannes; Greiser, Karin Halina

2016-01-20

To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Data of 10,258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥ 65 years). We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Suppression of LH during ovarian stimulation: analysing threshold values and effects on ovarian response and the outcome of assisted reproduction in down-regulated women stimulated with recombinant FSH.

PubMed

Balasch, J; Vidal, E; Peñarrubia, J; Casamitjana, R; Carmona, F; Creus, M; Fábregues, F; Vanrell, J A

2001-08-01

It has been recently suggested that gonadotrophin-releasing hormone agonist down-regulation in some normogonadotrophic women may result in profound suppression of LH concentrations, impairing adequate oestradiol synthesis and IVF and pregnancy outcome. The aims of this study, where receiver-operating characteristic (ROC) analysis was used, were: (i) to assess the usefulness of serum LH measurement on stimulation day 7 (S7) as a predictor of ovarian response, IVF outcome, implantation, and the outcome of pregnancy in patients treated with recombinant FSH under pituitary suppression; and (ii) to define the best threshold value, if any, to discriminate between women with 'low' or 'normal' LH concentrations. A total of 144 infertile women undergoing IVF/intracytoplasmic sperm injection (ICSI) treatment were included. Seventy-two consecutive patients having a positive pregnancy test (including 58 ongoing pregnancies and 14 early pregnancy losses) were initially selected. As a control non-pregnant group, the next non-conception IVF/ICSI cycle after each conceptual cycle in our assisted reproduction programme was used. The median and range of LH values in non-conception cycles, conception cycles, ongoing pregnancies, and early pregnancy losses, clearly overlapped. ROC analysis showed that serum LH concentration on S7 was unable to discriminate between conception and non-conception cycles (AUC(ROC) = 0.52; 95% CI: 0.44 to 0.61) or ongoing pregnancy versus early pregnancy loss groups (AUC(ROC) = 0.59; 95% CI: 0.46 to 0.70). To assess further the potential impact of suppressed concentrations of circulating LH during ovarian stimulation on the outcome of IVF/ICSI treatment, the three threshold values of mid-follicular serum LH proposed in the literature (<1, < or =0.7, <0.5 IU/l) to discriminate between women with 'low' or 'normal' LH were applied to our study population. No significant differences were found with respect to ovarian response, IVF/ICSI outcome, implantation, and the outcome of pregnancy between 'low' and 'normal' S7 LH women as defined by those threshold values. Our results do not support the need for additional exogenous LH supplementation in down-regulated women receiving a recombinant FSH-only preparation.

Validation of Thwaites Index for diagnosing tuberculous meningitis in a Colombian population.

PubMed

Saavedra, Juan Sebastián; Urrego, Sebastián; Toro, María Eugenia; Uribe, Carlos Santiago; García, Jenny; Hernández, Olga; Arango, Juan Carlos; Pérez, Ángela Beatriz; Franco, Andrés; Vélez, Isabel Cristina; Del Corral, Helena

2016-11-15

To determine the diagnostic accuracy of Thwaites Index (TI) in a Colombian population to distinguish meningeal tuberculosis (MTB) from bacterial meningitis (BM) and from non-tuberculous meningitis. Exploratory analyses were conducted to assess the TI's validity for patients with human immunodeficiency virus (HIV) and children above six-years-old. The study included 527 patients, the TI was calculated and results compared with those of a reference standard established by expert neurologists. Sensitivity, specificity, area under the curve of receiver-operator characteristics (AUC-ROC) and likelihood ratios were calculated. The AUC-ROC to distinguish MTB from non-tuberculous meningitis was 0.72 (95% CI: 0.67-0.77) for HIV negative adults. AUC-ROC was 0.62 (95% CI: 0.50-0.74) for HIV positive adults and 0.83 (95% CI: 0.68-0.97) for children. For distinguishing MTB from BM the AUC-ROC was 0.78 (95% CI: 0.73-0.83); furthermore, the AUC-ROC was 0.57 (95% CI: 0.31-0.83) for HIV positive adults and 0.86 (95% CI: 0.73-0.99) for children. The TI was sensitive but not specific when used to distinguish MTB from BM in HIV negative adults. In HIV positive adults the index had low diagnostic accuracy. Moreover, the TI showed discrimination capability for children over 6years; however, research with larger samples is required in these. Copyright © 2016 Elsevier B.V. All rights reserved.

Parameters for screening music performance anxiety.

PubMed

Barbar, Ana E; Crippa, José A; Osório, Flávia L

2014-09-01

To assess the discriminative capacity of the Kenny Music Performance Anxiety Inventory (K-MPAI), in its version adapted for Brazil, in a sample of 230 Brazilian adult musicians. The Social Phobia Inventory (SPIN) was used to assess the presence of social anxiety indicators, adopting it as the gold standard. The Mann-Whitney U test and the receiver operating characteristic (ROC) curve were used for statistical analysis, with p ≤ 0.05 set as the significance level. Subjects with social anxiety indicators exhibited higher mean total K-MPAI scores, as well as higher individual scores on 62% of its items. The area under the ROC curve was 0.734 (p = 0.001), and considered appropriate. Within the possible cutoff scores presented, the score -15 had the best balance of sensitivity and specificity values. However, the score -7 had greater specificity and accuracy. The K-MPAI showed appropriate discriminant validity, with a marked association between music performance anxiety and social anxiety. The cutoff scores presented in the study have both clinical and research value, allowing screening for music performance anxiety and identification of possible cases.

A dimensionless dynamic contrast enhanced MRI parameter for intra-prostatic tumour target volume delineation: initial comparison with histology

NASA Astrophysics Data System (ADS)

Hrinivich, W. Thomas; Gibson, Eli; Gaed, Mena; Gomez, Jose A.; Moussa, Madeleine; McKenzie, Charles A.; Bauman, Glenn S.; Ward, Aaron D.; Fenster, Aaron; Wong, Eugene

2014-03-01

Purpose: T2 weighted and diffusion weighted magnetic resonance imaging (MRI) show promise in isolating prostate tumours. Dynamic contrast enhanced (DCE)-MRI has also been employed as a component in multi-parametric tumour detection schemes. Model-based parameters such as Ktrans are conventionally used to characterize DCE images and require arterial contrast agent (CR) concentration. A robust parameter map that does not depend on arterial input may be more useful for target volume delineation. We present a dimensionless parameter (Wio) that characterizes CR wash-in and washout rates without requiring arterial CR concentration. Wio is compared to Ktrans in terms of ability to discriminate cancer in the prostate, as demonstrated via comparison with histology. Methods: Three subjects underwent DCE-MRI using gadolinium contrast and 7 s imaging temporal resolution. A pathologist identified cancer on whole-mount histology specimens, and slides were deformably registered to MR images. The ability of Wio maps to discriminate cancer was determined through receiver operating characteristic curve (ROC) analysis. Results: There is a trend that Wio shows greater area under the ROC curve (AUC) than Ktrans with median AUC values of 0.74 and 0.69 respectively, but the difference was not statistically significant based on a Wilcoxon signed-rank test (p = 0.13). Conclusions: Preliminary results indicate that Wio shows potential as a tool for Ktrans QA, showing similar ability to discriminate cancer in the prostate as Ktrans without requiring arterial CR concentration.

Waveforms for Active Sensing: Optical Waveform Design and Analysis for Ballistic Imaging Through Turbid Media

DTIC Science & Technology

2008-04-04

Poisson process, the probabilities of false alarm PFA and detection PD are computed as PFA P k1 N yk 0 k 1 eNXeNXek k! 1...character- istics (ROC) (PD versus PFA ) curves for detecting opaque objects in heavy fog, considering a detector with Xe 20 and a laser power as in...objects in this scattering me- dium up to a distance of 30 MFPs. Figure 4(b) shows the system performance curves by fixing the false alarm rate PFA at

A semiparametric separation curve approach for comparing correlated ROC data from multiple markers

PubMed Central

Tang, Liansheng Larry; Zhou, Xiao-Hua

2012-01-01

In this article we propose a separation curve method to identify the range of false positive rates for which two ROC curves differ or one ROC curve is superior to the other. Our method is based on a general multivariate ROC curve model, including interaction terms between discrete covariates and false positive rates. It is applicable with most existing ROC curve models. Furthermore, we introduce a semiparametric least squares ROC estimator and apply the estimator to the separation curve method. We derive a sandwich estimator for the covariance matrix of the semiparametric estimator. We illustrate the application of our separation curve method through two real life examples. PMID:23074360

Knowledge-Based Systems Approach to Wilderness Fire Management.

NASA Astrophysics Data System (ADS)

Saveland, James M.

The 1988 and 1989 forest fire seasons in the Intermountain West highlight the shortcomings of current fire policy. To fully implement an optimization policy that minimizes the costs and net value change of resources affected by fire, long-range fire severity information is essential, yet lacking. This information is necessary for total mobility of suppression forces, implementing contain and confine suppression strategies, effectively dealing with multiple fire situations, scheduling summer prescribed burning, and wilderness fire management. A knowledge-based system, Delphi, was developed to help provide long-range information. Delphi provides: (1) a narrative of advice on where a fire might spread, if allowed to burn, (2) a summary of recent weather and fire danger information, and (3) a Bayesian analysis of long-range fire danger potential. Uncertainty is inherent in long-range information. Decision theory and judgment research can be used to help understand the heuristics experts use to make decisions under uncertainty, heuristics responsible both for expert performance and bias. Judgment heuristics and resulting bias are examined from a fire management perspective. Signal detection theory and receiver operating curve (ROC) analysis can be used to develop a long-range forecast to improve decisions. ROC analysis mimics some of the heuristics and compensates for some of the bias. Most importantly, ROC analysis displays a continuum of bias from which an optimum operating point can be selected. ROC analysis is especially appropriate for long-range forecasting since (1) the occurrence of possible future events is stated in terms of probability, (2) skill prediction is displayed, (3) inherent trade-offs are displayed, and (4) fire danger is explicitly defined. Statements on the probability of the energy release component of the National Fire Danger Rating System exceeding a critical value later in the fire season can be made early July in the Intermountain West. Delphi was evaluated formally and informally. Continual evaluation and feedback to update knowledge-based systems results in a repository for current knowledge, and a means to devise policy that will augment existing knowledge. Thus, knowledge-based systems can help implement adaptive resource management.

Simplified Acute Physiology Score II as Predictor of Mortality in Intensive Care Units: A Decision Curve Analysis.

PubMed

Allyn, Jérôme; Ferdynus, Cyril; Bohrer, Michel; Dalban, Cécile; Valance, Dorothée; Allou, Nicolas

2016-01-01

End-of-life decision-making in Intensive care Units (ICUs) is difficult. The main problems encountered are the lack of a reliable prediction score for death and the fact that the opinion of patients is rarely taken into consideration. The Decision Curve Analysis (DCA) is a recent method developed to evaluate the prediction models and which takes into account the wishes of patients (or surrogates) to expose themselves to the risk of obtaining a false result. Our objective was to evaluate the clinical usefulness, with DCA, of the Simplified Acute Physiology Score II (SAPS II) to predict ICU mortality. We conducted a retrospective cohort study from January 2011 to September 2015, in a medical-surgical 23-bed ICU at University Hospital. Performances of the SAPS II, a modified SAPS II (without AGE), and age to predict ICU mortality, were measured by a Receiver Operating Characteristic (ROC) analysis and DCA. Among the 4.370 patients admitted, 23.3% died in the ICU. Mean (standard deviation) age was 56.8 (16.7) years, and median (first-third quartile) SAPS II was 48 (34-65). Areas under ROC curves were 0.828 (0.813-0.843) for SAPS II, 0.814 (0.798-0.829) for modified SAPS II and of 0.627 (0.608-0.646) for age. DCA showed a net benefit whatever the probability threshold, especially under 0.5. DCA shows the benefits of the SAPS II to predict ICU mortality, especially when the probability threshold is low. Complementary studies are needed to define the exact role that the SAPS II can play in end-of-life decision-making in ICUs.

Simplified Acute Physiology Score II as Predictor of Mortality in Intensive Care Units: A Decision Curve Analysis

PubMed Central

Allyn, Jérôme; Ferdynus, Cyril; Bohrer, Michel; Dalban, Cécile; Valance, Dorothée; Allou, Nicolas

2016-01-01

Background End-of-life decision-making in Intensive care Units (ICUs) is difficult. The main problems encountered are the lack of a reliable prediction score for death and the fact that the opinion of patients is rarely taken into consideration. The Decision Curve Analysis (DCA) is a recent method developed to evaluate the prediction models and which takes into account the wishes of patients (or surrogates) to expose themselves to the risk of obtaining a false result. Our objective was to evaluate the clinical usefulness, with DCA, of the Simplified Acute Physiology Score II (SAPS II) to predict ICU mortality. Methods We conducted a retrospective cohort study from January 2011 to September 2015, in a medical-surgical 23-bed ICU at University Hospital. Performances of the SAPS II, a modified SAPS II (without AGE), and age to predict ICU mortality, were measured by a Receiver Operating Characteristic (ROC) analysis and DCA. Results Among the 4.370 patients admitted, 23.3% died in the ICU. Mean (standard deviation) age was 56.8 (16.7) years, and median (first-third quartile) SAPS II was 48 (34–65). Areas under ROC curves were 0.828 (0.813–0.843) for SAPS II, 0.814 (0.798–0.829) for modified SAPS II and of 0.627 (0.608–0.646) for age. DCA showed a net benefit whatever the probability threshold, especially under 0.5. Conclusion DCA shows the benefits of the SAPS II to predict ICU mortality, especially when the probability threshold is low. Complementary studies are needed to define the exact role that the SAPS II can play in end-of-life decision-making in ICUs. PMID:27741304

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion.

PubMed

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka; Tonami, Hisao

2017-01-01

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Clinical application of MRI-respiratory gating technology in the evaluation of children with obstructive sleep apnea hypopnea syndrome.

PubMed

Zeng, Guohui; Teng, Yaoshu; Zhu, Jin; Zhu, Darong; Yang, Bin; Hu, Linping; Chen, Manman; Fu, Xiao

2018-01-01

The objective of the present study was to investigate the clinical application of magnetic resonance imaging (MRI)-respiratory gating technology for assessing illness severity in children with obstructive sleep apnea hypopnea syndrome (OSAHS).MRI-respiratory gating technology was used to scan the nasopharyngeal cavities of 51 children diagnosed with OSAHS during 6 respiratory phases. Correlations between the ratio of the area of the adenoid to the area of the nasopalatine pharyngeal cavity (Sa/Snp), with the main indexes of polysomnography (PSG), were analyzed. Receiver operator characteristic (ROC) curve and Kappa analysis were used to determine the diagnostic accuracy of Sa/Snp in pediatric OSAHS.The Sa/Snp was positively correlated with the apnea hypopnea index (AHI) (P < .001) and negatively correlated with the lowest oxygen saturation of blood during sleep (LaSO2) (P < .001). ROC analysis in the 6 respiratory phases showed that the area under the curve (AUC) of the Sa/Snp in the end-expiratory phase was the largest (0.992, P < .001), providing a threshold of 69.5% for the diagnosis of severe versus slight-moderate OSAHS in children. Consistency analysis with the AHI showed a diagnosis accordance rate of 96.0% in severe pediatric OSAHS and 96.2% in slight-moderate pediatric OSAHS (Kappa = 0.922, P < .001).Stenosis of the nasopalatine pharyngeal cavity in children with adenoidal hypertrophy was greatest at the end-expiration phase during sleep. The end-expiratory Sa/Snp obtained by a combination of MRI and respiratory gating technology has potential as an important imaging index for diagnosing and evaluating severity in pediatric OSAHS.

Exhaled gases online measurements for esophageal cancer patients and healthy people by proton transfer reaction mass spectrometry.

PubMed

Zou, Xue; Zhou, Wenzhao; Lu, Yan; Shen, Chengyin; Hu, Zongtao; Wang, Hongzhi; Jiang, Haihe; Chu, Yannan

2016-11-01

Esophageal cancer is a prevalent malignancy. There is a considerable demand for developing a fast and noninvasive method to screen out the suspect esophageal cancer patients who may undergo further clinical diagnosis. The exhaled breathes from 29 esophageal cancer patients and 57 healthy people were directly measured using our home-made proton transfer reaction mass spectrometer (PTR-MS). Mann-Whitney U test and stepwise discriminant analysis were applied to identify the ions in the breath mass spectral data which can distinguish cancer cohort from healthy group. Receiver operating characteristics (ROC) analysis was also performed. Seven kinds of ions in the breath mass spectrum, viz., m/z 136, m/z 34, m/z 63, m/z 27, m/z 95, m/z 107 and m/z 45, have been found to distinguish between the esophageal cancer patients and healthy people with a sensitivity of 86.2% and a specificity of 89.5%, respectively. Compared with that from the healthy people, the breath mass spectra from esophageal cancer patients show that the mediant intensities of five kinds of ions were decrease and the rest two kinds of ions were increase. ROC analysis gave the area under the curve (AUC) of 0.943. This pilot study shows that the ionic characteristics of exhaled VOCs detected by PTR-MS may be used to differentiate between the esophageal cancer patients and the healthy people. Although the breath tests for more patients are needed to confirm such results, the present work indicates that the PTR-MS may be a promising method in the esophageal cancer screening. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Evaluation of MIh Scoring System in Diagnosis of Obstructive Sleep Apnea Syndrome.

PubMed

Xu, Qinxing; Du, Junwei; Ling, Xiaobo; Lu, Yangfei

2017-10-02

BACKGROUND The objective of the present study was to investigate whether the analysis of magnesium (Mg), high-sensitivity C-reactive protein (hsCRP), and ischemia-modified albumin (IMA) concentrations can be used as a non-invasive and convenient method for diagnosing obstructive sleep apnea syndrome (OSAS). MATERIAL AND METHODS After polysomnography, venous blood was collected from 33 patients with OSAS and 30 control individuals. Serum levels of Mg, hsCRP, and IMA were investigated. The relationship between these factors and apnea-hypopnea index (AHI) was analyzed using the Pearson correlation coefficient. The role of the factors was determined using a receiver operating characteristic (ROC) curve and multivariate logistic regression analysis. RESULTS The levels of hsCRP and IMA were significantly higher in patients with OSAS than in control subjects, while the levels of Mg were lower (P<0.05 for all). A significant correlation was noted between serum IMA (r=0.614; P<0.001) and hsCRP (r=0.453; P<0.001) levels and the AHI. The ROC showed that serum Mg (AUC=0.74(0.62-0.85)), hsCRP (AUC=0.77(0.65-0.87)), and IMA (AUC=0.78(0.66-0.87)) levels could be used as markers to diagnose OSAS. Moreover, our new model, MIh, which is obtained by multivariate analysis, yielded an AUC value of 0.93 (0.83-0.98). Continuous positive airway pressure (CPAP) treatment reversed the changes in the serum levels of Mg, hsCRP, and IMA. CONCLUSIONS Patients with OSAS show reduced serum Mg levels and elevated serum hsCRP and IMA levels. These observed alterations can be reversed by CPAP treatment. A novel model, named MIh, may be a promising tool for OSAS diagnosis.

Statistical properties of a utility measure of observer performance compared to area under the ROC curve

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Samuelson, Frank W.; Gallas, Brandon D.; Boone, John M.; Niklason, Loren T.

2013-03-01

The receiver operating characteristic (ROC) curve has become a common tool for evaluating diagnostic imaging technologies, and the primary endpoint of such evaluations is the area under the curve (AUC), which integrates sensitivity over the entire false positive range. An alternative figure of merit for ROC studies is expected utility (EU), which focuses on the relevant region of the ROC curve as defined by disease prevalence and the relative utility of the task. However if this measure is to be used, it must also have desirable statistical properties keep the burden of observer performance studies as low as possible. Here, we evaluate effect size and variability for EU and AUC. We use two observer performance studies recently submitted to the FDA to compare the EU and AUC endpoints. The studies were conducted using the multi-reader multi-case methodology in which all readers score all cases in all modalities. ROC curves from the study were used to generate both the AUC and EU values for each reader and modality. The EU measure was computed assuming an iso-utility slope of 1.03. We find mean effect sizes, the reader averaged difference between modalities, to be roughly 2.0 times as big for EU as AUC. The standard deviation across readers is roughly 1.4 times as large, suggesting better statistical properties for the EU endpoint. In a simple power analysis of paired comparison across readers, the utility measure required 36% fewer readers on average to achieve 80% statistical power compared to AUC.

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

PubMed

Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu

2016-06-01

We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s. Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Reader performance in visual assessment of breast density using visual analogue scales: Are some readers more predictive of breast cancer?

NASA Astrophysics Data System (ADS)

Rayner, Millicent; Harkness, Elaine F.; Foden, Philip; Wilson, Mary; Gadde, Soujanya; Beetles, Ursula; Lim, Yit Y.; Jain, Anil; Bundred, Sally; Barr, Nicky; Evans, D. Gareth; Howell, Anthony; Maxwell, Anthony; Astley, Susan M.

2018-03-01

Mammographic breast density is one of the strongest risk factors for breast cancer, and is used in risk prediction and for deciding appropriate imaging strategies. In the Predicting Risk Of Cancer At Screening (PROCAS) study, percent density estimated by two readers on Visual Analogue Scales (VAS) has shown a strong relationship with breast cancer risk when assessed against automated methods. However, this method suffers from reader variability. This study aimed to assess the performance of PROCAS readers using VAS, and to identify those most predictive of breast cancer. We selected the seven readers who had estimated density on over 6,500 women including at least 100 cancer cases, analysing their performance using multivariable logistic regression and Receiver Operator Characteristic (ROC) analysis. All seven readers showed statistically significant odds ratios (OR) for cancer risk according to VAS score after adjusting for classical risk factors. The OR was greatest for reader 18 at 1.026 (95% Cl 1.018-1.034). Adjusted Area Under the ROC Curves (AUCs) were statistically significant for all readers, but greatest for reader 14 at 0.639. Further analysis of the VAS scores for these two readers showed reader 14 had higher sensitivity (78.0% versus 42.2%), whereas reader 18 had higher specificity (78.0% versus 46.0%). Our results demonstrate individual differences when assigning VAS scores; one better identified those with increased risk, whereas another better identified low risk individuals. However, despite their different strengths, both readers showed similar predictive abilities overall. Standardised training for VAS may improve reader variability and consistency of VAS scoring.

Alterations in regional homogeneity of resting-state brain activity in patients with major depressive disorder screening positive on the 32-item hypomania checklist (HCL-32).

PubMed

Yang, Haichen; Li, Linling; Peng, Hongjun; Liu, Tiebang; Young, Allan H; Angst, Jules; Ye, Rong; Rong, Han; Ji, Erni; Qiu, Yunhai; Li, Lingjiang

2016-10-01

Bipolar disorder (BD) is difficult to diagnose in the early stages of the illness, with the most frequent misdiagnosis being major depressive disorder (MDD). We aimed to use a regional homogeneity (ReHo) approach with resting-state functional magnetic resonance imaging (rs-fMRI) to investigate the features of spontaneous brain activity in MDD patients screening positive on the 32-item Hypomania Checklist (HCL-32). Nineteen MDD patients screening positive (HCL-32(+); 9 males; 24.9±5.7 years) and 18 patients screening negative (HCL-32(-); 9 males; 27.1±6.7 years), together with 24 healthy controls (HC; 11 males; 26.4±3.9 years) were studied. ReHo maps were compared and an receiver operating characteristic (ROC) analysis was conducted to confirm the utility of the identified ReHo differences in classifying the patients. The MDD versus HC showed different ReHo in many brain areas, especially in the frontal and parietal cortex. The HCL-32(+) versus HCL-32(-) showed significant increase of ReHo in the right medial superior frontal cortex, left inferior parietal cortex and middle/inferior temporal cortex, and decrease of ReHo in the left postcentral cortex and cerebellum. ROC analysis showed good sensitivity and specificity for distinguishing these two subgroups of MDD. Recruited patients were all on antidepressants and standard mania rating scales were not performed to assess their hypomanic symptoms. The rs-fMRI measurement of ReHo in distributed brain regions may be putative biomarkers which could differentiate subthreshold BD from MDD. Copyright © 2016 Elsevier B.V. All rights reserved.

Mutations in the LRRK2 Roc-COR tandem domain link Parkinson's disease to Wnt signalling pathways.

PubMed

Sancho, Rosa M; Law, Bernard M H; Harvey, Kirsten

2009-10-15

Mutations in PARK8, encoding LRRK2, are the most common known cause of Parkinson's disease. The LRRK2 Roc-COR tandem domain exhibits GTPase activity controlling LRRK2 kinase activity via an intramolecular process. We report the interaction of LRRK2 with the dishevelled family of phosphoproteins (DVL1-3), key regulators of Wnt (Wingless/Int) signalling pathways important for axon guidance, synapse formation and neuronal maintenance. Interestingly, DVLs can interact with and mediate the activation of small GTPases with structural similarity to the LRRK2 Roc domain. The LRRK2 Roc-COR domain and the DVL1 DEP domain were necessary and sufficient for LRRK2-DVL1 interaction. Co-expression of DVL1 increased LRRK2 steady-state protein levels, an effect that was dependent on the DEP domain. Strikingly, LRRK2-DVL1-3 interactions were disrupted by the familial PARK8 mutation Y1699C, whereas pathogenic mutations at residues R1441 and R1728 strengthened LRRK2-DVL1 interactions. Co-expression of DVL1 with LRRK2 in mammalian cells resulted in the redistribution of LRRK2 to typical cytoplasmic DVL1 aggregates in HEK293 and SH-SY5Y cells and co-localization in neurites and growth cones of differentiated dopaminergic SH-SY5Y cells. This is the first report of the modulation of a key LRRK2-accessory protein interaction by PARK8 Roc-COR domain mutations segregating with Parkinson's disease. Since the DVL1 DEP domain is known to be involved in the regulation of small GTPases, we propose that: (i) DVLs may influence LRRK2 GTPase activity, and (ii) Roc-COR domain mutations modulating LRRK2-DVL interactions indirectly influence kinase activity. Our findings also link LRRK2 to Wnt signalling pathways, suggesting novel pathogenic mechanisms and new targets for genetic analysis in Parkinson's disease.

Mutations in the LRRK2 Roc-COR tandem domain link Parkinson's disease to Wnt signalling pathways

PubMed Central

Sancho, Rosa M.; Law, Bernard M.H.; Harvey, Kirsten

2009-01-01

Mutations in PARK8, encoding LRRK2, are the most common known cause of Parkinson's disease. The LRRK2 Roc-COR tandem domain exhibits GTPase activity controlling LRRK2 kinase activity via an intramolecular process. We report the interaction of LRRK2 with the dishevelled family of phosphoproteins (DVL1-3), key regulators of Wnt (Wingless/Int) signalling pathways important for axon guidance, synapse formation and neuronal maintenance. Interestingly, DVLs can interact with and mediate the activation of small GTPases with structural similarity to the LRRK2 Roc domain. The LRRK2 Roc-COR domain and the DVL1 DEP domain were necessary and sufficient for LRRK2–DVL1 interaction. Co-expression of DVL1 increased LRRK2 steady-state protein levels, an effect that was dependent on the DEP domain. Strikingly, LRRK2–DVL1-3 interactions were disrupted by the familial PARK8 mutation Y1699C, whereas pathogenic mutations at residues R1441 and R1728 strengthened LRRK2–DVL1 interactions. Co-expression of DVL1 with LRRK2 in mammalian cells resulted in the redistribution of LRRK2 to typical cytoplasmic DVL1 aggregates in HEK293 and SH-SY5Y cells and co-localization in neurites and growth cones of differentiated dopaminergic SH-SY5Y cells. This is the first report of the modulation of a key LRRK2-accessory protein interaction by PARK8 Roc-COR domain mutations segregating with Parkinson's disease. Since the DVL1 DEP domain is known to be involved in the regulation of small GTPases, we propose that: (i) DVLs may influence LRRK2 GTPase activity, and (ii) Roc-COR domain mutations modulating LRRK2–DVL interactions indirectly influence kinase activity. Our findings also link LRRK2 to Wnt signalling pathways, suggesting novel pathogenic mechanisms and new targets for genetic analysis in Parkinson's disease. PMID:19625296

A new comparison of hyperspectral anomaly detection algorithms for real-time applications

NASA Astrophysics Data System (ADS)

Díaz, María.; López, Sebastián.; Sarmiento, Roberto

2016-10-01

Due to the high spectral resolution that remotely sensed hyperspectral images provide, there has been an increasing interest in anomaly detection. The aim of anomaly detection is to stand over pixels whose spectral signature differs significantly from the background spectra. Basically, anomaly detectors mark pixels with a certain score, considering as anomalies those whose scores are higher than a threshold. Receiver Operating Characteristic (ROC) curves have been widely used as an assessment measure in order to compare the performance of different algorithms. ROC curves are graphical plots which illustrate the trade- off between false positive and true positive rates. However, they are limited in order to make deep comparisons due to the fact that they discard relevant factors required in real-time applications such as run times, costs of misclassification and the competence to mark anomalies with high scores. This last fact is fundamental in anomaly detection in order to distinguish them easily from the background without any posterior processing. An extensive set of simulations have been made using different anomaly detection algorithms, comparing their performances and efficiencies using several extra metrics in order to complement ROC curves analysis. Results support our proposal and demonstrate that ROC curves do not provide a good visualization of detection performances for themselves. Moreover, a figure of merit has been proposed in this paper which encompasses in a single global metric all the measures yielded for the proposed additional metrics. Therefore, this figure, named Detection Efficiency (DE), takes into account several crucial types of performance assessment that ROC curves do not consider. Results demonstrate that algorithms with the best detection performances according to ROC curves do not have the highest DE values. Consequently, the recommendation of using extra measures to properly evaluate performances have been supported and justified by the conclusions drawn from the simulations.

Inverse probability weighting estimation of the volume under the ROC surface in the presence of verification bias.

PubMed

Zhang, Ying; Alonzo, Todd A

2016-11-01

In diagnostic medicine, the volume under the receiver operating characteristic (ROC) surface (VUS) is a commonly used index to quantify the ability of a continuous diagnostic test to discriminate between three disease states. In practice, verification of the true disease status may be performed only for a subset of subjects under study since the verification procedure is invasive, risky, or expensive. The selection for disease examination might depend on the results of the diagnostic test and other clinical characteristics of the patients, which in turn can cause bias in estimates of the VUS. This bias is referred to as verification bias. Existing verification bias correction in three-way ROC analysis focuses on ordinal tests. We propose verification bias-correction methods to construct ROC surface and estimate the VUS for a continuous diagnostic test, based on inverse probability weighting. By applying U-statistics theory, we develop asymptotic properties for the estimator. A Jackknife estimator of variance is also derived. Extensive simulation studies are performed to evaluate the performance of the new estimators in terms of bias correction and variance. The proposed methods are used to assess the ability of a biomarker to accurately identify stages of Alzheimer's disease. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Involvement of interaction between TRPC1 and Orai1 in calcium sensing receptor-mediated calcium influx and nitric oxide generation in human umbilical vein endothelial cells].

PubMed

Wang, La-Mei; Tang, Na; Zhong, Hua; Pang, Li-Juan; Zhang, Chun-Jun; He, Fang

2018-06-25

The present study was to investigate the role of the interaction between canonical transient receptor potential channel 1 (TRPC1) and calcium release-activated calcium modulator 1 (Orai1) in extracellular Ca 2+ -sensing receptor (CaR)-induced extracellular Ca 2+ influx and nitric oxide (NO) production. Human umbilical vein endothelial cells (HUVECs) were incubated with CaR agonist Spermine [activating store-operated calcium channels (SOC) and receptor-operated calcium channels (ROC)] alone or in combination with the following reagents: CaR negative allosteric modulator Calhex231 plus ROC analogue TPA (activating ROC and blocking SOC), Ro31-8220 (PKC inhibitor that activates SOC and blocks ROC) or Go6967 (PKCs and PKCµ inhibitor that activates SOC and blocks ROC). The protein expressions and co-localization of TRPC1 and Orai1 were determined using immunofluorescent staining. The interaction between TRPC1 and Orai1 was examined by co-immunoprecipitation. We silenced the expressions of their genes in the HUVECs by transfection of constructed TRPC1 and Orai1 shRNA plasmids. Intracellular Ca 2+ concentration ([Ca 2+ ] i ) was detected using Ca 2+ indicator Fura-2/AM, and NO production was determined by DAF-FM staining. The results showed that TRPC1 and Orai1 protein expressions were co-located on the cell membrane of the HUVECs. Compared with Spermine+Ca 2+ group, Calhex231+ TPA+Spermine+Ca 2+ , Ro31-8220+Spermine+Ca 2+ and Go6976+Spermine+Ca 2+ groups exhibited down-regulated protein expressions of TRPC1 and Orai1 in cytoplasm and decreased co-localization on the cell membrane. Co-immunoprecipitation results showed that the interaction between TRPC1 and Orai1 was reduced by Calhex231 plus TPA, Ro31-8220 or Go6976 addition in the Spermine-stimulated HUVECs. Double knockdown of Trpc1 and Orai1 genes significantly decreased [Ca 2+ ] i level and NO production in all of the Spermine+Ca 2+ , Calhex231+TPA+Spermine+Ca 2+ , Ro31-8220+Spermine+Ca 2+ and Go6976+Spermine+Ca 2+ groups. These results suggest that TRPC1/Orai1 may form a complex that mediates Ca 2+ influx and No production via SOC and ROC activation.

Comparison of computed radiography and conventional radiography in detection of small volume pneumoperitoneum.

PubMed

Marolf, Angela; Blaik, Margaret; Ackerman, Norman; Watson, Elizabeth; Gibson, Nicole; Thompson, Margret

2008-01-01

The role of digital imaging is increasing as these systems are becoming more affordable and accessible. Advantages of computed radiography compared with conventional film/screen combinations include improved contrast resolution and postprocessing capabilities. Computed radiography's spatial resolution is inferior to conventional radiography; however, this limitation is considered clinically insignificant. This study prospectively compared digital imaging and conventional radiography in detecting small volume pneumoperitoneum. Twenty cadaver dogs (15-30 kg) were injected with 0.25, 0.25, and 0.5 ml for 1 ml total of air intra-abdominally, and radiographed sequentially using computed and conventional radiographic technologies. Three radiologists independently evaluated the images, and receiver operating curve (ROC) analysis compared the two imaging modalities. There was no statistical difference between computed and conventional radiography in detecting free abdominal air, but overall computed radiography was relatively more sensitive based on ROC analysis. Computed radiographic images consistently and significantly demonstrated a minimal amount of 0.5 ml of free air based on ROC analysis. However, no minimal air amount was consistently or significantly detected with conventional film. Readers were more likely to detect free air on lateral computed images than the other projections, with no significant increased sensitivity between film/screen projections. Further studies are indicated to determine the differences or lack thereof between various digital imaging systems and conventional film/screen systems.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

Proximal caries detection: Sirona Sidexis versus Kodak Ektaspeed Plus.

PubMed

Khan, Emad A; Tyndall, Donald A; Ludlow, John B; Caplan, Daniel

2005-01-01

This study compared the accuracy of intraoral film and a charge-coupled device (CCD) receptor for proximal caries detection. Four observers evaluated images of the proximal surfaces of 40 extracted posterior teeth. The presence or absence of caries was scored using a five-point confidence scale. The actual status of each surface was determined from ground section histology. Responses were evaluated by means of receiver operating characteristic (ROC) analysis. Areas under ROC curves (Az) were assessed through a paired t-test. The performance of the CCD-based intraoral sensor was not different statistically from Ektaspeed Plus film in detecting proximal caries.

Predictive factors in patients with hepatocellular carcinoma receiving sorafenib therapy using time-dependent receiver operating characteristic analysis.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

To investigate variables before sorafenib therapy on the clinical outcomes in hepatocellular carcinoma (HCC) patients receiving sorafenib and to further assess and compare the predictive performance of continuous parameters using time-dependent receiver operating characteristics (ROC) analysis. A total of 225 HCC patients were analyzed. We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of continuous parameters which were significant in the multivariate analysis in terms of OS and PFS. Total sum of area under the ROC in all time points (defined as TAAT score) in each case was calculated. Our cohort included 175 male and 50 female patients (median age, 72 years) and included 158 Child-Pugh A and 67 Child-Pugh B patients. The median OS time was 0.68 years, while the median PFS time was 0.24 years. On multivariate analysis, gender, body mass index (BMI), Child-Pugh classification, extrahepatic metastases, tumor burden, aspartate aminotransferase (AST) and alpha-fetoprotein (AFP) were identified as significant predictors of OS and ECOG-performance status, Child-Pugh classification and extrahepatic metastases were identified as significant predictors of PFS. Among three continuous variables (i.e., BMI, AST and AFP), AFP had the highest TAAT score for the entire cohort. In subgroup analyses, AFP had the highest TAAT score except for Child-Pugh B and female among three continuous variables. In continuous variables, AFP could have higher predictive accuracy for survival in HCC patients undergoing sorafenib therapy.

Accuracy of specific BIVA for the assessment of body composition in the United States population.

PubMed

Buffa, Roberto; Saragat, Bruno; Cabras, Stefano; Rinaldi, Andrea C; Marini, Elisabetta

2013-01-01

Bioelectrical impedance vector analysis (BIVA) is a technique for the assessment of hydration and nutritional status, used in the clinical practice. Specific BIVA is an analytical variant, recently proposed for the Italian elderly population, that adjusts bioelectrical values for body geometry. Evaluating the accuracy of specific BIVA in the adult U.S. population, compared to the 'classic' BIVA procedure, using DXA as the reference technique, in order to obtain an interpretative model of body composition. A cross-sectional sample of 1590 adult individuals (836 men and 754 women, 21-49 years old) derived from the NHANES 2003-2004 was considered. Classic and specific BIVA were applied. The sensitivity and specificity in recognizing individuals below the 5(th) and above the 95(th) percentiles of percent fat (FMDXA%) and extracellular/intracellular water (ECW/ICW) ratio were evaluated by receiver operating characteristic (ROC) curves. Classic and specific BIVA results were compared by a probit multiple-regression. Specific BIVA was significantly more accurate than classic BIVA in evaluating FMDXA% (ROC areas: 0.84-0.92 and 0.49-0.61 respectively; p = 0.002). The evaluation of ECW/ICW was accurate (ROC areas between 0.83 and 0.96) and similarly performed by the two procedures (p = 0.829). The accuracy of specific BIVA was similar in the two sexes (p = 0.144) and in FMDXA% and ECW/ICW (p = 0.869). Specific BIVA showed to be an accurate technique. The tolerance ellipses of specific BIVA can be used for evaluating FM% and ECW/ICW in the U.S. adult population.

Recognition ROCS Are Curvilinear--Or Are They? On Premature Arguments against the Two-High-Threshold Model of Recognition

ERIC Educational Resources Information Center

Broder, Arndt; Schutz, Julia

2009-01-01

Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…

Variations in Recollection: The Effects of Complexity on Source Recognition

ERIC Educational Resources Information Center

Parks, Colleen M.; Murray, Linda J.; Elfman, Kane; Yonelinas, Andrew P.

2011-01-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in…

Cross validation of ROC generated thresholds for field assessed aerobic fitness related to weight status and cardiovascular disease risk in Portuguese young people.

PubMed

Duncan, Michael J; Vale, Susana; Santos, Maria Paula; Ribeiro, José Carlos; Mota, Jorge

2013-01-01

To examine the efficacy of aerobic fitness thresholds in predicting weight status and cardiovascular disease risk (CVD) in young people. A cross-sectional school-based study was conducted on 414 Portuguese young people (235 girls and 179 boys) aged 10-16 years (Mean age ± SD = 13.6 ± 1. 8 years). Height and mass were assessed to determine body mass index (BMI). The 20 m multistage shuttle-fitness test (MSFT) was used as an estimate of aerobic fitness. Capillary blood sampling was used to determine: total cholesterol, triglycerides, high-, and low-density lipoprotein. These were combined with measures of systolic blood pressure as z-scores and summed to create a CVD risk score. Analysis of covariance, controlling for sexual maturation, indicated a significant main effect for BMI as a result of fitness category (P = 0.0001). When applied to CVD risk data, there was no difference between "fit" and "unfit" groups (P = 0.136). Subsequent receiver operating curve (ROC) analysis indicated significant diagnostic accuracy of 20 mMSFT performance for boys and girls (both P = 0.0001) with subsequent cut-offs of estimated VO2 peak of 49.5 ml kg(-1) min(-1) for girls and 47.7 ml kg(-1) min(-1) for boys. When applied to BMI and CVD risk data, there was a significant main effect as a result of fitness category for BMI (P = 0.0001) and CVD risk score (P = 0.0001). Recently established cut-points proposed by Boddy et al. (Boddy et al. [2012]: PLoS One 7(9): e45755) show validity in distinguishing between weight status but not CVD risk in Portuguese young people. Alternative ROC generated cut points significantly predicted BMI and CVD risk in this sample. Copyright © 2013 Wiley Periodicals, Inc.

