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

pROC: an open-source package for R and S+ to analyze and compare ROC curves.

PubMed

Robin, Xavier; Turck, Natacha; Hainard, Alexandre; Tiberti, Natalia; Lisacek, Frédérique; Sanchez, Jean-Charles; Müller, Markus

2011-03-17

Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

The influence of averaging and noisy decision strategies on the recognition memory ROC.

PubMed

Malmberg, Kenneth J; Xu, Jing

2006-02-01

Many single- and dual-process models of recognition memory predict that the ratings and remember-know receiver operating characteristics (ROCs) are the same, but Rotello, Macmillan, and Reeder (2004) reported that the slopes of the remember-know and ratings z-transformed ROCs (zROCs) are different The authors show that averaging introduces nonlinearities to the form of the zROC and that ratings and remember-know zROCs are indistinguishable when constructed in a conventional manner. The authors show, further, that some nonoptimal decision strategies have a distinctive, nonlinear effect on the form of the single-process continuous-state zROC. The conclusion is that many factors having nothing to do with the nature of recognition memory can affect the shape of zROCs, and that therefore, the shape of the zROC does not, alone, characterize different memory models.

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.

Reader characteristics linked to detection of pulmonary nodules on radiographs: ROC vs. JAFROC analyses of performance

NASA Astrophysics Data System (ADS)

Kohli, Akshay; Robinson, John W.; Ryan, John; McEntee, Mark F.; Brennan, Patrick C.

2011-03-01

The purpose of this study is to explore whether reader characteristics are linked to heightened levels of diagnostic performance in chest radiology using receiver operating characteristic (ROC) and jackknife free response ROC (JAFROC) methodologies. A set of 40 postero-anterior chest radiographs was developed, of which 20 were abnormal containing one or more simulated nodules, of varying subtlety. Images were independently reviewed by 12 boardcertified radiologists including six chest specialists. The observer performance was measured in terms of ROC and JAFROC scores. For the ROC analysis, readers were asked to rate their degree of suspicion for the presence of nodules by using a confidence rating scale (1-6). JAFROC analysis required the readers to locate and rate as many suspicious areas as they wished using the same scale and resultant data were used to generate Az and FOM scores for ROC and JAFROC analyses respectively. Using Pearson methods, scores of performance were correlated with 7 reader characteristics recorded using a questionnaire. JAFROC analysis showed that improved reader performance was significantly (p<=0.05) linked with chest specialty (p<0.03), hours per week reading chest radiographs (p<0.03) and chest readings per year (p<0.04). ROC analyses demonstrated only one significant relationship, hours per week reading chest radiographs (p<0.02).The results of this study have shown that radiologist's performance in the detection of pulmonary nodules on radiographs is significantly linked to chest specialty, hours reading per week and number of radiographs read per year. Also, JAFROC is a more powerful predictor of performance as compared to ROC.

Recognition Errors Suggest Fast Familiarity and Slow Recollection in Rhesus Monkeys

ERIC Educational Resources Information Center

Basile, Benjamin M.; Hampton, Robert R.

2013-01-01

One influential model of recognition posits two underlying memory processes: recollection, which is detailed but relatively slow, and familiarity, which is quick but lacks detail. Most of the evidence for this dual-process model in nonhumans has come from analyses of receiver operating characteristic (ROC) curves in rats, but whether ROC analyses…

Beyond ROC Curvature: Strength Effects and Response Time Data Support Continuous-Evidence Models of Recognition Memory

ERIC Educational Resources Information Center

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

2012-01-01

A classic question in the recognition memory literature is whether retrieval is best described as a continuous-evidence process consistent with signal detection theory (SDT), or a threshold process consistent with many multinomial processing tree (MPT) models. Because receiver operating characteristics (ROCs) based on confidence ratings are…

Sensitivity to imputation models and assumptions in receiver operating characteristic analysis with incomplete data

PubMed Central

Karakaya, Jale; Karabulut, Erdem; Yucel, Recai M.

2015-01-01

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. PMID:26379316

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.

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.

Separating Mnemonic Process from Participant and Item Effects in the Assessment of ROC Asymmetries

ERIC Educational Resources Information Center

Pratte, Michael S.; Rouder, Jeffrey N.; Morey, Richard D.

2010-01-01

One of the most influential findings in the study of recognition memory is that receiver operating characteristic (ROC) curves are asymmetric about the negative diagonal. This result has led to the rejection of the equal-variance signal detection model of recognition memory and has provided motivation for more complex models, such as the…

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…

Use of Multiple Metabolic and Genetic Markers to Improve the Prediction of Type 2 Diabetes: the EPIC-Potsdam Study

PubMed Central

Schulze, Matthias B.; Weikert, Cornelia; Pischon, Tobias; Bergmann, Manuela M.; Al-Hasani, Hadi; Schleicher, Erwin; Fritsche, Andreas; Häring, Hans-Ulrich; Boeing, Heiner; Joost, Hans-Georg

2009-01-01

OBJECTIVE We investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors. RESEARCH DESIGN AND METHODS A case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2 diabetes cases identified in the cohort during 7 years of follow-up, 579 remained for analyses after exclusions. Prediction models were compared by receiver operatoring characteristic (ROC) curve and integrated discrimination improvement. RESULTS Case-control discrimination by the lifestyle characteristics (ROC-AUC: 0.8465) improved with plasma glucose (ROC-AUC: 0.8672, P < 0.001) and A1C (ROC-AUC: 0.8859, P < 0.001). ROC-AUC further improved with HDL cholesterol, triglycerides, γ-glutamyltransferase, and alanine aminotransferase (0.9000, P = 0.002). Twenty SNPs did not improve discrimination beyond these characteristics (P = 0.69). CONCLUSIONS Metabolic markers, but not genotyping for 20 diabetogenic SNPs, improve discrimination of incident type 2 diabetes beyond lifestyle risk factors. PMID:19720844

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.

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.

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.

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.

An extension of the receiver operating characteristic curve and AUC-optimal classification.

PubMed

Takenouchi, Takashi; Komori, Osamu; Eguchi, Shinto

2012-10-01

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.

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.

ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves.

PubMed

Carter, Jane V; Pan, Jianmin; Rai, Shesh N; Galandiuk, Susan

2016-06-01

It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine as a means of evaluating diagnostic tests. Sample data from a plasma test for the diagnosis of colorectal cancer were used to generate a prediction model. These are actual, unpublished data that have been used to describe the calculation of sensitivity, specificity, positive predictive and negative predictive values, and accuracy. The ROC curves were generated to determine the accuracy of this plasma test. These curves are generated by plotting the sensitivity (true-positive rate) on the y axis and 1 - specificity (false-positive rate) on the x axis. Curves that approach closest to the coordinate (x = 0, y = 1) are more highly predictive, whereas ROC curves that lie close to the line of equality indicate that the result is no better than that obtained by chance. The optimum sensitivity and specificity can be determined from the graph as the point where the minimum distance line crosses the ROC curve. This point corresponds to the Youden index (J), a function of sensitivity and specificity used commonly to rate diagnostic tests. The area under the curve is used to quantify the overall ability of a test to discriminate between 2 outcomes. By following these simple guidelines, interpretation of ROC curves will be less difficult and they can then be interpreted more reliably when writing, reviewing, or analyzing scientific papers. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Evaluating the Unequal-Variance and Dual-Process Explanations of zROC Slopes with Response Time Data and the Diffusion Model

ERIC Educational Resources Information Center

Starns, Jeffrey J.; Ratcliff, Roger; McKoon, Gail

2012-01-01

We tested two explanations for why the slope of the z-transformed receiver operating characteristic (zROC) is less than 1 in recognition memory: the unequal-variance account (target evidence is more variable than lure evidence) and the dual-process account (responding reflects both a continuous familiarity process and a threshold recollection…

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

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…

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…

The Obsessive Compulsive Scale of the Child Behavior Checklist Predicts Obsessive-Compulsive Disorder: A Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Hudziak, James J.; Althoff, Robert R.; Stanger, Catherine; van Beijsterveldt, C. E. M.; Nelson, Elliot C.; Hanna, Gregory L.; Boomsma, Dorret I.; Todd, Richard D.

2006-01-01

Background: The purpose of this study was to determine a score on the Obsessive Compulsive Scale (OCS) from the Child Behavior Checklist (CBCL) to screen for obsessive compulsive disorder (OCD) in children and to rigorously test the specificity and sensitivity of a single cutpoint. Methods: A receiver operating characteristic (ROC) curve analysis…

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.

Statistical evidences of seismo-ionospheric precursors applying receiver operating characteristic (ROC) curve on the GPS total electron content in China

NASA Astrophysics Data System (ADS)

Chen, Yuh-Ing; Huang, Chi-Shen; Liu, Jann-Yenq

2015-12-01

Evidence of the seismo-ionospheric precursor (SIP) is reported by statistically investigating the relationship between the total electron content (TEC) in global ionosphere map (GIM) and 56 M ⩾ 6.0 earthquakes during 1998-2013 in China. A median-based method together with the z test is employed to examine the TEC variations 30 days before and after the earthquake. It is found that the TEC significantly decreases 0600-1000 LT 1-6 days before the earthquake, and anomalously increases in 3 time periods of 1300-1700 LT 12-15 days; 0000-0500 LT 15-17 days; and 0500-0900 LT 22-28 days before the earthquake. The receiver operating characteristic (ROC) curve is then used to evaluate the efficiency of TEC for predicting M ⩾ 6.0 earthquakes in China during a specified time period. Statistical results suggest that the SIP is the significant TEC reduction in the morning period of 0600-1000 LT. The SIP is further confirmed since the area under the ROC curve is positively associated with the earthquake magnitude.

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.

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).

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry.

PubMed

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

2013-01-01

To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

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.

From Humans to Rats and Back Again: Bridging the Divide between Human and Animal Studies of Recognition Memory with Receiver Operating Characteristics

ERIC Educational Resources Information Center

Koen, Joshua D.; Yonelinas, Andrew P.

2011-01-01

Receiver operating characteristics (ROCs) have been used extensively to study the processes underlying human recognition memory, and this method has recently been applied in studies of rats. However, the extent to which the results from human and animal studies converge is neither entirely clear, nor is it known how the different methods used to…

Optimal threshold estimation for binary classifiers using game theory.

PubMed

Sanchez, Ignacio Enrique

2016-01-01

Many bioinformatics algorithms can be understood as binary classifiers. They are usually compared using the area under the receiver operating characteristic ( ROC ) curve. On the other hand, choosing the best threshold for practical use is a complex task, due to uncertain and context-dependent skews in the abundance of positives in nature and in the yields/costs for correct/incorrect classification. We argue that considering a classifier as a player in a zero-sum game allows us to use the minimax principle from game theory to determine the optimal operating point. The proposed classifier threshold corresponds to the intersection between the ROC curve and the descending diagonal in ROC space and yields a minimax accuracy of 1-FPR. Our proposal can be readily implemented in practice, and reveals that the empirical condition for threshold estimation of "specificity equals sensitivity" maximizes robustness against uncertainties in the abundance of positives in nature and classification costs.

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

Fluorescence spectroscopy for diagnosis of squamous intraepithelial lesions of the cervix.

PubMed

Mitchell, M F; Cantor, S B; Ramanujam, N; Tortolero-Luna, G; Richards-Kortum, R

1999-03-01

To calculate receiver operating characteristic (ROC) curves for fluorescence spectroscopy in order to measure its performance in the diagnosis of squamous intraepithelial lesions (SILs) and to compare these curves with those for other diagnostic methods: colposcopy, cervicography, speculoscopy, Papanicolaou smear screening, and human papillomavirus (HPV) testing. Data from our previous clinical study were used to calculate ROC curves for fluorescence spectroscopy. Curves for other techniques were calculated from other investigators' reports. To identify these, a MEDLINE search for articles published from 1966 to 1996 was carried out, using the search terms "colposcopy," "cervicoscopy," "cervicography," "speculoscopy," "Papanicolaou smear," "HPV testing," "fluorescence spectroscopy," and "polar probe" in conjunction with the terms "diagnosis," "positive predictive value," "negative predictive value," and "receiver operating characteristic curve." We found 270 articles, from which articles were selected if they reported results of studies involving high-disease-prevalence populations, reported findings of studies in which colposcopically directed biopsy was the criterion standard, and included sufficient data for recalculation of the reported sensitivities and specificities. We calculated ROC curves for fluorescence spectroscopy using Bayesian and neural net algorithms. A meta-analytic approach was used to calculate ROC curves for the other techniques. Areas under the curves were calculated. Fluorescence spectroscopy using the neural net algorithm had the highest area under the ROC curve, followed by fluorescence spectroscopy using the Bayesian algorithm, followed by colposcopy, the standard diagnostic technique. Cervicography, Papanicolaou smear screening, and HPV testing performed comparably with each other but not as well as fluorescence spectroscopy and colposcopy. Fluorescence spectroscopy performs better than colposcopy and other techniques in the diagnosis of SILs. Because it also permits real-time diagnosis and has the potential of being used by inexperienced health care personnel, this technology holds bright promise.