SU-F-R-14: PET Based Radiomics to Predict Outcomes in Patients with Hodgkin Lymphoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, J; Aristophanous, M; Akhtari, M

Purpose: To identify PET-based radiomics features associated with high refractory/relapsed disease risk for Hodgkin lymphoma patients. Methods: A total of 251 Hodgkin lymphoma patients including 19 primary refractory and 9 relapsed patients were investigated. All patients underwent an initial pre-treatment diagnostic FDG PET/CT scan. All cancerous lymph node regions (ROIs) were delineated by an experienced physician based on thresholding each volume of disease in the anatomical regions to SUV>2.5. We extracted 122 image features and evaluated the effect of ROI selection (the largest ROI, the ROI with highest mean SUV, merged ROI, and a single anatomic region [e.g. mediastinum]) onmore » classification accuracy. Random forest was used as a classifier and ROC analysis was used to assess the relationship between selected features and patient’s outcome status. Results: Each patient had between 1 and 9 separate ROIs, with much intra-patient variability in PET features. The best model, which used features from a single anatomic region (the mediastinal ROI, only volumes>5cc: 169 patients with 12 primary refractory) had a classification accuracy of 80.5% for primary refractory disease. The top five features, based on Gini index, consist of shape features (max 3D-diameter and volume) and texture features (correlation and information measure of correlation1&2). In the ROC analysis, sensitivity and specificity of the best model were 0.92 and 0.80, respectively. The area under the ROC (AUC) and the accuracy were 0.86 and 0.86, respectively. The classification accuracy was less than 60% for other ROI models or when ROIs less than 5cc were included. Conclusion: This study showed that PET-based radiomics features from the mediastinal lymph region are associated with primary refractory disease and therefore may play an important role in predicting outcomes in Hodgkin lymphoma patients. These features could be additive beyond baseline tumor and clinical characteristics, and may warrant more aggressive treatment.« less

CSL encodes a leucine-rich-repeat protein implicated in red/violet light signaling to the circadian clock in Chlamydomonas

PubMed Central

Kinoshita, Ayumi; Niwa, Yoshimi; Onai, Kiyoshi; Fukuzawa, Hideya; Ishiura, Masahiro

2017-01-01

The green alga Chlamydomonas reinhardtii shows various light responses in behavior and physiology. One such photoresponse is the circadian clock, which can be reset by external light signals to entrain its oscillation to daily environmental cycles. In a previous report, we suggested that a light-induced degradation of the clock protein ROC15 is a trigger to reset the circadian clock in Chlamydomonas. However, light signaling pathways of this process remained unclear. Here, we screened for mutants that show abnormal ROC15 diurnal rhythms, including the light-induced protein degradation at dawn, using a luciferase fusion reporter. In one mutant, ROC15 degradation and phase resetting of the circadian clock by light were impaired. Interestingly, the impairments were observed in response to red and violet light, but not to blue light. We revealed that an uncharacterized gene encoding a protein similar to RAS-signaling-related leucine-rich repeat (LRR) proteins is responsible for the mutant phenotypes. Our results indicate that a previously uncharacterized red/violet light signaling pathway is involved in the phase resetting of circadian clock in Chlamydomonas. PMID:28333924

Using a constrained formulation based on probability summation to fit receiver operating characteristic (ROC) curves

NASA Astrophysics Data System (ADS)

Swensson, Richard G.; King, Jill L.; Good, Walter F.; Gur, David

2000-04-01

A constrained ROC formulation from probability summation is proposed for measuring observer performance in detecting abnormal findings on medical images. This assumes the observer's detection or rating decision on each image is determined by a latent variable that characterizes the specific finding (type and location) considered most likely to be a target abnormality. For positive cases, this 'maximum- suspicion' variable is assumed to be either the value for the actual target or for the most suspicious non-target finding, whichever is the greater (more suspicious). Unlike the usual ROC formulation, this constrained formulation guarantees a 'well-behaved' ROC curve that always equals or exceeds chance- level decisions and cannot exhibit an upward 'hook.' Its estimated parameters specify the accuracy for separating positive from negative cases, and they also predict accuracy in locating or identifying the actual abnormal findings. The present maximum-likelihood procedure (runs on PC with Windows 95 or NT) fits this constrained formulation to rating-ROC data using normal distributions with two free parameters. Fits of the conventional and constrained ROC formulations are compared for continuous and discrete-scale ratings of chest films in a variety of detection problems, both for localized lesions (nodules, rib fractures) and for diffuse abnormalities (interstitial disease, infiltrates or pnumothorax). The two fitted ROC curves are nearly identical unless the conventional ROC has an ill behaved 'hook,' below the constrained ROC.

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application.

PubMed

Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D

2016-06-15

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

pROC-Chemotype Plots Enhance the Interpretability of Benchmarking Results in Structure-Based Virtual Screening.

PubMed

Ibrahim, Tamer M; Bauer, Matthias R; Dörr, Alexander; Veyisoglu, Erdem; Boeckler, Frank M

2015-11-23

Recently, we have reported a systematic comparison of molecular preparation protocols (using MOE or Maestro) in combination with two docking tools (GOLD or Glide), employing our DEKOIS 2.0 benchmark sets. Herein, we demonstrate how comparable settings of data preparation protocols can affect the profile and AUC of pROC curves based on variations in chemotype enrichment. We show how the recognition of different classes of chemotypes can affect the docking performance, particularly in the early enrichment, and monitor changes in this recognition behavior based on score normalization and rescoring strategies. For this, we have developed "pROC-Chemotype", which is an automated protocol that matches and visualizes ligand chemotype information together with potency classes in the pROC profiles obtained by docking. This tool enhances the understanding of the influence of chemotype recognition in early enrichment, but also reveals trends of impaired recognition of chemotype classes at the end of the score-ordered rank. Identifying such issues helps to devise score-normalization strategies to overcome this potential bias in an intuitive manner. Furthermore, strong perturbations in chemotype ranking between different methods can help to identify the underlying reasons (e.g., changes in the protonation/tautomerization state). It also assists in the selection of appropriate scoring functions that are capable to retrieve more potent and diverse hits. In summary, we demonstrate how this new tool can be utilized to identify and highlight chemotype-specific behavior, e.g., in dataset preparation. This can help to overcome some chemistry-related bias in virtual screening campaigns. pROC-Chemotype is made freely available at www.dekois.com.

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

Zanca, Federica; Jacobs, Jurgen; Van Ongeval, Chantal; Claus, Filip; Celis, Valerie; Geniets, Catherine; Provost, Veerle; Pauwels, Herman; Marchal, Guy; Bosmans, Hilde

2009-03-01

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.

Diabetes mellitus is associated with late-onset post-stroke depression.

PubMed

Zhang, Yu; He, Ji-Rong; Liang, Huai-Bin; Lu, Wen-Jing; Yang, Guo-Yuan; Liu, Jian-Rong; Zeng, Li-Li

2017-10-15

To explore the associated factors of late-onset post-stroke depression (PSD). A total of 251 patients with acute ischemic stroke were recruited. The evaluation of depression was performed 2 weeks after ischemia. 206 patients showing no depression in 2 weeks were followed up. They were divided into late-onset PSD group and non-depressed group by clinical interview with Hamilton depression scale score 3 months after stroke. On the first day following hospitalization, the clinical data including age, gender, educational level and vascular risk factors were recorded. The severity, etiological subtype and location of stroke were evaluated. The inflammatory mediators, glucose and lipid levels were recorded on the day of admission. The association between clinical factors and late-onset PSD was explored by logistic regression analysis. The ROC analysis was performed to evaluate the predicting power of the clinical factors. 187 of 206 patients completed the assessment 3 months after stroke. 19 (10.16%) patients were diagnosed as late onset PSD. Diabetes mellitus was an independent risk factor for late-onset PSD (OR 2.675, p = 0.047). ROC analysis demonstrated that glucose and HbA1C could predict late-onset PSD with specificity of 84.4%. The sample of our study was small. The results should be further confirmed in a larger cohort of patients with acute ischemic stroke. The acute ischemic stroke patients with diabetes mellitus were more tendered to suffer late-onset PSD. Copyright © 2017 Elsevier B.V. All rights reserved.

Circulating anti-mullerian hormone as predictor of ovarian response to clomiphene citrate in women with polycystic ovary syndrome.

PubMed

Xi, Wenyan; Yang, Yongkang; Mao, Hui; Zhao, Xiuhua; Liu, Ming; Fu, Shengyu

2016-02-11

To investigate the impact of high circulating AMH on the outcome of CC ovulation induction in women with PCOS. This prospective cohort observational study included 81 anovulatory women with PCOS who underwent 213 cycles of CC ovarian stimulation. Serum AMH concentrations were measured on cycle day 3 before the commencement of CC in the first cycle, which were compared between responders and CC-resistant anovulation (CRA). Logistic regression analysis was applied to study the value of serum AMH for the prediction of ovarian responsiveness to CC stimulation. The receiver-operating characteristic (ROC) curve was used to evaluate the prognostic value of circulating AMH. Serum AMH levels. Women who ovulated after CC therapy had a significantly lower AMH compared with the CRA (5.34 ± 1.97 vs.7.81 ± 3.49, P < 0.001). There was a significant gradient increase of serum AMH levels with the increasing dose of CC required to achieve ovulation (P < 0.05). In multivariate logistic regression analysis, AMH was an independent predictor of ovulation induction by CC in PCOS patients. ROC curve analysis showed AMH to be a useful predictor of ovulation induction by CC in PCOS patients, having 92 % specificity and 65 % sensitivity when the threshold AMH concentration was 7.77 ng/ml. Serum AMH may be clinically useful to predict which PCOS women are more likely to respond to CC treatment and thus to direct the selection of protocols of ovulation induction.

Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?

PubMed

De Robertis, Riccardo; Maris, Bogdan; Cardobi, Nicolò; Tinazzi Martini, Paolo; Gobbo, Stefano; Capelli, Paola; Ortolani, Silvia; Cingarlini, Sara; Paiella, Salvatore; Landoni, Luca; Butturini, Giovanni; Regi, Paolo; Scarpa, Aldo; Tortora, Giampaolo; D'Onofrio, Mirko

2018-06-01

To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness. Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter. ADC entropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADC kurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05). Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADC entropy and ADC kurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.

The global nonmethane reactive organic carbon budget: A modeling perspective

NASA Astrophysics Data System (ADS)

Safieddine, Sarah A.; Heald, Colette L.; Henderson, Barron H.

2017-04-01

The cycling of reactive organic carbon (ROC) is central to tropospheric chemistry. We characterize the global tropospheric ROC budget as simulated with the GEOS-Chem model. We expand the standard simulation by including new emissions and gas-phase chemistry, an expansion of dry and wet removal, and a mass tracking of all ROC species to achieve carbon closure. The resulting global annual mean ROC burden is 16 Tg C, with sources from methane oxidation and direct emissions contributing 415 and 935 Tg C yr-1. ROC is lost from the atmosphere via physical deposition (460 Tg C yr-1), and oxidation to CO/CO2 (875 Tg C yr-1). Ketones, alkanes, alkenes, and aromatic hydrocarbons dominate the ROC burden, whereas aldehydes and isoprene dominate the ROC global mean surface OH reactivity. Simulated OH reactivities are between 0.8-1 s-1, 3-14 s-1, and 12-34 s-1 over selected regions in the remote ocean, continental midlatitudes, and the tropics, respectively, and are consistent with observational constraints.

[Frail-VIG index: Design and evaluation of a new frailty index based on the Comprehensive Geriatric Assessment].

PubMed

Amblàs-Novellas, Jordi; Martori, Joan Carles; Molist Brunet, Núria; Oller, Ramon; Gómez-Batiste, Xavier; Espaulella Panicot, Joan

Frailty is closely linked to health results. Frailty indexes (FI) and the Comprehensive Geriatric Assessment (CGA) are multidimensional tools. FI serve to quantitatively measure frailty levels. They have shown to have an excellent correlation with mortality. However, they are infrequently used in clinical practice. Given the need for new, more concise, and pragmatic FI, a new FI is proposed based on a CGA (Frail-VIG Index). A prospective, observational, longitudinal study was conducted, with cohort follow up at 12 months or death. Participants were patients admitted in the Geriatric Unit of the University Hospital of Vic (Barcelona, Spain) during 2014. Contrast of hypothesis log-rank for survival curves according to Frail-VIG index, and analysis of ROC curves were performed to assess prognostic capacity. A total of 590 patients were included (mean age=86.39). Mortality rate at 12 months was 46.4%. The comparative analysis showed statistically significant differences (P<.05) for almost all variables included in the Frail-VIG index. Survival curves also show significant differences (X 2 =445, P<.001) for the different Frail-VIG index scores. The area under the ROC curve at 12 months was 0.9 (0.88-0.92). An administration time of the Index is estimated at less than 10minutes. Results endorse the Frail-VIG index as a simple (as for contents), rapid (for administration time) tool, with discriminative (for situational diagnosis) and predictive capacity (high correlation with mortality). Copyright © 2016 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

Discriminability of personality profiles in isolated and Co-morbid marijuana and nicotine users.

PubMed

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L; Filbey, Francesca M

2016-04-30

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana+nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

BAP1 immunohistochemistry and p16 FISH results in combination provide higher confidence in malignant pleural mesothelioma diagnosis: ROC analysis of the two tests.

PubMed

Hida, Tomoyuki; Hamasaki, Makoto; Matsumoto, Shinji; Sato, Ayuko; Tsujimura, Tohru; Kawahara, Kunimitsu; Iwasaki, Akinori; Okamoto, Tatsuro; Oda, Yoshinao; Honda, Hiroshi; Nabeshima, Kazuki

2016-10-01

Differentiation of malignant pleural mesothelioma (MPM) from benign mesothelial proliferation remains problematic. Loss of nuclear staining of BRCA1-associated protein 1 (BAP1; detected using immunohistochemistry (IHC)) and homozygous deletion (HD) of p16 (detected using fluorescence in situ hybridization (FISH)) are useful for differentiation of MPM from reactive mesothelial hyperplasia (RMH), but the correlation between BAP1 expression loss and p16 HD has not been fully described. We performed BAP1 IHC and p16-specific FISH for 40 MPM and 20 RMH cases, and measured proportions of cells showing BAP1 expression and p16 HD for each case. The diagnostic accuracy for MPM and the cut-off values of the two methods were assessed using receiver operating characteristic (ROC) analysis. BAP1 expression loss, p16 HD and coexistence of both were present in 27 (67.5 %), 27 (67.5 %) and 17 (42.5 %) MPM cases, respectively. Three MPM cases (7.5 %) and all 20 RMH cases had neither BAP1 loss nor p16 HD. There was no correlation between the results of the two methods. Their combination showed higher sensitivity (92.5 %, 37/40) and estimated probability than BAP1 IHC and p16-specific FISH used alone. BAP1 IHC and p16-specific FISH have independent diagnostic value, and have increased reliability when used in combination, for MPM diagnosis. © 2016 Japanese Society of Pathology and John Wiley & Sons Australia, Ltd.

A Serum Circulating miRNA Signature for Short-Term Risk of Progression to Active Tuberculosis Among Household Contacts.

PubMed

Duffy, Fergal J; Thompson, Ethan; Downing, Katrina; Suliman, Sara; Mayanja-Kizza, Harriet; Boom, W Henry; Thiel, Bonnie; Weiner Iii, January; Kaufmann, Stefan H E; Dover, Drew; Tabb, David L; Dockrell, Hazel M; Ottenhoff, Tom H M; Tromp, Gerard; Scriba, Thomas J; Zak, Daniel E; Walzl, Gerhard

2018-01-01

Biomarkers that predict who among recently Mycobacterium tuberculosis (MTB)-exposed individuals will progress to active tuberculosis are urgently needed. Intracellular microRNAs (miRNAs) regulate the host response to MTB and circulating miRNAs (c-miRNAs) have been developed as biomarkers for other diseases. We performed machine-learning analysis of c-miRNA measurements in the serum of adult household contacts (HHCs) of TB index cases from South Africa and Uganda and developed a c-miRNA-based signature of risk for progression to active TB. This c-miRNA-based signature significantly discriminated HHCs within 6 months of progression to active disease from HHCs that remained healthy in an independent test set [ROC area under the ROC curve (AUC) 0.74, progressors < 6 Mo to active TB and ROC AUC 0.66, up to 24 Mo to active TB], and complements the predictions of a previous cellular mRNA-based signature of TB risk.

Clinical utility of the Calgary Depression Scale for Schizophrenia in individuals at ultra-high risk of psychosis.

PubMed

Rekhi, Gurpreet; Ng, Wai Yee; Lee, Jimmy

2018-03-01

There is a pressing need for reliable and valid rating scales to assess and measure depression in individuals at ultra-high risk (UHR) of psychosis. The aim of this study was to examine the clinical utility of the Calgary Depression Scale for Schizophrenia (CDSS) in individuals at UHR of psychosis. 167 individuals at UHR of psychosis were included as participants in this study. The Structured Clinical Interview for DSM-IV Axis I Disorders, CDSS, Beck Anxiety Inventory and Global Assessment of Functioning were administered. A receiver operating characteristic (ROC) curve analysis and factor analyses were performed. Cronbach's alpha was computed. Correlations between CDSS factor scores and other clinical variables were examined. The median CDSS total score was 5.0 (IQR 1.0-9.0). The area under ROC curve was 0.886 and Cronbach's alpha was 0.855. A score of 7 on the CDSS yielded the highest sensitivity and specificity in detecting depression in UHR individuals. Exploratory factor analysis of the CDSS yielded two factors: depression-hopelessness and self depreciation-guilt, which was confirmed by confirmatory factor analysis. Further analysis showed that the depression-hopelessness factor predicted functioning; whereas the self depreciation-guilt factor was related to the severity of the attenuated psychotic symptoms. In conclusion, the CDSS demonstrates good psychometric properties when used to evaluate depression in individuals at UHR of psychosis. Our study results also support a two-factor structure of the CDSS in UHR individuals. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Influences on emergency department length of stay for older people.

PubMed

Street, Maryann; Mohebbi, Mohammadreza; Berry, Debra; Cross, Anthony; Considine, Julie

2018-02-14

The aim of this study was to examine the influences on emergency department (ED) length of stay (LOS) for older people and develop a predictive model for an ED LOS more than 4 h. This retrospective cohort study used organizational data linkage at the patient level from a major Australian health service. The study population was aged 65 years or older, attending an ED during the 2013/2014 financial year. We developed and internally validated a clinical prediction rule. Discriminatory performance of the model was evaluated by receiver operating characteristic (ROC) curve analysis. An integer-based risk score was developed using multivariate logistic regression. The risk score was evaluated using ROC analysis. There were 33 926 ED attendances: 57.5% (n=19 517) had an ED LOS more than 4 h. The area under ROC for age, usual accommodation, triage category, arrival by ambulance, arrival overnight, imaging, laboratory investigations, overcrowding, time to be seen by doctor, ED visits with admission and access block relating to ED LOS more than 4 h was 0.796, indicating good performance. In the validation set, area under ROC was 0.80, P-value was 0.36 and prediction mean square error was 0.18, indicating good calibration. The risk score value attributed to each risk factor ranged from 2 to 68 points. The clinical prediction rule stratified patients into five levels of risk on the basis of the total risk score. Objective identification of older people at intermediate and high risk of an ED LOS more than 4 h early in ED care enables targeted approaches to streamline the patient journey, decrease ED LOS and optimize emergency care for older people.

ROC-king onwards: intraepithelial lymphocyte counts, distribution & role in coeliac disease mucosal interpretation

PubMed Central

Rostami, Kamran; Marsh, Michael N; Johnson, Matt W; Mohaghegh, Hamid; Heal, Calvin; Holmes, Geoffrey; Ensari, Arzu; Aldulaimi, David; Bancel, Brigitte; Bassotti, Gabrio; Bateman, Adrian; Becheanu, Gabriel; Bozzola, Anna; Carroccio, Antonio; Catassi, Carlo; Ciacci, Carolina; Ciobanu, Alexandra; Danciu, Mihai; Derakhshan, Mohammad H; Elli, Luca; Ferrero, Stefano; Fiorentino, Michelangelo; Fiorino, Marilena; Ganji, Azita; Ghaffarzadehgan, Kamran; Going, James J; Ishaq, Sauid; Mandolesi, Alessandra; Mathews, Sherly; Maxim, Roxana; Mulder, Chris J; Neefjes-Borst, Andra; Robert, Marie; Russo, Ilaria; Rostami-Nejad, Mohammad; Sidoni, Angelo; Sotoudeh, Masoud; Villanacci, Vincenzo; Volta, Umberto; Zali, Mohammad R; Srivastava, Amitabh

2017-01-01

Objectives Counting intraepithelial lymphocytes (IEL) is central to the histological diagnosis of coeliac disease (CD), but no definitive ‘normal’ IEL range has ever been published. In this multicentre study, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off between normal and CD (Marsh III lesion) duodenal mucosa, based on IEL counts on >400 mucosal biopsy specimens. Design The study was designed at the International Meeting on Digestive Pathology, Bucharest 2015. Investigators from 19 centres, eight countries of three continents, recruited 198 patients with Marsh III histology and 203 controls and used one agreed protocol to count IEL/100 enterocytes in well-oriented duodenal biopsies. Demographic and serological data were also collected. Results The mean ages of CD and control groups were 45.5 (neonate to 82) and 38.3 (2–88) years. Mean IEL count was 54±18/100 enterocytes in CD and 13±8 in normal controls (p=0.0001). ROC analysis indicated an optimal cut-off point of 25 IEL/100 enterocytes, with 99% sensitivity, 92% specificity and 99.5% area under the curve. Other cut-offs between 20 and 40 IEL were less discriminatory. Additionally, there was a sufficiently high number of biopsies to explore IEL counts across the subclassification of the Marsh III lesion. Conclusion Our ROC curve analyses demonstrate that for Marsh III lesions, a cut-off of 25 IEL/100 enterocytes optimises discrimination between normal control and CD biopsies. No differences in IEL counts were found between Marsh III a, b and c lesions. There was an indication of a continuously graded dose–response by IEL to environmental (gluten) antigenic influence. PMID:28893865

[Law for the protection of returned overseas Chinese 7 September 1990].

PubMed

1990-09-10

The full text of the Beijing, China law on protection of returned overseas Chinese (ROC) (gui giao 2981 0294) and overseas Chinese families (OCF) (gui giao 0294 4187) is reported as effective on January 1, 1991 and adopted by the 7th National People's Congress Standing Committee on September 7, 1990. There are 22 articles. The 1st 2 articles define the population referred to: ROC are those Chinese who have returned and settled in China. OCF are those who have settled abroad. Family includes parents, children, spouses, brothers, sisters, grandparents, and grandchildren, and other relative receiving longterm support form overseas Chinese (OC). ROC and OCF have the same citizen rights and obligations prescribed in the constitution and other laws. ROC shall be resettled by the state. Concentrations of ROC in an area assures representation in the National People's Congress and people's congresses. ROC and OC have the right to organize social groups; the property of social groups is protected by law. In article 7, the state assures support for ranches and tree farms and school and medical care. Article 8 provides for local government support for investments of ROC, OC and OCF in industry and land commerce. Article 9 indicates government support at all levels for public services; tariffs will be reduced or exempted on donated materials and equipment brought from abroad. Private ownership of houses of ROC and OC is secured in article 10, and compensation is provided if the state appropriates the housing. ROC students and children of ROC and OC children in China are assured of support for education and employment assistance in article 11. Remittances of ROC and OCF received from abroad are protected in article 12. Article 13 secures the right of ROC and OCF to inheritance and gifts from relatives living abroad. ROC and OCF may dispose of overseas property. Article 15 requires examination of departure applications by relevant authorities. Emergency situations are accounted for. Article 16 protects the rights of visitation of a family still overseas. Article 17 assures the rights of ROC and OCF to settle abroad, and shall upon retirement continue to receive pensions, for instance. Article 18 assures assistance for study abroad. Article 19 assures rights of OC and OCF under international treaties. Article 10 provides the right to address grievances when laws have been violated. The State Council has the responsibility to prepare implementation measures pertinent to this law.

Comparative study of contrast-enhanced ultrasound qualitative and quantitative analysis for identifying benign and malignant breast tumor lumps.

PubMed

Liu, Jian; Gao, Yun-Hua; Li, Ding-Dong; Gao, Yan-Chun; Hou, Ling-Mi; Xie, Ting

2014-01-01

To compare the value of contrast-enhanced ultrasound (CEUS) qualitative and quantitative analysis in the identification of breast tumor lumps. Qualitative and quantitative indicators of CEUS for 73 cases of breast tumor lumps were retrospectively analyzed by univariate and multivariate approaches. Logistic regression was applied and ROC curves were drawn for evaluation and comparison. The CEUS qualitative indicator-generated regression equation contained three indicators, namely enhanced homogeneity, diameter line expansion and peak intensity grading, which demonstrated prediction accuracy for benign and malignant breast tumor lumps of 91.8%; the quantitative indicator-generated regression equation only contained one indicator, namely the relative peak intensity, and its prediction accuracy was 61.5%. The corresponding areas under the ROC curve for qualitative and quantitative analyses were 91.3% and 75.7%, respectively, which exhibited a statistically significant difference by the Z test (P<0.05). The ability of CEUS qualitative analysis to identify breast tumor lumps is better than with quantitative analysis.

76 FR 36923 - Announcement of Availability of the Report on Carcinogens, Twelfth Edition

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-23

... 12th RoC to the public on June 10, 2011. The report is available on the RoC Web site at: http://ntp... substances listed in the previous edition. Information about the RoC is available on the RoC Web site ( http... evaluate the scientific evidence on each candidate substance under review ( http://ntp.niehs.nih.gov/go...

Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361

A statistical investigation of z test and ROC curve on seismo-ionospheric anomalies in TEC associated earthquakes in Taiwan during 1999-2014

NASA Astrophysics Data System (ADS)

Shih, A. L.; Liu, J. Y. G.

2015-12-01

A median-based method and a z test are employed to find characteristics of seismo-ionospheric precursor (SIP) of the total electron content (TEC) in global ionosphere map (GIM) associated with 129 M≥5.5 earthquakes in Taiwan during 1999-2014. Results show that both negative and positive anomalies in the GIM TEC with the statistical significance of the z test appear few days before the earthquakes. The receiver operating characteristic (ROC) curve is further applied to see whether the SIPs exist in Taiwan.

Blood-based biomarkers used to predict disease activity in Crohn's disease and ulcerative colitis.

PubMed

Burakoff, Robert; Pabby, Vikas; Onyewadume, Louisa; Odze, Robert; Adackapara, Cheryl; Wang, Wei; Friedman, Sonia; Hamilton, Matthew; Korzenik, Joshua; Levine, Jonathan; Makrauer, Frederick; Cheng, Changming; Smith, Hai Choo; Liew, Choong-Chin; Chao, Samuel

2015-05-01

Identifying specific genes that are differentially expressed during inflammatory bowel disease flares may help stratify disease activity. The aim of this study was to identify panels of genes to be able to distinguish disease activity in Crohn's disease (CD) and ulcerative colitis (UC). Patients were grouped into categories based on disease and severity determined by histological grading. Whole blood was collected by PAXgene Blood RNA collection tubes, (PreAnalytiX) and gene expression analysis using messenger RNA was conducted. Logistic regression was performed on multiple combinations of common probe sets, and data were evaluated in terms of discrimination by computing the area under the receiving operator characteristic curve (ROC-AUC). Nine inactive CD, 8 mild CD, 10 moderate-to-severe CD, 9 inactive UC, 8 mild UC, 10 moderate-to-severe UC, and 120 controls were hybridized to Affymetrix U133 Plus 2 microarrays. Panels of 6 individual genes discriminated the stages of disease activity: CD with mild severity {ROC-AUC, 0.89 (95% confidence interval [CI], 0.84%-0.95%)}, CD with moderate-to-severe severity (ROC-AUC 0.98 [95% CI, 0.97-1.0]), UC with mild severity (ROC-AUC 0.92 [95% CI, 0.87-0.96]), and UC with moderate-to-severe severity (ROC-AUC 0.99 [95% CI, 0.97-1.0]). Validation by real-time reverse transcription-PCR confirmed the Affymetrix microarray data. The specific whole blood gene panels reliably distinguished CD and UC and determined the activity of disease, with high sensitivity and specificity in our cohorts of patients. This simple serological test has the potential to become a biomarker to determine the activity of disease.

Utility as a rationale for choosing observer performance assessment paradigms for detection tasks in medical imaging.

PubMed

Wunderlich, Adam; Abbey, Craig K

2013-11-01

Studies of lesion detectability are often carried out to evaluate medical imaging technology. For such studies, several approaches have been proposed to measure observer performance, such as the receiver operating characteristic (ROC), the localization ROC (LROC), the free-response ROC (FROC), the alternative free-response ROC (AFROC), and the exponentially transformed FROC (EFROC) paradigms. Therefore, an experimenter seeking to carry out such a study is confronted with an array of choices. Traditionally, arguments for different approaches have been made on the basis of practical considerations (statistical power, etc.) or the gross level of analysis (case-level or lesion-level). This article contends that a careful consideration of utility should form the rationale for matching the assessment paradigm to the clinical task of interest. In utility theory, task performance is commonly evaluated with total expected utility, which integrates the various event utilities against the probability of each event. To formalize the relationship between expected utility and the summary curve associated with each assessment paradigm, the concept of a "natural" utility structure is proposed. A natural utility structure is defined for a summary curve when the variables associated with the summary curve axes are sufficient for computing total expected utility, assuming that the disease prevalence is known. Natural utility structures for ROC, LROC, FROC, AFROC, and EFROC curves are introduced, clarifying how the utilities of correct and incorrect decisions are aggregated by summary curves. Further, conditions are given under which general utility structures for localization-based methodologies reduce to case-based assessment. Overall, the findings reveal how summary curves correspond to natural utility structures of diagnostic tasks, suggesting utility as a motivating principle for choosing an assessment paradigm.

Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

PubMed

Linden, Ariel

2006-04-01

Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

PubMed

Zhao, Jianhua; Lui, Harvey; Kalia, Sunil; Zeng, Haishan

2015-11-01

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

Receiver Operating Characteristic Curve Analysis of Beach Water Quality Indicator Variables

PubMed Central

Morrison, Ann Michelle; Coughlin, Kelly; Shine, James P.; Coull, Brent A.; Rex, Andrea C.

2003-01-01

Receiver operating characteristic (ROC) curve analysis is a simple and effective means to compare the accuracies of indicator variables of bacterial beach water quality. The indicator variables examined in this study were previous day's Enterococcus density and antecedent rainfall at 24, 48, and 96 h. Daily Enterococcus densities and 15-min rainfall values were collected during a 5-year (1996 to 2000) study of four Boston Harbor beaches. The indicator variables were assessed for their ability to correctly classify water as suitable or unsuitable for swimming at a maximum threshold Enterococcus density of 104 CFU/100 ml. Sensitivity and specificity values were determined for each unique previous day's Enterococcus density and antecedent rainfall volume and used to construct ROC curves. The area under the ROC curve was used to compare the accuracies of the indicator variables. Twenty-four-hour antecedent rainfall classified elevated Enterococcus densities more accurately than previous day's Enterococcus density (P = 0.079). An empirically derived threshold for 48-h antecedent rainfall, corresponding to a sensitivity of 0.75, was determined from the 1996 to 2000 data and evaluated to ascertain if the threshold would produce a 0.75 sensitivity with independent water quality data collected in 2001 from the same beaches. PMID:14602593

Fatty acids and plasmalogens of the phospholipids of the sperm membranes and their relation with the post-thaw quality of stallion spermatozoa.

PubMed

Macías García, B; González Fernández, L; Ortega Ferrusola, C; Morillo Rodríguez, A; Gallardo Bolaños, J M; Rodríguez Martinez, H; Tapia, J A; Morcuende, D; Peña, F J

2011-03-15

Fatty acids and plasmalogens were extracted from the phospholipids of the plasma membrane of stallion spermatozoa, to determine their relation with sperm quality after freezing and thawing. Sperm quality was rated using a quality index that combined the results of the analysis of sperm motility and velocity (CASA analysis), membrane status and mitochondrial membrane potential (flow cytometry) post thaw. Receiving operating system (ROC) curves were used to evaluate the value of specific lipid components of the sperm membrane herein studied as forecast of potential freezeability. From all parameters studied the ratio of percentage of C16 plasmalogens related to total phospholipids was the one with the better diagnostic value. For potentially bad freezers, the significant area under the ROC-curve was 0.74, with 75% sensitivity and 79.9% specificity for a cut off value of 26.9. Also the percentage of plasmalogens respect to total phospholipids gave good diagnostic value for bad freezers. On the other hand, the percentage of C18 fatty aldehydes related to total phospholipids of the sperm membrane properly forecasted freezeability with an area under the ROC curve of 0.70 with 70% sensitivity and 62.5% specificity for a cut off value of 0.32. Copyright © 2011 Elsevier Inc. All rights reserved.

Epidemiology, Causes and Prevention of Car Rollover Crashes with Ejection

PubMed Central

El-Hennawy, HM; El-Menyar, A; Al-Thani, H; Tuma, M; Parchani, A; Abdulrahman, H; Peralta, R; Asim, M; Zarour, A; Latifi, R

2014-01-01

Rollover crashes (ROCs) are responsible for almost a third of all highway vehicle occupant fatalities. Although ROCs are common and serious mechanism of injury, ROCs are under-reported. To analyze the causes, mechanism, impact and prevention of ROCs, we reviewed the literature between 1984 and 2013. By utilizing the search engines PubMed, MEDLINE and EMBASE by using key words “ROCs” “Ejection” and “vehicle” the initial search yielded 241 abstracts, of which 58 articles were relevant. Most of the articles were either retrospective or experimental studies funded by automobile companies. All vehicles are susceptible to rollovers to certain extents. Despite continuing innovation in vehicles’ safety, human factor is pivotal in prevention of ROCs. Distracted driving, speeding and drinking escalate the chances of rollover crashes. Wearing a seatbelt greatly improves the chances of surviving a ROC. PMID:25221693

Predictors of Gestational Diabetes Mellitus in Chinese Women with Polycystic Ovary Syndrome: A Cross-Sectional Study.

PubMed

Zhang, Ya-Jie; Jin, Hua; Qin, Zhen-Li; Ma, Jin-Long; Zhao, Han; Zhang, Ling; Chen, Zi-Jiang

2016-01-01

This study aims to explore the independent predictors of gestational diabetes mellitus (GDM) in Chinese women with polycystic ovary syndrome (PCOS). This cross-sectional study analyzed primigravid women with PCOS and classified them as those with and without GDM. Independent risk factors and model performance were analyzed using multivariate logistic regression and the area under the curve (AUC) of receiver operating characteristic (ROC), respectively. Maternal body mass index, waist circumference, waist-to-hip ratio (WHR), fasting glucose, insulin, sex hormone-binding globulin (SHBG), homeostasis model assessment-insulin resistance (HOMA-IR) before pregnancy, gestation weight gain before 24 weeks and the incidence of family history of diabetes were different in the 2 groups. Logistic regression analysis showed that pre-pregnancy WHR, SHBG, HOMA-IR and gestation weight gain before 24 weeks were the independent predictors of GDM. ROC curve analysis confirmed that gestation weight gain before 24 weeks (AUC 0.767, 95% CI 0.688-0.841), pre-pregnant WHR (AUC 0.725, 95% CI 0.649-0.802), HOMA-IR (AUC 0.711, 95% CI 0.632-0.790) and SHBG levels (AUC 0.709, 95% CI 0.625-0.793) were the strong risk factors. In Chinese women with PCOS, factors of gestation weight gain before 24 weeks, pre-pregnant WHR, HOMA-IR and SHBG levels are strongly associated with subsequent development of GDM. © 2015 S. Karger AG, Basel.

Assessing depression outcome in patients with moderate dementia: sensitivity of the HoNOS65+ scale.

PubMed

Canuto, Alessandra; Rudhard-Thomazic, Valérie; Herrmann, François R; Delaloye, Christophe; Giannakopoulos, Panteleimon; Weber, Kerstin

2009-08-15

To date, there is no widely accepted clinical scale to monitor the evolution of depressive symptoms in demented patients. We assessed the sensitivity to treatment of a validated French version of the Health of the Nation Outcome Scale (HoNOS) 65+ compared to five routinely used scales. Thirty elderly inpatients with ICD-10 diagnosis of dementia and depression were evaluated at admission and discharge using paired t-test. Using the Brief Psychiatric Rating Scale (BPRS) "depressive mood" item as gold standard, a receiver operating characteristic curve (ROC) analysis assessed the validity of HoNOS65+F "depressive symptoms" item score changes. Unlike Geriatric Depression Scale, Mini Mental State Examination and Activities of Daily Living scores, BPRS scores decreased and Global Assessment Functioning Scale score increased significantly from admission to discharge. Amongst HoNOS65+F items, "behavioural disturbance", "depressive symptoms", "activities of daily life" and "drug management" items showed highly significant changes between the first and last day of hospitalization. The ROC analysis revealed that changes in the HoNOS65+F "depressive symptoms" item correctly classified 93% of the cases with good sensitivity (0.95) and specificity (0.88) values. These data suggest that the HoNOS65+F "depressive symptoms" item may provide a valid assessment of the evolution of depressive symptoms in demented patients.

Can the pre-operative Western Ontario and McMaster score predict patient satisfaction following total hip arthroplasty?

PubMed

Rogers, B A; Alolabi, B; Carrothers, A D; Kreder, H J; Jenkinson, R J

2015-02-01

In this study we evaluated whether pre-operative Western Ontario and McMaster Universities (WOMAC) osteoarthritis scores can predict satisfaction following total hip arthroplasty (THA). Prospective data for a cohort of patients undergoing THA from two large academic centres were collected, and pre-operative and one-year post-operative WOMAC scores and a 25-point satisfaction questionnaire were obtained for 446 patients. Satisfaction scores were dichotomised into either improvement or deterioration. Scatter plots and Spearman's rank correlation coefficient were used to describe the association between pre-operative WOMAC and one-year post-operative WOMAC scores and patient satisfaction. Satisfaction was compared using receiver operating characteristic (ROC) analysis against pre-operative, post-operative and δ WOMAC scores. We found no relationship between pre-operative WOMAC scores and one-year post-operative WOMAC or satisfaction scores, with Spearman's rank correlation coefficients of 0.16 and -0.05, respectively. The ROC analysis showed areas under the curve (AUC) of 0.54 (pre-operative WOMAC), 0.67 (post-operative WOMAC) and 0.43 (δ WOMAC), respectively, for an improvement in satisfaction. We conclude that the pre-operative WOMAC score does not predict the post-operative WOMAC score or patient satisfaction after THA, and that WOMAC scores can therefore not be used to prioritise patient care. ©2015 The British Editorial Society of Bone & Joint Surgery.

Prognostic value of preoperative serum CA 242 in Esophageal squamous cell carcinoma cases.

PubMed

Feng, Ji-Feng; Huang, Ying; Chen, Qi-Xun

2013-01-01

Carbohydrate antigen (CA) 242 is inversely related to prognosis in many cancers. However, few data regarding CA 242 in esophageal cancer (EC) are available. The aim of this study was to determine the prognostic value of CA 242 and propose an optimum cut-off point in predicting survival difference in patients with esophageal squamous cell carcinoma (ESCC). A retrospective analysis was conducted of 192 cases. A receiver operating characteristic (ROC) curve for survival prediction was plotted to verify the optimum cuf- off point. Univariate and multivariate analyses were performed to evaluate prognostic parameters for survival. The positive rate for CA 242 was 7.3% (14/192). The ROC curve for survival prediction gave an optimum cut-off of 2.15 (U/ml). Patients with CA 242 ≤ 2.15 U/ml had significantly better 5-year survival than patients with CA 242 >2.15 U/ml (45.4% versus 22.6%; P=0.003). Multivariate analysis showed that differentiation (P=0.033), CA 242 (P=0.017), T grade (P=0.004) and N staging (P<0.001) were independent prognostic factors. Preoperative CA 242 is a predictive factor for long-term survival in ESCC, especially in nodal-negative patients. We conclude that 2.15 U/ml may be the optimum cuf-off point for CA 242 in predicting survival in ESCC.

Whole-lesion apparent diffusion coefficient histogram analysis: significance in T and N staging of gastric cancers.

PubMed

Liu, Song; Zhang, Yujuan; Chen, Ling; Guan, Wenxian; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang

2017-10-02

Whole-lesion apparent diffusion coefficient (ADC) histogram analysis has been introduced and proved effective in assessment of multiple tumors. However, the application of whole-volume ADC histogram analysis in gastrointestinal tumors has just started and never been reported in T and N staging of gastric cancers. Eighty patients with pathologically confirmed gastric carcinomas underwent diffusion weighted (DW) magnetic resonance imaging before surgery prospectively. Whole-lesion ADC histogram analysis was performed by two radiologists independently. The differences of ADC histogram parameters among different T and N stages were compared with independent-samples Kruskal-Wallis test. Receiver operating characteristic (ROC) analysis was performed to evaluate the performance of ADC histogram parameters in differentiating particular T or N stages of gastric cancers. There were significant differences of all the ADC histogram parameters for gastric cancers at different T (except ADC min and ADC max ) and N (except ADC max ) stages. Most ADC histogram parameters differed significantly between T1 vs T3, T1 vs T4, T2 vs T4, N0 vs N1, N0 vs N3, and some parameters (ADC 5% , ADC 10% , ADC min ) differed significantly between N0 vs N2, N2 vs N3 (all P < 0.05). Most parameters except ADC max performed well in differentiating different T and N stages of gastric cancers. Especially for identifying patients with and without lymph node metastasis, the ADC 10% yielded the largest area under the ROC curve of 0.794 (95% confidence interval, 0.677-0.911). All the parameters except ADC max showed excellent inter-observer agreement with intra-class correlation coefficients higher than 0.800. Whole-volume ADC histogram parameters held great potential in differentiating different T and N stages of gastric cancers preoperatively.

Predicting Ovarian Activity in Women Affected by Early Breast Cancer: A Meta-Analysis-Based Nomogram.

PubMed

Barnabei, Agnese; Strigari, Lidia; Marchetti, Paolo; Sini, Valentina; De Vecchis, Liana; Corsello, Salvatore Maria; Torino, Francesco

2015-10-01

The assessment of ovarian reserve in premenopausal women requiring anticancer gonadotoxic therapy can help clinicians address some challenging issues, including the probability of future pregnancies after the end of treatment. Anti-Müllerian hormone (AMH) and age can reliably estimate ovarian reserve. A limited number of studies have evaluated AMH and age as predictors of residual ovarian reserve following cytotoxic chemotherapy in breast cancer patients. To conduct a meta-analysis of published data on this topic, we searched the medical literature using the key MeSH terms "amenorrhea/chemically induced," "ovarian reserve," "anti-Mullerian hormone/blood," and "breast neoplasms/drug therapy." Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements guided the search strategy. U.K. National Health Service guidelines were used in abstracting data and assessing data quality and validity. Area under the receiver operating characteristic curve (ROC/AUC) analysis was used to evaluate the predictive utility of baseline AMH and age model. The meta-analysis of data pooled from the selected studies showed that both age and serum AMH are reliable predictors of post-treatment ovarian activity in breast cancer patients. Importantly, ROC/AUC analysis indicated AMH was a more reliable predictor of post-treatment ovarian activity in patients aged younger than 40 years (0.753; 95% confidence interval [CI]: 0.602-0.904) compared with those older than 40 years (0.678; 95% CI: 0.491-0.866). We generated a nomogram describing the correlations among age, pretreatment AMH serum levels, and ovarian activity at 1 year from the end of chemotherapy. After the ongoing validation process, the proposed nomogram may help clinicians discern premenopausal women requiring cytotoxic chemotherapy who should be considered high priority for fertility preservation counseling and procedures. ©AlphaMed Press.

Comparison of anthropometric indices for predicting the risk of metabolic syndrome and its components in Chinese adults: a prospective, longitudinal study

PubMed Central

Wang, Haoyu; Liu, Aihua; Zhao, Tong; Gong, Xun; Pang, Tianxiao; Zhou, Yingying; Xiao, Yue; Yan, Yumeng; Fan, Chenling; Teng, Weiping; Lai, Yaxin; Shan, Zhongyan

2017-01-01

Objectives Our study aimed to distinguish the ability of anthropometric indices to assess the risk of metabolic syndrome (MetS). Design Prospective cohort study. Setting Shenyang, China. Participants A total of 379 residents aged between 40 and 65 were enrolled. 253 of them were free of MetS and had been followed up for 4.5 years. Methods At baseline, all the participants underwent a thorough medical examination. A variety of anthropometric parameters were measured and calculated, including waist circumference (WC), body mass index (BMI), a body shape index (ABSI), abdominal volume index (AVI), body adiposity index, body roundness index, conicity index, waist-to-hip ratio and visceral adiposity index (VAI). After 4.5 year follow-up, we re-examined whether participants were suffering from MetS. A receiver operating characteristic (ROC) curve was applied to examine the potential of the above indices to identify the status and risk of MetS. Outcomes Occurrence of MetS. Results At baseline, 33.2% participants suffered from MetS. All of the anthropometric indices showed clinical significance, and VAI was superior to the other indices as it was found to have the largest area under the ROC curve. After a 4.5 year follow-up, 37.8% of men and 23.9% of women developed MetS. ROC curve analysis suggested that baseline BMI was the strongest predictor of MetS for men (0.77 (0.68–0.85)), and AVI was the strongest for women (0.72 (0.64–0.79)). However, no significant difference was observed between WC and both indices. In contrast, the baseline ABSI did not predict MetS in both genders. Conclusions The present study indicated that these different indices derived from anthropometric parameters have different discriminatory abilities for MetS. Although WC did not have the largest area under the ROC curve for diagnosing and predicting MetS, it may remain a better index of MetS status and risk because of its simplicity and wide use. PMID:28928179

Postoperative Decrease in Platelet Counts Is Associated with Delayed Liver Function Recovery and Complications after Partial Hepatectomy.

PubMed

Takahashi, Kazuhiro; Kurokawa, Tomohiro; Oshiro, Yukio; Fukunaga, Kiyoshi; Sakashita, Shingo; Ohkohchi, Nobuhiro

2016-05-01

Peripheral platelet counts decrease after partial hepatectomy; however, the implications of this phenomenon are unclear. We assessed if the observed decrease in platelet counts was associated with postoperative liver function and morbidity (complications grade ≤ II according to the Clavien-Dindo classification). We enrolled 216 consecutive patients who underwent partial hepatectomy for primary liver cancers, metastatic liver cancers, benign tumors, and donor hepatectomy. We classified patients as either low or high platelet percentage (postoperative platelet count/preoperative platelet count) using the optimal cutoff value calculated by a receiver operating characteristic (ROC) curve analysis, and analyzed risk factors for delayed liver functional recovery and morbidity after hepatectomy. Delayed liver function recovery and morbidity were significantly correlated with the lowest value of platelet percentage based on ROC analysis. Using a cutoff value of 60% acquired by ROC analysis, univariate and multivariate analysis determined that postoperative lowest platelet percentage ≤ 60% was identified as an independent risk factor of delayed liver function recovery (odds ratio (OR) 6.85; P < 0.01) and morbidity (OR, 4.90; P < 0.01). Furthermore, patients with the lowest platelet percentage ≤ 60% had decreased postoperative prothrombin time ratio and serum albumin level and increased serum bilirubin level when compared with patients with platelet percentage ≥ 61%. A greater than 40% decrease in platelet count after partial hepatectomy was an independent risk factor for delayed liver function recovery and postoperative morbidity. In conclusion, the decrease in platelet counts is an early marker to predict the liver function recovery and complications after hepatectomy.

Profound Effect of Profiling Platform and Normalization Strategy on Detection of Differentially Expressed MicroRNAs – A Comparative Study

PubMed Central

Meyer, Swanhild U.; Kaiser, Sebastian; Wagner, Carola; Thirion, Christian; Pfaffl, Michael W.

2012-01-01

Background Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms. Methodology/Principal Findings We included data from miRNA profiling analyses derived from a hybridization-based platform (Agilent Technologies) and an RT-qPCR platform (Applied Biosystems). Furthermore, we validated a subset of miRNAs by individual RT-qPCR assays. Our analyses incorporated data from the effect of differentiation and tumor necrosis factor alpha treatment on primary human skeletal muscle cells and a murine skeletal muscle cell line. Distinct normalization methods differed in their impact on (i) standard deviations, (ii) the area under the receiver operating characteristic (ROC) curve, (iii) the similarity of differential expression. Loess, loessM, and quantile analysis were most effective in minimizing standard deviations on the Agilent and TLDA platform. Moreover, loess, loessM, invariant selection and generalized procrustes analysis increased the area under the ROC curve, a measure for the statistical performance of a test. The Jaccard index revealed that inter-platform concordance of differential expression tended to be increased by loess, loessM, quantile, and GPA normalization of AGL and TLDA data as well as RGI normalization of TLDA data. Conclusions/Significance We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments. PMID:22723911

Practical determination of aortic valve calcium volume score on contrast-enhanced computed tomography prior to transcatheter aortic valve replacement and impact on paravalvular regurgitation: Elucidating optimal threshold cutoffs.

PubMed

Bettinger, Nicolas; Khalique, Omar K; Krepp, Joseph M; Hamid, Nadira B; Bae, David J; Pulerwitz, Todd C; Liao, Ming; Hahn, Rebecca T; Vahl, Torsten P; Nazif, Tamim M; George, Isaac; Leon, Martin B; Einstein, Andrew J; Kodali, Susheel K

The threshold for the optimal computed tomography (CT) number in Hounsfield Units (HU) to quantify aortic valvular calcium on contrast-enhanced scans has not been standardized. Our aim was to find the most accurate threshold to predict paravalvular regurgitation (PVR) after transcatheter aortic valve replacement (TAVR). 104 patients who underwent TAVR with the CoreValve prosthesis were studied retrospectively. Luminal attenuation (LA) in HU was measured at the level of the aortic annulus. Calcium volume score for the aortic valvular complex was measured using 6 threshold cutoffs (650 HU, 850 HU, LA × 1.25, LA × 1.5, LA+50, LA+100). Receiver-operating characteristic (ROC) analysis was performed to assess the predictive value for > mild PVR (n = 16). Multivariable analysis was performed to determine the accuracy to predict > mild PVR after adjustment for depth and perimeter oversizing. ROC analysis showed lower area under the curve (AUC) values for fixed threshold cutoffs (650 or 850 HU) compared to thresholds relative to LA. The LA+100 threshold had the highest AUC (0.81), and AUC was higher than all studied protocols, other than the LA x 1.25 and LA + 50 protocols, where the difference approached statistical significance (p = 0.05, and 0.068, respectively). Multivariable analysis showed calcium volume determined by the LAx1.25, LAx1.5, LA+50, and LA+ 100 HU protocols to independently predict PVR. Calcium volume scoring thresholds which are relative to LA are more predictive of PVR post-TAVR than those which use fixed cutoffs. A threshold of LA+100 HU had the highest predictive value. Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Combined use of susceptibility weighted magnetic resonance imaging sequences and dynamic susceptibility contrast perfusion weighted imaging to improve the accuracy of the differential diagnosis of recurrence and radionecrosis in high-grade glioma patients.

PubMed

Kim, Tae-Hyung; Yun, Tae Jin; Park, Chul-Kee; Kim, Tae Min; Kim, Ji-Hoon; Sohn, Chul-Ho; Won, Jae Kyung; Park, Sung-Hye; Kim, Il Han; Choi, Seung Hong

2017-03-21

Purpose was to assess predictive power for overall survival (OS) and diagnostic performance of combination of susceptibility-weighted MRI sequences (SWMRI) and dynamic susceptibility contrast (DSC) perfusion-weighted imaging (PWI) for differentiation of recurrence and radionecrosis in high-grade glioma (HGG). We enrolled 51 patients who underwent radiation therapy or gamma knife surgeryfollowed by resection for HGG and who developed new measurable enhancement more than six months after complete response. The lesions were confirmed as recurrence (n = 32) or radionecrosis (n = 19). The mean and each percentile value from cumulative histograms of normalized CBV (nCBV) and proportion of dark signal intensity on SWMRI (proSWMRI, %) within enhancement were compared. Multivariate regression was performed for the best differentiator. The cutoff value of best predictor from ROC analysis was evaluated. OS was determined with Kaplan-Meier method and log-rank test. Recurrence showed significantly lower proSWMRI and higher mean nCBV and 90th percentile nCBV (nCBV90) than radionecrosis. Regression analysis revealed both nCBV90 and proSWMRI were independent differentiators. Combination of nCBV90 and proSWMRI achieved 71.9% sensitivity (23/32), 100% specificity (19/19) and 82.3% accuracy (42/51) using best cut-off values (nCBV90 > 2.07 and proSWMRI≤15.76%) from ROC analysis. In subgroup analysis, radionecrosis with nCBV > 2.07 (n = 5) showed obvious hemorrhage (proSWMRI > 32.9%). Patients with nCBV90 > 2.07 and proSWMRI≤15.76% had significantly shorter OS. In conclusion, compared with DSC PWI alone, combination of SWMRI and DSC PWI have potential to be prognosticator for OS and lower false positive rate in differentiation of recurrence and radionecrosis in HGG who develop new measurable enhancement more than six months after complete response.

What is hypomania? Tetrachoric factor analysis and kernel estimation of DSM-IV hypomanic symptoms.

PubMed

Benazzi, Franco

2009-11-01

The DSM-IV definition of hypomania, which relies on clinical consensus and historical tradition, includes several "nonspecific" symptoms. The aim of this study was to identify the core symptoms of DSM-IV hypomania. In an outpatient private practice, 266 bipolar II disorder (BP-II) and 138 major depressive disorder (MDD) remitted patients were interviewed by a bipolar-trained psychiatrist, for different study goals. Patients were questioned, using the Structured Clinical Interview for DSM-IV, about the most common symptoms and duration of recent threshold and subthreshold hypomanic episodes. Data were recorded between 2002 and 2006. Four different samples, assessed with the same methodology, were pooled for the present analyses. Tetrachoric factor analysis was used to identify core hypomanic symptoms. Distribution of symptoms by kernel estimation was inspected for bimodality. Validity of core hypomania was tested by receiver operating characteristic (ROC) analysis. The distribution of subthreshold and threshold hypomanic episodes did not show bimodality. Tetrachoric factor analysis found 2 uncorrelated factors: factor 1 included the "classic" symptoms elevated mood, inflated self-esteem, decreased need for sleep, talkativeness, and increase in goal-directed activity (overactivity); factor 2 included the "nonspecific" symptoms irritable mood, racing/crowded thoughts, and distractibility. Factor 1 discriminatory accuracy for distinguishing BP-II versus MDD was high (ROC area = 0.94). The distribution of the 5-symptom episodes of factor 1 showed clear-cut bimodality. Similar results were found for episodes limited to 3 behavioral symptoms of factor 1 (decreased need for sleep, talkativeness, and overactivity) and 4 behavioral symptoms of factor 1 (adding elevated mood), with high discriminatory accuracy. A core, categorical DSM-IV hypomania was found that included 3 to 5 symptoms, ie, behavioral symptoms and elevated mood. Behavioral symptoms (overactivity domain) could be the basic phenotype of hypomania. This finding could help in probing for hypomania and reduce misdiagnosis. Biologic research could focus more on the underpinnings of the overactivity domain specifically. Copyright 2009 Physicians Postgraduate Press, Inc.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

PubMed

Rousson, Valentin; Zumbrunn, Thomas

2011-06-22

Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies

PubMed Central

2011-01-01

Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604

Differentiating benign from malignant mediastinal lymph nodes visible at EBUS using grey-scale textural analysis.

PubMed

Edey, Anthony J; Pollentine, Adrian; Doody, Claire; Medford, Andrew R L

2015-04-01

Recent data suggest that grey-scale textural analysis on endobronchial ultrasound (EBUS) imaging can differentiate benign from malignant lymphadenopathy. The objective of studies was to evaluate grey-scale textural analysis and examine its clinical utility. Images from 135 consecutive clinically indicated EBUS procedures were evaluated retrospectively using MATLAB software (MathWorks, Natick, MA, USA). Manual node mapping was performed to obtain a region of interest and grey-scale textural features (range of pixel values and entropy) were analysed. The initial analysis involved 94 subjects and receiver operating characteristic (ROC) curves were generated. The ROC thresholds were then applied on a second cohort (41 subjects) to validate the earlier findings. A total of 371 images were evaluated. There was no difference in proportions of malignant disease (56% vs 53%, P = 0.66) in the prediction (group 1) and validation (group 2) sets. There was no difference in range of pixel values in group 1 but entropy was significantly higher in the malignant group (5.95 vs 5.77, P = 0.03). Higher entropy was seen in adenocarcinoma versus lymphoma (6.00 vs 5.50, P < 0.05). An ROC curve for entropy gave an area under the curve of 0.58 with 51% sensitivity and 71% specificity for entropy greater than 5.94 for malignancy. In group 2, the entropy threshold phenotyped only 47% of benign cases and 20% of malignant cases correctly. These findings suggest that use of EBUS grey-scale textural analysis for differentiation of malignant from benign lymphadenopathy may not be accurate. Further studies are required. © 2015 Asian Pacific Society of Respirology.

Biomarker candidates for the detection of an infectious etiology of febrile neutropenia.

PubMed

Richter, Martin E; Neugebauer, Sophie; Engelmann, Falco; Hagel, Stefan; Ludewig, Katrin; La Rosée, Paul; Sayer, Herbert G; Hochhaus, Andreas; von Lilienfeld-Toal, Marie; Bretschneider, Tom; Pausch, Christine; Engel, Christoph; Brunkhorst, Frank M; Kiehntopf, Michael

2016-04-01

Infections and subsequent septicemia are major complications in neutropenic patients with hematological malignancies. Here, we identify biomarker candidates for the early detection of an infectious origin, and monitoring of febrile neutropenia (FN). Proteome, metabolome, and conventional biomarkers from 20 patients with febrile neutropenia without proven infection (FNPI) were compared to 28 patients with proven infection, including 17 patients with bacteremia. Three peptides (mass to charge ratio 1017.4-1057.3; p-values 0.011-0.024), six proteins (mass to charge ratio 6881-17,215; p-values 0.002-0.004), and six phosphatidylcholines (p-values 0.007-0.037) were identified that differed in FNPI patients compared to patients with infection or bacteremia. Seven of these marker candidates discriminated FNPI from infection at fever onset with higher sensitivity and specificity (ROC-AUC 0.688-0.824) than conventional biomarkers i.e., procalcitonin, C-reactive protein, or interleukin-6 (ROC-AUC 0.535-0.672). In a post hoc analysis, monitoring the time course of four lysophosphatidylcholines, threonine, and tryptophan allowed for discrimination of patients with or without resolution of FN (ROC-AUC 0.648-0.919) with higher accuracy compared to conventional markers (ROC-AUC 0.514-0.871). Twenty-one promising biomarker candidates for the early detection of an infectious origin or for monitoring the course of FN were found which might overcome known shortcomings of conventional markers.

3D quantitative breast ultrasound analysis for differentiating fibroadenomas and carcinomas smaller than 1cm.

PubMed

Meel-van den Abeelen, A S S; Weijers, G; van Zelst, J C M; Thijssen, J M; Mann, R M; de Korte, C L

2017-03-01

In (3D) ultrasound, accurate discrimination of small solid masses is difficult, resulting in a high frequency of biopsies for benign lesions. In this study, we investigate whether 3D quantitative breast ultrasound (3DQBUS) analysis can be used for improving non-invasive discrimination between benign and malignant lesions. 3D US studies of 112 biopsied solid breast lesions (size <1cm), were included (34 fibroadenomas and 78 invasive ductal carcinomas). The lesions were manually delineated and, based on sonographic criteria used by radiologists, 3 regions of interest were defined in 3D for analysis: ROI (ellipsoid covering the inside of the lesion), PER (peritumoural surrounding: 0.5mm around the lesion), and POS (posterior-tumoural acoustic phenomena: region below the lesion with the same size as delineated for the lesion). After automatic gain correction (AGC), the mean and standard deviation of the echo level within the regions were calculated. For the ROI and POS also the residual attenuation coefficient was estimated in decibel per cm [dB/cm]. The resulting eight features were used for classification of the lesions by a logistic regression analysis. The classification accuracy was evaluated by leave-one-out cross-validation. Receiver operating characteristic (ROC) curves were constructed to assess the performance of the classification. All lesions were delineated by two readers and results were compared to assess the effect of the manual delineation. The area under the ROC curve was 0.86 for both readers. At 100% sensitivity, a specificity of 26% and 50% was achieved for reader 1 and 2, respectively. Inter-reader variability in lesion delineation was marginal and did not affect the accuracy of the technique. The area under the ROC curve of 0.86 was reached for the second reader when the results of the first reader were used as training set yielding a sensitivity of 100% and a specificity of 40%. Consequently, 3DQBUS would have achieved a 40% reduction in biopsies for benign lesions for reader 2, without a decrease in sensitivity. This study shows that 3DQBUS is a promising technique to classify suspicious breast lesions as benign, potentially preventing unnecessary biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

[Prognostic value of three different staging schemes based on pN, MLR and LODDS in patients with T3 esophageal cancer].

PubMed

Wang, L; Cai, L; Chen, Q; Jiang, Y H

2017-10-23

Objective: To evaluate the prognostic value of three different staging schemes based on positive lymph nodes (pN), metastatic lymph nodes ratio (MLR) and log odds of positive lymph nodes (LODDS) in patients with T3 esophageal cancer. Methods: From 2007 to 2014, clinicopathological characteristics of 905 patients who were pathologically diagnosed as T3 esophageal cancer and underwent radical esophagectomy in Zhejiang Cancer Hospital were retrospectively analyzed. Kaplan-Meier curves and Multivariate Cox proportional hazards models were used to evaluate the independent prognostic factors. The values of three lymph node staging schemes for predicting 5-year survival were analyzed by using receiver operating characteristic (ROC) curves. Results: The 1-, 3- and 5-year overall survival rates of patients with T3 esophageal cancer were 80.9%, 50.0% and 38.4%, respectively. Multivariate analysis showed that MLR stage, LODDS stage and differentiation were independent prognostic survival factors ( P <0.05 for all). ROC curves showed that the area under the curve of pN stage, MLR stage, LODDS stage was 0.607, 0.613 and 0.618, respectively. However, the differences were not statistically significant ( P >0.05). Conclusions: LODDS is an independent prognostic factor for patients with T3 esophageal cancer. The value of LODDS staging system may be superior to pN staging system for evaluating the prognosis of these patients.

Data Mining Applied to Analysis of Contraceptive Methods Among College Students.

PubMed

Simões, Priscyla Waleska; Cesconetto, Samuel; Dalló, Eduardo Daminelli; de Souza Pires, Maria Marlene; Comunello, Eros; Borges Tomaz, Felipe; Xavier, Eduardo Pícolo; da Rosa Brunel Alves, Pedro Antonio; Ceretta, Luciane Bisognin; Manenti, Sandra Aparecida

2017-01-01

The aim of this study was to use the Data Mining to analyze the profile of the use of contraceptive methods in a university population. We used a database about sexuality performed on a university population in southern Brazil. The results obtained by the generated rules are largely in line with the literature and epidemiology worldwide, showing significant points of vulnerability in the university population. Validation measures of the study, as such, accuracy, sensitivity, specificity, and area under the ROC curve were higher or at least similar as compared to recent studies using the same methodology.

The Prognostic Role of Angiotensin II Type 1 Receptor Autoantibody in Non-Gravid Hypertension and Pre-eclampsia

PubMed Central

Lei, Jinghui; Li, Yafeng; Zhang, Suli; Wu, Ye; Wang, Pengli; Liu, Huirong

2016-01-01

Abstract Angiotensin II type 1 receptor autoantibody (AT1-AA) is found in patients with non-gravid hypertension or pre-eclampsia, but the relationship is uncertain. The aim of the present study was to assess the association between AT1-AA and high blood pressure using meta-analysis, and to evaluate the prognosis value of AT1-AA for hypertensive diseases. Literature search from PubMed, Embase, and Cochrane databases were conducted using keywords “hypertension” or “pre-eclampsia,” “angiotensin II receptor type 1 autoantibody,” and its aliases from April 1999 to December 2015. Studies evaluating the association between AT1-AA and non-gravid hypertension or pre-eclampsia were included in this analysis. The quality of the eligible studies was assessed based on the Newcastle–Ottawa Scale with some modifications. Two researchers then independently reviewed all included studies and extracted all relevant data. Association between AT1-AA and hypertension was tested with pooled odds ratios (ORs) and 95% confidence intervals (CIs). Finally, we evaluated whether AT1-AA predicted the prognosis of hypertension by using a summary receiver-operating characteristic (ROC) curve and sensitivity analysis. Ten studies were finally included in this meta-analysis. AT1-AA showed more significant association with pre-eclampsia than that with non-gravid hypertension (pooled OR 32.84, 95% CI 17.19–62.74; and pooled OR 4.18, 95% CI 2.20–7.98, respectively). Heterogeneity among studies was also detected probably due to different hypertensive subtypes and AT1-AA measuring methods. Area under summary ROC curve (AUC) of pre-eclampsia was 0.92 (sensitivity 0.76; specificity 0.86). Area under the ROC curve of overall hypertensive diseases or non-gravid hypertension was lower than that of pre-eclampsia (0.86 and 0.72, respectively) with lower sensitivities (0.46 and 0.26, respectively). The major limitation of this analysis was the publication bias due to lack of unpublished data and the language limitation during literature search. Prospective study with large simple size and specific measuring data collection are needed to enhance our findings in the future. Our analysis confirms that elevated AT1-AA in serum is significantly associated with hypertensive disorder, especially pre-eclampsia. AT1-AA may be a valuable indicator for poorer prognosis of patients with pre-eclampsia, and could be used in patients with hypertensive disease for risk evaluation and making individual treatment decision. PMID:27124051

Estimation of AUC or Partial AUC under Test-Result-Dependent Sampling.

PubMed

Wang, Xiaofei; Ma, Junling; George, Stephen; Zhou, Haibo

2012-01-01

The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.

Remote CT reading using an ultramobile PC and web-based remote viewing over a wireless network.

PubMed

Choi, Hyuk Joong; Lee, Jeong Hun; Kang, Bo Seung

2012-01-01

We developed a new type of mobile teleradiology system using an ultramobile PC (UMPC) for web-based remote viewing over a wireless network. We assessed the diagnostic performance of this system for abdominal CT interpretation. Performance was compared with an emergency department clinical monitor using a DICOM viewer. A total of 100 abdominal CT examinations were presented to four observers. There were 56 examinations showing appendicitis and 44 which were normal. The observers viewed the images using a UMPC display and an LCD monitor and rated each examination on a five-point scale. Receiver operating characteristics (ROC) analysis was used to test for differences. The sensitivity and specificities of all observers were similarly high. The average area under the ROC curve for readings performed on the UMPC and the LCD monitor was 0.959 and 0.976, respectively. There were no significant differences between the two display systems for interpreting abdominal CTs. The web-based mobile teleradiology system appears to be feasible for reading abdominal CTs for diagnosing appendicitis and may be valuable in emergency teleconsultation. Copyright © 2012 by the Royal Society of Medicine Press Ltd

Early thawing after snow removal and no straw mulching accelerates organic carbon cycling in a paddy soil in Northeast China.

PubMed

Zhang, Hao; Tang, Jie; Liang, Shuang; Li, Zhaoyang; Wang, Jingjing; Wang, Sining

2018-03-01

Variations in soil organic carbon (SOC) have implications for atmospheric CO 2 concentrations and the greenhouse effect. However, the effects of snow cover and straw mulching on the variations in SOC fractions across winter remain largely unknown. In this study, soil samples were collected during different stages of winter from an in situ experiment comprising three treatments: 1) snow removal with no straw mulching (Sn-SM-); 2) snow cover with no straw mulching (SC), and; 3) snow cover with straw mulching (SC + SM+). Results showed that labile organic carbon, semi-labile organic carbon, recalcitrant organic carbon (ROC), the light fraction of organic carbon (LFOC), and easily oxidized organic carbon (EOC) contents did not vary significantly (P > .05) during the unfrozen to hard frost stages. Compared to the unfrozen stage, microbial biomass carbon (MBC) contents decreased by 519.03 mg kg -1 , 325.21 mg kg -1 , and 244.09 mg kg -1 and dissolved organic carbon (DOC) contents increased by 473.36 mg kg -1 , 348.10 mg kg -1 , and 258.89 mg kg -1  at the hard frost stage in Sn-SM-, SC, and SC + SM + treatments, respectively. Throughout all thawing stages, > 61% and 59% of SOC and ROC accumulation, respectively in the three treatments were observed in thawing stage II, indicating that higher temperatures and microbial activities in thawing stage II accelerated the inputs of SOC and ROC. ROC accumulation accounted for >65% of the SOC accumulation and the proportions of ROC in SOC increased in the three treatments during the thawing stages. SC + SM + treatment maintained lower EOC contents during thawing stages than other treatments. The observation of lowest SOC and LFOC accumulation and contents in the SC + SM + treatment during thawing stages showed that SC + SM + experienced the least inputs of SOC in the soil. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Thermocycling effect on microshear bond strength to zirconia ceramic using Er:YAG and tribochemical silica coating as surface conditioning.

PubMed

Gomes, Ana Luísa; Ramos, João Carlos; Santos-del Riego, Sérgio; Montero, Javier; Albaladejo, Alberto

2015-02-01

The purpose of this study is to evaluate the thermocycling effect on the microshear bond strength (μSBS) of different self-adhesive resin cements to zirconia using tribochemical silica coating Rocatec™ (ROC) and Er:YAG as surface conditioners. Two hundred forty square-like zirconia samples were polished and randomly assigned in four groups according surface treatment applied as follows: (1) no treatment (NT), (2) silica coating with ROC, 3) Er:YAG laser irradiation (LAS: 2.940 nm, 200 mJ; 10 Hz), and (4) laser followed by Rocatec™ (LAROC). Each group was divided into two subgroups according the resin tested as follows: (A) BiFix SE (BIF) and (B) Clearfil SA (CLE). After 24 h, half of the specimens from each subgroup were tested. The other half was stored and thermocycled (5-55 °C/5,000 cycles). A μSBS test was performed using a universal testing machine (cross head speed = 0.5 mm/min). Failure modes were recorded and observed by scanning electronic microscopy. Data was analyzed with ANOVA, Student's t test, and chi-square tests, and linear regression was performed (p < 0.05). Before thermocycling, both cements showed higher μSBS results with ROC and LAROC. After aging, (1) all BIF specimens evidenced severely decreased adhesion with mostly adhesive failures and (2) CLE maintained the initial results in ROC and LAROC groups, performing better with ROC. Thermocycling did not negatively influence the resin-zirconia μSBS results in the self-adhesive resin cement containing 10-MDP when used on zirconia surface coated with silica, independently of previous Er:YAG surface treatment.

Comparison of rat epidermal keratinocyte organotypic culture (ROC) with intact human skin: lipid composition and thermal phase behavior of the stratum corneum.

PubMed

Pappinen, Sari; Hermansson, Martin; Kuntsche, Judith; Somerharju, Pentti; Wertz, Philip; Urtti, Arto; Suhonen, Marjukka

2008-04-01

The present report is a part of our continuing efforts to explore the utility of the rat epidermal keratinocyte organotypic culture (ROC) as an alternative model to human skin in transdermal drug delivery and skin irritation studies of new chemical entities and formulations. The aim of the present study was to compare the stratum corneum lipid content of ROC with the corresponding material from human skin. The lipid composition was determined by thin-layer chromatography (TLC) and mass-spectrometry, and the thermal phase transitions of stratum corneum were studied by differential scanning calorimetry (DSC). All major lipid classes of the stratum corneum were present in ROC in a similar ratio as found in human stratum corneum. Compared to human skin, the level of non-hydroxyacid-sphingosine ceramide (NS) was increased in ROC, while alpha-hydroxyacid-phytosphingosine ceramide (AP) and non-hydroxyacid-phytosphingosine ceramides (NP) were absent. Also some alterations in fatty acid profiles of ROC ceramides were noted, e.g., esterified omega-hydroxyacid-sphingosine contained increased levels of oleic acid instead of linoleic acid. The fraction of lipids covalently bound to corneocyte proteins was distinctly lower in ROC compared to human skin, in agreement with the results from DSC. ROC underwent a lipid lamellar order to disorder transition (T2) at a slightly lower temperature (68 degrees C) than human skin (74 degrees C). These differences in stratum corneum lipid composition and the thermal phase transitions may explain the minor differences previously observed in drug permeation between ROC and human skin.

Variations in recollection: the effects of complexity on source recognition.

PubMed

Parks, Colleen M; Murray, Linda J; Elfman, Kane; Yonelinas, Andrew P

2011-07-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in favor of the threshold assumption, but zROCs are not always as U-shaped as threshold theory predicts. Source zROCs have been shown to become more linear when the contribution of familiarity to source discriminations is increased, and this may account for the existing results. However, another way in which source zROCs may become more linear is if the recollection threshold begins to break down and recollection becomes more graded and Gaussian. We tested the "graded recollection" account in the current study. We found that increasing stimulus complexity (i.e., changing from single words to sentences) or increasing source complexity (i.e., changing the sources from audio to videos of speakers) resulted in flatter source zROCs. In addition, conditions expected to reduce recollection (i.e., divided attention and amnesia) had comparable effects on source memory in simple and complex conditions, suggesting that differences between simple and complex conditions were due to differences in the nature of recollection, rather than differences in the utility of familiarity. The results suggest that under conditions of high complexity, recollection can appear more graded, and it can produce curved ROCs. The results have implications for measurement models and for current theories of recognition memory.

Operating characteristics of depression and anxiety disorder phenotype dimensions and trait neuroticism: a theoretical examination of the fear and distress disorders from the Netherlands study of depression and anxiety.

PubMed

Tully, Phillip J; Wardenaar, Klaas J; Penninx, Brenda W J H

2015-03-15

The receiver operating characteristics (ROC) of anhedonic depression and anxious arousal to detect the distress- (major depression, dysthymia, generalized anxiety disorder) and fear-disorder clusters (i.e. panic disorder, agoraphobia, social phobia) have not been reported in a large sample. A sample of 2981 persons underwent structured psychiatric interview; n=652 were without lifetime depression and anxiety disorder history. Participants also completed a neuroticism scale (Revised NEO Five Factor Inventory [NEO-FFI]), and the 30-item short adaptation of the Mood and Anxiety Symptoms Questionnaire (MASQ-D30) measuring anhedonic depression, anxious arousal and general distress. Maximal sensitivity and specificity was determined by the Youden Index and the area-under-the-curve (AUC) in ROC analysis. A total of 2624 completed all measures (age M=42.4 years±13.1, 1760 females [67.1%]), including 1060 (40.4%) persons who met criteria for a distress-disorder, and 973 (37.1%) who met criteria for a fear-disorder. The general distress dimension provided the highest ROC values in the detection of the distress-disorders (AUC=.814, sensitivity=71.95%, specificity=76.34%, positive predictive value=67.33, negative predictive value=80.07). None of the measures provided suitable operating characteristics in the detection of the fear-disorders with specificity values <75%. Over sampling of depression and anxiety disorders may lead to inflated positive- and negative predictive values. The MASQ-D30 general distress dimension showed clinically suitable operating characteristics in the detection of distress-disorders. Neither neuroticism nor the MASQ-D30 dimensions provided suitable operating characteristics in the detection of the fear-disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

Strain ratio ultrasound elastography increases the accuracy of colour-Doppler ultrasound in the evaluation of Thy-3 nodules. A bi-centre university experience.

PubMed

Cantisani, Vito; Maceroni, Piero; D'Andrea, Vito; Patrizi, Gregorio; Di Segni, Mattia; De Vito, Corrado; Grazhdani, Hektor; Isidori, Andrea M; Giannetta, Elisa; Redler, Adriano; Frattaroli, Fabrizio; Giacomelli, Laura; Di Rocco, Giorgio; Catalano, Carlo; D'Ambrosio, Ferdinando

2016-05-01

To assess whether ultrasound elastography (USE) with strain ratio increases diagnostic accuracy of Doppler ultrasound in further characterisation of cytologically Thy3 thyroid nodules. In two different university diagnostic centres, 315 patients with indeterminate cytology (Thy3) in thyroid nodules aspirates were prospectively evaluated with Doppler ultrasound and strain ratio USE before surgery. Ultrasonographic features were analysed separately and together as ultrasound score, to assess sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Receiver operating characteristic (ROC) curves to identify optimal cut-off value of the strain ratio were also provided. Diagnosis on a surgical specimen was considered the standard of reference. Higher strain ratio values were found in malignant nodules, with an optimum strain ratio cut-off of 2.09 at ROC analysis. USE with strain ratio showed 90.6% sensitivity, 93% specificity, 82.8% PPV, 96.4% NPV, while US score yielded a sensitivity of 52.9%, specificity of 84.3%, PPV 55.6% and NPV 82.9%. The diagnostic gain with strain ratio was statistically significant as proved by ROC areas, which was 0.9182 for strain ratio and 0.6864 for US score. USE with strain ratio should be considered a useful additional tool to colour-Doppler US, since it improves characterisation of thyroid nodules with indeterminate cytology. • Strain ratio measurements improve differentiation of thyroid nodules with indeterminate cytology • Elastography with strain ratio is more reliable than ultrasound features and ultrasound score • Strain ratio may help to better select patients with Thy 3 nodules candidate for surgery.

Diagnostic accuracy of the Eurotest for dementia: a naturalistic, multicenter phase II study

PubMed Central

Carnero-Pardo, Cristobal; Gurpegui, Manuel; Sanchez-Cantalejo, Emilio; Frank, Ana; Mola, Santiago; Barquero, M Sagrario; Montoro-Rios, M Teresa

2006-01-01

Background Available screening tests for dementia are of limited usefulness because they are influenced by the patient's culture and educational level. The Eurotest, an instrument based on the knowledge and handling of money, was designed to overcome these limitations. The objective of this study was to evaluate the diagnostic accuracy of the Eurotest in identifying dementia in customary clinical practice. Methods A cross-sectional, multi-center, naturalistic phase II study was conducted. The Eurotest was administered to consecutive patients, older than 60 years, in general neurology clinics. The patients' condition was classified as dementia or no dementia according to DSM-IV diagnostic criteria. We calculated sensitivity (Sn), specificity (Sp) and area under the ROC curves (aROC) with 95% confidence intervals. The influence of social and educational factors on scores was evaluated with multiple linear regression analysis, and the influence of these factors on diagnostic accuracy was evaluated with logistic regression. Results Sixteen neurologists recruited a total of 516 participants: 101 with dementia, 380 without dementia, and 35 who were excluded. Of the 481 participants who took the Eurotest, 38.7% were totally or functionally illiterate and 45.5% had received no formal education. Mean time needed to administer the test was 8.2+/-2.0 minutes. The best cut-off point was 20/21, with Sn = 0.91 (0.84–0.96), Sp = 0.82 (0.77–0.85), and aROC = 0.93 (0.91–0.95). Neither the scores on the Eurotest nor its diagnostic accuracy were influenced by social or educational factors. Conclusion This naturalistic and pragmatic study shows that the Eurotest is a rapid, simple and useful screening instrument, which is free from educational influences, and has appropriate internal and external validity. PMID:16606455

Diagnostic evaluation of three cardiac software packages using a consecutive group of patients

PubMed Central

2011-01-01

Purpose The aim of this study was to compare the diagnostic performance of the three software packages 4DMSPECT (4DM), Emory Cardiac Toolbox (ECTb), and Cedars Quantitative Perfusion SPECT (QPS) for quantification of myocardial perfusion scintigram (MPS) using a large group of consecutive patients. Methods We studied 1,052 consecutive patients who underwent 2-day stress/rest 99mTc-sestamibi MPS studies. The reference/gold-standard classifications for the MPS studies were obtained from three physicians, with more than 25 years each of experience in nuclear cardiology, who re-evaluated all MPS images. Automatic processing was carried out using 4DM, ECTb, and QPS software packages. Total stress defect extent (TDE) and summed stress score (SSS) based on a 17-segment model were obtained from the software packages. Receiver-operating characteristic (ROC) analysis was performed. Results A total of 734 patients were classified as normal and the remaining 318 were classified as having infarction and/or ischemia. The performance of the software packages calculated as the area under the SSS ROC curve were 0.87 for 4DM, 0.80 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.03; other differences p < 0.0001). The area under the TDE ROC curve were 0.87 for 4DM, 0.82 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.0005; other differences p < 0.0001). Conclusion There are considerable differences in performance between the three software packages with 4DM showing the best performance and ECTb the worst. These differences in performance should be taken in consideration when software packages are used in clinical routine or in clinical studies. PMID:22214226

Required Operational Capability, USMC-ROC-LOG-216.3.5 for the Ration, Cold Weather.

DTIC Science & Technology

1987-05-06

in operations or training in an arctic environment . b. Organizational Concept. The ration , cold weather will be issued in accordance with established...all services. 2 ROC-ARCTIC 7. TECHNICAL FEASIBILITY AND ENERGY/ ENVIRONMENTAL IMPACTS a. Technical Feasibility. The risk of developing the ration ...r -A1833 963 REQUIRED OPERATIONAL CAPABILITY USMC-ROC-LOG-21635 FOR 1t/1 THE RATION COLD WEATHER(U) MARINE CORPS WASHINGTON DC 86 MAY 87 USMC-ROC-LOG

Usefulness of Cellular Analysis of Bronchoalveolar Lavage Fluid for Predicting the Etiology of Pneumonia in Critically Ill Patients

PubMed Central

Hong, Hyo-Lim; Kim, Sung-Han; Huh, Jin Won; Sung, Heungsup; Lee, Sang-Oh; Kim, Mi-Na; Jeong, Jin-Yong; Lim, Chae-Man; Kim, Yang Soo; Woo, Jun Hee; Koh, Younsuck

2014-01-01

Background The usefulness of bronchoalveolar lavage (BAL) fluid cellular analysis in pneumonia has not been adequately evaluated. This study investigated the ability of cellular analysis of BAL fluid to differentially diagnose bacterial pneumonia from viral pneumonia in adult patients who are admitted to intensive care unit. Methods BAL fluid cellular analysis was evaluated in 47 adult patients who underwent bronchoscopic BAL following less than 24 hours of antimicrobial agent exposure. The abilities of BAL fluid total white blood cell (WBC) counts and differential cell counts to differentiate between bacterial and viral pneumonia were evaluated using receiver operating characteristic (ROC) curve analysis. Results Bacterial pneumonia (n = 24) and viral pneumonia (n = 23) were frequently associated with neutrophilic pleocytosis in BAL fluid. BAL fluid median total WBC count (2,815/µL vs. 300/µL, P<0.001) and percentage of neutrophils (80.5% vs. 54.0%, P = 0.02) were significantly higher in the bacterial pneumonia group than in the viral pneumonia group. In ROC curve analysis, BAL fluid total WBC count showed the best discrimination, with an area under the curve of 0.855 (95% CI, 0.750–0.960). BAL fluid total WBC count ≥510/µL had a sensitivity of 83.3%, specificity of 78.3%, positive likelihood ratio (PLR) of 3.83, and negative likelihood ratio (NLR) of 0.21. When analyzed in combination with serum procalcitonin or C-reactive protein, sensitivity was 95.8%, specificity was 95.7%, PLR was 8.63, and NLR was 0.07. BAL fluid total WBC count ≥510/µL was an independent predictor of bacterial pneumonia with an adjusted odds ratio of 13.5 in multiple logistic regression analysis. Conclusions Cellular analysis of BAL fluid can aid early differential diagnosis of bacterial pneumonia from viral pneumonia in critically ill patients. PMID:24824328

Segmentation and feature extraction of retinal vascular morphology

NASA Astrophysics Data System (ADS)

Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

2017-02-01

Analysis of retinal fundus images is essential for physicians, optometrists and ophthalmologists in the diagnosis, care and treatment of patients. The first step of almost all forms of automated fundus analysis begins with the segmentation and subtraction of the retinal vasculature, while analysis of that same structure can aid in the diagnosis of certain retinal and cardiovascular conditions, such as diabetes or stroke. This paper investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using DRIVE, a database of fundus images. The result of the network with the application of a confidence threshold was slightly below the 2nd observer and gold standard, with an accuracy of 0.9419 and ROC of 0.9707. The output of the network with on post-processing boasted the highest sensitivity found in the literature with a score of 0.9568 and a good ROC score of 0.9689. The high sensitivity of the system makes it suitable for longitudinal morphology assessments, disease detection and other similar tasks.