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.

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.

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.

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.

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.

ROC curve analyses of eyewitness identification decisions: An analysis of the recent debate.

PubMed

Rotello, Caren M; Chen, Tina

2016-01-01

How should the accuracy of eyewitness identification decisions be measured, so that best practices for identification can be determined? This fundamental question is under intense debate. One side advocates for continued use of a traditional measure of identification accuracy, known as the diagnosticity ratio , whereas the other side argues that receiver operating characteristic curves (ROCs) should be used instead because diagnosticity is confounded with response bias. Diagnosticity proponents have offered several criticisms of ROCs, which we show are either false or irrelevant to the assessment of eyewitness accuracy. We also show that, like diagnosticity, Bayesian measures of identification accuracy confound response bias with witnesses' ability to discriminate guilty from innocent suspects. ROCs are an essential tool for distinguishing memory-based processes from decisional aspects of a response; simulations of different possible identification tasks and response strategies show that they offer important constraints on theory development.

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.

Fair lineups are better than biased lineups and showups, but not because they increase underlying discriminability.

PubMed

Smith, Andrew M; Wells, Gary L; Lindsay, R C L; Penrod, Steven D

2017-04-01

Receiver Operating Characteristic (ROC) analysis has recently come in vogue for assessing the underlying discriminability and the applied utility of lineup procedures. Two primary assumptions underlie recommendations that ROC analysis be used to assess the applied utility of lineup procedures: (a) ROC analysis of lineups measures underlying discriminability, and (b) the procedure that produces superior underlying discriminability produces superior applied utility. These same assumptions underlie a recently derived diagnostic-feature detection theory, a theory of discriminability, intended to explain recent patterns observed in ROC comparisons of lineups. We demonstrate, however, that these assumptions are incorrect when ROC analysis is applied to lineups. We also demonstrate that a structural phenomenon of lineups, differential filler siphoning, and not the psychological phenomenon of diagnostic-feature detection, explains why lineups are superior to showups and why fair lineups are superior to biased lineups. In the process of our proofs, we show that computational simulations have assumed, unrealistically, that all witnesses share exactly the same decision criteria. When criterial variance is included in computational models, differential filler siphoning emerges. The result proves dissociation between ROC curves and underlying discriminability: Higher ROC curves for lineups than for showups and for fair than for biased lineups despite no increase in underlying discriminability. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

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.

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

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.

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

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.

Comparison of two correlated ROC curves at a given specificity or sensitivity level

PubMed Central

Bantis, Leonidas E.; Feng, Ziding

2017-01-01

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 to other known approaches and present a real data application involving prostate cancer screening. PMID:27324068

Neyman-Pearson classification algorithms and NP receiver operating characteristics

PubMed Central

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-01-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies. PMID:29423442

Neyman-Pearson classification algorithms and NP receiver operating characteristics.

PubMed

Tong, Xin; Feng, Yang; Li, Jingyi Jessica

2018-02-01

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (that is, the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (that is, the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, α, on the type I error. Despite its century-long history in hypothesis testing, the NP paradigm has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than α do not satisfy the type I error control objective because the resulting classifiers are likely to have type I errors much larger than α, and the NP paradigm has not been properly implemented in practice. We develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, such as logistic regression, support vector machines, and random forests. Powered by this algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands motivated by the popular ROC curves. NP-ROC bands will help choose α in a data-adaptive way and compare different NP classifiers. We demonstrate the use and properties of the NP umbrella algorithm and NP-ROC bands, available in the R package nproc, through simulation and real data studies.

Bayesian semiparametric estimation of covariate-dependent ROC curves

PubMed Central

Rodríguez, Abel; Martínez, Julissa C.

2014-01-01

Receiver operating characteristic (ROC) curves are widely used to measure the discriminating power of medical tests and other classification procedures. In many practical applications, the performance of these procedures can depend on covariates such as age, naturally leading to a collection of curves associated with different covariate levels. This paper develops a Bayesian heteroscedastic semiparametric regression model and applies it to the estimation of covariate-dependent ROC curves. More specifically, our approach uses Gaussian process priors to model the conditional mean and conditional variance of the biomarker of interest for each of the populations under study. The model is illustrated through an application to the evaluation of prostate-specific antigen for the diagnosis of prostate cancer, which contrasts the performance of our model against alternative models. PMID:24174579

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.

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.

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.

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…

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.

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

PubMed

Lau, Lawrence; Kankanige, Yamuna; Rubinstein, Benjamin; Jones, Robert; Christophi, Christopher; Muralidharan, Vijayaragavan; Bailey, James

2017-04-01

The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritized. An index that is derived to predict graft failure using donor and recipient factors, based on local data sets, will be more beneficial in the Australian context. Liver transplant data from the Austin Hospital, Melbourne, Australia, from 2010 to 2013 has been included in the study. The top 15 donor, recipient, and transplant factors influencing the outcome of graft failure within 30 days were selected using a machine learning methodology. An algorithm predicting the outcome of interest was developed using those factors. Donor Risk Index predicts the outcome with an area under the receiver operating characteristic curve (AUC-ROC) value of 0.680 (95% confidence interval [CI], 0.669-0.690). The combination of the factors used in Donor Risk Index with the model for end-stage liver disease score yields an AUC-ROC of 0.764 (95% CI, 0.756-0.771), whereas survival outcomes after liver transplantation score obtains an AUC-ROC of 0.638 (95% CI, 0.632-0.645). The top 15 donor and recipient characteristics within random forests results in an AUC-ROC of 0.818 (95% CI, 0.812-0.824). Using donor, transplant, and recipient characteristics known at the decision time of a transplant, high accuracy in matching donors and recipients can be achieved, potentially providing assistance with clinical decision making.

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.

Clinical value of the neutrophil/lymphocyte ratio in diagnosing adult strangulated inguinal hernia.

PubMed

Zhou, Huanhao; Ruan, Xiaojiao; Shao, Xia; Huang, Xiaming; Fang, Guan; Zheng, Xiaofeng

2016-12-01

Diagnosis of incarcerated inguinal hernia (IIH) is not difficult, but currently, there are no diagnostic criteria that can be used to differentiate it from strangulated inguinal hernia (SIH). This research aimed to evaluate the clinical value of the neutrophil/lymphocyte ratio (NLR) in diagnosing SIH. We retrospectively analyzed 263 patients with IIH who had undergone emergency operation. The patients were divided into two groups according to IIH severity: group A, patients with pure IIH validated during operation as having no bowel ischemia; group B, patients with SIH validated during operation as having obvious bowel ischemia, including bowel necrosis. We statistically evaluated the relation between several clinical features and SIH. The accuracy of different indices was then evaluated and compared using receiver operating characteristic (ROC) curve analyses, and the corresponding cutoff values were calculated. Univariate analysis showed eight clinical features that were significantly different between the two groups. They were then subjected to multivariate analysis, which showed that the NLR, type of hernia, and incarcerated organ were significantly related to SIH. ROC curve analysis showed that the NLR had the largest area under the ROC curve. Among the different clinical features, the NLR appears to be the best index in diagnosing SIH. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

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.

Homology search with binary and trinary scoring matrices.

PubMed

Smith, Scott F

2006-01-01

Protein homology search can be accelerated with the use of bit-parallel algorithms in conjunction with constraints on the values contained in the scoring matrices. Trinary scoring matrices (containing only the values -1, 0, and 1) allow for significant acceleration without significant reduction in the receiver operating characteristic (ROC) score of a Smith-Waterman search. Binary scoring matrices (containing the values 0 and 1) result in some reduction in ROC score, but result in even more acceleration. Binary scoring matrices and five-bit saturating scores can be used for fast prefilters to the Smith-Waterman algorithm.

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.

ROC curves predicted by a model of visual search.

PubMed

Chakraborty, D P

2006-07-21

In imaging tasks where the observer is uncertain whether lesions are present, and where they could be present, the image is searched for lesions. In the free-response paradigm, which closely reflects this task, the observer provides data in the form of a variable number of mark-rating pairs per image. In a companion paper a statistical model of visual search has been proposed that has parameters characterizing the perceived lesion signal-to-noise ratio, the ability of the observer to avoid marking non-lesion locations, and the ability of the observer to find lesions. The aim of this work is to relate the search model parameters to receiver operating characteristic (ROC) curves that would result if the observer reported the rating of the most suspicious finding on an image as the overall rating. Also presented are the probability density functions (pdfs) of the underlying latent decision variables corresponding to the highest rating for normal and abnormal images. The search-model-predicted ROC curves are 'proper' in the sense of never crossing the chance diagonal and the slope is monotonically changing. They also have the interesting property of not allowing the observer to move the operating point continuously from the origin to (1, 1). For certain choices of parameters the operating points are predicted to be clustered near the initial steep region of the curve, as has been observed by other investigators. The pdfs are non-Gaussians, markedly so for the abnormal images and for certain choices of parameter values, and provide an explanation for the well-known observation that experimental ROC data generally imply a wider pdf for abnormal images than for normal images. Some features of search-model-predicted ROC curves and pdfs resemble those predicted by the contaminated binormal model, but there are significant differences. The search model appears to provide physical explanations for several aspects of experimental ROC curves.

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.

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.

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

Incidental Context Information Increases Recollection

ERIC Educational Resources Information Center

Ameen-Ali, Kamar E.; Norman, Liam J.; Eacott, Madeline J.; Easton, Alexander

2017-01-01

The current study describes a receiver-operating characteristic (ROC) task for human participants based on the spontaneous recognition memory paradigms typically used with rodents. Recollection was significantly higher when an object was in the same location and background as at encoding, a combination used to assess episodic-like memory in…

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.

[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.

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.

Diagnostic Utility of the Social Skills Improvement System Performance Screening Guide

ERIC Educational Resources Information Center

Krach, S. Kathleen; McCreery, Michael P.; Wang, Ye; Mohammadiamin, Houra; Cirks, Christen K.

2017-01-01

Researchers investigated the diagnostic utility of the Social Skills Improvement System: Performance Screening Guide (SSIS-PSG). Correlational, regression, receiver operating characteristic (ROC), and conditional probability analyses were run to compare ratings on the SSIS-PSG subscales of Prosocial Behavior, Reading Skills, and Math Skills, to…

Testing a Neurocomputational Model of Recollection, Familiarity, and Source Recognition

ERIC Educational Resources Information Center

Elfman, Kane W.; Parks, Colleen M.; Yonelinas, Andrew P.

2008-01-01

The authors assess whether the complementary learning systems model of the medial temporal lobes (Norman & O'Reilly, 2003) is able to account for source recognition receiver operating characteristics (ROCs). The model assumes that recognition reflects the contribution of a hippocampally mediated recollection process and a cortically mediated…

Recognition Memory: Adding a Response Deadline Eliminates Recollection but Spares Familiarity

ERIC Educational Resources Information Center

Sauvage, Magdalena M.; Beer, Zachery; Eichenbaum, Howard

2010-01-01

A current controversy in memory research concerns whether recognition is supported by distinct processes of familiarity and recollection, or instead by a single process wherein familiarity and recollection reflect weak and strong memories, respectively. Recent studies using receiver operating characteristic (ROC) analyses in an animal model have…

The Variance Reaction Time Model

ERIC Educational Resources Information Center

Sikstrom, Sverker

2004-01-01

The variance reaction time model (VRTM) is proposed to account for various recognition data on reaction time, the mirror effect, receiver-operating-characteristic (ROC) curves, etc. The model is based on simple and plausible assumptions within a neural network: VRTM is a two layer neural network where one layer represents items and one layer…

Visualization of the significance of Receiver Operating Characteristics based on confidence ellipses

NASA Astrophysics Data System (ADS)

Sarlis, Nicholas V.; Christopoulos, Stavros-Richard G.