Protein induced by vitamin K absence or antagonist-II (PIVKA-II) specifically increased in Italian hepatocellular carcinoma patients.

PubMed

Viggiani, Valentina; Palombi, Sara; Gennarini, Giuseppina; D'Ettorre, Gabriella; De Vito, Corrado; Angeloni, Antonio; Frati, Luigi; Anastasi, Emanuela

2016-10-01

As a marker for Hepatocellular Carcinoma (HCC), Protein Induced by Vitamin K Absence II (PIVKA-II) seems to be superior to alpha fetoprotein (AFP). To better characterize the role of PIVKA-II, both AFP and PIVKA-II have been measured in Italian patients with diagnosis of HCC compared with patients affected by non-oncological liver pathologies. Sixty serum samples from patients with HCC, 60 samples from patients with benign liver disease and 60 samples obtained from healthy blood donors were included in the study. PIVKA-II and AFP were measured by LUMIPULSE(®) G1200 (Fujirebio-Europe, Belgium). We considered as PIVKA-II cutoff 70 mAU/ml (mean +3SD) of the values observed in healthy subjects. The evaluation of PIVKA-II showed a positivity of 70% in patients with HCC and 5% in patients with benign diseases (p < 0.0001) whereas high levels of AFP were observed in 55% of HCC patients and in 47% of patients with benign diseases. The combined Receiver Operating Characteristic (ROC) analysis of the two analytes revealed a higher sensitivity (75%) compared to those observed for the individual biomarkers. In conclusion, we demonstrate that as a marker for HCC, PIVKA-II is more specific for HCC and less prone to elevation during chronic liver diseases. The combination of the two biomarkers, evaluated by the ROC analysis, improved the specificity compared to a single marker. These data suggest that the combined analysis of the two markers could be a useful tool in clinical practice.

Intact protein analysis of ubiquitin in cerebrospinal fluid by multiple reaction monitoring reveals differences in Alzheimer's disease and frontotemporal lobar degeneration.

PubMed

Oeckl, Patrick; Steinacker, Petra; von Arnim, Christine A F; Straub, Sarah; Nagl, Magdalena; Feneberg, Emily; Weishaupt, Jochen H; Ludolph, Albert C; Otto, Markus

2014-11-07

The impairment of the ubiquitin-proteasome system (UPS) is thought to be an early event in neurodegeneration, and monitoring UPS alterations might serve as a disease biomarker. Our aim was to establish an alternate method to antibody-based assays for the selective measurement of free monoubiquitin in cerebrospinal fluid (CSF). Free monoubiquitin was measured with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MS/MS) in CSF of patients with Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), behavioral variant of frontotemporal dementia (bvFTD), Creutzfeldt-Jakob disease (CJD), Parkinson's disease (PD), primary progressive aphasia (PPA), and progressive supranuclear palsy (PSP). The LC-MS/MS method showed excellent intra- and interassay precision (4.4-7.4% and 4.9-10.3%) and accuracy (100-107% and 100-106%). CSF ubiquitin concentration was increased compared with that of controls (33.0 ± 9.7 ng/mL) in AD (47.5 ± 13.1 ng/mL, p < 0.05) and CJD patients (171.5 ± 103.5 ng/mL, p < 0.001) but not in other neurodegenerative diseases. Receiver operating characteristic curve (ROC) analysis of AD vs control patients revealed an area under the curve (AUC) of 0.832, and the specificity and sensitivity were 75 and 75%, respectively. ROC analysis of AD and FTLD patients yielded an AUC of 0.776, and the specificity and sensitivity were 53 and 100%, respectively. In conclusion, our LC-MS/MS method may facilitate ubiquitin determination to a broader community and might help to discriminate AD, CJD, and FTLD patients.

Defining a new diagnostic assessment parameter for wound care: Elevated protease activity, an indicator of nonhealing, for targeted protease-modulating treatment.

PubMed

Serena, Thomas E; Cullen, Breda M; Bayliff, Simon W; Gibson, Molly C; Carter, Marissa J; Chen, Lingyun; Yaakov, Raphael A; Samies, John; Sabo, Matthew; DeMarco, Daniel; Le, Namchi; Galbraith, James

2016-05-01

It is widely accepted that elevated protease activity (EPA) in chronic wounds impedes healing. However, little progress has occurred in quantifying the level of protease activity that is detrimental for healing. The aim of this study was to determine the relationship between inflammatory protease activity and wound healing status, and to establish the level of EPA above which human neutrophil-derived elastase (HNE) and matrix metalloproteases (MMP) activities correlate with nonhealing wounds. Chronic wound swab samples (n = 290) were collected from four wound centers across the USA to measure HNE and MMP activity. Healing status was determined according to percentage reduction in wound area over the previous 2-4 weeks; this was available for 211 wounds. Association between protease activity and nonhealing wounds was determined by receiver operating characteristic analysis (ROC), a statistical technique used for visualizing and analyzing the performance of diagnostic tests. ROC analysis showed that area under the curve (AUC) for HNE were 0.69 for all wounds and 0.78 for wounds with the most reliable wound trajectory information, respectively. For MMP, the corresponding AUC values were 0.70 and 0.82. Analysis suggested that chronic wounds having values of HNE >5 and/or MMP ≥13, should be considered wound healing impaired. EPA is indicative of nonhealing wounds. Use of a diagnostic test to detect EPA in clinical practice could enable clinicians to identify wounds that are nonhealing, thus enabling targeted treatment with protease modulating therapies. © 2016 by the Wound Healing Society.

Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?

NASA Astrophysics Data System (ADS)

Shi, Bibo; Grimm, Lars J.; Mazurowski, Maciej A.; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2017-03-01

Reducing the overdiagnosis and overtreatment associated with ductal carcinoma in situ (DCIS) requires accurate prediction of the invasive potential at cancer screening. In this work, we investigated the utility of pre-operative histologic and mammographic features to predict upstaging of DCIS. The goal was to provide intentionally conservative baseline performance using readily available data from radiologists and pathologists and only linear models. We conducted a retrospective analysis on 99 patients with DCIS. Of those 25 were upstaged to invasive cancer at the time of definitive surgery. Pre-operative factors including both the histologic features extracted from stereotactic core needle biopsy (SCNB) reports and the mammographic features annotated by an expert breast radiologist were investigated with statistical analysis. Furthermore, we built classification models based on those features in an attempt to predict the presence of an occult invasive component in DCIS, with generalization performance assessed by receiver operating characteristic (ROC) curve analysis. Histologic features including nuclear grade and DCIS subtype did not show statistically significant differences between cases with pure DCIS and with DCIS plus invasive disease. However, three mammographic features, i.e., the major axis length of DCIS lesion, the BI-RADS level of suspicion, and radiologist's assessment did achieve the statistical significance. Using those three statistically significant features as input, a linear discriminant model was able to distinguish patients with DCIS plus invasive disease from those with pure DCIS, with AUC-ROC equal to 0.62. Overall, mammograms used for breast screening contain useful information that can be perceived by radiologists and help predict occult invasive components in DCIS.

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

Clinical Usefulness of Measuring Red Blood Cell Distribution Width in Patients with Hepatitis B Virus-Related Acute-On-Chronic Liver Failure.

PubMed

Jin, Lei; Gao, Yufeng; Ye, Jun; Zou, Guizhou; Li, Xu

2017-09-01

The red blood cell distribution width (RDW) is increased in chronic liver disease, but its clinical significance in hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is still unclear. The aim of the present study was to investigate the clinical significance of RDW in HBV-ACLF patients. The medical records of HBV-ACLF patients who were admitted to The Second Affiliated Hospital of Anhui Medical University between April 2012 and December 2015 were retrospectively reviewed. Correlations between RDW, neutrophil lymphocyte ratio (NLR), and the model for end-stage liver disease (MELD) scores were analyzed using the Spearman's approach. Multivariable stepwise logistic regression test was used to evaluate independent clinical parameters predicting 3-month mortality of HBV-ACLF patients. The association between RDW and hospitalization outcome was estimated by receiver operating curve (ROC) analysis. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank test. Sixty-two HBV-ACLF patients and sixty CHB patients were enrolled. RDW were increased in HBVACLF patients and positively correlated with the NLR as well as MELD scores. Multivariate analysis demonstrated that RDW value was an independent predictor for mortality. RDW had an area under the ROC of 0.799 in predicting 3-month mortality of HBV-ACLF patients. Patients with HBV-ACLF who had RDW > 17% showed significantly poorer survival than those who had RDW ≤ 17%. RDW values are significantly increased in patients with HBV-ACLF. Moreover, RDW values are an independent predicting factor for an in-hospital mortality in patients with HBV-ACLF.

Circulating tumor cells (CTCs) in malignant pleural mesothelioma (MPM).

PubMed

Yoneda, Kazue; Tanaka, Fumihiro; Kondo, Nobuyuki; Hashimoto, Masaki; Takuwa, Teruhisa; Matsumoto, Seiji; Okumura, Yoshitomo; Tsubota, Noriaki; Sato, Ayuko; Tsujimura, Tohru; Kuribayashi, Kozo; Fukuoka, Kazuya; Tabata, Chiharu; Nakano, Takashi; Hasegawa, Seiki

2014-12-01

To investigate the diagnostic and prognostic value of circulating tumor cells (CTCs), a potential surrogate of micrometastasis, in malignant pleural mesothelioma (MPM). We prospectively evaluated CTCs in 7.5 mL of peripheral blood sampled from patients with a suspicion of MPM. A semiautomated system was used to capture CTCs with an antibody against the epithelial cell adhesion molecule. Of 136 eligible patients, 32 were finally diagnosed with nonmalignant diseases (NM), and 104 had MPM. CTCs were detected in 32.7 % (34 of 104) of MPM patients but in only 9.4 % (3 of 32) of NM patients (P = 0.011). The CTC count was significantly higher in MPM patients than in NM patients (P = 0.007), and a receiver operating characteristic (ROC) curve analysis showed an insufficient capability of the CTC test in discrimination between MPM and NM, with an area under ROC curve of 0.623 (95 % confidence interval, 0.523-0.723; P = 0.036). Among MPM patients, CTCs were more frequently detected in patients with epithelioid subtype (39.7 %, 31 of 78) than in those with nonepithelioid subtypes (11.5 %, 3 of 26; P = 0.016). Positive CTCs (CTC count ≥ 1) were a significant factor to predict a poor prognosis among epithelioid patients (median overall survival, 22.3 months for positive CTCs vs. 12.6 months for negative CTCs; P = 0.004) and not in nonepithelioid patients (P = 0.649). A multivariate analysis showed that positive CTCs were a significant and independent factor to predict a poor prognosis (hazard ratio, 2.904; 95 % confidence interval, 1.530-5.511; P = 0.001) for epithelioid MPM patients. CTC was a promising marker in diagnosis and prediction of prognosis in MPM, especially in epithelioid MPM.

Plasma D-dimer as a Prognostic Marker in ICU Admitted Egyptian Children with Traumatic Brain Injury.

PubMed

Foaud, Hala Mohamed Amin; Labib, John Rene; Metwally, Hala Gabr; El-Twab, Khaled Mohamed Abd

2014-09-01

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in children. This study aimed at evaluation of the D-dimer blood levels as a new marker to predict prognosis and outcome of traumatic brain injuries among children. This case control study was conducted at the Paediatric Intensive Care Unit (ICU), Alharm Hospital in Giza, Egypt during 2012-2013, on 46 Paediatric cases admitted to ICU with head injury and 20 normal age-matched controls. Clinical data and venous blood samples were prospectively collected at 1(st), 3(rd) and 14(th) day of admission, in addition to examination finding as Glasgow coma scale (GCS), cranial brain computed tomography (CT), routine laboratory investigations (CBC, CRP, SGOT, SGPT, urea, creatinine, random blood glucose, Na, K and arterial blood gases) plasma D-dimer, INR, PT, aPTT and PC. Data analysis was carried out accordingly and ROC curve was performed to explore the discriminating ability of D-dimer through estimation of its accuracy in differentiating temporal survivorship of those with TBI. Cases were classified according to outcome into survivors and non-survivors. Significant difference was observed between cases and controls and between survivors and non-survivors during 1(st), 3(rd) and 14(th) day of the follow up including GCS, blood levels of D-dimer, PT and aPTT. ROC curve analysis for D-dimer showed decline in both sensitivity from 89.5% to 73.7% and specificity from 100% to 81.5% along the study days respectively. D-dimer time measurements showed significant decline among survivors from 4.2 to 0.7, while in the non survivor group this decline was much higher from 27.9 to 1.4. Low plasma D-dimer suggests the absence of brain injury, and good prognosis.

Pretreatment Nomogram to Predict the Risk of Acute Urinary Retention After I-125 Prostate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roeloffzen, Ellen M., E-mail: e.m.a.roeloffzen@umcutrecht.nl; Vulpen, Marco van; Battermann, Jan J.

Purpose: Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR. Methods: Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the finalmore » model was assessed with calibration and discrimination measures. Results: Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (<18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (>35 points), the risk of AUR was more than 20%. Conclusion: This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.« less

Comparison of Various Anthropometric and Body Fat Indices in Identifying Cardiometabolic Disturbances in Chinese Men and Women

PubMed Central

Zhang, Zhe-qing; Deng, Juan; He, Li-ping; Ling, Wen-hua; Su, Yi-xiang; Chen, Yu-ming

2013-01-01

Background Although many adiposity indices may be used to predict obesity-related health risks, uncertainty remains over which of them performs best. Objective This study compared the predictive capability of direct and indirect adiposity measures in identifying people at higher risk of metabolic abnormalities. Methods This population-based cross-sectional study recruited 2780 women and 1160 men. Body weight and height, waist circumference (WC), and hip circumference (HC) were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were calculated. Body fat (and percentage of fat) over the whole body and the trunk were determined by bioelectrical impedance analysis (BIA). Blood pressure, fasting lipid profiles, and glucose and urine acid levels were assessed. Results In women, the ROC and the multivariate logistic regression analyses both showed that WHtR consistently had the best performance in identifying hypertension, dyslipidemia, hyperuricemia, diabetes/IFG, and metabolic syndrome (MetS). In men, the ROC analysis showed that WHtR was the best predictor of hypertension, WHtR and WC were equally good predictors of dyslipidemia and MetS, and WHtR was the second-best predictor of hyperuricemia and diabetes/IFG. The multivariate logistic regression also found WHtR to be superior in discriminating between MetS, diabetes/IFG, and dyslipidemia while BMI performed better in predicting hypertension and hyperuricemia in men. The BIA-derived indices were the second-worst predictors for all of the endpoints, and HC was the worst. Conclusion WHtR was the best predictor of various metabolic abnormalities. BMI may be used as an alternative measure of obesity for identifying hypertension in both sexes. PMID:23951031

Metabolomic markers of fatigue: Association between circulating metabolome and fatigue in women with chronic widespread pain.

PubMed

Freidin, Maxim B; Wells, Helena R R; Potter, Tilly; Livshits, Gregory; Menni, Cristina; Williams, Frances M K

2018-02-01

Fatigue is a sensation of unbearable tiredness that frequently accompanies chronic widespread musculoskeletal pain (CWP) and inflammatory joint disease. Its mechanisms are poorly understood and there is a lack of effective biomarkers for diagnosis and onset prediction. We studied the circulating metabolome in a population sample characterised for CWP to identify biomarkers showing specificity for fatigue. Untargeted metabolomic profiling was conducted on fasting plasma and serum samples of 1106 females with and without CWP from the TwinsUK cohort. Linear mixed-effects models accounting for covariates were used to determine relationships between fatigue and metabolites. Receiver operating curve (ROC)-analysis was used to determine predictive value of metabolites for fatigue. While no association between fatigue and metabolites was identified in twins without CWP (n=711), in participants with CWP (n=395), levels of eicosapentaenoate (EPA) ω-3 fatty acid were significantly reduced in those with fatigue (β=-0.452±0.116; p=1.2×10 -4 ). A significant association between fatigue and two other metabolites also emerged when BMI was excluded from the model: 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF), and C-glycosyltryptophan (p=1.5×10 -4 and p=3.1×10 -4 , respectively). ROC analysis has identified a combination of 15 circulating metabolites with good predictive potential for fatigue in CWP (AUC=75%; 95% CI 69-80%). The results of this agnostic metabolomics screening show that fatigue is metabolically distinct from CWP, and is associated with a decrease in circulating levels of EPA. Our panel of circulating metabolites provides the starting point for a diagnostic test for fatigue in CWP. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Semi-quantitative analysis of salivary gland scintigraphy in Sjögren's syndrome diagnosis: a first-line tool.

PubMed

Angusti, Tiziana; Pilati, Emanuela; Parente, Antonella; Carignola, Renato; Manfredi, Matteo; Cauda, Simona; Pizzigati, Elena; Dubreuil, Julien; Giammarile, Francesco; Podio, Valerio; Skanjeti, Andrea

2017-09-01

The aim of this study was the assessment of semi-quantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to predict primary Sjögren's syndrome (pSS). Forty-six consecutive patients (41 females; age 61 ± 11 years) with sicca syndrome were studied by SGdS after injection of 200 MBq of pertechnetate. In sixteen patients, pSS was diagnosed, according to American-European Consensus Group criteria (AECGc). Semi-quantitative parameters (uptake (UP) and excretion fraction (EF)) were obtained for each gland. ROC curves were used to determine the best cut-off value. The area under the curve (AUC) was used to estimate the accuracy of each semi-quantitative analysis. To assess the correlation between scintigraphic results and disease severity, semi-quantitative parameters were plotted versus Sjögren's syndrome disease activity index (ESSDAI). A nomogram was built to perform an integrated evaluation of all the scintigraphic semi-quantitative data. Both UP and EF of salivary glands were significantly lower in pSS patients compared to those in non-pSS (p < 0.001). ROC curve showed significantly large AUC for both the parameters (p < 0.05). Parotid UP and submandibular EF, assessed by univariated and multivariate logistic regression, showed a significant and independent correlation with pSS diagnosis (p value <0.05). No correlation was found between SGdS semi-quantitative parameters and ESSDAI. The proposed nomogram accuracy was 87%. SGdS is an accurate and reproducible tool for the diagnosis of pSS. ESSDAI was not shown to be correlated with SGdS data. SGdS should be the first-line imaging technique in patients with suspected pSS.

Sesame allergy: role of specific IgE and skin-prick testing in predicting food challenge results.

PubMed

Permaul, Perdita; Stutius, Lisa M; Sheehan, William J; Rangsithienchai, Pitud; Walter, Jolan E; Twarog, Frank J; Young, Michael C; Scott, Jordan E; Schneider, Lynda C; Phipatanakul, Wanda

2009-01-01

There are conflicting data regarding the diagnostic value of sesame-specific IgE and sesame skin test. Currently, there are no established thresholds that predict clinical reactivity. We examined the correlation of sesame ImmunoCAP and skin-prick test (SPT) results with oral challenge outcomes in children suspected of having a sesame food allergy. We conducted a retrospective chart review of children, aged 2-12 years, receiving a sesame ImmunoCAP level, SPT, and food challenge from January 2004 to August 2008 at Children's Hospital Boston and affiliated allergy clinics. Food challenges were conducted in cases of questionable clinical history or a negative ImmunoCAP and/or negative SPT despite a convincing history. Thirty-three oral sesame challenges were conducted. Of the 33 challenges performed, 21% (n = 7) failed and 79% (n = 26) passed. A sesame-specific IgE level of > or = 7 kU(A)/L showed specificity of >90%. An SPT wheal size of > or = 6 mm showed specificity of >90%. Receiver operator characteristic (ROC) curve analysis for sesame-specific IgE revealed an area under the curve (AUC) of 0.56. ROC curve analysis for SPT wheal size revealed an AUC of 0.67. To our knowledge, this study represents the largest number of sesame challenges performed to evaluate the diagnostic value of both sesame-specific IgE and SPT. Based on our sample, both tests are not good predictors of true sesame allergy as determined by an oral challenge. We were unable to establish a threshold with a 95% positive predictive value for both sesame-specific IgE and SPT.

Danish translation and validation of Kessler's 10-item psychological distress scale - K10.

PubMed

Thelin, Camilla; Mikkelsen, Benjamin; Laier, Gunnar; Turgut, Louise; Henriksen, Bente; Olsen, Lis Raabaek; Larsen, Jens Knud; Arnfred, Sidse

2017-08-01

Psychological distress is a trans-diagnostic feature of mental suffering closely associated with mental disorders. Kessler's 10-item Psychological Distress Scale (K10), a scale with sound psychometric properties, is widely used in epidemiological studies. To translate and investigate whether K10 is a reliable and valid rating scale for the measurement of psychological distress in a Danish population. The translation was carried out according to official WHO translation guidelines. A sample of 100 subjects was included, 54 patients from the regional Mental Health Service (MHS) and 46 subjects with no psychiatric history. All participants were assessed with a psychiatric diagnostic interview (MINI) and handed out K10. Concurrent validity was assessed by WHO Well-being Index (WHO-5). Correlation matrix analysis was conducted for the full sample and receiver operating characteristic (ROC) curves for discriminating mental health service affiliation. Mean K10 scores differed, with decreasing levels, between inpatients and outpatient in MHS and the subjects with no psychiatric history. Factor analysis confirmed a unidimensional structure, and Cronbach's alpha and Omega showed excellent internal reliability. AUC for the K10 ROC curves showed excellent sensitivity (0.947 [0.900-0.995]), accurately differentiating mental health from non-mental health patients. The Danish K10 has the same strong internal reliability as the original English version, and scores differ between psychiatric patients in outpatient and emergency ward settings. The Danish K10 translation is authorized and freely available for download at https://www.hcp.med.harvard.edu/ncs/k6_scales.php . The utility as an instrument for clinical screening in a mental healthcare setting is supported.

How does the use of multiple needles/syringes per injecting episode impact on the measurement of individual level needle and syringe program coverage?

PubMed

O'Keefe, Daniel; McCormack, Angus; Cogger, Shelley; Aitken, Campbell; Burns, Lucinda; Bruno, Raimondo; Stafford, Jenny; Butler, Kerryn; Breen, Courtney; Dietze, Paul

2017-08-01

Recent work by McCormack et al. (2016) showed that the inclusion of syringe stockpiling improves the measurement of individual-level syringe coverage. We explored whether including the use of a new parameter, multiple sterile syringes per injecting episode, further improves coverage measures. Data comes from 838 people who inject drugs, interviewed as part of the 2015 Illicit Drug Reporting System. Along with syringe coverage questions, the survey recorded the number of sterile syringes used on average per injecting episode. We constructed three measures of coverage: one adapted from Bluthenthal et al. (2007), the McCormack et al. measure, and a new coverage measure that included use of multiple syringes. Predictors of multiple syringe use and insufficient coverage (<100% of injecting episodes using a sterile syringe) using the new measure, were tested in logistic regression and the ability of the measures to discriminate key risk behaviours was compared using ROC curve analysis. 134 (16%) participants reported needing multiple syringes per injecting episode. Women showed significantly increased odds of multiple syringe use, as did those reporting injection related injuries/diseases and injecting of opioid substitution drugs or pharmaceutical opioids. Levels of insufficient coverage across the three measures were substantial (20%-28%). ROC curve analysis suggested that our new measure was no better at discriminating injecting risk behaviours than the existing measures. Based on our findings, there appears to be little need for adding a multiple syringe use parameter to existing coverage formulae. Hence, we recommend that multiple syringe use is not included in the measurement of individual-level syringe coverage. Copyright © 2017 Elsevier B.V. All rights reserved.

Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

NASA Astrophysics Data System (ADS)

Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

2017-08-01

We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  <  0.0001). Survival analysis on immunohistochemical subgroups shows significant separation for the estrogen-receptor subtype tumors (P  <  0.0001) and the triple-negative subtype tumors (P  =  0.0039), but not for tumors of the HER2 subtype (P  =  0.41). The results of this retrospective study show the potential of early-stage pre-treatment eigentumors for use in prediction of treatment failure of breast cancer.

A unified Bayesian semiparametric approach to assess discrimination ability in survival analysis

PubMed Central

Zhao, Lili; Feng, Dai; Chen, Guoan; Taylor, Jeremy M.G.

2015-01-01

Summary The discriminatory ability of a marker for censored survival data is routinely assessed by the time-dependent ROC curve and the c-index. The time-dependent ROC curve evaluates the ability of a biomarker to predict whether a patient lives past a particular time t. The c-index measures the global concordance of the marker and the survival time regardless of the time point. We propose a Bayesian semiparametric approach to estimate these two measures. The proposed estimators are based on the conditional distribution of the survival time given the biomarker and the empirical biomarker distribution. The conditional distribution is estimated by a linear dependent Dirichlet process mixture model. The resulting ROC curve is smooth as it is estimated by a mixture of parametric functions. The proposed c-index estimator is shown to be more efficient than the commonly used Harrell's c-index since it uses all pairs of data rather than only informative pairs. The proposed estimators are evaluated through simulations and illustrated using a lung cancer dataset. PMID:26676324

Bayes’ theorem, the ROC diagram and reference values: Definition and use in clinical diagnosis

PubMed Central

Kallner, Anders

2017-01-01

Medicine is diagnosis, treatment and care. To diagnose is to consider the probability of the cause of discomfort experienced by the patient. The physician may face many options and all decisions are liable to uncertainty to some extent. The rational action is to perform selected tests and thereby increase the pre-test probability to reach a superior post-test probability of a particular option. To draw the right conclusions from a test, certain background information about the performance of the test is necessary. We set up a partially artificial dataset with measured results obtained from the laboratory information system and simulated diagnosis attached. The dataset is used to explore the use of contingency tables with a unique graphic design and software to establish and compare ROC graphs. The loss of information in the ROC curve is compensated by a cumulative data analysis (CDA) plot linked to a display of the efficiency and predictive values. A standard for the contingency table is suggested and the use of dynamic reference intervals discussed. PMID:29209139

Switching from subcutaneous insulin injection to oral vildagliptin administration in hemodialysis patients with type 2 diabetes: a pilot study.

PubMed

Yoshida, Naoshi; Babazono, Tetsuya; Hanai, Ko; Uchigata, Yasuko

2016-08-01

We conducted this pilot study to examine efficacy and safety of switching from subcutaneous injection of insulin to oral administration of a DPP-4 inhibitor, vildagliptin, in type 2 diabetic patients undergoing hemodialysis. Consecutive type 2 diabetic patients on hemodialysis who were switched from insulin to vildagliptin between August 2010 and April 2011 were extracted from the hospital database. In patients whose post-switch increase in glycated albumin (GA) levels was <1.5 % without resuming insulin at least 24 weeks, the switch was defined as efficacious. In patients who resumed insulin therapy due to worsening of glycemic control or in patients whose GA levels increased by 1.5 % or more, the switch was considered inefficacious. To predict patients in whom switch to vildagliptin proved efficacious, receiver-operating characteristic (ROC) analysis and logistic regression analysis were performed. A total of 20 patients were extracted; insulin dose was 12 ± 4 units/day; levels of GA and HbA1c was 21.0 ± 3.7 % and 6.5 ± 0.6 %, respectively. Among them, 11 patients were efficaciously switched to vildagliptin. ROC analysis and logistic analysis showed that patients with a shorter duration of diabetes, as well as lower levels of GA and HbA1c, appeared to have a higher likelihood of successful treatment switches. None of the patients developed hypoglycemic symptoms, ketoacidosis, or serious adverse events. In conclusion, efficacious change from insulin to vildagliptin was possible in approximately a half of type 2 diabetic dialysis patients. Long-term follow-up studies including large number of patients are needed to confirm these results.

A New Reassigned Spectrogram Method in Interference Detection for GNSS Receivers.

PubMed

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-09-02

Interference detection is very important for Global Navigation Satellite System (GNSS) receivers. Current work on interference detection in GNSS receivers has mainly focused on time-frequency (TF) analysis techniques, such as spectrogram and Wigner-Ville distribution (WVD), where the spectrogram approach presents the TF resolution trade-off problem, since the analysis window is used, and the WVD method suffers from the very serious cross-term problem, due to its quadratic TF distribution nature. In order to solve the cross-term problem and to preserve good TF resolution in the TF plane at the same time, in this paper, a new TF distribution by using a reassigned spectrogram has been proposed in interference detection for GNSS receivers. This proposed reassigned spectrogram method efficiently combines the elimination of the cross-term provided by the spectrogram itself according to its inherent nature and the improvement of the TF aggregation property achieved by the reassignment method. Moreover, a notch filter has been adopted in interference mitigation for GNSS receivers, where receiver operating characteristics (ROCs) are used as metrics for the characterization of interference mitigation performance. The proposed interference detection method by using a reassigned spectrogram is evaluated by experiments on GPS L1 signals in the disturbing scenarios in comparison to the state-of-the-art TF analysis approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-term problem and also keeps good TF localization properties, which has been proven to be valid and effective to enhance the interference Sensors 2015, 15 22168 detection performance; in addition, the adoption of the notch filter in interference mitigation has shown a significant acquisition performance improvement in terms of ROC curves for GNSS receivers in jamming environments.

A New Reassigned Spectrogram Method in Interference Detection for GNSS Receivers

PubMed Central

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-01-01

Interference detection is very important for Global Navigation Satellite System (GNSS) receivers. Current work on interference detection in GNSS receivers has mainly focused on time-frequency (TF) analysis techniques, such as spectrogram and Wigner–Ville distribution (WVD), where the spectrogram approach presents the TF resolution trade-off problem, since the analysis window is used, and the WVD method suffers from the very serious cross-term problem, due to its quadratic TF distribution nature. In order to solve the cross-term problem and to preserve good TF resolution in the TF plane at the same time, in this paper, a new TF distribution by using a reassigned spectrogram has been proposed in interference detection for GNSS receivers. This proposed reassigned spectrogram method efficiently combines the elimination of the cross-term provided by the spectrogram itself according to its inherent nature and the improvement of the TF aggregation property achieved by the reassignment method. Moreover, a notch filter has been adopted in interference mitigation for GNSS receivers, where receiver operating characteristics (ROCs) are used as metrics for the characterization of interference mitigation performance. The proposed interference detection method by using a reassigned spectrogram is evaluated by experiments on GPS L1 signals in the disturbing scenarios in comparison to the state-of-the-art TF analysis approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-term problem and also keeps good TF localization properties, which has been proven to be valid and effective to enhance the interference detection performance; in addition, the adoption of the notch filter in interference mitigation has shown a significant acquisition performance improvement in terms of ROC curves for GNSS receivers in jamming environments. PMID:26364637

Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

PubMed

Prabitha, Vasumathi Gopala; Suchetha, Sambasivan; Jayanthi, Jayaraj Lalitha; Baiju, Kamalasanan Vijayakumary; Rema, Prabhakaran; Anuraj, Koyippurath; Mathews, Anita; Sebastian, Paul; Subhash, Narayanan

2016-01-01

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

Timing of occurrence is the most important characteristic of spot sign

PubMed Central

Xu, Mengjun; Zhang, Sheng; Liu, Keqin; Hu, Haitao; Selim, Magdy; Lou, Min

2016-01-01

Background and Purpose Most previous studies have used single-phase CT angiography (CTA) to detect the spot sign, a marker for hematoma expansion (HE) in spontaneous intracerebral hemorrhage (SICH). We investigated whether defining the spot sign based on timing on perfusion CT (CTP) would improve its specificity for predicting HE. Methods We prospectively enrolled supratentorial SICH patients, who underwent CTP within 6 h of onset. Logistic regression were performed to assess the risk factors for HE and poor outcome. Predictive performance of individual CTP spot sign characteristics were examined with receiver operating characteristic (ROC) analysis. Results Sixty-two men and 21 women with SICH were included in this analysis. Spot sign was detected in 46% (38/83) patients. ROC analysis indicated that the timing of spot sign occurrence on CTP had the greatest AUC for HE (0.794; 95% CI, 0.630-0.958; P=0.007); the cutoff time was 23.13 seconds. On multivariable analysis, the presence of early-occurring spot sign (EOSS; i.e. spot sign before 23.13 seconds) was an independent predictor, not only of HE (OR=28.835; 95% CI, 6.960-119.458; P<0.001), but also of mortality at 3 months (OR=22.377; 95% CI, 1.773-282.334; P=0.016). Moreover, the predictive performance showed that the redefined EOSS maintained a higher specificity for HE compared to spot sign (91% vs 74%). Conclusions Redefining the spot sign based on timing of contrast leakage on CTP to determine EOSS, improves the specificity for predicting HE and 3-month mortality. The use of EOSS could improve the selection of ICH patients for potential hemostatic therapy. PMID:27026627

Tumor invasiveness defined by IASLC/ATS/ERS classification of ground-glass nodules can be predicted by quantitative CT parameters.

PubMed

Zhou, Qian-Jun; Zheng, Zhi-Chun; Zhu, Yong-Qiao; Lu, Pei-Ji; Huang, Jia; Ye, Jian-Ding; Zhang, Jie; Lu, Shun; Luo, Qing-Quan

2017-05-01

To investigate the potential value of CT parameters to differentiate ground-glass nodules between noninvasive adenocarcinoma and invasive pulmonary adenocarcinoma (IPA) as defined by IASLC/ATS/ERS classification. We retrospectively reviewed 211 patients with pathologically proved stage 0-IA lung adenocarcinoma which appeared as subsolid nodules, from January 2012 to January 2013 including 137 pure ground glass nodules (pGGNs) and 74 part-solid nodules (PSNs). Pathological data was classified under the 2011 IASLC/ATS/ERS classification. Both quantitative and qualitative CT parameters were used to determine the tumor invasiveness between noninvasive adenocarcinomas and IPAs. There were 154 noninvasive adenocarcinomas and 57 IPAs. In pGGNs, CT size and area, one-dimensional mean CT value and bubble lucency were significantly different between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate regression and ROC analysis revealed that CT size and one-dimensional mean CT value were predictive of noninvasive adenocarcinomas compared to IPAs. Optimal cutoff value was 13.60 mm (sensitivity, 75.0%; specificity, 99.6%), and -583.60 HU (sensitivity, 68.8%; specificity, 66.9%). In PSNs, there were significant differences in CT size and area, solid component area, solid proportion, one-dimensional mean and maximum CT value, three-dimensional (3D) mean CT value between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate and ROC analysis showed that CT size and 3D mean CT value were significantly differentiators. Optimal cutoff value was 19.64 mm (sensitivity, 53.7%; specificity, 93.9%), -571.63 HU (sensitivity, 85.4%; specificity, 75.8%). For pGGNs, CT size and one-dimensional mean CT value are determinants for tumor invasiveness. For PSNs, tumor invasiveness can be predicted by CT size and 3D mean CT value.

Identifying clinically important difference on the Epworth Sleepiness Scale: results from a narcolepsy clinical trial of JZP-110.

PubMed

Scrima, Lawrence; Emsellem, Helene A; Becker, Philip M; Ruoff, Chad; Lankford, Alan; Bream, Gary; Khayrallah, Moise; Lu, Yuan; Black, Jed

2017-10-01

While scores ≤10 on the Epworth Sleepiness Scale (ESS) are within the normal range, the reduction in elevated ESS score that is clinically meaningful in patients with narcolepsy has not been established. This post hoc analysis of a clinical trial of patients with narcolepsy evaluated correlations between Patient Global Impression of Change (PGI-C) and ESS. Data of adult patients with narcolepsy from a double-blind, 12-week placebo-controlled study of JZP-110, a wake-promoting agent, were used in this analysis. Descriptive statistics and receiver operating characteristic (ROC) analysis compared PGI-C (anchor measure) to percent change from baseline in ESS to establish the responder criterion from patients taking either placebo or JZP-110 (treatments). At week 12, patients (n = 10) who reported being "very much improved" on the PGI-C had a mean 76.7% reduction in ESS score, and patients (n = 33) who reported being "much improved" on the PGI-C had a mean 49.1% reduction in ESS score. ROC analysis showed that patients who improved were almost exclusively from JZP-110 treatment group, with an area-under-the-curve of 0.9, and revealed that a 25% reduction in ESS (sensitivity, 81.4%; specificity, 80.9%) may be an appropriate threshold for defining a meaningful patient response to JZP-110 and placebo. A ≥25% reduction in patients' subjective ESS score may be useful as a threshold to identify patients with narcolepsy who respond to JZP-110 treatment. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Long-term total sleep deprivation decreases the default spontaneous activity and connectivity pattern in healthy male subjects: a resting-state fMRI study

PubMed Central

Dai, Xi-Jian; Liu, Chun-Lei; Zhou, Ren-Lai; Gong, Hong-Han; Wu, Bin; Gao, Lei; Wang, Yi-Xiang J

2015-01-01

Objective The aim of this study is to use resting-state functional connectivity (rsFC) and amplitude of low-frequency fluctuation (ALFF) methods to explore intrinsic default-mode network (DMN) impairment after sleep deprivation (SD) and its relationships with clinical features. Methods Twelve healthy male subjects underwent resting-state functional magnetic resonance imaging twice: once following rested wakefulness (RW) and the other following 72 hours of total SD. Before the scans, all subjects underwent the attention network test (ANT). The independent component analysis (ICA), rsFC, and ALFF methods were used to examine intrinsic DMN impairment. Receiver operating characteristic (ROC) curve was used to distinguish SD status from RW status. Results Compared with RW subjects, SD subjects showed a lower accuracy rate (RW =96.83%, SD =77.67%; P<0.001), a slower reaction time (RW =695.92 ms; SD =799.18 ms; P=0.003), a higher lapse rate (RW =0.69%, SD =19.29%; P<0.001), and a higher intraindividual coefficient of variability in reaction time (RW =0.26, SD =0.33; P=0.021). The ICA method showed that, compared with RW subjects, SD subjects had decreased rsFC in the right inferior parietal lobule (IPL, BA40) and in the left precuneus (PrC)/posterior cingulate cortex (PCC) (BA30, 31). The two different areas were selected as regions of interest (ROIs) for future rsFC analysis. Compared with the same in RW subjects, in SD subjects, the right IPL showed decreased rsFC with the left PrC (BA7) and increased rsFC with the left fusiform gyrus (BA37) and the left cluster of middle temporal gyrus and inferior temporal gyrus (BA37). However, the left PrC/PCC did not show any connectivity differences. Compared with RW subjects, SD subjects showed lower ALFF area in the left IPL (BA39, 40). The left IPL, as an ROI, showed decreased rsFC with the right cluster of IPL and superior temporal gyrus (BA39, 40). ROC curve analysis showed that the area under the curve (AUC) value of the left IPL was 0.75, with a cutoff point of 0.834 (mean ALFF signal value). Further diagnostic analysis exhibited that the AUC alone discriminated SD status from RW status, with 75% sensitivity and 91.7% specificity. Conclusion Long-term SD disturbed the spontaneous activity and connectivity pattern of DMN. PMID:25834451

Quantitative Lesion-to-Fat Elasticity Ratio Measured by Shear-Wave Elastography for Breast Mass: Which Area Should Be Selected as the Fat Reference?

PubMed

Youk, Ji Hyun; Son, Eun Ju; Gweon, Hye Mi; Han, Kyung Hwa; Kim, Jeong-Ah

2015-01-01

To investigate whether the diagnostic performance of lesion-to-fat elasticity ratio (Eratio) was affected by the location of the reference fat. For 257 breast masses in 250 women who underwent shear-wave elastography before biopsy or surgery, multiple Eratios were measured with a fixed region-of-interest (ROI) in the mass along with multiple ROIs over the surrounding fat in different locations. Logistic regression analysis was used to determine that Eratio was independently associated with malignancy adjusted for the location of fat ROI (depth, laterality, and distance from lesion or skin). Mean (Emean) and maximum (Emax) elasticity values of fat were divided into four groups according to their interquartile ranges. Diagnostic performance of each group was evaluated using the area under the ROC curve (AUC). False diagnoses of Eratio were reviewed for ROIs on areas showing artifactual high or low stiffness and analyzed by logistic regression analysis to determine variables (associated palpable abnormality, lesion size, the vertical distance from fat ROI to skin, and elasticity values of lesion or fat) independently associated with false results. Eratio was independently associated with malignancy adjusted for the location of fat ROI (P<0.0001). Among four groups of fat elasticity values, the AUC showed no significant difference (<25th percentile, 25th percentile~median, median~75th percentile, and ≥75th percentile; 0.973, 0.982, 0.967, and 0.954 for Emean; 0.977, 0.967, 0.966, and 0.957 for Emax). Fat elasticity values were independently associated with false results of Eratio with the cut-off of 3.18 from ROC curve (P<0.0001). ROIs were set on fat showing artifactual high stiffness in 90% of 10 false negatives and on lesion showing vertical striped artifact or fat showing artifactual low stiffness in 77.5% of 71 false positives. Eratio shows good diagnostic performance regardless of the location of reference fat, except when it is placed in areas of artifacts.

Quantitative Lesion-to-Fat Elasticity Ratio Measured by Shear-Wave Elastography for Breast Mass: Which Area Should Be Selected as the Fat Reference?

PubMed Central

Youk, Ji Hyun; Son, Eun Ju; Gweon, Hye Mi; Han, Kyung Hwa; Kim, Jeong-Ah

2015-01-01

Objectives To investigate whether the diagnostic performance of lesion-to-fat elasticity ratio (Eratio) was affected by the location of the reference fat. Methods For 257 breast masses in 250 women who underwent shear-wave elastography before biopsy or surgery, multiple Eratios were measured with a fixed region-of-interest (ROI) in the mass along with multiple ROIs over the surrounding fat in different locations. Logistic regression analysis was used to determine that Eratio was independently associated with malignancy adjusted for the location of fat ROI (depth, laterality, and distance from lesion or skin). Mean (Emean) and maximum (Emax) elasticity values of fat were divided into four groups according to their interquartile ranges. Diagnostic performance of each group was evaluated using the area under the ROC curve (AUC). False diagnoses of Eratio were reviewed for ROIs on areas showing artifactual high or low stiffness and analyzed by logistic regression analysis to determine variables (associated palpable abnormality, lesion size, the vertical distance from fat ROI to skin, and elasticity values of lesion or fat) independently associated with false results. Results Eratio was independently associated with malignancy adjusted for the location of fat ROI (P<0.0001). Among four groups of fat elasticity values, the AUC showed no significant difference (<25th percentile, 25th percentile~median, median~75th percentile, and ≥75th percentile; 0.973, 0.982, 0.967, and 0.954 for Emean; 0.977, 0.967, 0.966, and 0.957 for Emax). Fat elasticity values were independently associated with false results of Eratio with the cut-off of 3.18 from ROC curve (P<0.0001). ROIs were set on fat showing artifactual high stiffness in 90% of 10 false negatives and on lesion showing vertical striped artifact or fat showing artifactual low stiffness in 77.5% of 71 false positives. Conclusion Eratio shows good diagnostic performance regardless of the location of reference fat, except when it is placed in areas of artifacts. PMID:26368920

Nonparametric EROC analysis for observer performance evaluation on joint detection and estimation tasks

NASA Astrophysics Data System (ADS)

Wunderlich, Adam; Goossens, Bart

2014-03-01

The majority of the literature on task-based image quality assessment has focused on lesion detection tasks, using the receiver operating characteristic (ROC) curve, or related variants, to measure performance. However, since many clinical image evaluation tasks involve both detection and estimation (e.g., estimation of kidney stone composition, estimation of tumor size), there is a growing interest in performance evaluation for joint detection and estimation tasks. To evaluate observer performance on such tasks, Clarkson introduced the estimation ROC (EROC) curve, and the area under the EROC curve as a summary figure of merit. In the present work, we propose nonparametric estimators for practical EROC analysis from experimental data, including estimators for the area under the EROC curve and its variance. The estimators are illustrated with a practical example comparing MRI images reconstructed from different k-space sampling trajectories.

Quantifying Uncertainties from Presence Data Sampling Methods for Species Distribution Modeling: Focused on Vegetation.

NASA Astrophysics Data System (ADS)

Sung, S.; Kim, H. G.; Lee, D. K.; Park, J. H.; Mo, Y.; Kil, S.; Park, C.

2016-12-01

The impact of climate change has been observed throughout the globe. The ecosystem experiences rapid changes such as vegetation shift, species extinction. In these context, Species Distribution Model (SDM) is one of the popular method to project impact of climate change on the ecosystem. SDM basically based on the niche of certain species with means to run SDM present point data is essential to find biological niche of species. To run SDM for plants, there are certain considerations on the characteristics of vegetation. Normally, to make vegetation data in large area, remote sensing techniques are used. In other words, the exact point of presence data has high uncertainties as we select presence data set from polygons and raster dataset. Thus, sampling methods for modeling vegetation presence data should be carefully selected. In this study, we used three different sampling methods for selection of presence data of vegetation: Random sampling, Stratified sampling and Site index based sampling. We used one of the R package BIOMOD2 to access uncertainty from modeling. At the same time, we included BioCLIM variables and other environmental variables as input data. As a result of this study, despite of differences among the 10 SDMs, the sampling methods showed differences in ROC values, random sampling methods showed the lowest ROC value while site index based sampling methods showed the highest ROC value. As a result of this study the uncertainties from presence data sampling methods and SDM can be quantified.

Ka-Band Link Study and Analysis for a Mars Hybrid RF/Optical Software Defined Radio

NASA Technical Reports Server (NTRS)

Zeleznikar, Daniel J.; Nappier, Jennifer M.; Downey, Joseph A.

2014-01-01

The integrated radio and optical communications (iROC) project at the NASA Glenn Research Center (GRC) is investigating the feasibility of a hybrid RF and optical communication subsystem for future deep space missions. The hybrid communications subsystem enables the advancement of optical communications while simultaneously mitigating the risk of infusion by combining an experimental optical transmitter and telescope with a reliable Ka-band RF transmitter and antenna. The iROC communications subsystem seeks to maximize the total data return over the course of a potential 2-year mission in Mars orbit beginning in 2021. Although optical communication by itself offers potential for greater data return over RF, the reliable Ka-band link is also being designed for high data return capability in this hybrid system. A daily analysis of the RF link budget over the 2-year span is performed to optimize and provide detailed estimates of the RF data return. In particular, the bandwidth dependence of these data return estimates is analyzed for candidate waveforms. In this effort, a data return modeling tool was created to analyze candidate RF modulation and coding schemes with respect to their spectral efficiency, amplifier output power back-off, required digital to analog conversion (DAC) sampling rates, and support by ground receivers. A set of RF waveforms is recommended for use on the iROC platform.

A novel multi-epitope recombined protein for diagnosis of human brucellosis.

PubMed

Yin, Dehui; Li, Li; Song, Xiuling; Li, Han; Wang, Juan; Ju, Wen; Qu, Xiaofeng; Song, Dandan; Liu, Yushen; Meng, Xiangjun; Cao, Hongqian; Song, Weiyi; Meng, Rizeng; Liu, Jinhua; Li, Juan; Xu, Kun

2016-05-21

In epidemic regions of the world, brucellosis is a reemerging zoonosis with minimal mortality but is a serious public hygiene problem. Currently, there are various methods for brucellosis diagnosis, however few of them are available to be used to diagnose, especially for serious cross-reaction with other bacteria. To overcome this disadvantage, we explored a novel multi-epitope recombinant protein as human brucellosis diagnostic antigen. We established an indirect enzyme-linked immunosorbent assay (ELISA) based on this recombinant protein. 248 sera obtained from three different groups including patients with brucellosis (146 samples), non-brucellosis patients (82 samples), and healthy individuals (20 samples) were tested by indirect ELISA. To evaluate the assay, a receiver-operating characteristic (ROC) analysis and immunoblotting were carried out using these characterized serum samples. For this test, the area under the ROC curve was 0.9409 (95 % confidence interval, 0.9108 to 0.9709), and a sensitivity of 88.89 % and a specificity of 85.54 % was given with a cutoff value of 0.3865 from this ROC analysis. The Western blot results indicate that it is feasible to differentiate human brucellosis and non-brucellosis with the newly established method based on this recombinant protein. Our results obtained high diagnostic accuracy of the ELISA assay which encourage the use of this novel recombinant protein as diagnostic antigen to implement serological diagnosis of brucellosis.

Rocking at 81 and Rolling at 34: ROC Cut-Off Scores for the Negative Acts Questionnaire–Revised in Serbia

PubMed Central

Petrović, Ivana B.; Vukelić, Milica; Čizmić, Svetlana

2017-01-01

Researchers are still searching for the ways to identify different categories of employees according to their exposure to negative acts and psychological experience of workplace bullying. We followed Notelaers and Einarsen’s application of the ROC analysis to determine the NAQ-R cut-off scores applying a “lower” and “higher” threshold. The main goal of this research was to develop and test different gold standards of personal and organizational relevance in determining the NAQ-R cut-off scores in a specific cultural and economic context of Serbia. Apart from combining self-labeling as a victim with self-perceived health, the objectives were to test the gold standards developed as a combination of self-labeling with life satisfaction, self-labeling with intention to leave and a complex gold standard based on self-labeling, self-perceived health, life satisfaction and intention to leave taken together. The ROC analysis on Serbian workforce data supports applying of different gold standards. For identifying employees in a preliminary stage of bullying, the most applicable was the gold standard based on self-labeling and intention to leave (score 34 and higher). The most accurate identification of victims could be based on the most complex gold standard (score 81 and higher). This research encourages further investigation of gold standards in different cultures. PMID:28119652

Histogram analysis of apparent diffusion coefficient at 3.0 T in urinary bladder lesions: correlation with pathologic findings.

PubMed

Suo, Shi-Teng; Chen, Xiao-Xi; Fan, Yu; Wu, Lian-Ming; Yao, Qiu-Ying; Cao, Meng-Qiu; Liu, Qiang; Xu, Jian-Rong

2014-08-01

To investigate the potential value of histogram analysis of apparent diffusion coefficient (ADC) obtained at standard (700 s/mm(2)) and high (1500 s/mm(2)) b values on a 3.0-T scanner in the differentiation of bladder cancer from benign lesions and in assessing bladder tumors of different pathologic T stages and to evaluate the diagnostic performance of ADC-based histogram parameters. In all, 52 patients with bladder lesions, including benign lesions (n = 7) and malignant tumors (n = 45; T1 stage or less, 23; T2 stage, 7; T3 stage, 8; and T4 stage, 7), were retrospectively evaluated. Magnetic resonance examination at 3.0 T and diffusion-weighted imaging were performed. ADC maps were obtained at two b values (b = 700 and 1500 s/mm(2); ie, ADC-700 and ADC-1500). Parameters of histogram analysis included mean, kurtosis, skewness, and entropy. The correlations between these parameters and pathologic results were revealed. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic value of histogram parameters. Significant differences were found in mean ADC-700, mean ADC-1500, skewness ADC-1500, and kurtosis ADC-1500 between bladder cancer and benign lesions (P = .002-.032). There were also significant differences in mean ADC-700, mean ADC-1500, and kurtosis ADC-1500 among bladder tumors of different pathologic T stages (P = .000-.046). No significant differences were observed in other parameters. Mean ADC-1500 and kurtosis ADC-1500 were significantly correlated with T stage, respectively (ρ = -0.614, P < .001; ρ = 0.374, P = .011). ROC analysis showed that the combination of mean ADC-1500 and kurtosis ADC-1500 has the maximal area under the ROC curve (AUC, 0.894; P < .001) in the differentiation of benign lesions and malignant tumors, with a sensitivity of 77.78% and specificity of 100%. AUCs for differentiating low- and high-stage tumors were 0.840 for mean ADC-1500 (P < .001) and 0.696 for kurtosis ADC-1500 (P = .015). Histogram analysis of ADC-1500 at 3.0 T can be useful in evaluation of bladder lesions. A combination of mean ADC-1500 and kurtosis ADC-1500 may be more beneficial in the differentiation of benign and malignant lesions. Mean ADC-1500 was the most promising parameter for differentiating low- from high-stage bladder cancer. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

[Predictive value of early phrase echocardiography and cardiac biological markers in patients with severe sepsis: a five-year single-center retrospective study].

PubMed

Zang, Xuefeng; Chen, Wei; Sheng, Bo; Zhao, Lei; Gu, Xuyun; Zhen, Jie; Liu, Ping

2018-04-01

To assess the predictive value of early phrase echocardiography and cardiac biomarkers in patients with severe sepsis. A retrospective analysis of severe septic patients (patients with acute coronary syndrome and end stage renal disease were excluded) in department of intensive care unit of Capital Medical University Affiliated Beijing Shijitan Hospital from January 2013 to December 2017 was conducted. The acute physiology and chronic health evaluation II (APACHE II) score, N-terminal prohormone of brain natriuretic peptide (NT-proBNP), cardiac troponin I (cTnI), myoglobin (MYO), creatine kinase (CK), MB isoenzyme of creatine kinase (CK-MB) within 6 hours after admission, and bedside echocardiography indexes [left ventricular ejection fraction (LVEF), the ratio of the peak blood flow velocity in the early stage of the mitral valve and the peak blood flow rate of the mitral valve (E/A ratio)] within 6 hours after diagnosis were recorded. The differences of indexes between patients with decreased contractile function (LVEF < 0.50) group and normal group, and the difference between dead group and survival group within 28-day were compared. Receiver operating characteristic (ROC) curve and Logistic regression analysis were conducted to assess the early detected prognostic value in severe sepsis patients. (1) A total of 316 patients were enrolled in the survey period. Decreased cardiac systolic function (LVEF < 0.50) was found in 89 cases (28.2%), and cardiac diastolic function impaired (E/A ratio < 1) in 269 cases (85.1%); while 79 cases (25.0%) had both systolic function and diastolic function impairment. (2) NT-proBNP and cTnI were statistically different between cardiac systolic function impaired group and normal group. Further Logistic regression analysis showed that only NT-proBNP was significantly correlated with LVEF [β=-1.311, odds ratio (OR) = 0.269, P < 0.001]. (3) Eighty-two of 316 cases were died in 28-day, and the 28-day mortality rate was 25.9%. Compared with the survival group, the ratio of E/A < 1, APACHE II score, NT-proBNP, cTnI, MYO, CK and CK-MB were significantly increased in death group. The ROC curve analysis showed that the above indexes had diagnosed value for prognosis in severe sepsis patient, among which NT-proBNP and cTnI had higher predictive value [the area under ROC curve (AUC) were 0.920 and 0.901 respectively, both P < 0.001]. Multivariate Logistic regression analysis showed that APACHE II score (β= 0.282, OR = 1.326, P < 0.001) and NT-proBNP (β= 0.402, OR = 1.261, P < 0.001) were independent risk factors for prognosis in patients with severe sepsis. The LVEF values measured by echocardiography in early phrase were unrelated to 28-day prognosis. APACHE II score, E/A ratio, NT-proBNP, cTnI, MYO, CK and CK-MB were related to 28-day prognosis. APACHE II scores and NT-proBNP were independent prognostic factors in severe sepsis patient.

Validation of a Brief PTSD Scale for Clients with Severe Mental Illnesses

ERIC Educational Resources Information Center

O'Hare, Thomas; Shen, Ce; Sherrer, Margaret

2012-01-01

Trauma and Posttraumatic Stress Disorder (PTSD) are more common in severe mental illnesses (SMI) clients than in the general population, yet brief screens for detecting probable PTSD in SMI clients are nonexistent. In a two-part study, the authors used correlation analysis and receiver operating characteristics (ROC) analysis to develop and…

Paired split-plot designs of multireader multicase studies.

PubMed

Chen, Weijie; Gong, Qi; Gallas, Brandon D

2018-07-01

The widely used multireader multicase ROC study design for comparing imaging modalities is the fully crossed (FC) design: every reader reads every case of both modalities. We investigate paired split-plot (PSP) designs that may allow for reduced cost and increased flexibility compared with the FC design. In the PSP design, case images from two modalities are read by the same readers, thereby the readings are paired across modalities. However, within each modality, not every reader reads every case. Instead, both the readers and the cases are partitioned into a fixed number of groups and each group of readers reads its own group of cases-a split-plot design. Using a [Formula: see text]-statistic based variance analysis for AUC (i.e., area under the ROC curve), we show analytically that precision can be gained by the PSP design as compared with the FC design with the same number of readers and readings. Equivalently, we show that the PSP design can achieve the same statistical power as the FC design with a reduced number of readings. The trade-off for the increased precision in the PSP design is the cost of collecting a larger number of truth-verified patient cases than the FC design. This means that one can trade-off between different sources of cost and choose a least burdensome design. We provide a validation study to show the iMRMC software can be reliably used for analyzing data from both FC and PSP designs. Finally, we demonstrate the advantages of the PSP design with a reader study comparing full-field digital mammography with screen-film mammography.

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

PubMed Central

Cheng, Karen Elizabeth; Crary, David J; Ray, Jaideep; Safta, Cosmin

2013-01-01

Objective We discuss the use of structural models for the analysis of biosurveillance related data. Methods and results Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm. Conclusions Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data. PMID:23037798

Quantitative methods and detection techniques in hyperspectral imaging involving medical and other applications

NASA Astrophysics Data System (ADS)

Roy, Ankita

2007-12-01

This research using Hyperspectral imaging involves recognizing targets through spatial and spectral matching and spectral un-mixing of data ranging from remote sensing to medical imaging kernels for clinical studies based on Hyperspectral data-sets generated using the VFTHSI [Visible Fourier Transform Hyperspectral Imager], whose high resolution Si detector makes the analysis achievable. The research may be broadly classified into (I) A Physically Motivated Correlation Formalism (PMCF), which places both spatial and spectral data on an equivalent mathematical footing in the context of a specific Kernel and (II) An application in RF plasma specie detection during carbon nanotube growing process. (III) Hyperspectral analysis for assessing density and distribution of retinopathies like age related macular degeneration (ARMD) and error estimation enabling the early recognition of ARMD, which is treated as an ill-conditioned inverse imaging problem. The broad statistical scopes of this research are two fold-target recognition problems and spectral unmixing problems. All processes involve experimental and computational analysis of Hyperspectral data sets is presented, which is based on the principle of a Sagnac Interferometer, calibrated to obtain high SNR levels. PMCF computes spectral/spatial/cross moments and answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required precisely for a particular target recognition. Spectral analysis of RF plasma radicals, typically Methane plasma and Argon plasma using VFTHSI has enabled better process monitoring during growth of vertically aligned multi-walled carbon nanotubes by instant registration of the chemical composition or density changes temporally, which is key since a significant correlation can be found between plasma state and structural properties. A vital focus of this dissertation is towards medical Hyperspectral imaging applied to retinopathies like age related macular degeneration targets taken with a Fundus imager, which is akin to the VFTHSI. Detection of the constituent components in the diseased hyper-pigmentation area is also computed. The target or reflectance matrix is treated as a highly ill-conditioned spectral un-mixing problem, to which methodologies like inverse techniques, principal component analysis (PCA) and receiver operating curves (ROC) for precise spectral recognition of infected area. The region containing ARMD was easily distinguishable from the spectral mesh plots over the entire band-pass area. Once the location was detected the PMCF coefficients were calculated by cross correlating a target of normal oxygenated retina with the deoxygenated one. The ROCs generated using PMCF shows 30% higher detection probability with improved accuracy than ROCs based on Spectral Angle Mapper (SAM). By spectral unmixing methods, the important endmembers/carotenoids of the MD pigment were found to be Xanthophyl and lutein, while beta-carotene which showed a negative correlation in the unconstrained inverse problem is a supplement given to ARMD patients to prevent the disease and does not occur in the eye. Literature also shows degeneration of meso-zeaxanthin. Ophthalmologists may assert the presence of ARMD and commence the diagnosis process if the Xanthophyl pigment have degenerated 89.9%, while the lutein has decayed almost 80%, as found deduced computationally. This piece of current research takes it to the next level of precise investigation in the continuing process of improved clinical findings by correlating the microanatomy of the diseased fovea and shows promise of an early detection of this disease.

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study

PubMed Central

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Background: Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. Aim: The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. Settings and Design: A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Methods: Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. Statistical Analysis Used: ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Results: Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). Conclusion: CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas. PMID:29386780

[Predicting very early rebleeding after acute variceal bleeding based in classification and regression tree analysis (CRTA).].

PubMed

Altamirano, J; Augustin, S; Muntaner, L; Zapata, L; González-Angulo, A; Martínez, B; Flores-Arroyo, A; Camargo, L; Genescá, J

2010-01-01

Variceal bleeding (VB) is the main cause of death among cirrhotic patients. About 30-50% of early rebleeding is encountered few days after the acute episode of VB. It is necessary to stratify patients with high risk of very early rebleeding (VER) for more aggressive therapies. However, there are few and incompletely understood prognostic models for this purpose. To determine the risk factors associated with VER after an acute VB. Assessment and comparison of a novel prognostic model generated by Classification and Regression Tree Analysis (CART) with classic-used models (MELD and Child-Pugh [CP]). Sixty consecutive cirrhotic patients with acute variceal bleeding. CART analysis, MELD and Child-Pugh scores were performed at admission. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of the models. Very early rebleeding rate was 13%. Variables associated with VER were: serum albumin (p = 0.027), creatinine (p = 0.021) and transfused blood units in the first 24 hrs (p = 0.05). The area under the ROC for MELD, CHILD-Pugh and CART were 0.46, 0.50 and 0.82, respectively. The value of cut analyzed by CART for the significant variables were: 1) Albumin 2.85 mg/dL, 2) Packed red cells 2 units and 3) Creatinine 1.65 mg/dL the ABC-ROC. Serum albumin, creatinine and number of transfused blood units were associated with VER. A simple CART algorithm combining these variables allows an accurate predictive assessment of VER after acute variceal bleeding. Key words: cirrhosis, variceal bleeding, esophageal varices, prognosis, portal hypertension.

Diagnostic Performance of (18)F-Fluorodeoxyglucose in 162 Small Pulmonary Nodules Incidentally Detected in Subjects Without a History of Malignancy.

PubMed

Calcagni, Maria Lucia; Taralli, Silvia; Cardillo, Giuseppe; Graziano, Paolo; Ialongo, Pasquale; Mattoli, Maria Vittoria; Di Franco, Davide; Caldarella, Carmelo; Carleo, Francesco; Indovina, Luca; Giordano, Alessandro

2016-04-01

Solitary pulmonary nodule (SPN) still represents a diagnostic challenge. The aim of our study was to evaluate the diagnostic performance of (18)F-fluorodeoxyglucose positron emission tomography-computed tomography in one of the largest samples of small SPNs, incidentally detected in subjects without a history of malignancy (nonscreening population) and undetermined at computed tomography. One-hundred and sixty-two small (>0.8 to 1.5 cm) and, for comparison, 206 large nodules (>1.5 to 3 cm) were retrospectively evaluated. Diagnostic performance of (18)F-fluorodeoxyglucose visual analysis, receiver-operating characteristic (ROC) analysis for maximum standardized uptake value (SUVmax), and Bayesian analysis were assessed using histology or radiological follow-up as a golden standard. In 162 small nodules, (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.3) provided 72.6% and 77.4% sensitivity and 88.0% and 82.0% specificity, respectively. The prevalence of malignancy was 38%; Bayesian analysis provided 78.8% positive and 16.0% negative posttest probabilities of malignancy. In 206 large nodules (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.9) provided 89.5% and 85.1% sensitivity and 70.8% and 79.2% specificity, respectively. The prevalence of malignancy was 65%; Bayesian analysis provided 85.0% positive and 21.6% negative posttest probabilities of malignancy. In both groups, malignant nodules had a significant higher SUVmax (p < 0.0001) than benign nodules. Only in the small group, malignant nodules were significantly larger (p = 0.0054) than benign ones. (18)F-fluorodeoxyglucose can be clinically relevant to rule in and rule out malignancy in undetermined small SPNs, incidentally detected in nonscreening population with intermediate pretest probability of malignancy, as well as in larger ones. Visual analysis can be considered an optimal diagnostic criterion, adequately detecting a wide range of malignant nodules with different metabolic activity. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance.

PubMed

Du, Tingting; Yuan, Gang; Zhang, Muxun; Zhou, Xinrong; Sun, Xingxing; Yu, Xuefeng

2014-10-20

To directly compare traditional lipid ratios (total cholesterol [TC]/high density lipoprotein cholesterol [HDL-C], non-HDL-C/HDL-C, low density lipoprotein cholesterol [LDL-C]/HDL-C, and triglycerides [TG]/HDL-C), apolipoprotein B (apoB)/apolipoprotein A-I (apoA-I) ratio, visceral adiposity index (VAI), lipid accumulation product (LAP), and the product of TG and fasting glucose (TyG) for strength and independence as risk factors for insulin resistance (IR). We conducted a cross-sectional analysis of 7629 Chinese adults using data from the China Health and Nutrition Survey 2009. For all lipid ratios (traditional lipid ratios and apoB/apoA-I), among both sexes, TG/HDL-C explained the most additional percentage of variation in HOMA-IR (2.9% in men, and 2.3% in women); for all variables of interest, the variability in HOMA-IR explained by VAI and TG/HDL-C were comparable; TyG had the most significant association with HOMA-IR, which explained 9.1% for men and 7.8% for women of the variability in HOMA-IR. Logistic regression analysis showed the similar patterns. Receiver operating characteristic (ROC) curve analysis showed that, among both sexes, TG/HDL-C was a better discriminator of IR than apoB/apoA-I; the area under the ROC curve (AUC) for VAI (0.695 in men and 0.682 in women) was greater than that for TG/HDL-C (AUC 0.665 in men and 0.664 in women); TyG presented the greatest value of AUC (0.709 in men and 0.711 in women). The apoB/apoA-I performs no better than any of the traditional lipid ratios in correlating with IR. The TG/HDL-C, VAI and TyG are better markers for early identification of IR individuals.

Comparison of procalcitonin and high-sensitivity C-reactive protein for the diagnosis of sepsis and septic shock in the oldest old patients.

PubMed

Zhang, Hongmin; Wang, Xiaoting; Zhang, Qing; Xia, Ying; Liu, Dawei

2017-08-01

Although the role of serum procalcitonin (PCT) and high-sensitivity C-reactive protein (hs-CRP) in the diagnosis of sepsis and septic shock is well studied, it has not been investigated among oldest old patients. The aim of our study is to determine the role of PCT and hs-CRP in the assessment of sepsis and septic shock in this specific group of patients in the ICU. This is a prospective observational study. Patients >85 years of age admitted to the ICU from May 1st, 2016 to February 1st, 2017 were evaluated. Patients were divided into a sepsis and septic shock group(sepsis/SS) and a non-sepsis group. Serum levels of PCT, hs-CRP and the WBC were measured within 12 h of admission. A total of 70 patients aged 85 years and older were enrolled in this study. Fifty patients were labelled as sepsis/SS and the other 20 were labelled non-sepsis. A ROC analysis showed that the area under the curves (AUC) of hs-CRP and PCT for the discrimination of sepsis/SS patients were 0.825 (95% confidence interval[CI]: 0.73-0.92; P < 0.001) and 0.819 (95%CI:0.72-0.92; p < 0.001), respectively. In a subgroup analysis of the sepsis/SS group, 27 patients had sepsis, while the other 23 patients had septic shock. The ROC analysis showed that the AUCs of hs-CRP and PCT for the discrimination of septic shock patients from sepsis patients were 0.751 (95% CI: 0.62-0.88; P = 0.002) and 0.719 (95% CI:0.57-0.86; p = 0.007), respectively. For the oldest old patients, hs-CRP is not inferior to PCT in the diagnosis of sepsis and septic shock.

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion

PubMed Central

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka

2017-01-01

Purpose Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. Materials and methods We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. Results The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. Conclusions ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion. PMID:28207858

Impulse oscillometry system as an alternative diagnostic method for chronic obstructive pulmonary disease.

PubMed

Wei, Xia; Shi, Zhihong; Cui, Yajuan; Mi, Jiuyun; Ma, Zhengquan; Ren, Jingting; Li, Jie; Xu, Shudi; Guo, Youmin

2017-11-01

We aimed to compare impulse oscillation system (IOS) and traditional pulmonary function tests (PFTs) for the assessment of the severity of chronic obstructive pulmonary disease (COPD), and to assess the use of IOS parameters to identify patients who were forced expiratory volume in 1 second (FEV1)%pred < 50%.Patients with COPD (n = 215) were enrolled at the Ninth Hospital of Xi'an Affiliated Hospital of Xi'an Jiaotong University between October 2014 and September 2016. All patients were assessed by traditional PFT and IOS. Diagnostic performance of IOS parameters to determine indication for patients of FEV1%pred < 50% was assessed on receiver-operating characteristics (ROC) curve analysis.Out of 215 patients, 18, 83, 78, and 36 patients were classified as grade 1, 2, 3, and 4, respectively, according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity grading. On Spearman correlation analysis, FEV1%pred, MMEF 75%-25%, and residual volume/total lung capacity (RV/TLC) correlated with total respiratory impedance (Z5)%pred, resistance at 5 Hz (R5)-resistance at 20 Hz (R20), R5-R20% R5, R5, R5%pred, frequency response (Fres), reactance area (Ax), and reactance at 5 Hz (X5). On ROC curve analysis, the area under the curve (AUC) of X5 absolute value, Fres, Ax, Z5%pred, R5-R20, and R5-R20% R5 were 0.748, 0.755, 0.760, 0.705, 0.715, and 0.735, respectively, for COPD patients who required inhalational glucocorticoid therapy.IOS parameters showed a good correlation with traditional pulmonary function parameters; reactance parameters showed a stronger correlation than that of the resistance parameters. IOS can be used as an alternative method for pulmonary function assessment in patients with COPD with FEV1%pred < 50% who need inhalational glucocorticoid therapy. ChiCTR-OCH-14004904.

Impulse oscillometry system as an alternative diagnostic method for chronic obstructive pulmonary disease

PubMed Central

Wei, Xia; Shi, Zhihong; Cui, Yajuan; Mi, Jiuyun; Ma, Zhengquan; Ren, Jingting; Li, Jie; Xu, Shudi; Guo, Youmin

2017-01-01

Abstract We aimed to compare impulse oscillation system (IOS) and traditional pulmonary function tests (PFTs) for the assessment of the severity of chronic obstructive pulmonary disease (COPD), and to assess the use of IOS parameters to identify patients who were forced expiratory volume in 1 second (FEV1)%pred < 50%. Patients with COPD (n = 215) were enrolled at the Ninth Hospital of Xi’an Affiliated Hospital of Xi’an Jiaotong University between October 2014 and September 2016. All patients were assessed by traditional PFT and IOS. Diagnostic performance of IOS parameters to determine indication for patients of FEV1%pred < 50% was assessed on receiver-operating characteristics (ROC) curve analysis. Out of 215 patients, 18, 83, 78, and 36 patients were classified as grade 1, 2, 3, and 4, respectively, according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity grading. On Spearman correlation analysis, FEV1%pred, MMEF 75%–25%, and residual volume/total lung capacity (RV/TLC) correlated with total respiratory impedance (Z5)%pred, resistance at 5 Hz (R5)-resistance at 20 Hz (R20), R5-R20% R5, R5, R5%pred, frequency response (Fres), reactance area (Ax), and reactance at 5 Hz (X5). On ROC curve analysis, the area under the curve (AUC) of X5 absolute value, Fres, Ax, Z5%pred, R5-R20, and R5-R20% R5 were 0.748, 0.755, 0.760, 0.705, 0.715, and 0.735, respectively, for COPD patients who required inhalational glucocorticoid therapy. IOS parameters showed a good correlation with traditional pulmonary function parameters; reactance parameters showed a stronger correlation than that of the resistance parameters. IOS can be used as an alternative method for pulmonary function assessment in patients with COPD with FEV1%pred < 50% who need inhalational glucocorticoid therapy. Clinical trial registration number: ChiCTR-OCH-14004904. PMID:29145259

Optimal Hemoglobin A1c Levels for Screening of Diabetes and Prediabetes in the Japanese Population.

PubMed

Shimodaira, Masanori; Okaniwa, Shinji; Hanyu, Norinao; Nakayama, Tomohiro

2015-01-01

The aim of this study was to evaluate the utility of hemoglobin A1c (HbA1c) to identify individuals with diabetes and prediabetes in the Japanese population. A total of 1372 individuals without known diabetes were selected for this study. A 75 g oral glucose tolerance test (OGTT) was used to diagnose diabetes and prediabetes. The ability of HbA1c to detect diabetes and prediabetes was investigated using receiver operating characteristic (ROC) analysis. The kappa (κ) coefficient was used to test the agreement between HbA1c categorization and OGTT-based diagnosis. ROC analysis demonstrated that HbA1c was a good test to identify diabetes and prediabetes, with areas under the curve of 0.918 and 0.714, respectively. Optimal HbA1c cutoffs for diagnosing diabetes and prediabetes were 6.0% (sensitivity 83.7%, specificity 87.6%) and 5.7% (sensitivity 60.6%, specificity 72.1%), respectively, although the cutoff for prediabetes showed low accuracy (67.6%) and a high false-negative rate (39.4%). Agreement between HbA1c categorization and OGTT-based diagnosis was low in diabetes (κ = 0.399) and prediabetes (κ = 0.324). In Japanese subjects, the HbA1c cutoff of 6.0% had appropriate sensitivity and specificity for diabetes screening, whereas the cutoff of 5.7% had modest sensitivity and specificity in identifying prediabetes. Thus, HbA1c may be inadequate as a screening tool for prediabetes.

Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

NASA Astrophysics Data System (ADS)

Zhang, Nannan; Zhou, Kefa; Du, Xishihui

2017-04-01

Mineral prospectivity mapping (MPM) is a multi-step process that ranks promising target areas for further exploration. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are knowledge-driven MPM approaches. In this study, both approaches were used for data processing, based on which MPM was performed for porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang. The results of the two methods were then compared. The two methods combined expert experience and the Studentized contrast (S(C)) values of the weights-of-evidence approach to calculate the weights of 15 layers, and these layers were then integrated by the gamma operator (γ). Through prediction-area (P-A) plot analysis, the optimal γ for fuzzy logic and fuzzy AHP was determined as 0.95 and 0.93, respectively. The thresholds corresponding to different levels of metallogenic probability were defined via concentration-area (C-A) fractal analysis. The prediction performances of the two methods were compared on this basis. The results showed that in MPM based on fuzzy logic, the area under the receiver operating characteristic (ROC) curve was 0.806 and 81.48% of the known deposits were predicted, whereas in MPM based on fuzzy AHP, the area under the ROC curve was 0.862 and 92.59% of the known deposits were predicted. Therefore, prediction based on fuzzy AHP is more accurate and can provide directions for future prospecting.

Prenatal diagnosis of fetal respiratory function: evaluation of fetal lung maturity using lung-to-liver signal intensity ratio at magnetic resonance imaging.

PubMed

Oka, Yasuko; Rahman, Mosfequr; Sasakura, Chihaya; Waseda, Tomoo; Watanabe, Yukio; Fujii, Ryota; Makinoda, Satoru

2014-12-01

The purpose of this retrospective study is to determine the fetal lung-to-liver signal intensity ratio (LLSIR) on T2-weighted images for the prediction of neonatal respiratory outcome. One hundred ten fetuses who underwent magnetic resonance imaging (MRI) examination for various indications after 22 weeks of gestation participated in this study. LLSIR was measured as the ratio of signal intensities of the fetal lung and liver on T2-weighted images at MRI. We examined the changes of the ratio with advancing gestation and the relations between LLSIR and the presence of the severe respiratory disorder (SRD) after birth. The best cut-off value of the LLSIR to predict respiratory outcome after birth was calculated using receiver operating characteristic (ROC) curve analysis. Lung-to-liver signal intensity ratio correlated significantly with advancing gestational age (R = 0.35, p < 0.001). The non-SRD group had higher LLSIR compared with the SRD group (2.15 ± 0.30 vs. 1.53 ± 0.40, p < 0.001). ROC curve analysis showed that fetuses with an LLSIR < 2.00 were more likely to develop SRD [sensitivity: 100%, 95% confidence interval (CI): 52-100%; specificity: 73%, 95% CI 54-88%]. The fetal LLSIR on T2-weighted images is an accurate marker to diagnose the fetal lung maturity. © 2014 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.

[Changes of monocyte and monocyte-platelet aggregates in different subgroups of thrombotic events in patients with acute myocardial infarction during PCI].

PubMed

Wang, Sheng; Sun, Cuifang; Liao, Wang; Wu, Zhongwei; Wang, Yudai; Huang, Xiuxian; Lu, Sijia; Dong, Xiaoli; Shuai, Fujie; Li, Bin

2017-07-01

Objective To investigate the impact of thrombotic events on the alterations of monocyte and monocyte-platelet aggregates (MPAs) in patients with acute myocardial infarction (AMI) during percutaneous coronary intervention (PCI). Methods Blood was collected before PCI for flow cytometry. Monocyte subsets and MPAs were detected by four-color platform (CDl4-APC, CDl6-PE-Cy7, CD86-PE and CD41-Alexa Fluor R 488). According to the expression of the platelet surface marker CD41, the number of monocyte subsets and MPAs was analyzed using the fluorescent microspheres of absolute counting tube. The Wilcoxon rank sum test and receiver operating characteristic (ROC) curve analysis were performed. Results CD14 + CD16 ++ monocytes in intraprocedural thrombotic events (IPTE) group were significantly fewer than those in non-IPTE group, and the percentage in total mononuclear cells decreased. Compared with non-IPTE group, MPA binding ratio and monocyte subset MPA binding ratio were significantly higher in IPTE group. ROC analysis showed that MPA binding ratio and subgroup MPA binding ratio had a better predictive value for IPTE in patients with AMI. Conclusion The CD14 + CD16 ++ monocytes in IPTE group were significantly fewer than those in the non-IPTE group. MPA binding ratio and MPA binding ratio of monocyte subsets were significantly higher in the IPTE group than in the non-IPTE group, so they have a good predictive value for IPTE in patients with AMI.

Evaluation of a diagnostic flow chart applying medical thoracoscopy, adenosine deaminase and T-SPOT.TB in diagnosis of tuberculous pleural effusion.

PubMed

He, Y; Zhang, W; Huang, T; Wang, X; Wang, M

2015-10-01

To evaluate a diagnostic flow chart applying medical thoracoscoy (MT), adenosine deaminase (ADA) and T-SPOT.TB in diagnosis of tuberculous pleural effusion (TPE) at a high TB burden country. 136 patients with pleural effusion (PE) were enrolled and divided into TPE and Non-TPE group. MT (histology), PE ADA and T-SPOT.TB were conducted on all patients. ROC analysis was performed for the best cut-off value of PE ADA in detection of TPE. The diagnostic flow chart applying MT, ADA and T-SPOT.TB was evaluated for improving the limitations of each diagnostic method. ROC analysis showed that the best cut-off value of PE ADA was 30U/L. The sensitivity and specificity of these tests were calculated respectively to be: 71.4% (58.5%-81.6%) and 100% (95.4-100.0%) for MT, 92.9% (83.0-97.2%) and 68.8% (57.9-77.9%) for T-SPOT.TB, and 80.0% (69.6-88.1%) and 92.9% (82.7-98.0%) for PE ADA. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value and negative predictive value of the diagnostic flow chart were 96.4% (87.9-99.0%), 96.3% (89.6-98.7%), 25.714, 0.037, 97.4 and 94.9, respectively. The diagnostic flow chart applying MT, ADA and T-SPOT.TB is an accurate and rapid diagnostic method in detection of TPE.

New scoring system combining the FIB-4 index and cytokeratin-18 fragments for predicting steatohepatitis and liver fibrosis in patients with nonalcoholic fatty liver disease.

PubMed

Tada, Toshifumi; Kumada, Takashi; Toyoda, Hidenori; Saibara, Toshiji; Ono, Masafumi; Kage, Masayoshi

To establish a new scoring system as a noninvasive tool for predicting steatohepatitis and liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). A total of 170 patients histologically diagnosed with nonalcoholic steatohepatitis (NASH) (n = 130) or nonalcoholic fatty liver (NAFL) (n = 40) were enrolled. We analyzed receiver operating characteristic (ROC) curves and performed multivariate analysis to predict steatohepatitis and liver fibrosis. Multivariate analysis showed that cytokeratin-18 fragment (CK18-F) levels (≥278 U/L) (odds ratio [OR], 4.46; 95% confidence interval [CI], 1.42-14.00; p = 0.010) and the FIB-4 index (≥1.46) (OR, 4.54; 95% CI, 1.93-29.50; p = 0.004) were independently associated with prediction of NASH. We then established a new scoring system (named the FIC-22 score) for predicting NASH using CK18-F levels and FIB-4 index. The areas under the ROC curve (AUROCs) of the FIC-22 score and NAFIC score were 0.82 (95% CI, 0.75-0.89) and 0.71 (95% CI, 0.62-0.78) (p = 0.044). Additionally, the AUROC of the FIC-22 score for predicting the presence of fibrosis (F ≥ 1) was 0.78 (95% CI, 0.70-0.85). In patients with NAFLD, the FIC-22 score had high predictive accuracy not only for steatohepatitis but also for the presence of liver fibrosis.

CT volumetric measurement of colorectal cancer helps predict tumor staging and prognosis

PubMed Central

Park, Jin Young; Lee, Sang Min; Lee, Jeong Sub; Han, Joon Koo

2017-01-01

Purpose To evaluate feasibility of CT colonography (CTC) volumetry of colorectal cancer (CRC) and its correlation with disease stage and patients’ survival. Materials and methods CTC volumetry was performed for 126 patients who underwent preoperative CTC. Reproducibility of tumor volume (Tvol) between two readers was assessed. One-way ANOVA and ROC analysis evaluated correlation between Tvol and pTNM staging. ROC analysis compared diagnostic performance to predict pTNM staging between Tvol and radiologist. Kaplan-Meier test compared overall survival. Results Reproducibility among readers was excellent (interclass correlation = 0.9829). Mean Tvol showed an incremental trend with T stage and Tvol of pT4b stage was significantly larger than other stages (P<0.0001). Az value (0.780) of Tvol to predict pT4b stage was significantly larger than that (0.591) of radiologist (P = 0.004). However, Tvol was not significantly different according to pN stage. Az values (0.723~0.857) of Tvol to predict M1 or M1b were comparable to those (0.772~0.690) of radiologist (P>0.05). Smaller tumor burden (≤12.85cm3), ≤T3, N0, M0 stages, and curative surgery were significantly associated with patients’ longer survival (P<0.05). Conclusion CT volumetry has a limited value to predict N stage; however, it may outperform the radiologist’s performance when predicting pT4b and M1b stage and can be a useful prognostic marker. PMID:28570580

ROC-king onwards: intraepithelial lymphocyte counts, distribution & role in coeliac disease mucosal interpretation.