2014-03-01

The Receiver Operating Characteristics (ROC) is used for the evaluation of prediction methods in various disciplines like meteorology, geophysics, complex system physics, medicine etc. The estimation of the significance of a binary prediction method, however, remains a cumbersome task and is usually done by repeating the calculations by Monte Carlo. The FORTRAN code provided here simplifies this problem by evaluating the significance of binary predictions for a family of ellipses which are based on confidence ellipses and cover the whole ROC space. Catalogue identifier: AERY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERY_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 11511 No. of bytes in distributed program, including test data, etc.: 72906 Distribution format: tar.gz Programming language: FORTRAN. Computer: Any computer supporting a GNU FORTRAN compiler. Operating system: Linux, MacOS, Windows. RAM: 1Mbyte Classification: 4.13, 9, 14. Nature of problem: The Receiver Operating Characteristics (ROC) is used for the evaluation of prediction methods in various disciplines like meteorology, geophysics, complex system physics, medicine etc. The estimation of the significance of a binary prediction method, however, remains a cumbersome task and is usually done by repeating the calculations by Monte Carlo. The FORTRAN code provided here simplifies this problem by evaluating the significance of binary predictions for a family of ellipses which are based on confidence ellipses and cover the whole ROC space. Solution method: Using the statistics of random binary predictions for a given value of the predictor threshold ɛt, one can construct the corresponding confidence ellipses. The envelope of these corresponding confidence ellipses is estimated when ɛt varies from 0 to 1. This way a new family of ellipses is obtained, named k-ellipses, which covers the whole ROC plane and leads to a well defined Area Under the Curve (AUC). For the latter quantity, Mason and Graham [1] have shown that it follows the Mann-Whitney U-statistics [2] which can be applied [3] for the estimation of the statistical significance of each k-ellipse. As the transformation is invertible, any point on the ROC plane corresponds to a unique value of k, thus to a unique p-value to obtain this point by chance. The present FORTRAN code provides this p-value field on the ROC plane as well as the k-ellipses corresponding to the (p=)10%, 5% and 1% significance levels using as input the number of the positive (P) and negative (Q) cases to be predicted. Unusual features: In some machines, the compiler directive -O2 or -O3 should be used to avoid NaN’s in some points of the p-field along the diagonal. Running time: Depending on the application, e.g., 4s for an Intel(R) Core(TM)2 CPU E7600 at 3.06 GHz with 2 GB RAM for the examples presented here References: [1] S.J. Mason, N.E. Graham, Quart. J. Roy. Meteor. Soc. 128 (2002) 2145. [2] H.B. Mann, D.R. Whitney, Ann. Math. Statist. 18 (1947) 50. [3] L.C. Dinneen, B.C. Blakesley, J. Roy. Stat. Soc. Ser. C Appl. Stat. 22 (1973) 269.

First trimester prediction of maternal glycemic status.

PubMed

Gabbay-Benziv, Rinat; Doyle, Lauren E; Blitzer, Miriam; Baschat, Ahmet A

2015-05-01

To predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics. We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state. Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC - area under the curve 0.819, CI - confidence interval 0.769-0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668-0.746). GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

Estimating the relative utility of screening mammography.

PubMed

Abbey, Craig K; Eckstein, Miguel P; Boone, John M

2013-05-01

The concept of diagnostic utility is a fundamental component of signal detection theory, going back to some of its earliest works. Attaching utility values to the various possible outcomes of a diagnostic test should, in principle, lead to meaningful approaches to evaluating and comparing such systems. However, in many areas of medical imaging, utility is not used because it is presumed to be unknown. In this work, we estimate relative utility (the utility benefit of a detection relative to that of a correct rejection) for screening mammography using its known relation to the slope of a receiver operating characteristic (ROC) curve at the optimal operating point. The approach assumes that the clinical operating point is optimal for the goal of maximizing expected utility and therefore the slope at this point implies a value of relative utility for the diagnostic task, for known disease prevalence. We examine utility estimation in the context of screening mammography using the Digital Mammographic Imaging Screening Trials (DMIST) data. We show how various conditions can influence the estimated relative utility, including characteristics of the rating scale, verification time, probability model, and scope of the ROC curve fit. Relative utility estimates range from 66 to 227. We argue for one particular set of conditions that results in a relative utility estimate of 162 (±14%). This is broadly consistent with values in screening mammography determined previously by other means. At the disease prevalence found in the DMIST study (0.59% at 365-day verification), optimal ROC slopes are near unity, suggesting that utility-based assessments of screening mammography will be similar to those found using Youden's index.

Exploration of Analysis Methods for Diagnostic Imaging Tests: Problems with ROC AUC and Confidence Scores in CT Colonography

PubMed Central

Mallett, Susan; Halligan, Steve; Collins, Gary S.; Altman, Doug G.

2014-01-01

Background Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. Methods In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Results Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. Conclusions The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests. PMID:25353643

Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography.

PubMed

Mallett, Susan; Halligan, Steve; Collins, Gary S; Altman, Doug G

2014-01-01

Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.

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.

Meta-analysis of Diagnostic Accuracy and ROC Curves with Covariate Adjusted Semiparametric Mixtures.

PubMed

Doebler, Philipp; Holling, Heinz

2015-12-01

Many screening tests dichotomize a measurement to classify subjects. Typically a cut-off value is chosen in a way that allows identification of an acceptable number of cases relative to a reference procedure, but does not produce too many false positives at the same time. Thus for the same sample many pairs of sensitivities and false positive rates result as the cut-off is varied. The curve of these points is called the receiver operating characteristic (ROC) curve. One goal of diagnostic meta-analysis is to integrate ROC curves and arrive at a summary ROC (SROC) curve. Holling, Böhning, and Böhning (Psychometrika 77:106-126, 2012a) demonstrated that finite semiparametric mixtures can describe the heterogeneity in a sample of Lehmann ROC curves well; this approach leads to clusters of SROC curves of a particular shape. We extend this work with the help of the [Formula: see text] transformation, a flexible family of transformations for proportions. A collection of SROC curves is constructed that approximately contains the Lehmann family but in addition allows the modeling of shapes beyond the Lehmann ROC curves. We introduce two rationales for determining the shape from the data. Using the fact that each curve corresponds to a natural univariate measure of diagnostic accuracy, we show how covariate adjusted mixtures lead to a meta-regression on SROC curves. Three worked examples illustrate the method.

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/ .

Spatiotemporal correlation of optical coherence tomography in-vivo images of rabbit airway for the diagnosis of edema

NASA Astrophysics Data System (ADS)

Kang, DongYel; Wang, Alex; Volgger, Veronika; Chen, Zhongping; Wong, Brian J. F.

2015-07-01

Detection of an early stage of subglottic edema is vital for airway management and prevention of stenosis, a life-threatening condition in critically ill neonates. As an observer for the task of diagnosing edema in vivo, we investigated spatiotemporal correlation (STC) of full-range optical coherence tomography (OCT) images acquired in the rabbit airway with experimentally simulated edema. Operating the STC observer on OCT images generates STC coefficients as test statistics for the statistical decision task. Resulting from this, the receiver operating characteristic (ROC) curves for the diagnosis of airway edema with full-range OCT in-vivo images were extracted and areas under ROC curves were calculated. These statistically quantified results demonstrated the potential clinical feasibility of the STC method as a means to identify early airway edema.

Validation of a Competitive Enzyme-Linked Immunosorbent Assay for Detection of Babesia bigemina Antibodies in Cattle

USDA-ARS?s Scientific Manuscript database

A competitive ELISA (cELISA) based on a broadly conserved, species-specific, B-cell epitope within the C-terminus of Babesia bigemina rhoptry-associated protein-1a was validated for international use. Receiver Operating Characteristic (ROC) analysis revealed 16% inhibition as the threshold for a neg...

Examining Classification Criteria: A Comparison of Three Cut Score Methods

ERIC Educational Resources Information Center

DiStefano, Christine; Morgan, Grant

2011-01-01

This study compared 3 different methods of creating cut scores for a screening instrument, T scores, receiver operating characteristic curve (ROC) analysis, and the Rasch rating scale method (RSM), for use with the Behavioral and Emotional Screening System (BESS) Teacher Rating Scale for Children and Adolescents (Kamphaus & Reynolds, 2007).…

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…

Use of the Child Behavior Checklist as a Diagnostic Screening Tool in Community Mental Health

ERIC Educational Resources Information Center

Rishel, Carrie W.; Greeno, Catherine; Marcus, Steven C.; Shear, M. Katherine; Anderson, Carol

2005-01-01

Objective: This study examines whether the Child Behavior Checklist (CBCL) can be used as an accurate psychiatric screening tool for children in community mental health settings. Method: Associations, logistic regression models, and receiver operating characteristic (ROC) analysis were used to test the predictive relationship between the CBCL and…

Investigating Strength and Frequency Effects in Recognition Memory Using Type-2 Signal Detection Theory

ERIC Educational Resources Information Center

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…

International ring trial to detect anti-Trichinella IgG by ELISA on pig sera.

USDA-ARS?s Scientific Manuscript database

In the present study, the sensitivity and specificity of the ELISA assay determined by the CRLP validation was 100% and 98.29%, respectively. The assay was reproducible, moreover, based on the receiver-operator characteristic (ROC) curve, the sensitivity and specificity of the assay reached 97.5% an...

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.

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.

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 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.

Assessing Internalizing, Externalizing, and Attention Problems in Young Children: Validation of the MacArthur HBQ

ERIC Educational Resources Information Center

Lemery-Chalfant, Kathryn; Schreiber, Jane E.; Schmidt, Nicole L.; Van Hulle, Carol A.; Essex, Marilyn J.; Goldsmith, H. H.

2007-01-01

Objective: To test the validity of the MacArthur Health and Behavior Questionnaire (HBQ) using receiver operating characteristic (ROC) analysis to determine optimal thresholds for the HBQ in predicting Diagnostic Interview Schedule for Children Version-IV (DISC-IV)diagnoses. The roles of child sex, level of impairment, and physical health in…

Some Memories Are Odder than Others: Judgments of Episodic Oddity Violate Known Decision Rules

ERIC Educational Resources Information Center

O'Connor, Akira R.; Guhl, Emily N.; Cox, Justin C.; Dobbins, Ian G.

2011-01-01

Current decision models of recognition memory are based almost entirely on one paradigm, single item old/new judgments accompanied by confidence ratings. This task results in receiver operating characteristics (ROCs) that are well fit by both signal-detection and dual-process models. Here we examine an entirely new recognition task, the judgment…

The Relation between DIBELS, Reading Comprehension, and Vocabulary in Urban First-Grade Students

ERIC Educational Resources Information Center

Riedel, Brant W.

2007-01-01

The relation between Dynamic Indicators of Basic Early Literacy Skills (DIBELS) and reading comprehension at the end of first grade and second grade was examined in a sample of 1,518 first-grade students from a large urban school district. Receiver Operating Characteristic (ROC) analyses were used to determine optimal DIBELS cut scores for…

Three Tests and Three Corrections: Comment on Koen and Yonelinas (2010)

ERIC Educational Resources Information Center

Jang, Yoonhee; Mickes, Laura; Wixted, John T.

2012-01-01

The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory experiments is usually less than 1, which has long been interpreted to mean that the variance of the target distribution is greater than the variance of the lure distribution. The greater variance of the target distribution could arise because the…

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).

Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

PubMed

Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

2016-03-15

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Assessing multiple-group diagnostic problems with multi-dimensional receiver operating characteristic surfaces: Application to proton MR Spectroscopy (MRS) in HIV-related neurological injury

PubMed Central

Yiannoutsos, Constantin T.; Nakas, Christos T.; Navia, Bradford A.