PubMed

Rostami, Kamran; Marsh, Michael N; Johnson, Matt W; Mohaghegh, Hamid; Heal, Calvin; Holmes, Geoffrey; Ensari, Arzu; Aldulaimi, David; Bancel, Brigitte; Bassotti, Gabrio; Bateman, Adrian; Becheanu, Gabriel; Bozzola, Anna; Carroccio, Antonio; Catassi, Carlo; Ciacci, Carolina; Ciobanu, Alexandra; Danciu, Mihai; Derakhshan, Mohammad H; Elli, Luca; Ferrero, Stefano; Fiorentino, Michelangelo; Fiorino, Marilena; Ganji, Azita; Ghaffarzadehgan, Kamran; Going, James J; Ishaq, Sauid; Mandolesi, Alessandra; Mathews, Sherly; Maxim, Roxana; Mulder, Chris J; Neefjes-Borst, Andra; Robert, Marie; Russo, Ilaria; Rostami-Nejad, Mohammad; Sidoni, Angelo; Sotoudeh, Masoud; Villanacci, Vincenzo; Volta, Umberto; Zali, Mohammad R; Srivastava, Amitabh

2017-12-01

Counting intraepithelial lymphocytes (IEL) is central to the histological diagnosis of coeliac disease (CD), but no definitive 'normal' IEL range has ever been published. In this multicentre study, receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off between normal and CD (Marsh III lesion) duodenal mucosa, based on IEL counts on >400 mucosal biopsy specimens. The study was designed at the International Meeting on Digestive Pathology, Bucharest 2015. Investigators from 19 centres, eight countries of three continents, recruited 198 patients with Marsh III histology and 203 controls and used one agreed protocol to count IEL/100 enterocytes in well-oriented duodenal biopsies. Demographic and serological data were also collected. The mean ages of CD and control groups were 45.5 (neonate to 82) and 38.3 (2-88) years. Mean IEL count was 54±18/100 enterocytes in CD and 13±8 in normal controls (p=0.0001). ROC analysis indicated an optimal cut-off point of 25 IEL/100 enterocytes, with 99% sensitivity, 92% specificity and 99.5% area under the curve. Other cut-offs between 20 and 40 IEL were less discriminatory. Additionally, there was a sufficiently high number of biopsies to explore IEL counts across the subclassification of the Marsh III lesion. Our ROC curve analyses demonstrate that for Marsh III lesions, a cut-off of 25 IEL/100 enterocytes optimises discrimination between normal control and CD biopsies. No differences in IEL counts were found between Marsh III a, b and c lesions. There was an indication of a continuously graded dose-response by IEL to environmental (gluten) antigenic influence. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

PubMed

Jin, Bo; Krishnan, Balu; Adler, Sophie; Wagstyl, Konrad; Hu, Wenhan; Jones, Stephen; Najm, Imad; Alexopoulos, Andreas; Zhang, Kai; Zhang, Jianguo; Ding, Meiping; Wang, Shuang; Wang, Zhong Irene

2018-05-01

Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers. Sixty-one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1-volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k-fold cross-validation. The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance. Automated surface-based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Rationale, development and implementation of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest.

PubMed

Morrison, Laurie J; Nichol, Graham; Rea, Thomas D; Christenson, Jim; Callaway, Clifton W; Stephens, Shannon; Pirrallo, Ronald G; Atkins, Dianne L; Davis, Daniel P; Idris, Ahamed H; Newgard, Craig

2008-08-01

To describe the development, design and consequent scientific implications of the Resuscitation Outcomes Consortium (ROC) population-based registry; ROC Epistry-Cardiac Arrest. The ROC Epistry--Cardiac Arrest is designed as a prospective population-based registry of all Emergency Medical Services (EMSs)-attended 9-1-1 calls for patients with out-of-hospital cardiac arrest occurring in the geographical area described by the eight US and three Canadian regions. The dataset was derived by an North American interdisciplinary steering committee. Enrolled cases include individuals of all ages who experience cardiac arrest outside the hospital, with evaluation by organized EMS personnel and: (a) attempts at external defibrillation (by lay responders or emergency personnel), or chest compressions by organized EMS personnel; (b) were pulseless but did not receive attempts to defibrillate or CPR by EMS personnel. Selected data items are categorized as mandatory or optional and undergo revisions approximately every 12 months. Where possible all definitions are referenced to existing literature. Where a common definition did not exist one was developed. Optional items include standardized CPR process data elements. It is anticipated the ROC Epistry--Cardiac Arrest will enroll between approximately 9000 and 13,500 treated all rhythm arrests and 4000 and 5000 ventricular fibrillation arrests annually and approximately 8000 EMS-attended but untreated arrests. We describe the rationale, development, design and future implications of the ROC Epistry--Cardiac Arrest. This paper will serve as the reference for subsequent ROC manuscripts and for the common data elements captured in both ROC Epistry--Cardiac Arrest and the ROC trials.

Structural vascular disease in Africans: Performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: The SABPA study.

PubMed

Botha, J; de Ridder, J H; Potgieter, J C; Steyn, H S; Malan, L

2013-10-01

A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fasting bloods (glucose, high density lipoprotein (HDL) and triglycerides) were obtained in a well-controlled setting. The RPWC male model (LR ROC AUC: 0.71, NN ROC AUC: 0.71) was practically equal to the JSC model (LR ROC AUC: 0.71, NN ROC AUC: 0.69) to predict structural vascular -disease. Similarly, the female RPWC model (LR ROC AUC: 0.84, NN ROC AUC: 0.82) and JSC model (LR ROC AUC: 0.82, NN ROC AUC: 0.81) equally predicted CIMT as surrogate marker for structural vascular disease. Odds ratios supported validity where prediction of CIMT revealed -clinical -significance, well over 1, for both the JSC and RPWC models in African males and females (OR 3.75-13.98). In conclusion, the proposed RPWC model was substantially validated utilizing linear and non-linear analyses. We therefore propose ethnic-specific WC cut points (African males, ≥90 cm; -females, ≥98 cm) to predict a surrogate marker for structural vascular disease. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

Expression and Clinical Significance of Serum Dipeptidyl Peptidase IV Chronic Obstructive Pulmonary Disease.

PubMed

Chang, Xiao-Yue; Yang, Yong; Jia, Xiao-Qing; Wang, Yuan; Peng, Li-Na; Ai, Xiao-Hong; Jiang, Cui-Ying; Guo, Jian-Hua; Wu, Ting-Ting

2016-03-01

The purpose of this study is to explore the correlation between serum dipeptidyl peptidase IV (DPPIV) and chronic obstructive pulmonary disease (COPD) at its various disease states, analyze its applications in the prediction and diagnosis of COPD and test the possibility of DPPIV as the serologic marker for COPD screening. Samples from 74 patients (42 cases with acute exacerbation of COPD or acute exacerbation COPD (AECOPD) and 32 cases with stable COPD) and 29 control subjects were collected in this study. Those patients with AECOPD were classified as COPD remission group if their clinical symptoms relieved after nonintravenous or oral hormone therapy for 7 ± 3 days. DPPIV concentration was measured by enzyme-linked immunosorbent assay, and the difference in serum concentration of DPPIV was compared among different groups. The correlation between DPPIV concentration and age, sex or smoking history was analyzed, and the diagnostic value of DPPIV was evaluated by receiver-operating characteristic (ROC) curve analysis. Serum DPPIV concentration was significantly lower in all COPD groups as compared with that in healthy control group (P < 0.001). Serum DPPIV concentration in AECOPD group was increased after treatment (P < 0.001). There was no significant correlation between DPPIV concentration and age, sex or smoking history (P > 0.05). ROC analysis indicated that serum DPPIV concentration in all groups showed a good diagnostic accuracy, especially in stable COPD and AECOPD groups. The area under the ROC curve values were 0.901 and 0.906, respectively, with a high specificity of 0.931 for both groups and a high sensitivity of 0.75 for stable COPD and 0.875 for AECOPD. Serum DPPIV concentration in patients with COPD is decreased significantly, and there is no correlation between serum DPPIV concentration and sex or age. Serum DPPIV not only is an independent predictive factor, but also of high value as a good serologic marker for the diagnosis of COPD. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Responsiveness of two Persian-versions of shoulder outcome measures following physiotherapy intervention in patients with shoulder disorders.

PubMed

Negahban, Hossein; Behtash, Zeinab; Sohani, Soheil Mansour; Salehi, Reza

2015-01-01

To identify the ability of the Persian-version of the Shoulder Pain and Disability Index (SPADI) and the Disabilities of the Arm, Shoulder, and Hand (DASH) to detect changes in shoulder function following physiotherapy intervention (i.e. responsiveness) and to determine the change score that indicates a meaningful change in functional ability of the patient (i.e. Minimally Clinically Important Difference (MCID)). A convenient sample of 200 Persian-speaking patients with shoulder disorders completed the SPADI and the DASH at baseline and then again 4 weeks after physiotherapy intervention. Furthermore, patients were asked to rate their global rating of shoulder function at follow-up. The responsiveness was evaluated using two methods: the receiver operating characteristics (ROC) method and the correlation analysis. Two useful statistics extracted from the ROC method are the area under curve (AUC) and the optimal cutoff point called as MCID. Both the SPADI and the DASH showed the AUC of greater than 0.70 (AUC ranges = 0.77-0.82). The best cutoff points (or change scores) for the SPADI-total, SPADI-pain, SPADI-disability and the DASH were 14.88, 26.36, 23.86, and 25.41, respectively. Additionally, moderate to good correlations (Gamma = -0.51 to -0.58) were found between the changes in SPADI/DASH and changes in global rating scale. The Persian SPADI and DASH have adequate responsiveness to clinical changes in patients with shoulder disorders. Moreover, the MCIDs obtained in this study will help the clinicians and researchers to determine if a Persian-speaking patient with shoulder disorder has experienced a true change following a physiotherapy intervention. Implications for Rehabilitation Responsiveness was evaluated using two methods; the receiver operating characteristics (ROC) method and the correlation analysis. The Persian SPADI and DASH can be used as two responsive instruments in both clinical practice and research settings. The MCIDs of 14.88 and 25.41 points obtained for the SPADI-total and DASH indicated that the change scores of at least 14.88 points on the SPADI-total and 25.41 points on the DASH is necessary to certain that a true change has occurred following a physiotherapy intervention.

Quantitative Differentiation of LV Myocardium with and without Layer-Specific Fibrosis Using MRI in Hypertrophic Cardiomyopathy and Layer-Specific Strain TTE Analysis.

PubMed

Funabashi, Nobusada; Takaoka, Hiroyuki; Ozawa, Koya; Kamata, Tomoko; Uehara, Masae; Komuro, Issei; Kobayashi, Yoshio

2018-05-30

To achieve further risk stratification in hypertrophic cardiomyopathy (HCM) patients, we localized and quantified layer-specific LVM fibrosis on MRI in HCM patients using regional layer-specific peak longitudinal strain (PLS) and peak circumferential strain (PCS) in LV myocardium (LVM) on speckle tracking transthoracic echocardiography (TTE). A total of 18 HCM patients (14 males; 58 ± 17 years) underwent 1.5T-MRI and TTE. PLS and PCS in each layer of the LVM (endocardium, epicardium, and whole-layer myocardium) were calculated for 17 AHA-defined lesions. MRI assessment showed that fibrosis was classified as endocardial, epicardial, or whole-layer (= either or both of these). Regional PLS was smaller in fibrotic endocardial lesions than in non-fibrotic endocardial lesions (P = 0.004). To detect LV endocardial lesions with fibrosis, ROC curves of regional PLS revealed an area under the curve (AUC) of 0.609 and a best cut-off point of 13.5%, with sensitivity of 65.3% and specificity of 54.3%. Regional PLS was also smaller in fibrotic epicardial lesions than in non-fibrotic epicardial lesions (P < 0.001). To detect LV epicardial lesions with fibrosis, ROC curves of PLS revealed an AUC of 0.684 and a best cut-off point of 9.5%, with sensitivity of 73.5% and specificity of 55.5%. Using whole-layer myocardium analysis, PLS was smaller in fibrotic lesions than in non-fibrotic lesions (P < 0.001). To detect whole-layer LV lesions with fibrosis, ROC curves of regional PLS revealed an AUC of 0.674 and a best cut-off point of 12.5%, with sensitivity of 79.0% and specificity of 50.7%. There were no significant differences in PCS of LV myocardium (endocardium, epicardium, and whole-layer) between fibrotic and non-fibrotic lesions. Quantitative regional PLS but not PCS in LV endocardium, epicardium, and whole-layer myocardium provides useful non-invasive information for layer-specific localization of fibrosis in HCM patients.

Differentiation of Low- and High-Grade Pediatric Brain Tumors with High b-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

PubMed Central

Sui, Yi; Wang, He; Liu, Guanzhong; Damen, Frederick W.; Wanamaker, Christian; Li, Yuhua

2015-01-01

Purpose To demonstrate that a new set of parameters (D, β, and μ) from a fractional order calculus (FROC) diffusion model can be used to improve the accuracy of MR imaging for differentiating among low- and high-grade pediatric brain tumors. Materials and Methods The institutional review board of the performing hospital approved this study, and written informed consent was obtained from the legal guardians of pediatric patients. Multi-b-value diffusion-weighted magnetic resonance (MR) imaging was performed in 67 pediatric patients with brain tumors. Diffusion coefficient D, fractional order parameter β (which correlates with tissue heterogeneity), and a microstructural quantity μ were calculated by fitting the multi-b-value diffusion-weighted images to an FROC model. D, β, and μ values were measured in solid tumor regions, as well as in normal-appearing gray matter as a control. These values were compared between the low- and high-grade tumor groups by using the Mann-Whitney U test. The performance of FROC parameters for differentiating among patient groups was evaluated with receiver operating characteristic (ROC) analysis. Results None of the FROC parameters exhibited significant differences in normal-appearing gray matter (P ≥ .24), but all showed a significant difference (P < .002) between low- (D, 1.53 μm2/msec ± 0.47; β, 0.87 ± 0.06; μ, 8.67 μm ± 0.95) and high-grade (D, 0.86 μm2/msec ± 0.23; β, 0.73 ± 0.06; μ, 7.8 μm ± 0.70) brain tumor groups. The combination of D and β produced the largest area under the ROC curve (0.962) in the ROC analysis compared with individual parameters (β, 0.943; D,0.910; and μ, 0.763), indicating an improved performance for tumor differentiation. Conclusion The FROC parameters can be used to differentiate between low- and high-grade pediatric brain tumor groups. The combination of FROC parameters or individual parameters may serve as in vivo, noninvasive, and quantitative imaging markers for classifying pediatric brain tumors. © RSNA, 2015 PMID:26035586

Waist circumference cut-off points for identification of abdominal obesity among the tunisian adult population.

PubMed

Bouguerra, R; Alberti, H; Smida, H; Salem, L B; Rayana, C B; El Atti, J; Achour, A; Gaigi, S; Slama, C B; Zouari, B; Alberti, K G M M

2007-11-01

Waist circumference (WC) is a convenient measure of abdominal adipose tissue. It itself is a cardiovascular disease (CVD) and diabetes-risk factor and is strongly linked to other CVD risk factors. There are, however, ethnic differences in the relationship of WC to the other risk factors. The aim of this study was to determine the optimal cut-off points of WC and body mass index (BMI) at which cardiovascular risk factors can be identified with maximum sensitivity and specificity in a representative sample of the Tunisian adult population and to investigate any correlation between WC and BMI. We used a sample of the Tunisian National Nutrition Survey, a cross-sectional population-based survey, conducted in 1996 on a large nationally representative sample, which included 3435 adults (1244 men and 2191 women) of 20 years or older. WC, BMI, blood pressure and fasting blood measurements (plasma glucose, total cholesterol, triglycerides) were recorded. Receiver operating characteristic (ROC) curve analysis was used to identify optimal cut-off values of WC and BMI to identify with maximum sensitivity and specificity the detection of high blood pressure, hyperglycaemia, high blood cholesterol and hypertriglyceridaemia. ROC curve analysis suggested WC cut-off points of 85 cm in men and 85 cm in women for the optimum detection of high blood pressure, diabetes and dyslipidaemia. The optimum BMI cut-off points for predicting cardiovascular risk factors were 24 kg/m(2) in men and 27 kg/m(2) in women. The cut-off points recommended for the Caucasian population differ from those appropriate for the Tunisian population. The data show a continuous increase in odds ratios of each cardiovascular risk factor, with increasing level of WC and BMI. WC exceeding 85 cm in men and 79 cm in women correctly identified subjects with a BMI of >/=25 kg/m(2), sensitivity of >90% and specificity of >83%. Based on the ROC analysis, we suggest a WC of 85 cm for both men and women as appropriate cut-off points to identify central obesity for the purposes of CVD and diabetes-risk detection among Tunisians. WCs of 85 cm in men and 79 cm in women were the most sensitive and specific to identify most subjects with a BMI >/=25 kg/m(2).

Analysis of injury patterns and roles of care in US and Israel militaries during recent conflicts: Two are better than one.

PubMed

Antebi, Ben; Benov, Avi; Mann-Salinas, Elizabeth A; Le, Tuan D; Cancio, Leopoldo C; Wenke, Joseph C; Paran, Haim; Yitzhak, Avraham; Tarif, Bader; Gross, Kirby R; Dagan, David; Glassberg, Elon

2016-11-01

As new conflicts emerge and enemies evolve, military medical organizations worldwide must adopt the "lessons learned." In this study, we describe roles of care (ROCs) deployed and injuries sustained by both US and Israeli militaries during recent conflicts. The purpose of this collaborative work is facilitate exchange of medical data among allied forces in order to advance military medicine and facilitate strategic readiness for future military engagements that may involve less predictable situations of evacuation and care, such as prolonged field care. This retrospective study was conducted for the periods of 2003 to 2014 from data retrieved from the Department of Defense Trauma Registry and the Israel Defense Force (IDF) Trauma Registry. Comparative analyses included ROC capabilities, casualties who died of wounds, as well as mechanism of injury, anatomical wound distribution, and Injury Severity Score of US and IDF casualties during recent conflicts. Although concept of ROCs was similar among militaries, the IDF supports increased capabilities at point of injury and Role 1 including the presence of physicians, but with limited deployment of other ROCs; conversely, the US maintains fewer capabilities at Role 1 but utilized the entire spectrum of care, including extensive deployment of Roles 2/2+, during recent conflicts. Casualties from US forces (n = 19,005) and IDF (n = 2,637) exhibited significant differences in patterns of injury with higher proportions of casualties who died of wounds in the US forces (4%) compared with the IDF (0.6%). As these data suggest deployed ROCs and injury patterns of US and Israeli militaries were both conflict and system specific. We envision that identification of discordant factors and common medical strategies of the two militaries will enable strategic readiness for future conflicts as well as foster further collaboration among allied forces with the overarching universal goal of eliminating preventable death on the battlefield.

Prohibitin plays a critical role in Enterovirus 71 neuropathogenesis

PubMed Central

Too, Issac Horng Khit; Bonne, Isabelle; Tan, Eng Lee; Chu, Justin Jang Hann; Alonso, Sylvie

2018-01-01

A close relative of poliovirus, enterovirus 71 (EV71) is regarded as an important neurotropic virus of serious public health concern. EV71 causes Hand, Foot and Mouth Disease and has been associated with neurological complications in young children. Our limited understanding of the mechanisms involved in its neuropathogenesis has hampered the development of effective therapeutic options. Here, using a two-dimensional proteomics approach combined with mass spectrometry, we have identified a unique panel of host proteins that were differentially and dynamically modulated during EV71 infection of motor-neuron NSC-34 cells, which are found at the neuromuscular junctions where EV71 is believed to enter the central nervous system. Meta-analysis with previously published proteomics studies in neuroblastoma or muscle cell lines revealed minimal overlapping which suggests unique host-pathogen interactions in NSC-34 cells. Among the candidate proteins, we focused our attention on prohibitin (PHB), a protein that is involved in multiple cellular functions and the target of anti-cancer drug Rocaglamide (Roc-A). We demonstrated that cell surface-expressed PHB is involved in EV71 entry into neuronal cells specifically, while membrane-bound mitochondrial PHB associates with the virus replication complex and facilitates viral replication. Furthermore, Roc-A treatment of EV71-infected neuronal cells reduced significantly virus yields. However, the inhibitory effect of Roc-A on PHB in NSC-34 cells was not through blocking the CRAF/MEK/ERK pathway as previously reported. Instead, Roc-A treated NSC-34 cells had lower mitochondria-associated PHB and lower ATP levels that correlated with impaired mitochondria integrity. In vivo, EV71-infected mice treated with Roc-A survived longer than the vehicle-treated animals and had significantly lower virus loads in their spinal cord and brain, whereas virus titers in their limb muscles were comparable to controls. Together, this study uncovers PHB as the first host factor that is specifically involved in EV71 neuropathogenesis and a potential drug target to limit neurological complications. PMID:29324904

Binary ROCs in Perception and Recognition Memory Are Curved

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.

2012-01-01

In recognition memory, a classic finding is that receiver operating characteristics (ROCs) are curvilinear. This has been taken to support the fundamental assumptions of signal detection theory (SDT) over discrete-state models such as the double high-threshold model (2HTM), which predicts linear ROCs. Recently, however, Broder and Schutz (2009)…

Design and Optimization of the SPOT Primary Mirror Segment

NASA Technical Reports Server (NTRS)

Budinoff, Jason G.; Michaels, Gregory J.

2005-01-01

The 3m Spherical Primary Optical Telescope (SPOT) will utilize a single ring of 0.86111 point-to-point hexagonal mirror segments. The f2.85 spherical mirror blanks will be fabricated by the same replication process used for mass-produced commercial telescope mirrors. Diffraction-limited phasing will require segment-to-segment radius of curvature (ROC) variation of approx.1 micron. Low-cost, replicated segment ROC variations are estimated to be almost 1 mm, necessitating a method for segment ROC adjustment & matching. A mechanical architecture has been designed that allows segment ROC to be adjusted up to 400 microns while introducing a minimum figure error, allowing segment-to-segment ROC matching. A key feature of the architecture is the unique back profile of the mirror segments. The back profile of the mirror was developed with shape optimization in MSC.Nastran(TradeMark) using optical performance response equations written with SigFit. A candidate back profile was generated which minimized ROC-adjustment-induced surface error while meeting the constraints imposed by the fabrication method. Keywords: optimization, radius of curvature, Pyrex spherical mirror, Sigfit

Neuronal Effects of Sugammadex in combination with Rocuronium or Vecuronium

PubMed Central

Aldasoro, Martin; Jorda, Adrian; Aldasoro, Constanza; Marchio, Patricia; Guerra-Ojeda, Sol; Gimeno-Raga, Marc; Mauricio, Mª Dolores; Iradi, Antonio; Obrador, Elena; Vila, Jose Mª; Valles, Soraya L.

2017-01-01

Rocuronium (ROC) and Vecuronium (VEC) are the most currently used steroidal non-depolarizing neuromuscular blocking (MNB) agents. Sugammadex (SUG) rapidly reverses steroidal NMB agents after anaesthesia. The present study was conducted in order to evaluate neuronal effects of SUG alone and in combination with both ROC and VEC. Using MTT, CASP-3 activity and Western-blot we determined the toxicity of SUG, ROC or VEC in neurons in primary culture. SUG induces apoptosis/necrosis in neurons in primary culture and increases cytochrome C (CytC), apoptosis-inducing factor (AIF), Smac/Diablo and Caspase 3 (CASP-3) protein expression. Our results also demonstrated that both ROC and VEC prevent these SUG effects. The protective role of both ROC and VEC could be explained by the fact that SUG encapsulates NMB drugs. In BBB impaired conditions it would be desirable to control SUG doses to prevent the excess of free SUG in plasma that may induce neuronal damage. A balance between SUG, ROC or VEC would be necessary to prevent the risk of cell damage. PMID:28367082

Diagnostic value of KLK6 as an ovarian cancer biomarker: A meta-analysis.

PubMed

Yang, Fan; Hu, Zhi-DE; Chen, Yingjian; Hu, Cheng-Jin

2016-06-01

Kallikrein-related peptidase 6 (KLK6) is a new potential serum biomarker of ovarian cancer. The aim of the present study was to assess the diagnostic value of KLK6 systematically for ovarian cancer. All the selected studies regarding the changes of KLK6 in ovarian cancer were published prior to April 2015. Five studies involving 485 patients with ovarian cancer, 420 benign cysts and 245 healthy controls met the inclusion criteria. The value of sensitivity, specificity, positive-likelihood ratio (LR+), negative-likelihood ratio (LR-) and area under the receiver operating characteristic curve (ROC) were obtained. All these indices were used to evaluate the diagnostic value of KLK6 for ovarian cancer. The values of sensitivity, specificity, LR+ and LR- (95% confidence interval) of KLK6 were 0.50 (0.47-0.54), 0.91 (0.89-0.93), 7.20 (3.34-15.52) and 0.51 (0.43-0.62), respectively. The area under the summary ROC of KLK6 was 0.86. The index of Q* was 0.79. In conclusion, KLK6 showed high specificity for the diagnosis of ovarian cancer. It can improve the diagnostic accuracy of cancer antigen 125 (CA125). A combined panel of CA125 and KL K6 shows a high diagnostic efficiency for advanced ovarian cancer. Owing to the small number of studies and lack of samples, additional studies meeting the inclusion criteria are required to further analyze the diagnostic value of KLK6 for ovarian cancer.

Search for Partner Proteins of A. thaliana Immunophilins Involved in the Control of Plant Immunity.

PubMed

Abdeeva, Inna A; Pogorelko, Gennady V; Maloshenok, Liliya G; Mokrykova, Maria V; Fursova, Oksana V; Bruskin, Sergey A

2018-04-19

The involvement of plant immunophilins in multiple essential processes such as development, various ways of adapting to biotic and abiotic stresses, and photosynthesis has already been established. Previously, research has demonstrated the involvement of three immunophilin genes ( AtCYP19-1/ROC3 , AtFKBP65/ROF2 , and AtCYP57 ) in the control of plant response to invasion by various pathogens. Current research attempts to identify host target proteins for each of the selected immunophilins. As a result, candidate interactors have been determined and confirmed using a yeast 2-hybrid (Y2H) system for protein⁻protein interaction assays. The generation of mutant isoforms of ROC3 and AtCYP57 harboring substituted amino acids in the in silico-predicted active sites became essential to achieving significant binding to its target partners. This data shows that ROF2 targets calcium-dependent lipid-binding domain-containing protein (At1g70790; AT1) and putative protein phosphatase (At2g30020; АТ2), whereas ROC3 interacts with GTP-binding protein (At1g30580; ENGD-1) and RmlC-like cupin (At5g39120). The immunophilin AtCYP57 binds to putative pyruvate decarboxylase-1 (Pdc1) and clathrin adaptor complex-related protein (At5g05010). Identified interactors confirm our previous findings that immunophilins ROC3 , ROF2 , and AtCYP57 are directly involved with stress response control. Further, these findings extend our understanding of the molecular functional pathways of these immunophilins.

Protein Quality Control Under Oxidative Stress Conditions

PubMed Central

Dahl, Jan-Ulrik; Gray, Michael J.; Jakob, Ursula

2015-01-01

Accumulation of reactive oxygen and chlorine species (RO/CS) is generally regarded to be a toxic and highly undesirable event, which serves as contributing factor in aging and many age-related diseases. However, it is also put to excellent use during host defense, when high levels of RO/CS are produced to kill invading microorganisms and regulate bacterial colonization. Biochemical and cell biological studies of how bacteria and other microorganisms deal with RO/CS have now provided important new insights into the physiological consequences of oxidative stress, the major targets that need protection, and the cellular strategies employed by organisms to mitigate the damage. This review examines the redox-regulated mechanisms by which cells maintain a functional proteome during oxidative stress. We will discuss the well-characterized redox-regulated chaperone Hsp33, and review recent discoveries demonstrating that oxidative stress-specific activation of chaperone function is a much more widespread phenomenon than previously anticipated. New members of this group include the cytosolic ATPase Get3 in yeast, the E. coli protein RidA, and the mammalian protein α2-macroglobin. We will conclude our review with recent evidence showing that inorganic polyphosphate (polyP), whose accumulation significantly increases bacterial oxidative stress resistance, works by a protein-like chaperone mechanism. Understanding the relationship between oxidative and proteotoxic stresses will improve our understanding of both host-microbe interactions and of how mammalian cells combat the damaging side effects of uncontrolled RO/CS production, a hallmark of inflammation. PMID:25698115

Low levels of serum serotonin and amino acids identified in migraine patients.

PubMed

Ren, Caixia; Liu, Jia; Zhou, Juntuo; Liang, Hui; Wang, Yayun; Sun, Yinping; Ma, Bin; Yin, Yuxin

2018-02-05

Migraine is a highly disabling primary headache associated with a high socioeconomic burden and a generally high prevalence. The clinical management of migraine remains a challenge. This study was undertaken to identify potential serum biomarkers of migraine. Using Liquid Chromatography coupled to Mass Spectrometry (LC-MS), the metabolomic profile of migraine was compared with healthy individuals. Principal component analysis (PCA) and Orthogonal partial least squares-discriminant analysis (orthoPLS-DA) showed the metabolomic profile of migraine is distinguishable from controls. Volcano plot analysis identified 10 serum metabolites significantly decreased during migraine. One of these was serotonin, and the other 9 were amino acids. Pathway analysis and enrichment analysis showed tryptophan metabolism (serotonin metabolism), arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently altered pathways in migraine. ROC curve analysis indicated Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine are potential sensitive and specific biomarkers for migraine. Our results show Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine may be as specific or more specific for migraine than serotonin which is the traditional biomarker of migraine. We propose that therapeutic manipulation of these metabolites or metabolic pathways may be helpful in the prevention and treatment of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R.

PubMed

Grau, Jan; Grosse, Ivo; Keilwagen, Jens

2015-08-01

Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation between the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves. © The Author 2015. Published by Oxford University Press.

Reach Out Central: a serious game designed to engage young men to improve mental health and wellbeing.

PubMed

Burns, Jane M; Webb, Marianne; Durkin, Lauren A; Hickie, Ian B

2010-06-07

Reach Out Central (ROC) is a serious game drawing on the principles of cognitive behaviour theory that has been designed to improve the mental health and wellbeing of young people, particularly men. ROC was developed over a 3-year period from 2003 to 2006, in consultation with young people aged 16-25 years who use the Reach Out mental health website http://www.reachout.com). ROC was launched online in September 2007. A traditional and viral awareness campaign was designed to engage young men, particularly "gamers". In the first month after launch, ROC had 76 045 unique website visits, with 10 542 new members (52% male) joining Reach Out. An independent online evaluation involving 266 young people aged 18-25 years was conducted between August 2007 and February 2008 to examine psychological wellbeing, stigma and help seeking in ROC players. Overall results indicated that ROC was successful in attracting, engaging and educating young people. Young women reported reduced psychological distress and improved life satisfaction, problem solving and help seeking; however, no significant changes were observed for young men. Although ROC was successful in attracting young men, demonstrating that the concept resonates with them, the service failed to keep them engaged. Further research is needed to explore how (or what changes need to be made) to sustain young men's engagement in the game.

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2011-01-01

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

Least squares regression methods for clustered ROC data with discrete covariates.

PubMed

Tang, Liansheng Larry; Zhang, Wei; Li, Qizhai; Ye, Xuan; Chan, Leighton

2016-07-01

The receiver operating characteristic (ROC) curve is a popular tool to evaluate and compare the accuracy of diagnostic tests to distinguish the diseased group from the nondiseased group when test results from tests are continuous or ordinal. A complicated data setting occurs when multiple tests are measured on abnormal and normal locations from the same subject and the measurements are clustered within the subject. Although least squares regression methods can be used for the estimation of ROC curve from correlated data, how to develop the least squares methods to estimate the ROC curve from the clustered data has not been studied. Also, the statistical properties of the least squares methods under the clustering setting are unknown. In this article, we develop the least squares ROC methods to allow the baseline and link functions to differ, and more importantly, to accommodate clustered data with discrete covariates. The methods can generate smooth ROC curves that satisfy the inherent continuous property of the true underlying curve. The least squares methods are shown to be more efficient than the existing nonparametric ROC methods under appropriate model assumptions in simulation studies. We apply the methods to a real example in the detection of glaucomatous deterioration. We also derive the asymptotic properties of the proposed methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study.

PubMed

Wu, Li; Lin, Huandong; Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen; Gao, Xin

2017-01-01

Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45-54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study

PubMed Central

Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen

2017-01-01

Background and aims Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. Methods In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. Results The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45–54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. Conclusions The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count. PMID:28886160

Sensitivity and specificity of the Distress Thermometer in screening for distress in long-term nasopharyngeal cancer survivors.

PubMed

Hong, J S; Tian, J

2013-12-01

The Distress Thermometer (dt) is a screening tool recommended to quickly identify cancer patients with distress. Our study aimed to examine the sensitivity and specificity of the dt in detecting psychological distress in long-term Chinese nasopharyngeal cancer (npc) survivors. Data for the 442 participating npc survivors were collected through a self-administered questionnaire based on the dt and the Hospital Anxiety and Depression Scale (hads). The hads was used to define cases of psychological distress. Positive and negative groups were defined based on 4 hads criteria (Anxiety, Depression, Anxiety or Depression, and overall score). Receiver operating characteristic (roc) curves were used to examine the ability of all possible cut-off values of the dt to detect positive and negative cases. For each roc curve, the area under the curve (auc) was used as an indicator of the overall accuracy of the dt to identify positive cases of distress. The positive auc values [with 95% confidence intervals (ci)] for the 4 hads criteria were 0.715 (95% ci: 0.667 to 0.764), 0.714 (95% ci: 0.661 to 0.768), 0.724 (95% ci: 0.677 to 0.771), and 0.724 (95% ci: 0.664 to 0.775) respectively. At a cut-off score of 4, the sensitivity of the dt to the four hads criteria was, respectively, 0.366 (95% ci: 0.296 to 0.436), 0.448 (95% ci: 0.364 to 0.532), 0.362 (95% ci: 0.299 to 0.425), and 0.421 (95% ci: 0.339 to 0.502), and the specificity of the dt to the 4 hads criteria was, respectively, 0.860 (95% ci: 0.818 to 0.902), 0.860 (95% ci: 0.821 to 0.899), 0.854 (95% ci: 0.814 to 0.894), and 0.854 (95% ci: 0.814 to 0.894). At a cut-off score of 5, the corresponding sensitivities were lower than those at the cut-off score of 4. All potential cut-off scores showed poor sensitivity (<0.90). The roc analysis showed poor discrimination. No potential dt cut-off score had an acceptable sensitivity. The dt showed poor sensitivity in npc survivors. Thus, the dt might not be a valid scale for psychological distress screening in long-term Chinese npc survivors.

Sensitivity and specificity of the Distress Thermometer in screening for distress in long-term nasopharyngeal cancer survivors

PubMed Central

Hong, J.S.; Tian, J.

2013-01-01

Background The Distress Thermometer (dt) is a screening tool recommended to quickly identify cancer patients with distress. Our study aimed to examine the sensitivity and specificity of the dt in detecting psychological distress in long-term Chinese nasopharyngeal cancer (npc) survivors. Methods Data for the 442 participating npc survivors were collected through a self-administered questionnaire based on the dt and the Hospital Anxiety and Depression Scale (hads). The hads was used to define cases of psychological distress. Positive and negative groups were defined based on 4 hads criteria (Anxiety, Depression, Anxiety or Depression, and overall score). Receiver operating characteristic (roc) curves were used to examine the ability of all possible cut-off values of the dt to detect positive and negative cases. For each roc curve, the area under the curve (auc) was used as an indicator of the overall accuracy of the dt to identify positive cases of distress. Results The positive auc values [with 95% confidence intervals (ci)] for the 4 hads criteria were 0.715 (95% ci: 0.667 to 0.764), 0.714 (95% ci: 0.661 to 0.768), 0.724 (95% ci: 0.677 to 0.771), and 0.724 (95% ci: 0.664 to 0.775) respectively. At a cut-off score of 4, the sensitivity of the dt to the four hads criteria was, respectively, 0.366 (95% ci: 0.296 to 0.436), 0.448 (95% ci: 0.364 to 0.532), 0.362 (95% ci: 0.299 to 0.425), and 0.421 (95% ci: 0.339 to 0.502), and the specificity of the dt to the 4 hads criteria was, respectively, 0.860 (95% ci: 0.818 to 0.902), 0.860 (95% ci: 0.821 to 0.899), 0.854 (95% ci: 0.814 to 0.894), and 0.854 (95% ci: 0.814 to 0.894). At a cut-off score of 5, the corresponding sensitivities were lower than those at the cut-off score of 4. All potential cut-off scores showed poor sensitivity (<0.90). Conclusions The roc analysis showed poor discrimination. No potential dt cut-off score had an acceptable sensitivity. The dt showed poor sensitivity in npc survivors. Thus, the dt might not be a valid scale for psychological distress screening in long-term Chinese npc survivors. PMID:24311958

CSmetaPred: a consensus method for prediction of catalytic residues.

PubMed

Choudhary, Preeti; Kumar, Shailesh; Bachhawat, Anand Kumar; Pandit, Shashi Bhushan

2017-12-22

Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic residues at lower (better) ranked positions, which can facilitate and expedite their experimental characterization. The benchmarking studies showed that employing meta-approach in combining residue-level scores derived from well-known catalytic residue predictors can improve prediction accuracy as well as provide improved ranked positions of known catalytic residues. Hence, such predictions can assist experimentalist to prioritize residues for mutational studies in their efforts to characterize catalytic residues. Both meta-predictors are available as webserver at: http://14.139.227.206/csmetapred/ .

Acoustic cue weighting in the singleton vs geminate contrast in Lebanese Arabic: The case of fricative consonants.

PubMed

Al-Tamimi, Jalal; Khattab, Ghada

2015-07-01

This paper is the first reported investigation of the role of non-temporal acoustic cues in the singleton-geminate contrast in Lebanese Arabic, alongside the more frequently reported temporal cues. The aim is to explore the extent to which singleton and geminate consonants show qualitative differences in a language where phonological length is prominent and where moraic structure governs segment timing and syllable weight. Twenty speakers (ten male, ten female) were recorded producing trochaic disyllables with medial singleton and geminate fricatives preceded by phonologically short and long vowels. The following acoustic measures were applied on the medial fricative and surrounding vowels: absolute duration; intensity; fundamental frequency; spectral peak and shape, dynamic amplitude, and voicing patterns of medial fricatives; and vowel quality and voice quality correlates of surrounding vowels. Discriminant analysis and receiver operating characteristics (ROC) curves were used to assess each acoustic cue's contribution to the singleton-geminate contrast. Classification rates of 89% and ROC curves with an area under the curve rate of 96% confirmed the major role played by temporal cues, with non-temporal cues contributing to the contrast but to a much lesser extent. These results confirm that the underlying contrast for gemination in Arabic is temporal, but highlight [+tense] (fortis) as a secondary feature.

Assessment of Diagnostic and Prognostic Role of Copeptin in the Clinical Setting of Sepsis.

PubMed

Battista, Stefania; Audisio, Umberto; Galluzzo, Claudia; Maggiorotto, Matteo; Masoero, Monica; Forno, Daniela; Pizzolato, Elisa; Ulla, Marco; Lucchiari, Manuela; Vitale, Annarita; Moiraghi, Corrado; Lupia, Enrico; Settanni, Fabio; Mengozzi, Giulio

2016-01-01

The diagnostic and prognostic usefulness of copeptin were evaluated in septic patients, as compared to procalcitonin assessment. In this single centre and observational study 105 patients were enrolled: 24 with sepsis, 25 with severe sepsis, 15 with septic shock, and 41 controls, divided in two subgroups (15 patients with gastrointestinal bleeding and 26 with suspected SIRS secondary to trauma, acute coronary syndrome, and pulmonary embolism). Biomarkers were determined at the first medical evaluation and thereafter 24, 48, and 72 hours after admission. Definitive diagnosis and in-hospital survival rates at 30 days were obtained through analysis of medical records. At entry, copeptin proved to be able to distinguish cases from controls and also sepsis group from septic shock group, while procalcitonin could distinguish also severe sepsis from septic shock group. Areas under the ROC curve for copeptin and procalcitonin were 0.845 and 0.861, respectively. Noteworthy, patients with copeptin concentrations higher than the threshold value (23.2 pmol/L), calculated from the ROC curve, at admission presented higher 30-day mortality. No significant differences were found in copeptin temporal profile among different subgroups. Copeptin showed promising diagnostic and prognostic role in the management of sepsis, together with its possible role in monitoring the response to treatment.

Assessment of Diagnostic and Prognostic Role of Copeptin in the Clinical Setting of Sepsis

PubMed Central

Battista, Stefania; Audisio, Umberto; Galluzzo, Claudia; Maggiorotto, Matteo; Masoero, Monica; Forno, Daniela; Pizzolato, Elisa; Ulla, Marco; Lucchiari, Manuela; Vitale, Annarita; Moiraghi, Corrado; Lupia, Enrico; Settanni, Fabio; Mengozzi, Giulio

2016-01-01

The diagnostic and prognostic usefulness of copeptin were evaluated in septic patients, as compared to procalcitonin assessment. In this single centre and observational study 105 patients were enrolled: 24 with sepsis, 25 with severe sepsis, 15 with septic shock, and 41 controls, divided in two subgroups (15 patients with gastrointestinal bleeding and 26 with suspected SIRS secondary to trauma, acute coronary syndrome, and pulmonary embolism). Biomarkers were determined at the first medical evaluation and thereafter 24, 48, and 72 hours after admission. Definitive diagnosis and in-hospital survival rates at 30 days were obtained through analysis of medical records. At entry, copeptin proved to be able to distinguish cases from controls and also sepsis group from septic shock group, while procalcitonin could distinguish also severe sepsis from septic shock group. Areas under the ROC curve for copeptin and procalcitonin were 0.845 and 0.861, respectively. Noteworthy, patients with copeptin concentrations higher than the threshold value (23.2 pmol/L), calculated from the ROC curve, at admission presented higher 30-day mortality. No significant differences were found in copeptin temporal profile among different subgroups. Copeptin showed promising diagnostic and prognostic role in the management of sepsis, together with its possible role in monitoring the response to treatment. PMID:27366743

The balance between the serum levels of IL-6 and IL-10 cytokines discriminates mild and severe acute pneumonia.

PubMed

de Brito, Rita de Cássia Coelho Moraes; Lucena-Silva, Norma; Torres, Leuridan Cavalcante; Luna, Carlos Feitosa; Correia, Jaílson de Barros; da Silva, Giselia Alves Pontes

2016-12-01

To identify markers for earlier diagnosis of severe pneumonia, we assess the correlation between serum cytokine profile of children with different pneumonia severity. In 25 hospitalized children, 7 with mild pneumonia and 18 with severe pneumonia, the serum concentration of 11 cytokines in three sampling times were dosed. Statistical analysis included parametric and non-parametric tests, Pearson correlation and ROC curve for cut-off definition of cytokines. At admission, IL-6 serum levels were high in mild or severe pneumonia, and was associated to vomiting (P = 0.019) in both groups; and also to dyspnea (P = 0.012) and white blood cell count (P = 0.045) in patients with severe pneumonia. IL-10 levels were also high in patients with pneumonia and were associated to lymphocytosis (P = 0.025). The ROC curve of the IL-6:IL-10 serum levels ratio discriminated severe pneumonia cases at admission, and persistence of infection in the third day of antibiotic therapy, with positive predictive values of 93% and 89%, respectively. The balance between IL-6 and IL-10 serum levels showed to be a more discriminative marker for severity definition and evaluation of recovery in patients with pneumonia.