2013-01-01

We present the multi-dimensional Receiver Operating Characteristic (ROC) surface, a plot of the true classification rates of tests based on levels of biological markers, for multi-group discrimination, as an extension of the ROC curve, commonly used in two-group diagnostic testing. The volume under this surface (VUS) is a global accuracy measure of a test to classify subjects in multiple groups and useful to detect trends in marker measurements. We used three-dimensional ROC surfaces, and associated VUS, to discriminate between HIV-negative (NEG), HIV-positive neurologically asymptomatic (NAS) subjects and patients with AIDS demential complex (ADC), using brain metabolites measured by proton MRS. These were ratios of markers of inflammation, Choline (Cho) and myoinositol (MI), and brain injury, N-acetyl aspartate (NAA), divided by Creatine (Cr), measured in the basal ganglia and the frontal white matter. Statistically significant trends were observed in the three groups with respect to MI/Cr (VUS=0.43; 95% confidence interval (CI) 0.33-0.53), Cho/Cr (0.36; 0.27-0.45) in the basal ganglia and NAA/Cr in the frontal white matter (FWM) (0.29; 0.20-0.38), suggesting a continuum of injury during the neurologically asymptomatic stage of HIV infection, particularly with respect to brain inflammation. Adjusting for age increased the combined classification accuracy of age and NAA/Cr (p=0.053). Pairwise comparisons suggested that neuronal damage associated with NAA/Cr decreases was mainly observed in individuals with ADC, raising issues of synergism between HIV infection and age and possible acceleration of neurological deterioration in an aging HIV-positive population. The three-dimensional ROC surface and its associated VUS are useful for assessing marker accuracy, detecting data trends and offering insight in disease processes affecting multiple groups. PMID:18191586

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.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

Discriminating Famous from Fictional Names Based on Lifetime Experience: Evidence in Support of a Signal-Detection Model Based on Finite Mixture Distributions

ERIC Educational Resources Information Center

Bowles, Ben; Harlow, Iain M.; Meeking, Melissa M.; Kohler, Stefan

2012-01-01

It is widely accepted that signal-detection mechanisms contribute to item-recognition memory decisions that involve discriminations between targets and lures based on a controlled laboratory study episode. Here, the authors employed mathematical modeling of receiver operating characteristics (ROC) to determine whether and how a signal-detection…

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.

Assessing the Belief Bias Effect with ROCs: Reply to Dube, Rotello, and Heit (2010)

ERIC Educational Resources Information Center

Klauer, Karl Christoph; Kellen, David

2011-01-01

Dube, Rotello, and Heit (2010) argued (a) that the so-called receiver operating characteristic is nonlinear for data on belief bias in syllogistic reasoning; (b) that their data are inconsistent with Klauer, Musch, and Naumer's (2000) model of belief bias; (c) that their data are inconsistent with any of the existing accounts of belief bias and…

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma.

PubMed

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian J; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F; Chen, Teresa C

2017-06-01

To determine the diagnostic capability of spectral domain optical coherence tomography peripapillary retinal volume (RV) measurements. A total of 156 patients, 89 primary open-angle glaucoma and 67 normal subjects, were recruited. Spectral domain optical coherence tomography peripapillary RV was calculated for 4 quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing primary open-angle glaucoma. The pairwise comparisons of the best ROC curves for RV and retinal nerve fiber layer (RNFL) were performed. The artifact rates were analyzed. Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (P<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (P=0.0033). The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. RV measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable with that of RNFL parameters in glaucoma but with lower artifact rates.

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma

PubMed Central

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian John; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F.; Chen, Teresa C.

2017-01-01

Purpose To determine the diagnostic capability of spectral domain optical coherence tomography (SD-OCT) peripapillary retinal volume (RV) measurements. Materials and Methods A total of 156 patients, 89 primary open angle (POAG) and 67 normal subjects, were recruited. SD-OCT peripapillary RV was calculated for four quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic (AUROC) curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing POAG. The pairwise comparisons of the best ROC curves for RV and RNFL were performed. The artifact rates were analyzed. Results Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (p<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (p=0.0033).The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. Retinal volume measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Conclusion Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable to that of RNFL parameters in glaucoma but with lower artifact rates. PMID:28079657

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities.

PubMed

Cheung, Rex

2016-01-01

This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

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

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.

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.

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

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.

Objective Assessment of Image Quality VI: Imaging in Radiation Therapy

PubMed Central

Barrett, Harrison H.; Kupinski, Matthew A.; Müeller, Stefan; Halpern, Howard J.; Morris, John C.; Dwyer, Roisin

2015-01-01

Earlier work on Objective Assessment of Image Quality (OAIQ) focused largely on estimation or classification tasks in which the desired outcome of imaging is accurate diagnosis. This paper develops a general framework for assessing imaging quality on the basis of therapeutic outcomes rather than diagnostic performance. By analogy to Receiver Operating Characteristic (ROC) curves and their variants as used in diagnostic OAIQ, the method proposed here utilizes the Therapy Operating Characteristic or TOC curves, which are plots of the probability of tumor control vs. the probability of normal-tissue complications as the overall dose level of a radiotherapy treatment is varied. The proposed figure of merit is the area under the TOC curve, denoted AUTOC. This paper reviews an earlier exposition of the theory of TOC and AUTOC, which was specific to the assessment of image-segmentation algorithms, and extends it to other applications of imaging in external-beam radiation treatment as well as in treatment with internal radioactive sources. For each application, a methodology for computing the TOC is presented. A key difference between ROC and TOC is that the latter can be defined for a single patient rather than a population of patients. PMID:24200954

Computed tomographic (CT) neuroradiological evaluation of intra-axial and extra-axial lesions: a receiver operating characteristic (ROC) study of film and 1K workstation

NASA Astrophysics Data System (ADS)

El-Saden, Suzie; Hademenos, George J.; Zhu, Wei; Sayre, James W.; Glenn, Brad; Steidler, Jim; Kode, L.; King, Brian; Quinones, Diana; Valentino, Daniel J.; Bentsen, John R.

1995-04-01

Digital display workstations are now commonly used for cross-sectional image viewing; however, few receiver operating characteristic (ROC) studies have been performed to evaluate the diagnostic efficiency of hard copy versus a workstation display for neuroradiology applications. We have performed an ROC study of film and 1K workstation based on the diagnostic performance of neuroradiology fellows to detect subtle intra- axial (high density (HD) and low density (LD)) and extra-axial (fluid, blood) lesions presented on computed tomographic (CT) images. An ROC analysis of the interpretation of approximately 200 CT images (1/2 normals and 1/2 abnormals) was performed by five experienced observers. The total number of abnormal images were equally divided among the three represented types of lesions (HD, LD, and extra-axial lesions). The images comprising the extra-axial lesion group were further subdivided into the following three distinct types: subdural hemorrhage, subarachnoid hemorrhage, and epidural hemorrhage. A fraction of the abnormal images were represented by more than one type of lesion, e.g., one abnormal image could contain both a HD and LD lesion. The digitized CT images were separated into four groups and read on the standard light box and a 1K workstation monitor equipped with simple image processing functions. Confidence ratings were scaled on a range from 0 (least confident) to 4 (most confident). Reader order sequences were randomized for each reader and for each modality. Each observer read from a total of eight different groups with a four-week intermission following the fourth group. The randomly assigned image number, lesion type and approximate location, incidental findings and comments, and confidence ratings were reported in individual worksheets for each image. ROC curves that were generated and analyzed for the various subgroups are presented in addition to the overall generalized jackknifed estimates of the grouped data. Also, 95% confidence intervals are presented for the differences in the area under the ROC curves. Although there were no statistically significant differences in the diagnostic accuracy between the original CT slice with HD and LD lesions viewed on the light box and on the 1K display workstation, the observers tended to record extra- axial lesions more frequently and with more confidence on the 1K display in comparison to the light box primarily due to the added advantage of adjusting the display window levels.

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.

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

Efficient cost-sensitive human-machine collaboration for offline signature verification

NASA Astrophysics Data System (ADS)

Coetzer, Johannes; Swanepoel, Jacques; Sabourin, Robert

2012-01-01

We propose a novel strategy for the optimal combination of human and machine decisions in a cost-sensitive environment. The proposed algorithm should be especially beneficial to financial institutions where off-line signatures, each associated with a specific transaction value, require authentication. When presented with a collection of genuine and fraudulent training signatures, produced by so-called guinea pig writers, the proficiency of a workforce of human employees and a score-generating machine can be estimated and represented in receiver operating characteristic (ROC) space. Using a set of Boolean fusion functions, the majority vote decision of the human workforce is combined with each threshold-specific machine-generated decision. The performance of the candidate ensembles is estimated and represented in ROC space, after which only the optimal ensembles and associated decision trees are retained. When presented with a questioned signature linked to an arbitrary writer, the system first uses the ROC-based cost gradient associated with the transaction value to select the ensemble that minimises the expected cost, and then uses the corresponding decision tree to authenticate the signature in question. We show that, when utilising the entire human workforce, the incorporation of a machine streamlines the authentication process and decreases the expected cost for all operating conditions.

Basic concepts and development of an all-purpose computer interface for ROC/FROC observer study.

PubMed

Shiraishi, Junji; Fukuoka, Daisuke; Hara, Takeshi; Abe, Hiroyuki

2013-01-01

In this study, we initially investigated various aspects of requirements for a computer interface employed in receiver operating characteristic (ROC) and free-response ROC (FROC) observer studies which involve digital images and ratings obtained by observers (radiologists). Secondly, by taking into account these aspects, an all-purpose computer interface utilized for these observer performance studies was developed. Basically, the observer studies can be classified into three paradigms, such as one rating for one case without an identification of a signal location, one rating for one case with an identification of a signal location, and multiple ratings for one case with identification of signal locations. For these paradigms, display modes on the computer interface can be used for single/multiple views of a static image, continuous viewing with cascade images (i.e., CT, MRI), and dynamic viewing of movies (i.e., DSA, ultrasound). Various functions on these display modes, which include windowing (contrast/level), magnifications, and annotations, are needed to be selected by an experimenter corresponding to the purpose of the research. In addition, the rules of judgment for distinguishing between true positives and false positives are an important factor for estimating diagnostic accuracy in an observer study. We developed a computer interface which runs on a Windows operating system by taking into account all aspects required for various observer studies. This computer interface requires experimenters to have sufficient knowledge about ROC/FROC observer studies, but allows its use for any purpose of the observer studies. This computer interface will be distributed publicly in the near future.

Increasing time to postoperative stereotactic radiation therapy for patients with resected brain metastases: investigating clinical outcomes and identifying predictors associated with time to initiation.

PubMed

Yusuf, Mehran B; Amsbaugh, Mark J; Burton, Eric; Nelson, Megan; Williams, Brian; Koutourousiou, Maria; Nauta, Haring; Woo, Shiao

2018-02-01

We sought to determine the impact of time to initiation (TTI) of post-operative radiosurgery on clinical outcomes for patients with resected brain metastases and to identify predictors associated with TTI. All patients with resected brain metastases treated with postoperative SRS or fractionated stereotactic radiation therapy (fSRT) from 2012 to 2016 at a single institution were reviewed. TTI was defined as the interval from resection to first day of radiosurgery. Receiver operating characteristic (ROC) curves were used to identify an optimal threshold for TTI with respect to local failure (LF). Survival outcomes were estimated using the Kaplan-Meier method and analyzed using the log-rank test and Cox proportional hazards models. Logistic regression models were used to identify factors associated with ROC-determined TTI covariates. A total of 79 resected lesions from 73 patients were evaluated. An ROC curve of LF and TTI identified an optimal threshold for TTI of 30.5 days, with an area under the curve of 0.637. TTI > 30 days was associated with an increased hazard of LF (HR 4.525, CI 1.239-16.527) but was not significantly associated with survival (HR 1.002, CI 0.547-1.823) or distant brain failure (DBF, HR 1.943, CI 0.989-3.816). Fifteen patients (20.5%) required post-operative inpatient rehabilitation. Post-operative rehabilitation was associated with TTI > 30 days (OR 1.48, CI 1.142-1.922). In our study of resected brain metastases, longer time to initiation of post-operative radiosurgery was associated with increased local failure. Ideally, post-op SRS should be initiated within 30 days of resection if feasible.

Immunohistochemistry of cytokeratins 7, 8, 17, 18, and 19, and GLUT-1 aids differentiation of desmoplastic malignant mesothelioma from fibrous pleuritis.