CSF lactate for accurate diagnosis of community-acquired bacterial meningitis.

PubMed

Giulieri, S; Chapuis-Taillard, C; Jaton, K; Cometta, A; Chuard, C; Hugli, O; Du Pasquier, R; Bille, J; Meylan, P; Manuel, O; Marchetti, O

2015-10-01

CSF lactate measurement is recommended when nosocomial meningitis is suspected, but its value in community-acquired bacterial meningitis is controversial. We evaluated the diagnostic performance of lactate and other CSF parameters in a prospective cohort of adult patients with acute meningitis. Diagnostic accuracy of lactate and other CSF parameters in patients with microbiologically documented episodes was assessed by receiver operating characteristic (ROC) curves. The cut-offs with the best diagnostic performance were determined. Forty-five of 61 patients (74%) had a documented bacterial (n = 18; S. pneumoniae, 11; N. meningitidis, 5; other, 2) or viral (n = 27 enterovirus, 21; VZV, 3; other, 3) etiology. CSF parameters were significantly different in bacterial vs. viral meningitis, respectively (p < 0.001 for all comparisons): white cell count (median 1333 vs. 143/mm(3)), proteins (median 4115 vs. 829 mg/l), CSF/blood glucose ratio (median 0.1 vs. 0.52), lactate (median 13 vs. 2.3 mmol/l). ROC curve analysis showed that CSF lactate had the highest accuracy for discriminating bacterial from viral meningitis, with a cutoff set at 3.5 mmol/l providing 100% sensitivity, specificity, PPV, NPV, and efficiency. CSF lactate had the best accuracy for discriminating bacterial from viral meningitis and should be included in the initial diagnostic workup of this condition.

Problematic smartphone use, nature connectedness, and anxiety.

PubMed

Richardson, Miles; Hussain, Zaheer; Griffiths, Mark D

2018-03-01

Background Smartphone use has increased greatly at a time when concerns about society's disconnection from nature have also markedly increased. Recent research has also indicated that smartphone use can be problematic for a small minority of individuals. Methods In this study, associations between problematic smartphone use (PSU), nature connectedness, and anxiety were investigated using a cross-sectional design (n = 244). Results Associations between PSU and both nature connectedness and anxiety were confirmed. Receiver operating characteristic (ROC) curves were used to identify threshold values on the Problematic Smartphone Use Scale (PSUS) at which strong associations with anxiety and nature connectedness occur. The area under the curve was calculated and positive likelihood ratios used as a diagnostic parameter to identify optimal cut-off for PSU. These provided good diagnostic ability for nature connectedness, but poor and non-significant results for anxiety. ROC analysis showed the optimal PSUS threshold for high nature connectedness to be 15.5 (sensitivity: 58.3%; specificity: 78.6%) in response to an LR+ of 2.88. Conclusions The results demonstrate the potential utility for the PSUS as a diagnostic tool, with a level of smartphone use that users may perceive as non-problematic being a significant cut-off in terms of achieving beneficial levels of nature connectedness. Implications of these findings are discussed.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

Can we predict pneumococcal bacteremia in patients with severe community-acquired pneumonia?

PubMed

Pereira, José Manuel; Teixeira-Pinto, Armando; Basílio, Carla; Sousa-Dias, Conceição; Mergulhão, Paulo; Paiva, José Artur

2013-12-01

This study aimed to evaluate the role of biomarkers as markers of pneumococcal bacteremia in severe community-acquired pneumonia (SCAP). A prospective, single-center, observational cohort study of 108 patients with SCAP admitted to the intensive care department of a university hospital in Portugal was conducted. Leucocytes, C-reactive protein (CRP), lactate, procalcitonin (PCT), d-dimer, brain natriuretic peptide (BNP), and cortisol were measured within 12 hours after the first antibiotic dose. Fifteen patients (14%) had bacteremic pneumococcal pneumonia (BPP). They had significantly higher levels of median CRP (301 [interquartile range, or IQR], 230-350] mg/L vs 201 [IQR, 103-299] mg/L; P = .023), PCT (40 [IQR, 25-102] ng/mL vs 8 [IQR, 2-26] ng/mL; P < .001), BNP (568 [IQR, 478-2841] pg/mL vs 407 [IQR, 175-989] pg/mL; P = .027), and lactate (5.5 [IQR, 4.5-9.8] mmol/L vs 3.1 [IQR, 1.9-6.2] mmol/L; P = .009) than did patients without BPP. The discriminatory power evaluated by the area under the receiver operating characteristic curve (aROC) for PCT (aROC, 0.79) was superior to lactate (aROC, 0.71), BNP (aROC, 0.67), and CRP (aROC, 0.70). At a cutoff point of 17 ng/mL, PCT showed a sensitivity of 87%, a specificity of 67%, a positive predictive value of 30% and a negative predictive value of 97%, as a marker of pneumococcal bacteremia. In this cohort, significantly higher PCT, BNP, lactate, and CRP levels were found in BPP, and PCT presented the best ability to identify pneumococcal bacteremia. A PCT serum level lower than 17 ng/mL could identify patients with SCAP unlikely to have pneumococcal bacteremia. Copyright © 2013 Elsevier Inc. All rights reserved.

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

The ROC program: accelerated restoration of competency in a jail setting.

PubMed

Rice, Kevin; Jennings, Jerry L

2014-01-01

In 29 months of operation, the restoration of competency (ROC) program provided treatment services to 192 incompetent to stand trial patients in a jail setting. The ROC restored competency for 55% of the patients in an average of 57 days compared to the state hospital average of 180 days. The average cost of treatment/restoration per admission was $15,568 compared to the state hospital average of $81,000. The ROC model accelerates needed treatment for mentally ill defendants, cuts demand for costly state hospital forensic beds, and assists jails in better managing inmates with severe psychiatric disorders--yielding major cost savings and improved care. In addition to preventing readmissions and negative behavioral episodes, the ROC improved the broader forensic system by eliminating the state hospital waiting list, accelerating access to psychiatric services, promoting local access for lawyers and family, and gaining stakeholder satisfaction.

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study.

PubMed

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas.

Predictive inference for best linear combination of biomarkers subject to limits of detection.

PubMed

Coolen-Maturi, Tahani

2017-08-15

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

OP007. PLGF in combination with other commonly utilised tests and other biomarkers for predicting need for delivery for pre-eclampsia within 14days in women presenting prior to 35weeks' gestation.

PubMed

Lucy, Chappell; Suzy, Duckworth; Melanie, Griffin; Paul, Seed; Christopher, Redman; Andrew, Shennan

2013-04-01

Current means of assessing women presenting with suspected pre-eclampsia using BP and proteinuria are of limited use in predicting need for imminent delivery. We undertook a prospective multicentre study to determine diagnostic accuracy of PlGF <5th centile (Triage assay) and other candidate biomarkers in women presenting with suspected pre-eclampsia at 20-35weeks' gestation, in determining need for delivery for pre-eclampsia within 14days. We calculated ROC curves for predictive potential and undertook principal factor analysis to determine additional predictive ability for biomarker combinations. In 287 women enrolled prior to 35weeks, ROC area (0.88, SE 0.03) for PlGF <5th centile for pre-eclampsia requiring delivery within 14days was greater than all other commonly utilised tests (systolic and diastolic BP, urate, ALT), either singly (range 0.58-0.68), or in combination (0.69) (p<0.001 for all comparisons), and was greater than that of all other biomarkers; addition of 2 other biomarker panels (either procalcitonin, nephrin and BNP; or cystatin and PAPP-A) increased ROC area to 0.90 but these biomarkers had limited predictive ability on their own. In women presenting prior to 35weeks' gestation with suspected pre-eclampsia, low PlGF has a greater ROC area than other commonly utilised tests. Additional biomarkers add only a small increment to the predictive value of a single PlGF measurement. Copyright © 2013. Published by Elsevier B.V.

1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI).

PubMed

Lussu, Milena; Camboni, Tania; Piras, Cristina; Serra, Corrado; Del Carratore, Francesco; Griffin, Julian; Atzori, Luigi; Manzin, Aldo

2017-09-21

Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1 H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R 2 Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.

Prediction of major complications after hepatectomy using liver stiffness values determined by magnetic resonance elastography.

PubMed

Sato, N; Kenjo, A; Kimura, T; Okada, R; Ishigame, T; Kofunato, Y; Shimura, T; Abe, K; Ohira, H; Marubashi, S

2018-04-23

Liver fibrosis is a risk factor for hepatectomy but cannot be determined accurately before hepatectomy because diagnostic procedures are too invasive. Magnetic resonance elastography (MRE) can determine liver stiffness (LS), a surrogate marker for assessing liver fibrosis, non-invasively. The aim of this study was to investigate whether the LS value determined by MRE is predictive of major complications after hepatectomy. This prospective study enrolled consecutive patients who underwent hepatic resection between April 2013 and August 2016. LS values were measured by imaging shear waves by MRE in the liver before hepatectomy. The primary endpoint was major complications, defined as Clavien-Dindo grade IIIa or above. Logistic regression analysis identified independent predictive factors, from which a logistic model to estimate the probability of major complications was constructed. A total of 96 patients were included in the study. Major complications were observed in 15 patients (16 per cent). Multivariable logistic analysis confirmed that higher LS value (P = 0·021) and serum albumin level (P = 0·009) were independent predictive factors for major complications after hepatectomy. Receiver operating characteristic (ROC) analysis showed that the best LS cut-off value was 4·3 kPa for detecting major complications, comparable to liver fibrosis grade F4, with a sensitivity of 80 per cent and specificity of 82 per cent. A logistic model using the LS value and serum albumin level to estimate the probability of major complications was constructed; the area under the ROC curve for predicting major complications was 0·84. The LS value determined by MRE in patients undergoing hepatectomy was an independent predictive factor for major complications. © 2018 BJS Society Ltd Published by John Wiley & Sons Ltd.

Comparison of bi-exponential and mono-exponential models of diffusion-weighted imaging for detecting active sacroiliitis in ankylosing spondylitis.

PubMed

Sun, Haitao; Liu, Kai; Liu, Hao; Ji, Zongfei; Yan, Yan; Jiang, Lindi; Zhou, Jianjun

2018-04-01

Background There has been a growing need for a sensitive and effective imaging method for the differentiation of the activity of ankylosing spondylitis (AS). Purpose To compare the performances of intravoxel incoherent motion (IVIM)-derived parameters and the apparent diffusion coefficient (ADC) for distinguishing AS-activity. Material and Methods One hundred patients with AS were divided into active (n = 51) and non-active groups (n = 49) and 21 healthy volunteers were included as control. The ADC, diffusion coefficient ( D), pseudodiffusion coefficient ( D*), and perfusion fraction ( f) were calculated for all groups. Kruskal-Wallis tests and receiver operator characteristic (ROC) curve analysis were performed for all parameters. Results There was good reproducibility of ADC /D and relatively poor reproducibility of D*/f. ADC, D, and f were significantly higher in the active group than in the non-active and control groups (all P < 0.0001, respectively). D* was slightly but significant lower in the active group than in the non-active and control group ( P = 0.0064, 0.0215). There was no significant difference in any parameter between the non-active group and the control group (all P > 0.050). In the ROC analysis, ADC had the largest AUC for distinguishing between the active group and the non-active group (0.988) and between the active and control groups (0.990). Multivariate logistic regression analysis models showed no diagnostic improvement. Conclusion ADC provided better diagnostic performance than IVIM-derived parameters in differentiating AS activity. Therefore, a straightforward and effective mono-exponential model of diffusion-weighted imaging may be sufficient for differentiating AS activity in the clinic.

Cutoff values for bacteria and leukocytes for urine sediment analyzer FUS200 in culture-positive urinary-tract infections.

PubMed

Kocer, Derya; Sarıguzel, Fatma M; Karakukcu, Cıgdem

2014-08-01

The microscopic analysis of urine is essential for the diagnosis of patients with urinary tract infections. Quantitative urine culture is the 'gold standard' method for definitive diagnosis of urinary-tract infections, but it is labor-intensive, time consuming, and does not provide the same-day results. The aim of this study was to evaluate the analytical and diagnostic performance of the FUS200 (Changchun Dirui Industry, China), a new urine sedimentation analyzer in comparison to urine culture as the reference method. We evaluated 1000 urine samples, submitted for culture and urine analysis with a preliminary diagnosis of urinary-tract infection. Cut-off values for the FUS200 were determined by comparing the results with urine cultures. The cut-off values by the receiver operating characteristic (ROC) curve technique, sensitivity, and specificity were calculated for bacteria and white blood cells (WBCs). Among the 1000 urine specimens submitted for culture, 637 cultures (63.7%) were negative, and 363 were (36.3%) positive. The best cut-off values obtained from ROC analysis were 16/μL for bacteriuria (sensitivity: 82.3%, specificity: 58%), and 34/μL for WBCs (sensitivity: 72.3%, specificity: 65.2%). The area under the curve (AUC) for the bacteria and WBCs count were 0.71 (95% CI: 0.67-0.74) and, 0.72 (95% CI: 0.69-0.76) respectively. The most important requirement of a rapid diagnostic screening test is sensitivity, and, in this perspective, an unsatisfactory sensitivity by using bacteria recognition and quantification performed by the FUS200 analyzer has been observed. After further technical improvements in particle recognition and laboratory personnel training, the FUS200 might show better results.

Eyewitness identification in simultaneous and sequential lineups: an investigation of position effects using receiver operating characteristics.

PubMed

Meisters, Julia; Diedenhofen, Birk; Musch, Jochen

2018-04-20

For decades, sequential lineups have been considered superior to simultaneous lineups in the context of eyewitness identification. However, most of the research leading to this conclusion was based on the analysis of diagnosticity ratios that do not control for the respondent's response criterion. Recent research based on the analysis of ROC curves has found either equal discriminability for sequential and simultaneous lineups, or higher discriminability for simultaneous lineups. Some evidence for potential position effects and for criterion shifts in sequential lineups has also been reported. Using ROC curve analysis, we investigated the effects of the suspect's position on discriminability and response criteria in both simultaneous and sequential lineups. We found that sequential lineups suffered from an unwanted position effect. Respondents employed a strict criterion for the earliest lineup positions, and shifted to a more liberal criterion for later positions. No position effects and no criterion shifts were observed in simultaneous lineups. This result suggests that sequential lineups are not superior to simultaneous lineups, and may give rise to unwanted position effects that have to be considered when conducting police lineups.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gai, E.

1975-01-01

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

The Belief Bias Effect Is Aptly Named: A Reply to Klauer and Kellen (2011)

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.; Heit, Evan

2011-01-01

In "Assessing the Belief Bias Effect With ROCs: It's a Response Bias Effect," Dube, Rotello, and Heit (2010) examined the form of receiver operating characteristic (ROC) curves for reasoning and the effects of belief bias on measurement indices that differ in whether they imply a curved or linear ROC function. We concluded that the ROC…

Reliable optical card-edge (ROC) connector for avionics applications

NASA Astrophysics Data System (ADS)

Darden, Bruce V.; Pimpinella, Richard J.; Seals, John D.

1994-10-01

The Reliable Optical Card-Edge (ROC) Connector is a blind-mate backplane unit designed to meet military stress requirements for avionics applications. Its modular design represents the first significant advance in connector optics since the biconic butt-coupled connector was introduced twenty years ago. This multimode connector utilizes beam optics, micro-machined silicon, and a floating, low mass subassembly design to maintain low coupling loss under high levels of shock and vibration. The ROC connector also incorporates retracting doors to protect the unmated termini from environmental contamination and abusive handling. Design features and test results for the ROC connector are presented in this paper.

Comparison of two correlated ROC curves at a given specificity or sensitivity level.

PubMed

Bantis, Leonidas E; Feng, Ziding

2016-10-30

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC -1 (t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare them with other known approaches, and present a real-data application involving prostate cancer screening. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

[Establishment of the prediction model for ischemic cardiovascular disease of elderly male population under current health care program].

PubMed

Chen, Jin-hong; Wu, Hai-yun; He, Kun-lun; He, Yao; Qin, Yin-he

2010-10-01

To establish and verify the prediction model for ischemic cardiovascular disease (ICVD) among the elderly population who were under the current health care programs. Statistical analysis on data from physical examination, hospitalization of the past years, from questionnaire and telephone interview was carried out in May, 2003. Data was from a hospital which implementing a health care program. Baseline population with a proportion of 4:1 was randomly selected to generate both module group and verification group. Baseline data was induced to make the verification group into regression model of module group and to generate the predictive value. Distinguished ability with area under ROC curve and the predictive veracity were verified through comparing the predictive incidence rate and actual incidence rate of every deciles group by Hosmer-Lemeshow test. Predictive veracity of the prediction model at population level was verified through comparing the predictive 6-year incidence rates of ICVD with actual 6-year accumulative incidence rates of ICVD with error rate calculated. The samples included 2271 males over the age of 65 with 1817 people for modeling population and 454 for verified population. All of the samples were stratified into two layers to establish hierarchical Cox proportional hazard regression model, including one advanced age group (greater than or equal to 75 years old), and another elderly group (less than 75 years old). Data from the statically analysis showed that the risk factors in aged group were age, systolic blood pressure, serum creatinine level, fasting blood glucose level, while protective factor was high density lipoprotein;in advanced age group, the risk factors were body weight index, systolic blood pressure, serum total cholesterol level, serum creatinine level, fasting blood glucose level, while protective factor was HDL-C. The area under the ROC curve (AUC) and 95%CI were 0.723 and 0.687 - 0.759 respectively. Discriminating power was good. All individual predictive ICVD cumulative incidence and actual incidence were analyzed using Hosmer-Lemeshow test, χ(2) = 1.43, P = 0.786, showing that the predictive veracity was good. The stratified Cox Hazards Regression model was used to establish prediction model of the aged male population under a certain health care program. The common prediction factor of the two age groups were: systolic blood pressure, serum creatinine level, fasting blood glucose level and HDL-C. The area under the ROC curve of the verification group was 0.723, showing that the distinguished ability was good and the predict ability at the individual level and at the group level were also satisfactory. It was feasible to using Cox Proportional Hazards Regression Model for predicting the population groups.

Diagnostic performance of traditional hepatobiliary biomarkers of drug-induced liver injury in the rat.

PubMed

Ennulat, Daniela; Magid-Slav, Michal; Rehm, Sabine; Tatsuoka, Kay S

2010-08-01

Nonclinical studies provide the opportunity to anchor biochemical with morphologic findings; however, liver injury is often complex and heterogeneous, confounding the ability to relate biochemical changes with specific patterns of injury. The aim of the current study was to compare diagnostic performance of hepatobiliary markers for specific manifestations of drug-induced liver injury in rat using data collected in a recent hepatic toxicogenomics initiative in which rats (n = 3205) were given 182 different treatments for 4 or 14 days. Diagnostic accuracy of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbili), serum bile acids (SBA), alkaline phosphatase (ALP), gamma glutamyl transferase (GGT), total cholesterol (Chol), and triglycerides (Trig) was evaluated for specific types of liver histopathology by Receiver Operating Characteristic (ROC) analysis. To assess the relationship between biochemical and morphologic changes in the absence of hepatocellular necrosis, a second ROC analysis was performed on a subset of rats (n = 2504) given treatments (n = 152) that did not cause hepatocellular necrosis. In the initial analysis, ALT, AST, Tbili, and SBA had the greatest diagnostic utility for manifestations of hepatocellular necrosis and biliary injury, with comparable magnitude of area under the ROC curve and serum hepatobiliary marker changes for both. In the absence of hepatocellular necrosis, ALT increases were observed with biochemical or morphologic evidence of cholestasis. In both analyses, diagnostic utility of ALP and GGT for biliary injury was limited; however, ALP had modest diagnostic value for peroxisome proliferation, and ALT, AST, and total Chol had moderate diagnostic utility for phospholipidosis. None of the eight markers evaluated had diagnostic value for manifestations of hypertrophy, cytoplasmic rarefaction, inflammation, or lipidosis.

Bronchial lavage P 16INK4A gene promoter methylation and lung cancer diagnosis: A meta-analysis.

PubMed

Yifan, D; Qun, L; Yingshuang, H; Xulin, L; Jianjun, W; Qian, M; Yuman, Yu; Zhaoyang, R

2015-12-01

To evaluate the diagnostic value of bronchial lavage P16INK4A promoter methylation and lung cancer. The databases of PubMed, Medline, China National Knowledge Infrastructure, and Wanfang were electronically searched by two reviewers to find the suitable studies related to the association between P16INK4A promoter methylation and lung cancer. The P16INK4A promoter methylation rate was extracted from each included individual study. The diagnostic sensitivity, specificity, and area under the receiver operating characteristic ROC curve of bronchial lavage P16INK4Aas a biomarker for diagnosis of lung cancer were pooled by stata 11.0 software (Stata Corporation, College Station, TX, USA). At last, 10 publications were included in this meta-analysis. Of the included 10 studies, five are published in English with relatively high quality and other five papers published in Chinese have relatively low quality. The pooled sensitivity and specificity of bronchial lavage P16INK4A promoter methylation for lung cancer diagnosis were 0.61 (95% confidence interval [CI]: 0.57-0.65) and 0.81 (95% CI: 0.78-0.85), respectively, with random effect model. The ROC curve were calculated and drawn according to Bayes' theorem by stata 11.0 software. The systematic area under the ROC was 0.72 (95% CI: 0.68-0.76), which indicated that the diagnostic value of bronchial lavage P16INK4A promoter methylation for lung cancer was relatively high. Moreover, no significant publication bias was existed in this meta-analysis (t = 0.69, P > 0.05). Bronchial lavage P16INK4A promoter methylation can be a potential biomarker for diagnosis of lung cancer.

Three new potential ovarian cancer biomarkers detected in human urine with equalizer bead technology.

PubMed

Petri, Anette Lykke; Simonsen, Anja Hviid; Yip, Tai-Tung; Hogdall, Estrid; Fung, Eric T; Lundvall, Lene; Hogdall, Claus

2009-01-01

To examine whether urine can be used to measure specific ovarian cancer proteomic profiles and whether one peak alone or in combination with other peaks or CA125 has the sensitivity and specificity to discriminate between ovarian cancer pelvic mass and benign pelvic mass. A total of 209 women were admitted for surgery for pelvic mass at the Gynaecological Department at Rigshospitalet, Copenhagen. Of the women, 156 had benign gynaecological tumors, 13 had borderline tumors and 40 had malignant epithelial ovarian cancer. The prospectively and preoperatively collected urine samples were aliquotted and frozen at -80 degrees until the time of analysis. The urine was fractionated using equalizer bead technology and then analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Biomarkers were purified and identified using combinations of chromatographic techniques and tandem mass spectrometry. Benign and malignant ovarian cancer cases were compared; 21 significantly different peaks (p<0.001) were visualized using Mann-Whitney analysis, ranging in m/z values from 1,500 to 185,000. The three most significant peaks were purified and identified as fibrinogen alpha fragment (m/z=2570.21), collagen alpha 1 (III) fragment (m/z=2707.32) and fibrinogen beta NT fragment (m/z=4425.09). The area under the receiver operator characteristic curve (ROC AUC) value for these three peaks in combination was 0.88, and their ROC AUC value in combination with CA125 was 0.96. This result supports the feasibility of using urine as a clinical diagnostic medium, and the ROC AUC value for the three most significant peaks in combination with or without CA125 demonstrates the enhanced prediction performance of combined marker analysis.

Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas.

PubMed

Xu, Boyan; Su, Lu; Wang, Zhenxiong; Fan, Yang; Gong, Gaolang; Zhu, Wenzhen; Gao, Peiyi; Gao, Jia-Hong

2018-04-17

Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas. Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (α) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis. The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (0.979) and H (0.594), indicating an improved performance for tumor differentiation. The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues. Copyright © 2018 Elsevier Inc. All rights reserved.

Differential gene expression profiles of peripheral blood mononuclear cells in childhood asthma.

PubMed

Kong, Qian; Li, Wen-Jing; Huang, Hua-Rong; Zhong, Ying-Qiang; Fang, Jian-Pei

2015-05-01

Asthma is a common childhood disease with strong genetic components. This study compared whole-genome expression differences between asthmatic young children and healthy controls to identify gene signatures of childhood asthma. Total RNA extracted from peripheral blood mononuclear cells (PBMC) was subjected to microarray analysis. QRT-PCR was performed to verify the microarray results. Classification and functional characterization of differential genes were illustrated by hierarchical clustering and gene ontology analysis. Multiple logistic regression (MLR) analysis, receiver operating characteristic (ROC) curve analysis, and discriminate power were used to scan asthma-specific diagnostic markers. For fold-change>2 and p < 0.05, there were 758 named differential genes. The results of QRT-PCR confirmed successfully the array data. Hierarchical clustering divided 29 highly possible genes into seven categories and the genes in the same cluster were likely to possess similar expression patterns or functions. Gene ontology analysis presented that differential genes primarily enriched in immune response, response to stress or stimulus, and regulation of apoptosis in biological process. MLR and ROC curve analysis revealed that the combination of ADAM33, Smad7, and LIGHT possessed excellent discriminating power. The combination of ADAM33, Smad7, and LIGHT would be a reliable and useful childhood asthma model for prediction and diagnosis.

Basic arterial blood gas biomarkers as a predictor of mortality in tetralogy of Fallot patients.

PubMed

Bhardwaj, Vandana; Kapoor, Poonam Malhotra; Irpachi, Kalpana; Ladha, Suruchi; Chowdhury, Ujjwal Kumar

2017-01-01

Serum lactate and base deficit have been shown to be a predictor of morbidity and mortality in critically ill patients. Poor preoperative oxygenation appears to be one of the significant factors that affects early mortality in tetralogy of Fallot (TOF). There is little published literature evaluating the utility of serum lactate, base excess (BE), and oxygen partial pressure (PO 2 ) as simple, widely available, prognostic markers in patients undergoing surgical repair of TOF. This prospective, observational study was conducted in 150 TOF patients, undergoing elective intracardiac repair. PO 2 , BE, and lactate levels at three different time intervals were recorded. Arterial blood samples were collected after induction (T1), after cardiopulmonary bypass (T2), and 48 h (T3) after surgery in the Intensive Care Unit (ICU). To observe the changes in PO 2 , BE, and lactate levels over a period of time, repeated measures analysis was performed with Bonferroni method. The receiver operating characteristics (ROC) analysis was used to find area under curve (AUC) and cutoff values of various biomarkers for predicting mortality in ICU. The patients who could not survive showed significant elevated lactate levels at baseline (T1) and postoperatively (T2) as compared to patients who survived after surgery (P < 0.001). However, in nonsurvivors, the BE value decreased significantly in the postoperative period in comparison to survivors (-2.8 ± 4.27 vs. 5.04 ± 2.06) (P < 0.001). In nonsurvivors, there was a significant fall of PO 2 to a mean value of 59.86 ± 15.09 in ICU (T3), whereas those who survived had a PO 2 of 125.86 ± 95.09 (P < 0.001). The ROC curve analysis showed that lactate levels (T3) have highest mortality predictive value (AUC: 96.9%) as compared to BE (AUC: 94.5%) and PO 2 (AUC: 81.1%). Serum lactate and BE may be used as prognostic markers to predict mortality in patients undergoing TOF repair. The routine analysis of these simple, fast, widely available, and cost-effective biomarkers should be encouraged to predict prognosis of TOF patients.

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

PubMed

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamics of receptor-operated Ca(2+) currents through TRPC channels controlled via the PI(4,5)P2-PLC signaling pathway.

PubMed

Mori, Masayuki X; Itsuki, Kyohei; Hase, Hideharu; Sawamura, Seishiro; Kurokawa, Tatsuki; Mori, Yasuo; Inoue, Ryuji

2015-01-01

Transient receptor potential canonical (TRPC) channels are Ca(2+)-permeable, nonselective cation channels that carry receptor-operated Ca(2+) currents (ROCs) triggered by receptor-induced, phospholipase C (PLC)-catalyzed hydrolysis of phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]. Within the vasculature, TRPC channel ROCs contribute to smooth muscle cell depolarization, vasoconstriction, and vascular remodeling. However, TRPC channel ROCs exhibit a variable response to receptor-stimulation, and the regulatory mechanisms governing TRPC channel activity remain obscure. The variability of ROCs may be explained by their complex regulation by PI(4,5)P2 and its metabolites, which differentially affect TRPC channel activity. To resolve the complex regulation of ROCs, the use of voltage-sensing phosphoinositide phosphatases and model simulation have helped to reveal the time-dependent contribution of PI(4,5)P2 and the possible role of PI(4,5)P2 in the regulation of ROCs. These approaches may provide unprecedented insight into the dynamics of PI(4,5)P2 regulation of TRPC channels and the fundamental mechanisms underlying transmembrane ion flow. Within that context, we summarize the regulation of TRPC channels and their coupling to receptor-mediated signaling, as well as the application of voltage-sensing phosphoinositide phosphatases to this research. We also discuss the controversial bidirectional effects of PI(4,5)P2 using a model simulation that could explain the complicated effects of PI(4,5)P2 on different ROCs.

Effect of coagulation on treatment of municipal wastewater reverse osmosis concentrate by UVC/H2O2.

PubMed

Umar, Muhammad; Roddick, Felicity; Fan, Linhua

2014-02-15

Disposal of reverse osmosis concentrate (ROC) is a growing concern due to potential health and ecological risks. Alum coagulation was investigated as pre-treatment for the UVC/H2O2 treatment of two high salinity ROC samples (ROC A and B) of comparable organic and inorganic content. Coagulation removed a greater fraction of the organic content for ROC B (29%) than ROC A (16%) which correlated well with the reductions of colour and A254. Although the total reductions after 60 min UVC/H2O2 treatment with and without coagulation were comparable, large differences in the trends of reduction were observed which were attributed to the different nature of the organic content (humic-like) of the samples as indicated by the LC-OCD analyses and different initial (5% and 16%) biodegradability. Coagulation and UVC/H2O2 treatment preferentially removed humic-like compounds which resulted in low reaction rates after UVC/H2O2 treatment of the coagulated samples. The improvement in biodegradability was greater (2-3-fold) during UVC/H2O2 treatment of the pre-treated samples than without pre-treatment. The target DOC residual (≤ 15 mg/L) was obtained after 30 and 20 min irradiation of pre-treated ROC A and ROC B with downstream biological treatment, corresponding to reductions of 55% and 62%, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Syntheses, structural determinations of [Ru(ROCS2)2(PPh3)2](+/0) pairs, and kinetic analyses of thermal reactions involving transient trans-[Ru(iPrOCS2)2(PPh3)2] species (ROCS2(-) = ethyl- or isopropyldithiocarbonate and PPh3 = triphenylphosphine).

PubMed

Noda, Kyoko; Ohuchi, Yuko; Hashimoto, Akira; Fujiki, Masayuki; Itoh, Sumitaka; Iwatsuki, Satoshi; Noda, Toshiaki; Suzuki, Takayoshi; Kashiwabara, Kazuo; Takagi, Hideo D

2006-02-06

Controlled-potential electrochemical oxidation of cis-[Ru(ROCS2)2(PPh3)2] (R = Et, iPr) yielded corresponding Ru(III) complexes, and the crystal structures of cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2](PF6) were determined. Both pairs of complexes exhibited almost identical coordination structures. The Ru-P distances in trans-[Ru(III)(ROCS2)2(PPh3)2](PF6) [2.436(3)-2.443(3) A] were significantly longer than those in cis-[Ru(II)(ROCS2)2(PPh3)2] [2.306(1)-2.315(2) A]: the smaller ionic radius of Ru(III) than that of Ru(II) stabilizes the trans conformation for the Ru(III) complex due to the steric requirement of bulky phosphine ligands while mutual trans influence by the phosphine ligands induces significant elongation of the Ru(III)-P bonds. Cyclic voltammograms of the cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2]+ complexes in dichloromethane solution exhibited typical dual redox signals corresponding to the cis-[Ru(ROCS2)2(PPh3)2](+/0) (ca. +0.15 and +0.10 V vs ferrocenium/ferrocene couple for R = Et and iPr, respectively) and to trans-[Ru(ROCS2)2(PPh3)2](+/0) (-0.05 and -0.15 V vs ferrocenium/ferrocene for R = Et and iPr, respectively) couples. Analyses on the basis of the Nicholson and Shain's method revealed that the thermal disappearance rate of transient trans-[Ru(ROCS2)2(PPh3)2] was dependent on the concentration of PPh3 in the bulk: the rate constant for the intramolecular isomerization reaction of trans-[Ru(iPrOCS2)2(PPh3)2] was determined as 0.338 +/- 0.004 s(-1) at 298.3 K (deltaH* = 41.8 +/- 1.5 kJ mol(-1) and deltaS* = -114 +/- 7 J mol(-1) K(-1)), while the dissociation rate constant of coordinated PPh3 from the trans-[Ru(iPrOCS2)2(PPh3)2] species was estimated as 0.113 +/- 0.008 s(-1) at 298.3 K (deltaH* = 97.6 +/- 0.8 kJ mol(-1) and deltaS* = 64 +/- 3 J mol(-1) K(-1)), by monitoring the EC reaction (electrode reaction followed by chemical processes) at different concentrations of PPh3 in the bulk. It was found that the trans to cis isomerization reaction takes place via the partial dissociation of iPrOCS2(-) from Ru(II), contrary to the previous claim that it takes place by the twist mechanism.

Assessing the Classification Accuracy of Early Numeracy Curriculum-Based Measures Using Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Laracy, Seth D.; Hojnoski, Robin L.; Dever, Bridget V.

2016-01-01

Receiver operating characteristic curve (ROC) analysis was used to investigate the ability of early numeracy curriculum-based measures (EN-CBM) administered in preschool to predict performance below the 25th and 40th percentiles on a quantity discrimination measure in kindergarten. Areas under the curve derived from a sample of 279 students ranged…

Receiver Operating Characteristic Analysis for Classification Based on Various Prior Probabilities of Groups with an Application to Breath Analysis

NASA Astrophysics Data System (ADS)

Cimermanová, K.

2009-01-01

In this paper we illustrate the influence of prior probabilities of diseases on diagnostic reasoning. For various prior probabilities of classified groups characterized by volatile organic compounds of breath profile, smokers and non-smokers, we constructed the ROC curve and the Youden index with related asymptotic pointwise confidence intervals.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding.

PubMed

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-05-28

To distinguish upper from lower gastrointestinal (GI) bleeding. Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding

PubMed Central

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-01-01

AIM: To distinguish upper from lower gastrointestinal (GI) bleeding. METHODS: Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. RESULTS: Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. CONCLUSION: The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL. PMID:26034359

Oxidative status in different settings and with different methodological approaches compared by Receiver Operating Characteristic curve analysis.

PubMed

Cighetti, Giuliana; Bamonti, Fabrizia; Aman, Caroline S; Gregori, Dario; De Giuseppe, Rachele; Novembrino, Cristina; de Liso, Federica; Maiavacca, Rita; Paroni, Rita

2015-01-01

To test the performance of different analytical approaches in highlighting the occurrence of deregulated redox status in various physio-pathological situations. 35 light and 61 heavy smokers, 19 chronic renal failure, 59 kidney transplanted patients, and 87 healthy controls were retrospectively considered for the study. Serum oxidative stress and antioxidant status, assessed by spectrophotometric Reactive Oxygen Metabolites (d-ROMs) and Total Antioxidant Capacity (TAC) tests, respectively, were compared with plasma free (F-MDA) and total (T-MDA) malondialdehyde, both quantified by isotope-dilution-gas chromatography-mass spectrometry (ID-GC-MS). Sensitivity, specificity and cut-off points of T-MDA, F-MDA, d-ROMs and TAC were evaluated by both Receiver Operating Characteristic (ROC) analyses and area under the ROC curve (AUC). Only T-MDA assay showed a clear absence of oxidative stress in controls and significant increase in all patients (AUC 1.00, sensitivity and specificity 100%). Accuracy was good for d-ROMs (AUC 0.87, sensitivity 72.8%, specificity 100%) and F-MDA (AUC 0.82, sensitivity 74.7%, specificity 83.9%), but not high enough for TAC to show in patients impaired antioxidant defense (AUC 0.66, sensitivity 52.0%, specificity 92.9%). This study reveals T-MDA as the best marker to detect oxidative stress, shows the ability of d-ROMs to identify modified oxidative status particularly in the presence of high damages, and evidences the poor TAC performance. d-ROMs and TAC assays could be useful for routine purposes; however, for an accurate clinical data evaluation, their comparison versus a "gold standard method" is required. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Application of κ free light chains in cerebrospinal fluid as a biomarker in multiple sclerosis diagnosis: development of a diagnosis algorithm.

PubMed

Valencia-Vera, Estefania; Martinez-Escribano Garcia-Ripoll, Ana; Enguix, Alfredo; Abalos-Garcia, Carmen; Segovia-Cuevas, Maria Jesus

2018-03-28

The determination of κ free light chains (KFLC) in cerebrospinal fluid (CSF) by nephelometry is a feasible alternative to immunoglobulin G oligoclonal bands (OCB) in the evaluation of intrathecal synthesis of immunoglobulin in multiple sclerosis (MS) and other demyelinating diseases. The aim of this study was to assess the diagnostic value of KFLC and its inclusion in a procedure algorithm along with OCB interpretation. A cross-sectional study, which included 123 patients with a CSF OCB request, was carried out. Isoelectric focusing followed by immunofixation was used to detect OCB, and nephelometry was used to analyze KFLC. The KFLC index was calculated using CSF/serum quotient of KFLC and albumin. The KFLC index was compared with MS diagnosis to find the optimal cutoff. It was obtained from the receiver operating characteristic (ROC) curves and the Youden method. The CSF KFLC median was 1.66 mg/L in the MS group, whereas in other central nervous system diseases, KFLC showed generally no or only moderate increase in CSF (median 0.10 mg/L). KFLC index showed a significant difference between groups. ROC analysis for CSF KFLC concentration, and KFLC indexes were 91.88% and 93.94%, respectively. The best cutoff for the KFLC index was 2.91 for MS diagnosis (sensitivity: 83.78%; specificity: 85.88%). The proposed algorithm showed high sensitivity (89.19%) and specificity (84.71%). KFLC determination is rapid and automatized, but it has no higher sensitivity and specificity than OCB in MS diagnosis. Nevertheless, when used in screening, it could reduce the number of manual OCB tests.

Universal School Readiness Screening at Kindergarten Entry

ERIC Educational Resources Information Center

Quirk, Matthew; Dowdy, Erin; Dever, Bridget; Carnazzo, Katherine; Bolton, Courtney

2018-01-01

Researchers examined the concurrent and predictive validity of a brief (12-item) teacher-rated school readiness screener, the Kindergarten Student Entrance Profile (KSEP), using receiver operating characteristic (ROC) curve analysis to examine associations between (N = 78) children's social-emotional (SE) and cognitive (COG) readiness with…

Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System.

PubMed

Chai, Rifai; Naik, Ganesh R; Nguyen, Tuan Nghia; Ling, Sai Ho; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-05-01

This paper presents a two-class electroencephal-ography-based classification for classifying of driver fatigue (fatigue state versus alert state) from 43 healthy participants. The system uses independent component by entropy rate bound minimization analysis (ERBM-ICA) for the source separation, autoregressive (AR) modeling for the features extraction, and Bayesian neural network for the classification algorithm. The classification results demonstrate a sensitivity of 89.7%, a specificity of 86.8%, and an accuracy of 88.2%. The combination of ERBM-ICA (source separator), AR (feature extractor), and Bayesian neural network (classifier) provides the best outcome with a p-value < 0.05 with the highest value of area under the receiver operating curve (AUC-ROC = 0.93) against other methods such as power spectral density as feature extractor (AUC-ROC = 0.81). The results of this study suggest the method could be utilized effectively for a countermeasure device for driver fatigue identification and other adverse event applications.

Processes and process development in Taiwan

NASA Technical Reports Server (NTRS)

Hwang, H. L.

1986-01-01

Silicon material research in the Republic of China (ROC) parallels its development in the electronic industry. A brief outline of the historical development in ROC silicon material research is given. Emphasis is placed on the recent Silane Project managed by the National Science Council, ROC, including project objectives, task forces, and recent accomplishments. An introduction is also given to industrialization of the key technologies developed in this project.

Feasibility of body roundness index for identifying a clustering of cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices: the China Health and Nutrition Survey, 2008 to 2009

PubMed Central

Tian, Simiao; Zhang, Xiuzhi; Xu, Yang; Dong, Huimin

2016-01-01

Abstract The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA. We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices. In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst. Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power. PMID:27559964

Feasibility of body roundness index for identifying a clustering of cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices: the China Health and Nutrition Survey, 2008 to 2009.

PubMed

Tian, Simiao; Zhang, Xiuzhi; Xu, Yang; Dong, Huimin

2016-08-01

The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA.We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices.In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst.Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power.

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

ROC Analysis of Chest Radiographs Using Computed Radiography and Conventional Analog Films

NASA Astrophysics Data System (ADS)

Morioka, Craig A.; Brown, Kathy; Hayrapetian, Alek S.; Kangarloo, Hooshang; Balter, Stephen; Huang, H. K.

1989-05-01

Receiver operating characteristic is used to compare the image quality of films obtained digitally using computed radiography (CR) and conventionally using analog film following fluoroscopic examination. Similar radiological views were obtained by both modalities. Twenty-four cases, some with a solitary noncalcified nodule and/or pneumothorax, were collected. Ten radiologists have been tested viewing analog and CR digital films separately. Final results indicate that there is no statistically significant difference in the ability to detect either a pneumothorax or a solitary noncalcified nodule when comparing CR digital film with conventional analog film. However, there is a trend that indicated the area under the ROC curves for detection of either a pneumothorax or solitary noncalcified nodule were greater for the analog film than for the digital film.