PubMed

Horiuchi, Toshikatsu; Ogata, Sho; Tominaga, Susumu; Hiroi, Sadayuki; Kawahara, Kunimitsu; Hebisawa, Akira; Irei, Isao; Ito, Ichiro; Kameya, Toru; Tsujimura, Tohru; Nakano, Takashi; Nakanishi, Kuniaki; Kawai, Toshiaki

2013-05-01

It is difficult to distinguish desmoplastic malignant mesothelioma (DMM) from fibrous pleuritis (FP). We investigated the utility of immunohistochemistry as a way of differentiating between DMM and FP. We examined 11 DMMs and 46 FPs with the aid of antibodies against 18 cytokeratin (CK) subtypes, calponin, caldesmon, desmin, and GLUT-1. The best sensitivity and specificity cut-off values in the receiver operating characteristic curves (ROC) for CKs 7, 8, 17, 18, and 19, and GLUT-1 were each above 60%. When cases with either DMM or FP were partitioned by the staining score associated with the best sensitivity and specificity cut-off values in ROC, the incidence of a positive expression for CKs 7, 8, 17, 18, and 19, and GLUT-1 was significantly higher in DMM than in FP. In conclusion, immunohistochemistry for CKs 7, 8, 17, 18, and 19, and GLUT-1 may be useful, alongside histological characteristics, for separating DMM from FP.

PET-CT Animal Model for Surveillance of Embedded Metal Fragments

DTIC Science & Technology

2012-12-15

area under the curve ( AUC ) were calculated. Significance level was set at p < .05. Histopathology was assessed by a pathologist, blinded to...were determined. Receiver Operating Characteristic (ROC) curve and the area under the curve ( AUC ) were calculated. Significance...False negatives 10 Principal Investigator (Shinn, Antoinette, Marie) USU Project Number: N11-C18 The area under the curve ( AUC ) was 0.938

Spectral Detection of Acute Mental Stress with VIS-SWIR Hyperspectral Imagery

DTIC Science & Technology

2013-03-01

collected with a contact probe. The variance of “stress” (red solid lines) is lower on average than “non-stress” (blue dashed lines) because the HRV ...6 ROC Receiver Operating Characteristic . . . . . . . . . . . . . . . . . . . . . 6 HRV Heart Rate Variability...systems. A stressor involving the cognitive system manifests 7 in the form of anxiety , for example, the reaction to a quiz or speech, whereas a

Receiver Operating Characteristic curves of the seismo-ionospheric precursors in GIM TEC associated with magnitude greater than 6.0 earthquakes in China during 1998-2013.

NASA Astrophysics Data System (ADS)

Huang, C. H.; Chen, Y. I.; Liu, J. Y. G.; Huang, Y. H.

2014-12-01

Statistical evidence of the Seismo-Ionospheric Precursors (SIPs) is reported by statistically investigating the relationship between the Total Electron Content (TEC) in Global Ionosphere Map (GIM) and 56 M≥6.0 earthquakes during 1998-2013 in China. A median-based method and a z test are employed to detect the overall earthquake signatures. It is found that a reduction of positive signatures and an enhancement of negative signatures appear simultaneously on 3-5 days prior to the earthquakes in China. Finally, receiver operating characteristic (ROC) curves are used to measure the power of TEC for predicting M≥6.0 earthquakes in China.

Assessment of insulin sensitivity by the hyperinsulinemic euglycemic clamp: Comparison with the spectral analysis of photoplethysmography.

PubMed

De Souza, Aglecio Luiz; Batista, Gisele Almeida; Alegre, Sarah Monte

2017-01-01

We compare spectral analysis of photoplethysmography (PTG) with insulin resistance measured by the hyperinsulinemic euglycemic clamp (HEC) technique. A total of 100 nondiabetic subjects, 43 men and 57 women aged 20-63years, 30 lean, 42 overweight and 28 obese were enrolled in the study. These patients underwent an examination with HEC, and an examination with the PTG spectral analysis and calculation of the PTG Total Power (PTG-TP). Receiver-operating characteristic (ROC) curves were constructed to determine the specificity and sensitivity of PTG-TP in the assessment of insulin resistance. There is a moderate correlation between insulin sensitivity (M-value) and PTG-TP (r=- 0.64, p<0.0001). The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP>406.2. This cut-off had a sensitivity=95.7%, specificity =84,4% and the area under the ROC curve (AUC)=0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p<0.0001). The use of the PTG-TP marker measured from the PTG spectral analysis is a useful tool in screening and follow up of IR, especially in large-scale studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea

NASA Astrophysics Data System (ADS)

Kim, M. S.; Onda, Y.; Kim, J. K.

2015-01-01

SHALSTAB model applied to shallow landslides induced by rainfall to evaluate soil properties related with the effect of soil depth for a granite area in Jinbu region, Republic of Korea. Soil depth measured by a knocking pole test and two soil parameters from direct shear test (a and b) as well as one soil parameters from a triaxial compression test (c) were collected to determine the input parameters for the model. Experimental soil data were used for the first simulation (Case I) and, soil data represented the effect of measured soil depth and average soil depth from soil data of Case I were used in the second (Case II) and third simulations (Case III), respectively. All simulations were analysed using receiver operating characteristic (ROC) analysis to determine the accuracy of prediction. ROC analysis results for first simulation showed the low ROC values under 0.75 may be due to the internal friction angle and particularly the cohesion value. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. The accuracy of Case II and Case III using ROC analysis showed higher accuracy values rather than first simulation. Our results clearly demonstrate that the accuracy of shallow landslide prediction can be improved when soil parameters represented the effect of soil thickness.

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.

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.

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.

Differentiation between microcystin contaminated and uncontaminated fish by determination of unconjugated MCs using an ELISA anti-Adda test based on receiver-operating characteristic curves threshold values: application to Tinca tinca from natural ponds.

PubMed

Moreno, Isabel María; Herrador, M Ángeles; Atencio, Loyda; Puerto, María; González, A Gustavo; Cameán, Ana María

2011-02-01

The aim of this study was to evaluate whether the enzyme-linked immunosorbent assay (ELISA) anti-Adda technique could be used to monitor free microcystins (MCs) in biological samples from fish naturally exposed to toxic cyanobacteria by using receiver operating characteristic (ROC) curve software to establish an optimal cut-off value for MCs. The cut-off value determined by ROC curve analysis in tench (Tinca tinca) exposed to MCs under laboratory conditions by ROC curve analysis was 5.90-μg MCs/kg tissue dry weight (d.w.) with a sensitivity of 93.3%. This value was applied in fish samples from natural ponds (Extremadura, Spain) in order to asses its potential MCs bioaccumulation by classifying samples as either true positive (TP), false positive (FP), true negative (TN), or false negative (FN). In this work, it has been demonstrated that toxic cyanobacteria, mainly Microcystis aeruginosa, Aphanizomenon issatchenkoi, and Anabaena spiroides, were present in two of these ponds, Barruecos de Abajo (BDown) and Barruecos de Arriba (BUp). The MCs levels were detected in waters from both ponds with an anti-MC-LR ELISA immunoassay and were of similar values (between 3.8-6.5-μg MC-LR equivalent/L in BDown pond and 4.8-6.0-μg MC-LR equivalent/L in BUp). The MCs cut-off values were applied in livers from fish collected from these two ponds using the ELISA anti-Adda technique. A total of 83% of samples from BDown pond and only 42% from BUp were TP with values of free MCs higher than 8.8-μg MCs/kg tissue (d.w.). Copyright © 2009 Wiley Periodicals, Inc.

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.

A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method.

PubMed

Zou, Kelly H; Resnic, Frederic S; Talos, Ion-Florin; Goldberg-Zimring, Daniel; Bhagwat, Jui G; Haker, Steven J; Kikinis, Ron; Jolesz, Ferenc A; Ohno-Machado, Lucila

2005-10-01

Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported. In the interventional cardiology example, logit and Box-Cox transformations of the predictive probabilities led to satisfactory AUCs (AUC=0.888; p=0.78, and AUC=0.888; p=0.73, respectively), while in the brain tumor resection example, log and Box-Cox transformations of the tumor size also led to satisfactory AUCs (AUC=0.898; p=0.61, and AUC=0.899; p=0.42, respectively). In contrast, significant departures from GOF were observed without applying any transformation prior to assuming a binormal model (AUC=0.766; p=0.004, and AUC=0.831; p=0.03), respectively. In both studies the p values suggested that transformations were important to consider before applying any binormal model to estimate the AUC. Our analyses also demonstrated and confirmed the predictive values of different classifiers for determining the interventional complications following PCIs and resection outcomes in image-guided neurosurgery.

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.

Determining decision thresholds and evaluating indicators when conservation status is measured as a continuum.

PubMed

Connors, B M; Cooper, A B

2014-12-01

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade-offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade-offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status. © 2014 Society for Conservation Biology.

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.

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.

Cardiopulmonary exercise testing for the prediction of morbidity risk after rectal cancer surgery.

PubMed

West, M A; Parry, M G; Lythgoe, D; Barben, C P; Kemp, G J; Grocott, M P W; Jack, S

2014-08-01

This study investigated the relationship between objectively measured physical fitness variables derived by cardiopulmonary exercise testing (CPET) and in-hospital morbidity after rectal cancer surgery. Patients scheduled for rectal cancer surgery underwent preoperative CPET (reported blind to patient characteristics) with recording of morbidity (recorded blind to CPET variables). Non-parametric receiver operating characteristic (ROC) curves and logistic regression were used to assess the relationship between CPET variables and postoperative morbidity. Of 105 patients assessed, 95 (72 men) were included; ten patients had no surgery and were excluded (3 by choice, 7 owing to unresectable metastasis). Sixty-eight patients had received neoadjuvant treatment. ROC curve analysis of oxygen uptake (V˙o2 ) at estimated lactate threshold (θ^L ) and peak V˙o2 gave an area under the ROC curve of 0·87 (95 per cent confidence interval 0·78 to 0·95; P < 0·001) and 0·85 (0·77 to 0·93; P < 0·001) respectively, indicating that they can help discriminate patients at risk of postoperative morbidity. The optimal cut-off points identified were 10·6 and 18·6 ml per kg per min for V˙o2 at θ^L and peak respectively. CPET can help predict morbidity after rectal cancer surgery. © 2014 BJS Society Ltd. Published by John Wiley & Sons Ltd.

ROC evaluation of SPECT myocardial lesion detectability with and without single iteration non-uniform Chang attenuation compensation using an anthropomorphic female phantom

NASA Astrophysics Data System (ADS)

Jang, Sunyoung; Jaszczak, R. J.; Tsui, B. M. W.; Metz, C. E.; Gilland, D. R.; Turkington, T. G.; Coleman, R. E.

1998-08-01

The purpose of this work was to evaluate lesion detectability with and without nonuniform attenuation compensation (AC) in myocardial perfusion SPECT imaging in women using an anthropomorphic phantom and receiver operating characteristics (ROC) methodology. Breast attenuation causes artifacts in reconstructed images and may increase the difficulty of diagnosis of myocardial perfusion imaging in women. The null hypothesis tested using the ROC study was that nonuniform AC does not change the lesion detectability in myocardial perfusion SPECT imaging in women. The authors used a filtered backprojection (FBP) reconstruction algorithm and Chang's (1978) single iteration method for AC. In conclusion, with the authors' proposed myocardial defect model nuclear medicine physicians demonstrated no significant difference for the detection of the anterior wall defect; however, a greater accuracy for the detection of the inferior wall defect was observed without nonuniform AC than with it (P-value=0.0034). Medical physicists did not demonstrate any statistically significant difference in defect detection accuracy with or without nonuniform AC in the female phantom.

Comparison of different classification algorithms for underwater target discrimination.

PubMed

Li, Donghui; Azimi-Sadjadi, Mahmood R; Robinson, Marc

2004-01-01

Classification of underwater targets from the acoustic backscattered signals is considered here. Several different classification algorithms are tested and benchmarked not only for their performance but also to gain insight to the properties of the feature space. Results on a wideband 80-kHz acoustic backscattered data set collected for six different objects are presented in terms of the receiver operating characteristic (ROC) and robustness of the classifiers wrt reverberation.

Practical UXO Classification: Enhanced Data Processing Strategies for Technology Transition - Fort Ord: Dynamic and Cued Metalmapper Processing and Classification

DTIC Science & Technology

2017-06-06

OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for...Geophysical Mapping, Electromagnetic Induction, Instrument Verification Strip, Time Domain Electromagnetic, Unexploded Ordnance 16. SECURITY...Munitions Response QA Quality Assurance QC Quality Control ROC Receiver Operating Characteristic RTK Real- time Kinematic s Second SNR

Colonoscopy can miss diverticula of the left colon identified by barium enema.

PubMed

Niikura, Ryota; Nagata, Naoyoshi; Shimbo, Takuro; Akiyama, Junichi; Uemura, Naomi

2013-04-21

To identify the diagnostic value of colonoscopy for diverticulosis as determined by barium enema. A total of 65 patients with hematochezia who underwent colonoscopy and barium enema were analyzed, and the diagnostic value of colonoscopy for diverticula was assessed. The receiver operating characteristic area under the curve was compared in relation to age (< 70 or ≥ 70 years), sex, and colon location. The number of diverticula was counted, and the detection ratio was calculated. Colonic diverticula were observed in 46 patients with barium enema. Colonoscopy had a sensitivity of 91% and specificity of 90%. No significant differences were found in the receiver operating characteristic area under the curve (ROC-AUC) for age group or sex. The ROC-AUC of the left colon was significantly lower than that of the right colon (0.81 vs 0.96, P = 0.02). Colonoscopy identified 486 colonic diverticula, while barium enema identified 1186. The detection ratio for the entire colon was therefore 0.41 (486/1186). The detection ratio in the left colon (0.32, 189/588) was significantly lower than that of the right colon (0.50, 297/598) (P < 0.01). Compared with barium enema, only half the number of colonic diverticula can be detected by colonoscopy in the entire colon and even less in the left colon.

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

Improvement of diagnostic efficiency in distinguishing the benign and malignant thyroid nodules via conventional ultrasound combined with ultrasound contrast and elastography

PubMed Central

Liu, Mei-Juan; Men, Yan-Ming; Zhang, Yong-Lin; Zhang, Yu-Xi; Liu, Hao

2017-01-01

We aimed to evaluate the diagnostic values of conventional ultrasound (US), ultrasound contrast (UC) and ultrasound elastography (UE) in distinguishing the benign and malignant thyroid nodules. A total of 100 patients with thyroid nodules receiving operative treatment were selected; they underwent the conventional US, UE and UC examinations before operation, respectively. The nodules received pathological examination after operation to distinguish benign from malignant lesions. The sensitivity, specificity and diagnostic accordance rate of each diagnostic method was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC) of ROC was calculated. The manifestations of malignant thyroid nodules in conventional US examination were mostly the hypoecho, heterogeneous echo, irregular shape, unclear boundary, aspect ratio <1, microcalcification and irregular peripheral echo halo, and there were statistically significant differences compared with the benign nodules (P<0.05). UE showed that the differences between benign and malignant nodules in 2, 3 and 4 points were statistically significant (P<0.05). The manifestations of malignant nodules in UC were mostly the irregular shape, obscure boundary, no obvious enhancement, heterogeneous enhancement and visible perfusion defects, and there were statistically significant differences compared with the benign nodules (P<0.05). ROC curve showed that both sensitivity and specificity of UE and UC were superior to those of conventional US. AUC was the largest (AUC = 0.908) and the diagnostic value was the highest in the conventional US combined with UE and UC. Conventional US combined with elastography and UC can significantly improve the sensitivity, specificity and accuracy of diagnosis of benign and malignant thyroid nodules. PMID:28693244

Improvement of diagnostic efficiency in distinguishing the benign and malignant thyroid nodules via conventional ultrasound combined with ultrasound contrast and elastography.

PubMed

Liu, Mei-Juan; Men, Yan-Ming; Zhang, Yong-Lin; Zhang, Yu-Xi; Liu, Hao

2017-07-01

We aimed to evaluate the diagnostic values of conventional ultrasound (US), ultrasound contrast (UC) and ultrasound elastography (UE) in distinguishing the benign and malignant thyroid nodules. A total of 100 patients with thyroid nodules receiving operative treatment were selected; they underwent the conventional US, UE and UC examinations before operation, respectively. The nodules received pathological examination after operation to distinguish benign from malignant lesions. The sensitivity, specificity and diagnostic accordance rate of each diagnostic method was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC) of ROC was calculated. The manifestations of malignant thyroid nodules in conventional US examination were mostly the hypoecho, heterogeneous echo, irregular shape, unclear boundary, aspect ratio <1, microcalcification and irregular peripheral echo halo, and there were statistically significant differences compared with the benign nodules (P<0.05). UE showed that the differences between benign and malignant nodules in 2, 3 and 4 points were statistically significant (P<0.05). The manifestations of malignant nodules in UC were mostly the irregular shape, obscure boundary, no obvious enhancement, heterogeneous enhancement and visible perfusion defects, and there were statistically significant differences compared with the benign nodules (P<0.05). ROC curve showed that both sensitivity and specificity of UE and UC were superior to those of conventional US. AUC was the largest (AUC = 0.908) and the diagnostic value was the highest in the conventional US combined with UE and UC. Conventional US combined with elastography and UC can significantly improve the sensitivity, specificity and accuracy of diagnosis of benign and malignant thyroid nodules.

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.

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.

Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST)

NASA Astrophysics Data System (ADS)

Ganesan, A.; Alakhras, M.; Brennan, P. C.; Lee, W.; Tapia, K.; Mello-Thoms, C.

2018-03-01

Purpose: To determine the impact of Breast Screen Reader Assessment Strategy (BREAST) over time in improving radiologists' breast cancer detection performance, and to identify the group of radiologists that benefit the most by using BREAST as a training tool. Materials and Methods: Thirty-six radiologists who completed three case-sets offered by BREAST were included in this study. The case-sets were arranged in radiologists' chronological order of completion and five performance measures (sensitivity, specificity, location sensitivity, receiver operating characteristics area under the curve (ROC AUC) and jackknife alternative free-response receiver operating characteristic (JAFROC) figure-of-merit (FOM)), available from BREAST, were compared between case-sets to determine the level of improvement achieved. The radiologists were then grouped based on their characteristics and the above performance measures between the case-sets were compared. Paired t-tests or Wilcoxon signed-rank tests with statistical significance set at p < 0.05 were used to compare the performance measures. Results: Significant improvement was demonstrated in radiologists' case-set performance in terms of location sensitivity and JAFROC FOM over the years, and radiologists' location sensitivity and JAFROC FOM showed significant improvement irrespective of their characteristics. In terms of ROC AUC, significant improvement was shown for radiologists who were reading screen mammograms for more than 7 years and spent more than 9 hours per week reading mammograms. Conclusion: Engaging with case-sets appears to enhance radiologists' performance suggesting the important value of initiatives such as BREAST. However, such performance enhancement was not shown for everyone, highlighting the need to tailor the BREAST platform to benefit all radiologists.

A review of automatic mass detection and segmentation in mammographic images.

PubMed

Oliver, Arnau; Freixenet, Jordi; Martí, Joan; Pérez, Elsa; Pont, Josep; Denton, Erika R E; Zwiggelaar, Reyer

2010-04-01

The aim of this paper is to review existing approaches to the automatic detection and segmentation of masses in mammographic images, highlighting the key-points and main differences between the used strategies. The key objective is to point out the advantages and disadvantages of the various approaches. In contrast with other reviews which only describe and compare different approaches qualitatively, this review also provides a quantitative comparison. The performance of seven mass detection methods is compared using two different mammographic databases: a public digitised database and a local full-field digital database. The results are given in terms of Receiver Operating Characteristic (ROC) and Free-response Receiver Operating Characteristic (FROC) analysis. Copyright 2009 Elsevier B.V. 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.

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.

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.

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.

Identification of Warthin tumor: magnetic resonance imaging versus salivary scintigraphy with technetium-99m pertechnetate.

PubMed

Motoori, Ken; Ueda, Takuya; Uchida, Yoshitaka; Chazono, Hideaki; Suzuki, Homare; Ito, Hisao

2005-01-01

The aim of this study was to evaluate the accuracy of technetium-99m (Tc-99m) pertechnetate scintigraphy and magnetic resonance (MR) imaging in the diagnosis of Warthin tumor. Sixteen cases of Warthin tumor and 17 cases of non-Warthin tumor were examined by Tc-99m pertechnetate scintigraphy with lemon juice stimulation and MR imaging, including T1-weighted, T2-weighted, short inversion time inversion recovery, diffusion-weighted, and contrast-enhanced dynamic images. We used the receiver operating characteristic (ROC) curve to evaluate diagnostic accuracy. The mean area under the ROC curves of MR imaging in the diagnosis of Warthin tumor (0.97) was higher than that of Tc-99m pertechnetate scintigraphy (0.88). Magnetic resonance imaging is more useful in the evaluation of Warthin tumor than Tc-99m pertechnetate scintigraphy.

Multicategory reclassification statistics for assessing improvements in diagnostic accuracy

PubMed Central

Li, Jialiang; Jiang, Binyan; Fine, Jason P.

2013-01-01

In this paper, we extend the definitions of the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) in the context of multicategory classification. Both measures were proposed in Pencina and others (2008. Evaluating the added predictive ability of a new marker: from area under the receiver operating characteristic (ROC) curve to reclassification and beyond. Statistics in Medicine 27, 157–172) as numeric characterizations of accuracy improvement for binary diagnostic tests and were shown to have certain advantage over analyses based on ROC curves or other regression approaches. Estimation and inference procedures for the multiclass NRI and IDI are provided in this paper along with necessary asymptotic distributional results. Simulations are conducted to study the finite-sample properties of the proposed estimators. Two medical examples are considered to illustrate our methodology. PMID:23197381

Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation.

PubMed

Perandini, Simone; Soardi, G A; Larici, A R; Del Ciello, A; Rizzardi, G; Solazzo, A; Mancino, L; Zeraj, F; Bernhart, M; Signorini, M; Motton, M; Montemezzi, S

2017-05-01

To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.

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.

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.

Does consideration of either psychological or material disadvantage improve coronary risk prediction? Prospective observational study of Scottish men.

PubMed

Macleod, John; Metcalfe, Chris; Smith, George Davey; Hart, Carole

2007-09-01

To assess the value of psychosocial risk factors in discriminating between individuals at higher and lower risk of coronary heart disease, using risk prediction equations. Prospective observational study. Scotland. 5191 employed men aged 35 to 64 years and free of coronary heart disease at study enrollment Area under receiver operating characteristic (ROC) curves for risk prediction equations including different risk factors for coronary heart disease. During the first 10 years of follow up, 203 men died of coronary heart disease and a further 200 were admitted to hospital with this diagnosis. Area under the ROC curve for the standard Framingham coronary risk factors was 74.5%. Addition of "vital exhaustion" and psychological stress led to areas under the ROC curve of 74.5% and 74.6%, respectively. Addition of current social class and lifetime social class to the standard Framingham equation gave areas under the ROC curve of 74.6% and 74.9%, respectively. In no case was there strong evidence for improved discrimination of the model containing the novel risk factor over the standard model. Consideration of psychosocial risk factors, including those that are strong independent predictors of heart disease, does not substantially influence the ability of risk prediction tools to discriminate between individuals at higher and lower risk of coronary heart disease.

Classification of breast abnormalities using artificial neural network

NASA Astrophysics Data System (ADS)

Zaman, Nur Atiqah Kamarul; Rahman, Wan Eny Zarina Wan Abdul; Jumaat, Abdul Kadir; Yasiran, Siti Salmah

2015-05-01

Classification is the process of recognition, differentiation and categorizing objects into groups. Breast abnormalities are calcifications which are tumor markers that indicate the presence of cancer in the breast. The aims of this research are to classify the types of breast abnormalities using artificial neural network (ANN) classifier and to evaluate the accuracy performance using receiver operating characteristics (ROC) curve. The methods used in this research are ANN for breast abnormalities classifications and Canny edge detector as a feature extraction method. Previously the ANN classifier provides only the number of benign and malignant cases without providing information for specific cases. However in this research, the type of abnormality for each image can be obtained. The existing MIAS MiniMammographic database classified the mammogram images into three features only namely characteristic of background tissues, class of abnormality and radius of abnormality. However, in this research three other features are added-in. These three features are number of spots, area and shape of abnormalities. Lastly the performance of the ANN classifier is evaluated using ROC curve. It is found that ANN has an accuracy of 97.9% which is considered acceptable.