Can Shear-Wave Elastography be Used to Discriminate Obstructive Hydronephrosis from Nonobstructive Hydronephrosis in Children?

PubMed

Dillman, Jonathan R; Smith, Ethan A; Davenport, Matthew S; DiPietro, Michael A; Sanchez, Ramon; Kraft, Kate H; Brown, Richard K J; Rubin, Jonathan M

2015-10-01

To determine if ultrasonographic (US) renal shear-wave speed (SWS) measurements obtained either before or after intravenous diuretic administration can be used to discriminate obstructive hydronephrosis from unobstructive hydronephrosis in children, with diuretic renal scintigraphy as the reference standard. Institutional review board approval and parental informed consent were obtained for this HIPAA-compliant prospective cross-sectional blind comparison with a reference standard. Between November 2012 and September 2014, 37 children (mean age, 4.1 years; age range, 1 month to 17 years) underwent shear-wave elastography of the kidneys immediately before and immediately after diuretic renal scintigraphy (reference standard for presence of urinary tract obstruction). Median SWS measurements (in meters per second), as well as change in median SWS (median SWS after diuretic administration minus median SWS before diuretic administration) were correlated with the amount of time required for kidney radiotracer activity to fall by 50% after intravenous administration of the diuretic (T1/2). Median SWS measurements were compared with degree of obstruction and degree of hydronephrosis with analysis of variance. Receiver operating characteristic (ROC) curves were created. Radiotracer T1/2 values after diuretic administration did not correlate with median SWS measurements obtained before (r = -0.08, P = .53) or after (r = -0.0004, P >.99) diuretic administration, nor did they correlate with intraindividual change in median SWS (r = 0.07, P = .56). There was no significant difference in pre- or postdiuretic median SWS measurements between kidneys with scintigraphic evidence of no, equivocal, or definite urinary tract obstruction (P > .5) or for median SWS measurements between kidneys with increasing degree of hydronephrosis (P > .5). ROC curves showed poor diagnostic performance of median SWS in discerning no, equivocal, or definite urinary tract obstruction (area under the ROC curve ranged from 0.50 to 0.62). US SWS measurements did not enable discrimination of obstructive hydronephrosis from unobstructive hydronephrosis in children. (©) RSNA, 2015 Online supplemental material is available for this article.

User-friendly tools on handheld devices for observer performance study

NASA Astrophysics Data System (ADS)

Matsumoto, Takuya; Hara, Takeshi; Shiraishi, Junji; Fukuoka, Daisuke; Abe, Hiroyuki; Matsusako, Masaki; Yamada, Akira; Zhou, Xiangrong; Fujita, Hiroshi

2012-02-01

ROC studies require complex procedures to select cases from many data samples, and to set confidence levels in each selected case to generate ROC curves. In some observer performance studies, researchers have to develop software with specific graphical user interface (GUI) to obtain confidence levels from readers. Because ROC studies could be designed for various clinical situations, it is difficult task for preparing software corresponding to every ROC studies. In this work, we have developed software for recording confidence levels during observer studies on tiny personal handheld devices such as iPhone, iPod touch, and iPad. To confirm the functions of our software, three radiologists performed observer studies to detect lung nodules by using public database of chest radiograms published by Japan Society of Radiological Technology. The output in text format conformed to the format for the famous ROC kit from the University of Chicago. Times required for the reading each case was recorded very precisely.

Verification of a model for the detection of intrauterine growth restriction (IUGR) by receiver operating characteristics (ROC)

NASA Astrophysics Data System (ADS)

Liu, Pengbo; Mongelli, Max; Mondry, Adrian

2004-07-01

The purpose of this study is to verify by Receiver Operating Characteristics (ROC) a mathematical model supporting the hypothesis that IUGR can be diagnosed by estimating growth velocity. The ROC compare computerized simulation results with clinical data from 325 pregnant British women. Each patient had 6 consecutive ultrasound examinations for fetal abdominal circumference (fac). Customized and un-customized fetal weights were calculated according to Hadlock"s formula. IUGR was diagnosed by the clinical standard, i.e. estimated weight below the tenth percentile. Growth velocity was estimated by calculating the changes of fac (Dzfac/dt) at various time intervals from 3 to 10 weeks. Finally, ROC was used to compare the methods. At 3~4 weeks scan interval, the area under the ROC curve is 0.68 for customized data and 0.66 for the uncustomized data with 95% confidence interval. Comparison between simulation data and real pregnancies verified that the model is clinically acceptable.

Useful Immunochromatographic Assay of Calprotectin in Gingival Crevicular Fluid for Diagnosis of Diseased Sites in Patients with Periodontal Diseases.

PubMed

Kido, Jun-Ichi; Murakami, Shinya; Kitamura, Masahiro; Yanagita, Manabu; Tabeta, Koichi; Yamazaki, Kazuhisa; Yoshie, Hiromasa; Watanabe, Hisashi; Izumi, Yuichi; Suda, Reiko; Yamamoto, Matsuo; Shiba, Hideki; Fujita, Tsuyoshi; Kurihara, Hidemi; Mizuno, Mitsuharu; Mishima, Akihiro; Kawahara, Nobumasa; Hashimoto, Kazuhiro; Naruishi, Koji; Nagata, Toshihiko

2017-09-06

Calprotectin, an inflammation-related protein, is present in gingival crevicular fluid (GCF) and the determination of calprotectin is useful for diagnosing periodontal diseases. We have recently developed a novel immunochromatographic (IC) chip system (SI-101402) to determine calprotectin levels in GCF. In the present study, the usefulness of this diagnostic system was investigated in patients with periodontal diseases. Thirty-six patients with periodontal diseases participated in this clinical test at multiple centers. Periodontitis sites (n=118) and non-periodontitis (healthy) sites (n=120) were selected after periodontal examination. GCF collection and periodontal examination were performed at baseline, after supragingival and subgingival scaling and root planing. Calprotectin amount in GCF was determined using a novel IC chip system and evaluated as a visual score and an IC reader value. The correlation between GCF calprotectin levels, clinical indicators and changes in calprotectin levels by periodontal treatments were investigated. Receiver operating characteristic (ROC) analysis of IC reader value for GCF calprotectin was performed to predict periodontal diseases. The visual score of GCF calprotectin was highly correlated the IC reader value. IC reader values of GCF calprotectin in periodontitis group were higher than those of healthy group at three dental examination stages and they significantly decreased with periodontal treatments. Visual scores and IC reader values of GCF calprotectin were correlated to the levels of clinical indicators. ROC analysis for GCF calprotectin showed an optimal cutoff value to predict periodontal diseases. Determination of GCF calprotectin using a novel IC chip system is useful for diagnosis of periodontal diseases.

Coated-platelets predict stroke at 30 days following TIA.

PubMed

Kirkpatrick, Angelia C; Vincent, Andrea S; Dale, George L; Prodan, Calin I

2017-07-11

To examine the potential for coated-platelets, a subset of highly procoagulant platelets observed on dual agonist stimulation with collagen and thrombin, for predicting stroke at 30 days in patients with TIA. Consecutive patients with TIA were enrolled and followed up prospectively. ABCD2 scores were obtained for each patient. Coated-platelet levels, reported as percent of cells converted to coated-platelets, were determined at baseline. The primary endpoint was the occurrence of stroke at 30 days. Receiver operator characteristic (ROC) analysis was used to calculate area under the curve (AUC) values for a model including coated-platelets to predict incident stroke at 30 days. A total of 171 patients with TIA were enrolled, and 10 strokes were observed at 30 days. A cutoff of 51.1% for coated-platelet levels yielded a sensitivity of 0.80 (95% confidence interval [CI] 0.55-1.0), specificity of 0.73 (95% CI 0.66-0.80), positive predictive value of 0.16 (95% CI 0.06-0.26), and negative predictive value of 0.98 (95% CI 0.96-1.0). The adjusted hazard ratio of incident stroke in patients with coated-platelet levels ≥51.1% was 10.72 compared to those with levels <51.1%. ROC analysis showed significant improvement in the predictive ability of the coated-platelet model compared to ABCD2 score (AUC 0.78 ± 0.07 vs 0.54 ± 0.07, p = 0.01). These findings suggest a role for coated-platelets in risk stratification for stroke at 30 days after TIA. © 2017 American Academy of Neurology.

Ultrasonographic Evaluation of Cervical Lymph Nodes in Thyroid Cancer.

PubMed

Machado, Maria Regina Marrocos; Tavares, Marcos Roberto; Buchpiguel, Carlos Alberto; Chammas, Maria Cristina

2017-02-01

Objective To determine what ultrasonographic features can identify metastatic cervical lymph nodes, both preoperatively and in recurrences after complete thyroidectomy. Study Design Prospective. Setting Outpatient clinic, Department of Head and Neck Surgery, School of Medicine, University of São Paulo, Brazil. Subjects and Methods A total of 1976 lymph nodes were evaluated in 118 patients submitted to total thyroidectomy with or without cervical lymph node dissection. All the patients were examined by cervical ultrasonography, preoperatively and/or postoperatively. The following factors were assessed: number, size, shape, margins, presence of fatty hilum, cortex, echotexture, echogenicity, presence of microcalcification, presence of necrosis, and type of vascularity. The specificity, sensitivity, positive predictive value, and negative predictive value of each variable were calculated. Univariate and multivariate logistic regression analyses were conducted. A receiver operator characteristic (ROC) curve was plotted to determine the best cutoff value for the number of variables to discriminate malignant lymph nodes. Results Significant differences were found between metastatic and benign lymph nodes with regard to all of the variables evaluated ( P < .05). Logistic regression analysis revealed that size and echogenicity were the best combination of altered variables (odds ratio, 40.080 and 7.288, respectively) in discriminating malignancy. The ROC curve analysis showed that 4 was the best cutoff value for the number of altered variables to discriminate malignant lymph nodes, with a combined specificity of 85.7%, sensitivity of 96.4%, and efficiency of 91.0%. Conclusion Greater diagnostic accuracy was achieved by associating the ultrasonographic variables assessed rather than by considering them individually.

Faces are special but not too special: Spared face recognition in amnesia is based on familiarity

PubMed Central

Aly, Mariam; Knight, Robert T.; Yonelinas, Andrew P.

2014-01-01

Most current theories of human memory are material-general in the sense that they assume that the medial temporal lobe (MTL) is important for retrieving the details of prior events, regardless of the specific type of materials. Recent studies of amnesia have challenged the material-general assumption by suggesting that the MTL may be necessary for remembering words, but is not involved in remembering faces. We examined recognition memory for faces and words in a group of amnesic patients, which included hypoxic patients and patients with extensive left or right MTL lesions. Recognition confidence judgments were used to plot receiver operating characteristics (ROCs) in order to more fully quantify recognition performance and to estimate the contributions of recollection and familiarity. Consistent with the extant literature, an analysis of overall recognition accuracy showed that the patients were impaired at word memory but had spared face memory. However, the ROC analysis indicated that the patients were generally impaired at high confidence recognition responses for faces and words, and they exhibited significant recollection impairments for both types of materials. Familiarity for faces was preserved in all patients, but extensive left MTL damage impaired familiarity for words. These results suggest that face recognition may appear to be spared because performance tends to rely heavily on familiarity, a process that is relatively well preserved in amnesia. The findings challenge material-general theories of memory, and suggest that both material and process are important determinants of memory performance in amnesia, and different types of materials may depend more or less on recollection and familiarity. PMID:20833190

The prognostic value of preoperative inflammation-based prognostic scores and nutritional status for overall survival in resected patients with nonmetastatic Siewert type II/III adenocarcinoma of esophagogastric junction.

PubMed

Zhang, Lixiang; Su, Yezhou; Chen, Zhangming; Wei, Zhijian; Han, Wenxiu; Xu, Aman

2017-07-01

Immune and nutritional status of patients have been reported to predict postoperative complications, recurrence, and prognosis of patients with cancer. Therefore, this retrospective study aimed to explore the prognostic value of preoperative inflammation-based prognostic scores [neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR)] and nutritional status [prognostic nutritional index (PNI), body mass index (BMI), hemoglobin, albumin, and prealbumin] for overall survival (OS) in adenocarcinoma of esophagogastric junction (AEG) patients. A total of 355 patients diagnosed with Siewert type II/III AEG and underwent surgery between October 2010 and December 2011 were followed up until October 2016. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff values of NLR, PLR, and PNI. Kaplan-Meier curves and Cox regression analyses were used to calculate the OS characteristics. The ideal cutoff values for predicting OS were 3.5 for NLR, 171 for PLR, and 51.3 for PNI according to the ROC curve. The patients with hemoglobin <120 g/L (P = .001), prealbumin <180 mg/L (P = .000), PNI <51.3 (P = .010), NLR >3.5 (P = .000), PLR >171 (P = .006), and low BMI group (P = .000) had shorter OS. And multivariate survival analysis using the Cox proportional hazards model showed that the tumor-node-metastasis stage, BMI, NLR, and prealbumin levels were independent risk factors for the OS. Our study demonstrated that preoperative prealbumin, BMI, and NLR were independent prognostic factors of AEG patients.

Large meniscus extrusion ratio is a poor prognostic factor of conservative treatment for medial meniscus posterior root tear.

PubMed

Kwak, Yoon-Ho; Lee, Sahnghoon; Lee, Myung Chul; Han, Hyuk-Soo

2018-03-01

The purpose of this study was to find a prognostic factor of medial meniscus posterior root tear (MMPRT) for surgical decision making. Eighty-eight patients who were diagnosed as acute or subacute MMPRT without severe degeneration of the meniscus were treated conservatively for 3 months. Fifty-seven patients with MMPRT showed good response to conservative treatment (group 1), while the remaining 31 patients who failed to conservative treatment (group 2) received arthroscopic meniscus repair. Their demographic characteristics and radiographic features including hip-knee-ankle angle, joint line convergence angle, Kellgren-Lawrence grade in plain radiographs, meniscus extrusion (ME) ratio (ME-medial femoral condyle ratio, ME-medial tibial plateau ratio, ME-meniscus width ratio), the location of bony edema, and cartilage lesions in MRI were compared. Receiver operating characteristic (ROC) curve analysis was also performed to determine the cut-off values of risk factors. The degree of ME-medial femoral condyle and medial tibia plateau ratio of group 2 was significantly higher than group 1 (0.08 and 0.07 vs. 0.1 and 0.09, respectively, both p < 0.001). No significant (n.s.) difference in other variables was found between the two groups. On ROC curve analysis, ME-medial femoral condyle ratio was confirmed as the most reliable prognostic factor of conservative treatment for MMPRT (area under ROC = 0.8). The large meniscus extrusion ratio was the most reliable poor prognostic factor of conservative treatment for MMPRT. Therefore, for MMPRT patients with large meniscus extrusion, early surgical repair could be considered as the primary treatment option. III.

Evaluation of the predictive capacity of vertical segmental tetrapolar bioimpedance for excess weight detection in adolescents.

PubMed

Neves, Felipe Silva; Leandro, Danielle Aparecida Barbosa; Silva, Fabiana Almeida da; Netto, Michele Pereira; Oliveira, Renata Maria Souza; Cândido, Ana Paula Carlos

2015-01-01

To analyze the predictive capacity of the vertical segmental tetrapolar bioimpedance apparatus in the detection of excess weight in adolescents, using tetrapolar bioelectrical impedance as a reference. This was a cross-sectional study conducted with 411 students aged between 10 and 14 years, of both genders, enrolled in public and private schools, selected by a simple and stratified random sampling process according to the gender, age, and proportion in each institution. The sample was evaluated by the anthropometric method and underwent a body composition analysis using vertical bipolar, horizontal tetrapolar, and vertical segmental tetrapolar assessment. The ROC curve was constructed based on calculations of sensitivity and specificity for each point of the different possible measurements of body fat. The statistical analysis used Student's t-test, Pearson's correlation coefficient, and McNemar's chi-squared test. Subsequently, the variables were interpreted using SPSS software, version 17.0. Of the total sample, 53.7% were girls and 46.3%, boys. Of the total, 20% and 12.5% had overweight and obesity, respectively. The body segment measurement charts showed high values of sensitivity and specificity and high areas under the ROC curve, ranging from 0.83 to 0.95 for girls and 0.92 to 0.98 for boys, suggesting a slightly higher performance for the male gender. Body fat percentage was the most efficient criterion to detect overweight, while the trunk segmental fat was the least accurate indicator. The apparatus demonstrated good performance to predict excess weight. Copyright © 2015 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Bone marrow with diffuse tumor infiltration in patients with lymphoproliferative diseases: dynamic gadolinium-enhanced MR imaging.

PubMed

Rahmouni, Alain; Montazel, Jean-Luc; Divine, Marine; Lepage, Eric; Belhadj, Karim; Gaulard, Philippe; Bouanane, Mohamed; Golli, Mondher; Kobeiter, Hicham

2003-12-01

To evaluate gadolinium enhancement of bone marrow in patients with lymphoproliferative diseases and diffuse bone marrow involvement. Dynamic contrast material-enhanced magnetic resonance (MR) imaging of the thoracolumbar spine was performed in 42 patients with histologically proved diffuse bone marrow involvement and newly diagnosed myeloma (n = 31), non-Hodgkin lymphoma (n = 8), or Hodgkin disease (n = 3). The maximum percentage of enhancement (Emax), enhancement slope, and enhancement washout were determined from enhancement time curves (ETCs). A three-grade system for scoring bone marrow involvement was based on the percentage of neoplastic cells in bone marrow samples. Quantitative ETC values for the 42 patients were compared with ETC values for healthy subjects and with grades of bone marrow involvement by using mean t test comparisons. Receiver operating characteristic (ROC) analysis was conducted by comparing Emax values between patients with and those without bone marrow involvement. Baseline and follow-up MR imaging findings were compared in nine patients. Significant differences in Emax (P <.001), slope (P <.001), and washout (P =.005) were found between subjects with normal bone marrow and patients with diffuse bone marrow involvement. ROC analysis results showed Emax values to have a diagnostic accuracy of 99%. Emax, slope, and washout values increased with increasing bone marrow involvement grade. The mean Emax increased from 339% to 737%. Contrast enhancement decreased after treatment in all six patients who responded to treatment but not in two of three patients who did not respond to treatment. Dynamic contrast-enhanced MR images can demonstrate increased bone marrow enhancement in patients with lymphoproliferative diseases and marrow involvement.

Resonance Raman Spectroscopy of human brain metastasis of lung cancer analyzed by blind source separation

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-Hui; Pu, Yang; Cheng, Gangge; Yu, Xinguang; Zhou, Lixin; Lin, Dongmei; Zhu, Ke; Alfano, Robert R.

2017-02-01

Resonance Raman (RR) spectroscopy offers a novel Optical Biopsy method in cancer discrimination by a means of enhancement in Raman scattering. It is widely acknowledged that the RR spectrum of tissue is a superposition of spectra of various key building block molecules. In this study, the Resonance Raman (RR) spectra of human metastasis of lung cancerous and normal brain tissues excited by a visible selected wavelength at 532 nm are used to explore spectral changes caused by the tumor evolution. The potential application of RR spectra human brain metastasis of lung cancer was investigated by Blind Source Separation such as Principal Component Analysis (PCA). PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components (PCs). The results show significant RR spectra difference between human metastasis of lung cancerous and normal brain tissues analyzed by PCA. To evaluate the efficacy of for cancer detection, a linear discriminant analysis (LDA) classifier is utilized to calculate the sensitivity, and specificity and the receiver operating characteristic (ROC) curves are used to evaluate the performance of this criterion. Excellent sensitivity of 0.97, specificity (close to 1.00) and the Area Under ROC Curve (AUC) of 0.99 values are achieved under best optimal circumstance. This research demonstrates that RR spectroscopy is effective for detecting changes of tissues due to the development of brain metastasis of lung cancer. RR spectroscopy analyzed by blind source separation may have potential to be a new armamentarium.

HOMA-IR and QUICKI: decide on a general standard instead of making further comparisons.

PubMed

Rössner, Sophia M; Neovius, Martin; Mattsson, Anna; Marcus, Claude; Norgren, Svante

2010-11-01

To limit further comparisons between the two fasting indices Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and Quantitative Insulin Sensitivity Check Index (QUICKI), and to examine their robustness in assessing insulin sensitivity. A total of 191 obese children and adolescents (age 13.9 ± 2.9 years, BMI SDS 6.1 ± 1.6), who had undergone a Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT), were included. Receiver operating characteristic curve (ROC) analysis was used to compare indices in detecting insulin resistance and Bland-Altman plots to investigate agreement between three consecutive fasting samples when compared to using single samples. ROC analysis showed that the diagnostic accuracy was identical for QUICKI and HOMA-IR [area under the curve (AUC) boys 0.80, 95%CI 0.70-0.89; girls 0.80, 0.71-0.88], while insulin had a nonsignificantly lower AUC (boys 0.76, 0.66-0.87; girls 0.75, 0.66-0.84). Glucose did not perform better than chance as a diagnostic test (boys 0.47, 0.34-0.60; girls 0.57, 0.46-0.68). Indices varied with consecutive sampling, mainly attributable to fasting insulin variations (mean maximum difference in HOMA-IR -0.8; -0.9 to -0.7). Using both HOMA-IR and QUICKI in further studies is superfluous as these indices function equally well as predictors of the FSIVGTT sensitivity index. Focus should be on establishing a general standard for research and clinical purposes. © 2010 The Author(s)/Journal Compilation © 2010 Foundation Acta Paediatrica.

Analysis of deep inferior epigastric perforator (DIEP) arteries by using MDCTA: Comparison between 2 post-processing techniques.

PubMed

Saba, Luca; Atzeni, Matteo; Ribuffo, Diego; Mallarini, Giorgio; Suri, Jasjit S

2012-08-01

Our purpose was to compare two post-processing techniques, Maximum-Intensity-Projection (MIP) and Volume Rendering (VR) for the study of perforator arteries. Thirty patients who underwent Multi-Detector-Row CT Angiography (MDCTA) between February 2010 and May 2010 were retrospectively analyzed. For each patient and for each reconstruction method, the image quality was evaluated and the inter- and intra-observer agreement was calculated according to the Cohen statistics. The Hounsfield Unit (HU) value in the common femoral artery was quantified and the correlation (Pearson Statistic) between image quality and HU value was explored. The Pearson r between the right and left common femoral artery was excellent (r=0.955). The highest image quality score was obtained using MIP for both observers (total value 75, with a mean value 2.67 for observer 1 and total value of 79 and a mean value of 2.82 for observer 2). The highest agreement between the two observers was detected using the MIP protocol with a Cohen kappa value of 0.856. The ROC area under the curve (Az) for the VR is 0.786 (0.086 SD; p value=0.0009) whereas the ROC area under the curve (Az) for the MIP is 0.0928 (0.051 SD; p value=0.0001). MIP showed the optimal inter- and intra-observer agreement and the highest quality scores and therefore should be used as post-processing techniques in the analysis of perforating arteries. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Ultrasound biomicroscopy and iris pigment dispersion: a case--control study.

PubMed

Mora, P; Sangermani, C; Ghirardini, S; Carta, A; Ungaro, N; Gandolfi, Sa

2010-04-01

The study involved eyes affected by pigment dispersion syndrome (PDS) or pigmentary glaucoma (PG) investigated by ultrasound biomicroscopy (UBM). Different irido-corneal parameters were assessed and compared with those from healthy controls. The aim was to investigate the capacity of the UBM in differentiating the cases and, potentially, in confirming the pathogenic mechanisms. Patients with a first diagnosis of PDS or PG were included. A cohort of healthy volunteers matched for sex, age and refractive errors was recruited. All underwent UBM examination: the following parameters were assessed in relaxed and stimulated accommodative state in one eye: iris-lens contact (ILC), irido-corneal angle (ICA) and iris concavity (IC). A receiver operating characteristic (ROC) analysis assessed the ability of UBM to discriminate between subjects with and without PDS/PG. There were 24 eyes in the case group: four diagnosed as PG and the remaining 20 as PDS. There were 25 eyes in the control group. The two groups were statistically superimposable except for baseline intraocular pressure, which was higher in the case group (p=0.0001). All UBM parameters were statistically different between the two groups. ICA in near vision was the best-performing parameter, reaching a sensitivity (=specificity) of 0.875 with a cut-off at 53.0 degrees . The second most sensitive parameter was IC, still in near vision. All UBM parameters examined were statistically different between the two groups. ROC analysis showed ICA and IC in near vision to be the most discriminatory parameters. This evidence confirms the importance of iris movements in inducing the particular features of PDS/PG.

Social subordination produces distinct stress-related phenotypes in female rhesus monkeys

PubMed Central

Michopoulos, Vasiliki; Higgins, Melinda; Toufexis, Donna; Wilson, Mark E

2012-01-01

Social subordination in female macaques is imposed by harassment and the threat of aggression and produces reduced control over one's social and physical environment and a dysregulation of the limbic-hypothalamic-pituitary-adrenal axis resembling that observed in people suffering from psychopathologies. These effects support the contention that this particular animal model is an ethologically relevant paradigm in which to investigate the etiology of stress-induced psychological illness related to women. Here, we sought to expand this model by performing a discriminate analysis (DA) on 33 variables within three domains; behavioral, metabolic/anthropomorphic, and neuroendocrine, collected from socially housed female rhesus monkeys in order to assess whether exposure to social subordination produces a distinct phenotype. A receiver operating characteristic (ROC) curve was also calculated to determine each domain's classification accuracy. DA found significant markers within each domain that differentiated dominant and subordinate females. Subordinate females received more aggression, showed more submissive behavior, and received less of affiliation from others than did dominant females. Metabolic differences included increased leptin, and reduced adiponectin in dominant compared to subordinate females. Dominant females exhibited increased sensitivity to hormonal stimulation with higher serum LH in response to estradiol, cortisol in response to ACTH, and increased glucocorticoid negative feedback. Serum oxytocin, CSF DOPAC and serum PACAP were all significantly higher in dominant females. ROC curve analysis accurately predicted social status in all three domains. Results suggest that socially house rhesus monkeys represent a cogent animal model in which to study the physiology and behavioral consequences of chronic psychosocial stress in humans. PMID:22244748

A comprehensive visual rating scale of brain magnetic resonance imaging: application in elderly subjects with Alzheimer's disease, mild cognitive impairment, and normal cognition.

PubMed

Jang, Jae-Won; Park, So Young; Park, Young Ho; Baek, Min Jae; Lim, Jae-Sung; Youn, Young Chul; Kim, SangYun

2015-01-01

Brain magnetic resonance imaging (MRI) shows cerebral structural changes. However, a unified comprehensive visual rating scale (CVRS) has seldom been studied. Thus, we combined brain atrophy and small vessel disease scales and used an MRI template as a CVRS. The aims of this study were to design a simple and reliable CVRS, validate it by investigating cerebral structural changes in clinical groups, and made comparison to the volumetric measurements. Elderly subjects (n = 260) with normal cognition (NC, n = 65), mild cognitive impairment (MCI, n = 101), or Alzheimer's disease (AD, n = 94) were evaluated with brain MRI according to the CVRS of brain atrophy and small vessel disease. Validation of the CVRS with structural changes, neuropsychological tests, and volumetric analyses was performed. The CVRS revealed a high intra-rater and inter-rater agreement and it reflected the structural changes of subjects with NC, MCI, and AD better than volumetric measures (CVRS-coronal: F = 13.5, p < 0.001; CVRS-axial: F = 19.9, p < 0.001). The area under the receiver operation curve (aROC) of the CVRS showed higher accuracy than volumetric analyses. (NC versus MCI aROC: CVRS-coronal, 0.777; CVRS-axial, 0.773; MCI versus AD aROC: CVRS-coronal, 0.680; CVRS-axial, 0.681). The CVRS can be used clinically to conveniently measure structural changes of brain. It reflected cerebral structural changes of clinical groups and correlated with the age better than volumetric measures.

An enhancement of ROC curves made them clinically relevant for diagnostic-test comparison and optimal-threshold determination.

PubMed

Subtil, Fabien; Rabilloud, Muriel

2015-07-01

The receiver operating characteristic curves (ROC curves) are often used to compare continuous diagnostic tests or determine the optimal threshold of a test; however, they do not consider the costs of misclassifications or the disease prevalence. The ROC graph was extended to allow for these aspects. Two new lines are added to the ROC graph: a sensitivity line and a specificity line. Their slopes depend on the disease prevalence and on the ratio of the net benefit of treating a diseased subject to the net cost of treating a nondiseased one. First, these lines help researchers determine the range of specificities within which test comparisons of partial areas under the curves is clinically relevant. Second, the ROC curve point the farthest from the specificity line is shown to be the optimal threshold in terms of expected utility. This method was applied: (1) to determine the optimal threshold of ratio specific immunoglobulin G (IgG)/total IgG for the diagnosis of congenital toxoplasmosis and (2) to select, among two markers, the most accurate for the diagnosis of left ventricular hypertrophy in hypertensive subjects. The two additional lines transform the statistically valid ROC graph into a clinically relevant tool for test selection and threshold determination. Copyright © 2015 Elsevier Inc. All rights reserved.

Fractal and Gray Level Cooccurrence Matrix Computational Analysis of Primary Osteosarcoma Magnetic Resonance Images Predicts the Chemotherapy Response.

PubMed

Djuričić, Goran J; Radulovic, Marko; Sopta, Jelena P; Nikitović, Marina; Milošević, Nebojša T

2017-01-01

The prediction of induction chemotherapy response at the time of diagnosis may improve outcomes in osteosarcoma by allowing for personalized tailoring of therapy. The aim of this study was thus to investigate the predictive potential of the so far unexploited computational analysis of osteosarcoma magnetic resonance (MR) images. Fractal and gray level cooccurrence matrix (GLCM) algorithms were employed in retrospective analysis of MR images of primary osteosarcoma localized in distal femur prior to the OsteoSa induction chemotherapy. The predicted and actual chemotherapy response outcomes were then compared by means of receiver operating characteristic (ROC) analysis and accuracy calculation. Dbin, Λ, and SCN were the standard fractal and GLCM features which significantly associated with the chemotherapy outcome, but only in one of the analyzed planes. Our newly developed normalized fractal dimension, called the space-filling ratio (SFR) exerted an independent and much better predictive value with the prediction significance accomplished in two of the three imaging planes, with accuracy of 82% and area under the ROC curve of 0.20 (95% confidence interval 0-0.41). In conclusion, SFR as the newly designed fractal coefficient provided superior predictive performance in comparison to standard image analysis features, presumably by compensating for the tumor size variation in MR images.

Shallow Water Acoustics Studies

DTIC Science & Technology

2015-09-30

and 2) a demonstration that the predictive probability of detection ( PPD ) formalism of Dyer and Abbot works well, using QPE field data. The...applications, and 3) showing that the PPD formalism for detection could be a useful extension of the usual sonar equation ROC curves. TRANSITIONS

Persistent free radicals in carbon-based materials on transformation of refractory organic contaminants (ROCs) in water: A critical review.

PubMed

Qin, Yaxin; Li, Guiying; Gao, Yanpeng; Zhang, Lizhi; Ok, Yong Sik; An, Taicheng

2018-06-15

With the increased concentrations and kinds of refractory organic contaminants (ROCs) in aquatic environments, many previous reviews systematically summarized the applications of carbon-based materials in the adsorption and catalytic degradation of ROCs for their economically viable and environmentally friendly behavior. Interestingly, recent studies indicated that carbon-based materials in natural environment can also mediate the transformation of ROCs directly or indirectly due to their abundant persistent free radicals (PFRs). Understanding the formation mechanisms of PFRs in carbo-based materials and their interactions with ROCs is essential to develop their further applications in environment remediation. However, there is no comprehensive review so far about the direct and indirect removal of ROCs mediated by PFRs in amorphous, porous and crystalline carbon-based materials. The review aims to evaluate the formation mechanisms of PFRs in carbon-based materials synthesized through pyrolysis and hydrothermal carbonization processes. The influence of synthesis conditions (temperature and time) and carbon sources on the types as well as the concentrations of PFRs in carbon-based materials are also discussed. In particular, the effects of metals on the concentrations and types of PFRs in carbon-based materials are highlighted because they are considered as the catalysts for the formation of PFRs. The formation mechanisms of reactive species and the further transformation mechanisms of ROCs are briefly summarized, and the surface properties of carbon-based materials including surface area, types and number of functional groups, etc. are found to be the key parameters controlling their activities. However, due to diversity and complexity of carbon-based materials, the exact relationships between the activities of carbon-based materials and PFRs are still uncertain. Finally, the existing problems and current challenges for the ROCs transformation with carbon-based materials are also pointed out. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computerized detection of noncalcified plaques in coronary CT angiography: Evaluation of topological soft gradient prescreening method and luminal analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Jun, E-mail: jvwei@umich.edu; Zhou, Chuan; Chan, Heang-Ping

2014-08-15

Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronarymore » artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features were selected during the tenfold cross-validation training. The average area under the ROC curve (AUC) value for training was 0.87 ± 0.01 and the AUC value for validation was 0.85 ± 0.01. Using the NCP score, FROC analysis of the validation set showed that the FP rates were reduced to 3.16, 1.90, and 1.39 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively. Conclusions: The topological soft-gradient prescreening method in combination with the luminal analysis for FP reduction was effective for detection of NCPs in cCTA, including NCPs causing positive or negative vessel remodeling. The accuracy of vessel segmentation, tracking, and centerline identification has a strong impact on NCP detection. Studies are underway to further improve these techniques and reduce the FPs of the CADe system.« less

Real-data comparison of data mining methods in prediction of diabetes in iran.

PubMed

Tapak, Lily; Mahjub, Hossein; Hamidi, Omid; Poorolajal, Jalal

2013-09-01

Diabetes is one of the most common non-communicable diseases in developing countries. Early screening and diagnosis play an important role in effective prevention strategies. This study compared two traditional classification methods (logistic regression and Fisher linear discriminant analysis) and four machine-learning classifiers (neural networks, support vector machines, fuzzy c-mean, and random forests) to classify persons with and without diabetes. The data set used in this study included 6,500 subjects from the Iranian national non-communicable diseases risk factors surveillance obtained through a cross-sectional survey. The obtained sample was based on cluster sampling of the Iran population which was conducted in 2005-2009 to assess the prevalence of major non-communicable disease risk factors. Ten risk factors that are commonly associated with diabetes were selected to compare the performance of six classifiers in terms of sensitivity, specificity, total accuracy, and area under the receiver operating characteristic (ROC) curve criteria. Support vector machines showed the highest total accuracy (0.986) as well as area under the ROC (0.979). Also, this method showed high specificity (1.000) and sensitivity (0.820). All other methods produced total accuracy of more than 85%, but for all methods, the sensitivity values were very low (less than 0.350). The results of this study indicate that, in terms of sensitivity, specificity, and overall classification accuracy, the support vector machine model ranks first among all the classifiers tested in the prediction of diabetes. Therefore, this approach is a promising classifier for predicting diabetes, and it should be further investigated for the prediction of other diseases.

Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis.

PubMed

Zhang, Yang; Xiao, Xiong; Zhang, Junting; Gao, Zhixian; Ji, Nan; Zhang, Liwei

2017-06-01

To evaluate the diagnostic accuracy of routine blood examinations and Cerebrospinal Fluid (CSF) lactate level for Post-neurosurgical Bacterial Meningitis (PBM) at a large sample-size of post-neurosurgical patients. The diagnostic accuracies of routine blood examinations and CSF lactate level to distinguish between PAM and PBM were evaluated with the values of the Area Under the Curve of the Receiver Operating Characteristic (AUC -ROC ) by retrospectively analyzing the datasets of post-neurosurgical patients in the clinical information databases. The diagnostic accuracy of routine blood examinations was relatively low (AUC -ROC <0.7). The CSF lactate level achieved rather high diagnostic accuracy (AUC -ROC =0.891; CI 95%, 0.852-0.922). The variables of patient age, operation duration, surgical diagnosis and postoperative days (the interval days between the neurosurgery and examinations) were shown to affect the diagnostic accuracy of these examinations. The variables were integrated with routine blood examinations and CSF lactate level by Fisher discriminant analysis to improve their diagnostic accuracy. As a result, the diagnostic accuracy of blood examinations and CSF lactate level was significantly improved with an AUC -ROC value=0.760 (CI 95%, 0.737-0.782) and 0.921 (CI 95%, 0.887-0.948) respectively. The PBM diagnostic accuracy of routine blood examinations was relatively low, whereas the accuracy of CSF lactate level was high. Some variables that are involved in the incidence of PBM can also affect the diagnostic accuracy for PBM. Taking into account the effects of these variables significantly improves the diagnostic accuracies of routine blood examinations and CSF lactate level. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tumor necrosis factor receptor 1 (TNFRI) for ventilator-associated pneumonia diagnosis by cytokine multiplex analysis.

PubMed

Martin-Loeches, Ignacio; Bos, Lieuwe D; Povoa, Pedro; Ramirez, Paula; Schultz, Marcus J; Torres, Antoni; Artigas, Antonio

2015-12-01

The diagnosis of ventilator-associated pneumonia (VAP) is challenging. An important aspect to improve outcome is early recognition of VAP and the initiation of the appropriate empirical treatment. We hypothesized that biological markers in plasma can rule out VAP at the moment of clinical suspicion and could rule in VAP before the diagnosis can be made clinically. In this prospective study, patients with VAP (n = 24, microbiology confirmed) were compared to controls (n = 19) with a similar duration of mechanical ventilation. Blood samples from the day of VAP diagnosis and 1 and 3 days before were analyzed with a multiplex array for markers of inflammation, coagulation, and apoptosis. The best biomarker combination was selected and the diagnostic accuracy was given by the area under the receiver operating characteristic curve (ROC-AUC). TNF-receptor 1 (TNFRI) and granulocyte colony-stimulating factor (GCSF) were selected as optimal biomarkers at the day of VAP diagnosis, which resulted in a ROC-AUC of 0.96, with excellent sensitivity. Three days before the diagnosis TNFRI and plasminogen activator inhibitor-1 (PAI-1) levels in plasma predicted VAP with a ROC-AUC of 0.79. The slope of IL-10 and PAI-1 resulted in a ROC-AUC of 0.77. These biomarkers improved the classification of the clinical pulmonary infection score when combined. Concentration of TNFRI and PAI-1 and the slope of PAI-1 and IL-10 may be used to predict the development of VAP as early as 3 days before the diagnosis made clinically. TNFRI and GCSF may be used to exclude VAP at the moment of clinical suspicion. Especially TNFRI seems to be a promising marker for the prediction and diagnosis of VAP.

Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.

PubMed

Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R

2017-01-01

This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.

Drain the lysosome: Development of the novel orally available autophagy inhibitor ROC-325.

PubMed

Carew, Jennifer S; Nawrocki, Steffan T

2017-04-03

Although macroautophagy/autophagy is a key contributor to malignant pathogenesis and therapeutic resistance, there are few FDA-approved agents that significantly affect this pathway. We used medicinal chemistry strategies to develop ROC-325, an orally available novel inhibitor of lysosomal-mediated autophagy. Detailed in vitro and in vivo studies in preclinical models of renal cell carcinoma demonstrated that ROC-325 triggered the hallmark features of lysosomal autophagy inhibition, was very well tolerated, and exhibited significant superiority with respect to autophagy inhibition and anticancer activity over hydroxychloroquine. Our findings support the clinical investigation of the safety and preliminary efficacy of ROC-325 in patients with autophagy-dependent malignancies and other disorders where aberrant autophagy contributes to disease pathogenesis.

Influence of optic disc size on the diagnostic performance of macular ganglion cell complex and peripapillary retinal nerve fiber layer analyses in glaucoma.

PubMed

Cordeiro, Daniela Valença; Lima, Verônica Castro; Castro, Dinorah P; Castro, Leonardo C; Pacheco, Maria Angélica; Lee, Jae Min; Dimantas, Marcelo I; Prata, Tiago Santos

2011-01-01

To evaluate the influence of optic disc size on the diagnostic accuracy of macular ganglion cell complex (GCC) and conventional peripapillary retinal nerve fiber layer (pRNFL) analyses provided by spectral domain optical coherence tomography (SD-OCT) in glaucoma. Eighty-two glaucoma patients and 30 healthy subjects were included. All patients underwent GCC (7 × 7 mm macular grid, consisting of RNFL, ganglion cell and inner plexiform layers) and pRNFL thickness measurement (3.45 mm circular scan) by SD-OCT. One eye was randomly selected for analysis. Initially, receiver operating characteristic (ROC) curves were generated for different GCC and pRNFL parameters. The effect of disc area on the diagnostic accuracy of these parameters was evaluated using a logistic ROC regression model. Subsequently, 1.5, 2.0, and 2.5 mm(2) disc sizes were arbitrarily chosen (based on data distribution) and the predicted areas under the ROC curves (AUCs) and sensitivities were compared at fixed specificities for each. Average mean deviation index for glaucomatous eyes was -5.3 ± 5.2 dB. Similar AUCs were found for the best pRNFL (average thickness = 0.872) and GCC parameters (average thickness = 0.824; P = 0.19). The coefficient representing disc area in the ROC regression model was not statistically significant for average pRNFL thickness (-0.176) or average GCC thickness (0.088; P ≥ 0.56). AUCs for fixed disc areas (1.5, 2.0, and 2.5 mm(2)) were 0.904, 0.891, and 0.875 for average pRNFL thickness and 0.834, 0.842, and 0.851 for average GCC thickness, respectively. The highest sensitivities - at 80% specificity for average pRNFL (84.5%) and GCC thicknesses (74.5%) - were found with disc sizes fixed at 1.5 mm(2) and 2.5 mm(2). Diagnostic accuracy was similar between pRNFL and GCC thickness parameters. Although not statistically significant, there was a trend for a better diagnostic accuracy of pRNFL thickness measurement in cases of smaller discs. For GCC analysis, an inverse effect was observed.