High Tumor Volume to Fetal Weight Ratio Is Associated with Worse Fetal Outcomes and Increased Maternal Risk in Fetuses with Sacrococcygeal Teratoma.

PubMed

Gebb, Juliana S; Khalek, Nahla; Qamar, Huma; Johnson, Mark P; Oliver, Edward R; Coleman, Beverly G; Peranteau, William H; Hedrick, Holly L; Flake, Alan W; Adzick, N Scott; Moldenhauer, Julie S

2018-03-01

Tumor volume to fetal weight ratio (TFR) > 0.12 before 24 weeks has been associated with poor outcome in fetuses with sacrococcygeal teratoma (SCT). We evaluated TFR in predicting poor fetal outcome and increased maternal operative risk in our cohort of SCT pregnancies. This is a retrospective, single-center review of fetuses seen with SCT from 1997 to 2015. Patients who chose termination of pregnancy (TOP), delivered elsewhere, or had initial evaluation at > 24 weeks were excluded. Receiver operating characteristic (ROC) analysis determined the optimal TFR to predict poor fetal outcome and increased maternal operative risk. Poor fetal outcome included fetal demise, neonatal demise, or fetal deterioration warranting open fetal surgery or delivery < 32 weeks. Increased maternal operative risk included cases necessitating open fetal surgery, classical cesarean delivery, or ex utero intrapartum treatment (EXIT). Of 139 pregnancies with SCT, 27 chose TOP, 14 delivered elsewhere, and 40 had initial evaluation at > 24 weeks. Thus, 58 fetuses were reviewed. ROC analysis revealed that at ≤24 weeks, TFR > 0.095 was predictive of poor fetal outcome and TFR > 0.12 was predictive of increased maternal operative risk. This study supports the use of TFR at ≤24 weeks for risk stratification of pregnancies with SCT. © 2018 S. Karger AG, Basel.

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.

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

DTIC Science & Technology

2010-10-01

steps applied for generating the 3D ROC surface diagnostic metrics: 1. Obtain system data: Gain access to a suitable database of system data under...surface, VUSTPR and VUSCCR, can be calculated. This can be accomplished by partitioning the VUSTPR and VUSCCR volumes into polyhedrons as illustrated... polyhedron volumes to produce VUSTPR and VUSCCR. In the example given in Figures 7 and 8 a logarithmic scaling has been applied to the TL axis. This places

A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets.

PubMed

Zhai, Xuetong; Chakraborty, Dev P

2017-06-01

The objective was to design and implement a bivariate extension to the contaminated binormal model (CBM) to fit paired receiver operating characteristic (ROC) datasets-possibly degenerate-with proper ROC curves. Paired datasets yield two correlated ratings per case. Degenerate datasets have no interior operating points and proper ROC curves do not inappropriately cross the chance diagonal. The existing method, developed more than three decades ago utilizes a bivariate extension to the binormal model, implemented in CORROC2 software, which yields improper ROC curves and cannot fit degenerate datasets. CBM can fit proper ROC curves to unpaired (i.e., yielding one rating per case) and degenerate datasets, and there is a clear scientific need to extend it to handle paired datasets. In CBM, nondiseased cases are modeled by a probability density function (pdf) consisting of a unit variance peak centered at zero. Diseased cases are modeled with a mixture distribution whose pdf consists of two unit variance peaks, one centered at positive μ with integrated probability α, the mixing fraction parameter, corresponding to the fraction of diseased cases where the disease was visible to the radiologist, and one centered at zero, with integrated probability (1-α), corresponding to disease that was not visible. It is shown that: (a) for nondiseased cases the bivariate extension is a unit variances bivariate normal distribution centered at (0,0) with a specified correlation ρ 1 ; (b) for diseased cases the bivariate extension is a mixture distribution with four peaks, corresponding to disease not visible in either condition, disease visible in only one condition, contributing two peaks, and disease visible in both conditions. An expression for the likelihood function is derived. A maximum likelihood estimation (MLE) algorithm, CORCBM, was implemented in the R programming language that yields parameter estimates and the covariance matrix of the parameters, and other statistics. A limited simulation validation of the method was performed. CORCBM and CORROC2 were applied to two datasets containing nine readers each contributing paired interpretations. CORCBM successfully fitted the data for all readers, whereas CORROC2 failed to fit a degenerate dataset. All fits were visually reasonable. All CORCBM fits were proper, whereas all CORROC2 fits were improper. CORCBM and CORROC2 were in agreement (a) in declaring only one of the nine readers as having significantly different performances in the two modalities; (b) in estimating higher correlations for diseased cases than for nondiseased ones; and (c) in finding that the intermodality correlation estimates for nondiseased cases were consistent between the two methods. All CORCBM fits yielded higher area under curve (AUC) than the CORROC2 fits, consistent with the fact that a proper ROC model like CORCBM is based on a likelihood-ratio-equivalent decision variable, and consequently yields higher performance than the binormal model-based CORROC2. The method gave satisfactory fits to four simulated datasets. CORCBM is a robust method for fitting paired ROC datasets, always yielding proper ROC curves, and able to fit degenerate datasets. © 2017 American Association of Physicists in Medicine.

Colonoscopy can miss diverticula of the left colon identified by barium enema

PubMed Central

Niikura, Ryota; Nagata, Naoyoshi; Shimbo, Takuro; Akiyama, Junichi; Uemura, Naomi

2013-01-01

AIM: To identify the diagnostic value of colonoscopy for diverticulosis as determined by barium enema. METHODS: A total of 65 patients with hematochezia who underwent colonoscopy and barium enema were analyzed, and the diagnostic value of colonoscopy for diverticula was assessed. The receiver operating characteristic area under the curve was compared in relation to age (< 70 or ≥ 70 years), sex, and colon location. The number of diverticula was counted, and the detection ratio was calculated. RESULTS: Colonic diverticula were observed in 46 patients with barium enema. Colonoscopy had a sensitivity of 91% and specificity of 90%. No significant differences were found in the receiver operating characteristic area under the curve (ROC-AUC) for age group or sex. The ROC-AUC of the left colon was significantly lower than that of the right colon (0.81 vs 0.96, P = 0.02). Colonoscopy identified 486 colonic diverticula, while barium enema identified 1186. The detection ratio for the entire colon was therefore 0.41 (486/1186). The detection ratio in the left colon (0.32, 189/588) was significantly lower than that of the right colon (0.50, 297/598) (P < 0.01). CONCLUSION: Compared with barium enema, only half the number of colonic diverticula can be detected by colonoscopy in the entire colon and even less in the left colon. PMID:23613630

Validation of the minimal citrate tube fill volume for routine coagulation tests on ACL TOP 500 CTS®.

PubMed

Ver Elst, K; Vermeiren, S; Schouwers, S; Callebaut, V; Thomson, W; Weekx, S

2013-12-01

CLSI recommends a minimal citrate tube fill volume of 90%. A validation protocol with clinical and analytical components was set up to determine the tube fill threshold for international normalized ratio of prothrombin time (PT-INR), activated partial thromboplastin time (aPTT) and fibrinogen. Citrated coagulation samples from 16 healthy donors and eight patients receiving vitamin K antagonists (VKA) were evaluated. Eighty-nine tubes were filled to varying volumes of >50%. Coagulation tests were performed on ACL TOP 500 CTS(®) . Receiver Operating Characteristic (ROC) plot, with Total error (TE) and critical difference (CD) as possible acceptance criteria, was used to determine the fill threshold. Receiving Operating Characteristic was the most accurate with CD for PT-INR and TE for aPTT resulting in thresholds of 63% for PT and 80% for aPTT. By adapted ROC, based on threshold setting at a point of 100% sensitivity at a maximum specificity, CD was best for PT and TE for aPTT resulting in thresholds of 73% for PT and 90% for aPTT. For fibrinogen, the method was only valid with the TE criterion at a 63% fill volume. In our study, we validated the minimal citrate tube fill volumes of 73%, 90% and 63% for PT-INR, aPTT and fibrinogen, respectively. © 2013 John Wiley & Sons Ltd.

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

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.

Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

PubMed

Akram, Pakeeza; Liao, Li

2017-12-06

Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

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.

A concordance index for matched case-control studies with applications in cancer risk.

PubMed

Brentnall, Adam R; Cuzick, Jack; Field, John; Duffy, Stephen W

2015-02-10

In unmatched case-control studies, the area under the receiver operating characteristic (ROC) curve (AUC) may be used to measure how well a variable discriminates between cases and controls. The AUC is sometimes used in matched case-control studies by ignoring matching, but it lacks interpretation because it is not based on an estimate of the ROC for the population of interest. We introduce an alternative measure of discrimination that is the concordance of risk factors conditional on the matching factors. Parametric and non-parametric estimators are given for different matching scenarios, and applied to real data from breast and lung cancer case-control studies. Diagnostic plots to verify the constancy of discrimination over matching factors are demonstrated. The proposed simple measure is easy to use, interpret, more efficient than unmatched AUC statistics and may be applied to compare the conditional discrimination performance of risk factors. Copyright © 2014 John Wiley & Sons, Ltd.

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2008-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Diagnosis of focal liver lesions suspected of metastases by diffusion-weighted imaging (DWI): systematic comparison favors free-breathing technique.

PubMed

Baltzer, Pascal A T; Schelhorn, Juliane; Benndorf, Matthias; Dietzel, Matthias; Kaiser, Werner A

2013-01-01

Two echo planar imaging diffusion-weighted imaging (DWI) techniques [one breath hold (DWI(bh)), repetition time/echo time (TR/TE) 2100/62 ms; one at free breathing (DWI(fb)), TR/TE 2000/65 ms] were compared regarding diagnosis of focal liver lesions (FLLs) in 45 patients with suspected liver metastasis without prior treatment. Apparent diffusion coefficient values of 46 benign and 67 malignant FLLs were analyzed by receiver operating characteristics (ROC) analysis. DWI(fb) detected more malignant lesions than DWI(bh) (P=.002). Lesion size ≤10 mm was associated with FLLs missed by DWI(bh) (P=.018). Area under the ROC curve of DWI(fb) (0.801) was higher compared to that of DWI(bh) (0.669, P<.0113), demonstrating the diagnostic superiority of DWI(fb). Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Aedes aegypti Larval Indices and Risk for Dengue Epidemics

PubMed Central

Sanchez, Lizet; Vanlerberghe, Veerle; Alfonso, Lázara; Marquetti, María del Carmen; Guzman, María Guadalupe; Bisset, Juan; van der Stuyft, Patrick

2006-01-01

We assessed in a case-control study the test-validity of Aedes larval indices for the 2000 Havana outbreak. "Cases" were blocks where a dengue fever patient lived during the outbreak. "Controls" were randomly sampled blocks. Before, during, and after the epidemic, we calculated Breteau index (BI) and house index at the area, neighborhood, and block level. We constructed receiver operating characteristic (ROC) curves to determine their performance as predictors of dengue transmission. We observed a pronounced effect of the level of measurement. The BImax (maximum block BI in a radius of 100 m) at 2-month intervals had an area under the ROC curve of 71%. At a cutoff of 4.0, it significantly (odds ratio 6.00, p<0.05) predicted transmission with 78% sensitivity and 63% specificity. Analysis of BI at the local level, with human-defined boundaries, could be introduced in control programs to identify neighborhoods at high risk for dengue transmission. PMID:16704841

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2009-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

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.

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.

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/

Circulating basal anti-Müllerian hormone levels as predictor of ovarian response in women undergoing ovarian stimulation for in vitro fertilization.

PubMed

Nardo, Luciano G; Gelbaya, Tarek A; Wilkinson, Hannah; Roberts, Stephen A; Yates, Allen; Pemberton, Phil; Laing, Ian

2009-11-01

To evaluate the clinical value of basal anti-Müllerian hormone (AMH) measurements compared with other available determinants, apart from chronologic age, in the prediction of ovarian response to gonadotrophin stimulation. Prospective cohort study. Tertiary referral center for reproductive medicine and an IVF unit. Women undergoing their first cycle of controlled ovarian hyperstimulation (COH) for in vitro fertilization (IVF). Basal levels of FSH and AMH as well as antral follicle count (AFC) were measured in 165 subjects. All patients were followed prospectively and their cycle outcomes recorded. Predictive value of FSH, AMH, and AFC for extremes of ovarian response to stimulation. Out of the 165 women, 134 were defined as normal responders, 15 as poor responders, and 16 as high responders. Subjects in the poor response group were significantly older then those in the other two groups. Anti-Müllerian hormone levels and AFC were markedly raised in the high responders and decreased in the poor responders. Compared with FSH and AFC, AMH performed better in the prediction of excessive response to ovarian stimulation-AMH area under receiver operating characteristic curve (ROC(AUC)) 0.81, FSH ROC(AUC) 0.66, AFC ROC(AUC) 0.69. For poor response, AMH (ROC(AUC) 0.88) was a significantly better predictor than FSH (ROC(AUC) 0.63) but not AFC (ROC(AUC) 0.81). AMH prediction of ovarian response was independent of age and PCOS. Anti-Müllerian hormone cutoffs of >3.75 ng/mL and <1.0 ng/mL would have modest sensitivity and specificity in predicting the extremes of response. Circulating AMH has the ability to predict excessive and poor response to stimulation with exogenous gonadotrophins. Overall, this biomarker is superior to basal FSH and AFC, and has the potential to be incorporated in to work-up protocols to predict patient's ovarian response to treatment and to individualize strategies aiming at reducing the cancellation rate and the iatrogenic complications of COH.

Using ROC Curves to Choose Minimally Important Change Thresholds when Sensitivity and Specificity Are Valued Equally: The Forgotten Lesson of Pythagoras. Theoretical Considerations and an Example Application of Change in Health Status

PubMed Central

Froud, Robert; Abel, Gary

2014-01-01

Background Receiver Operator Characteristic (ROC) curves are being used to identify Minimally Important Change (MIC) thresholds on scales that measure a change in health status. In quasi-continuous patient reported outcome measures, such as those that measure changes in chronic diseases with variable clinical trajectories, sensitivity and specificity are often valued equally. Notwithstanding methodologists agreeing that these should be valued equally, different approaches have been taken to estimating MIC thresholds using ROC curves. Aims and objectives We aimed to compare the different approaches used with a new approach, exploring the extent to which the methods choose different thresholds, and considering the effect of differences on conclusions in responder analyses. Methods Using graphical methods, hypothetical data, and data from a large randomised controlled trial of manual therapy for low back pain, we compared two existing approaches with a new approach that is based on the addition of the sums of squares of 1-sensitivity and 1-specificity. Results There can be divergence in the thresholds chosen by different estimators. The cut-point selected by different estimators is dependent on the relationship between the cut-points in ROC space and the different contours described by the estimators. In particular, asymmetry and the number of possible cut-points affects threshold selection. Conclusion Choice of MIC estimator is important. Different methods for choosing cut-points can lead to materially different MIC thresholds and thus affect results of responder analyses and trial conclusions. An estimator based on the smallest sum of squares of 1-sensitivity and 1-specificity is preferable when sensitivity and specificity are valued equally. Unlike other methods currently in use, the cut-point chosen by the sum of squares method always and efficiently chooses the cut-point closest to the top-left corner of ROC space, regardless of the shape of the ROC curve. PMID:25474472

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.

Diagnosis of adrenal insufficiency.

PubMed

Dorin, Richard I; Qualls, Clifford R; Crapo, Lawrence M

2003-08-05

The cosyntropin stimulation test is the initial endocrine evaluation of suspected primary or secondary adrenal insufficiency. To critically review the utility of the cosyntropin stimulation test for evaluating adrenal insufficiency. The MEDLINE database was searched from 1966 to 2002 for all English-language papers related to the diagnosis of adrenal insufficiency. Studies with fewer than 5 persons with primary or secondary adrenal insufficiency or with fewer than 10 persons as normal controls were excluded. For secondary adrenal insufficiency, only studies that stratified participants by integrated tests of adrenal function were included. Summary receiver-operating characteristic (ROC) curves were generated from all studies that provided sensitivity and specificity data for 250-microg and 1-microg cosyntropin tests; these curves were then compared by using area under the curve (AUC) methods. All estimated values are given with 95% CIs. At a specificity of 95%, sensitivities were 97%, 57%, and 61% for summary ROC curves in tests for primary adrenal insufficiency (250-microg cosyntropin test), secondary adrenal insufficiency (250-microg cosyntropin test), and secondary adrenal insufficiency (1-microg cosyntropin test), respectively. The area under the curve for primary adrenal insufficiency was significantly greater than the AUC for secondary adrenal insufficiency for the high-dose cosyntropin test (P < 0.001), but AUCs for the 250-microg and 1-microg cosyntropin tests did not differ significantly (P > 0.5) for secondary adrenal insufficiency. At a specificity of 95%, summary ROC analysis for the 250-microg cosyntropin test yielded a positive likelihood ratio of 11.5 (95% CI, 8.7 to 14.2) and a negative likelihood ratio of 0.45 (CI, 0.30 to 0.60) for the diagnosis of secondary adrenal insufficiency. Cortisol response to cosyntropin varies considerably among healthy persons. The cosyntropin test performs well in patients with primary adrenal insufficiency, but the lower sensitivity in patients with secondary adrenal insufficiency necessitates use of tests involving stimulation of the hypothalamus if the pretest probability is sufficiently high. The operating characteristics of the 250-microg and 1-microg cosyntropin tests are similar.

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.

Influencing clinicians and healthcare managers: can ROC be more persuasive?

NASA Astrophysics Data System (ADS)

Taylor-Phillips, S.; Wallis, M. G.; Duncan, A.; Gale, A. G.

2010-02-01

Receiver Operating Characteristic analysis provides a reliable and cost effective performance measurement tool, without using full clinical trials. However, when ROC analysis shows that performance is statistically superior in one condition than another it is difficult to relate this result to effects in practice, or even to determine whether it is clinically significant. In this paper we present two concurrent analyses: using ROC methods alongside single threshold recall rate data, and suggest that reporting both provides complimentary data. Four mammographers read 160 difficult cases (41% malignant) twice, with and without prior mammograms. Lesion location and probability of malignancy was reported for each case and analyzed using JAFROC. Concurrently each participant chose recall or return to screen for each case. JAFROC analysis showed that the presence of prior mammograms improved performance (p<.05). Single threshold data showed a trend towards a 26% increase in the number of false positive recalls without prior mammograms (p=.056). If this trend were present throughout the NHS Breast Screening Programme then discarding prior mammograms would correspond to an increase in recall rate from 4.6% to 5.3%, and 12,414 extra women recalled annually for assessment. Whilst ROC methods account for all possible thresholds of recall and have higher power, providing a single threshold example of false positive, false negative, and recall rates when reporting results could be more influential for clinicians. This paper discusses whether this is a useful additional method of presenting data, or whether it is misleading and inaccurate.

Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

PubMed

Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

2010-01-01

In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

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

Wurtz, R.; Kaplan, A.

Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejectionmore » rate (GRR) relevant for realistic applications.« less

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

Using patient data similarities to predict radiation pneumonitis via a self-organizing map

NASA Astrophysics Data System (ADS)

Chen, Shifeng; Zhou, Sumin; Yin, Fang-Fang; Marks, Lawrence B.; Das, Shiva K.

2008-01-01

This work investigates the use of the self-organizing map (SOM) technique for predicting lung radiation pneumonitis (RP) risk. SOM is an effective method for projecting and visualizing high-dimensional data in a low-dimensional space (map). By projecting patients with similar data (dose and non-dose factors) onto the same region of the map, commonalities in their outcomes can be visualized and categorized. Once built, the SOM may be used to predict pneumonitis risk by identifying the region of the map that is most similar to a patient's characteristics. Two SOM models were developed from a database of 219 lung cancer patients treated with radiation therapy (34 clinically diagnosed with Grade 2+ pneumonitis). The models were: SOMall built from all dose and non-dose factors and, for comparison, SOMdose built from dose factors alone. Both models were tested using ten-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Models SOMall and SOMdose yielded ten-fold cross-validated ROC areas of 0.73 (sensitivity/specificity = 71%/68%) and 0.67 (sensitivity/specificity = 63%/66%), respectively. The significant difference between the cross-validated ROC areas of these two models (p < 0.05) implies that non-dose features add important information toward predicting RP risk. Among the input features selected by model SOMall, the two with highest impact for increasing RP risk were: (a) higher mean lung dose and (b) chemotherapy prior to radiation therapy. The SOM model developed here may not be extrapolated to treatment techniques outside that used in our database, such as several-field lung intensity modulated radiation therapy or gated radiation therapy.

Unsupervised classification of cirrhotic livers using MRI data

NASA Astrophysics Data System (ADS)

Lee, Gobert; Kanematsu, Masayuki; Kato, Hiroki; Kondo, Hiroshi; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Hoshi, Hiroaki

2008-03-01

Cirrhosis of the liver is a chronic disease. It is characterized by the presence of widespread nodules and fibrosis in the liver which results in characteristic texture patterns. Computerized analysis of hepatic texture patterns is usually based on regions-of-interest (ROIs). However, not all ROIs are typical representatives of the disease stage of the liver from which the ROIs originated. This leads to uncertainties in the ROI labels (diseased or non-diseased). On the other hand, supervised classifiers are commonly used in determining the assignment rule. This presents a problem as the training of a supervised classifier requires the correct labels of the ROIs. The main purpose of this paper is to investigate the use of an unsupervised classifier, the k-means clustering, in classifying ROI based data. In addition, a procedure for generating a receiver operating characteristic (ROC) curve depicting the classification performance of k-means clustering is also reported. Hepatic MRI images of 44 patients (16 cirrhotic; 28 non-cirrhotic) are used in this study. The MRI data are derived from gadolinium-enhanced equilibrium phase images. For each patient, 10 ROIs selected by an experienced radiologist and 7 texture features measured on each ROI are included in the MRI data. Results of the k-means classifier are depicted using an ROC curve. The area under the curve (AUC) has a value of 0.704. This is slightly lower than but comparable to that of LDA and ANN classifiers which have values 0.781 and 0.801, respectively. Methods in constructing ROC curve in relation to k-means clustering have not been previously reported in the literature.

Analysis of glottal source parameters in Parkinsonian speech.

PubMed

Hanratty, Jane; Deegan, Catherine; Walsh, Mary; Kirkpatrick, Barry

2016-08-01

Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics of the glottal source signal in Parkinsonian speech. An experiment is conducted in which a selection of glottal parameters are tested for their ability to discriminate between healthy and Parkinsonian speech. Results for each glottal parameter are presented for a database of 50 healthy speakers and a database of 16 speakers with Parkinsonian speech symptoms. Receiver operating characteristic (ROC) curves were employed to analyse the results and the area under the ROC curve (AUC) values were used to quantify the performance of each glottal parameter. The results indicate that glottal parameters can be used to discriminate between healthy and Parkinsonian speech, although results varied for each parameter tested. For the task of separating healthy and Parkinsonian speech, 2 out of the 7 glottal parameters tested produced AUC values of over 0.9.

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.

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.

Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30.

PubMed

Dong, Wang; Shunliang, Yang; Weizhen, Wu; Qinghua, Wang; Zhangxin, Zeng; Jianming, Tan; He, Wang

2006-06-01

To evaluate the feasibility of serum sCD30 for prediction of acute graft rejection, we analyzed clinical data of 231 patients, whose serum levels of sCD30 were detected by ELISA before and after transplantation. They were divided into three groups: acute rejection group (AR, n = 49), uncomplicated course group (UC, n = 171) and delayed graft function group (DGF, n = 11). Preoperative sCD30 levels of three groups were 183 +/- 74, 177 +/- 82 and 168 +/- 53 U/ml, respectively (P = 0.82). Significant decrease of sCD30 was detected in three groups on day 5 and 10 post-transplantation respectively (52 +/- 30 and 9 +/- 5 U/ml respectively, P < 0.001). Compared with Group UC and DGF, patients of Group AR had higher sCD30 values on day 5 post-transplantation (92 +/- 27 U/ml vs. 41 +/- 20 U/ml and 48 +/- 18 U/ml, P < 0.001). However, sCD30 levels on day 10 post-transplantation were virtually similar in patients of three groups (P = 0.43). Receiver operating characteristic (ROC) curve demonstrated that sCD30 level on day 5 post-transplantation could differentiate patients who subsequently suffered acute allograft rejection from others (area under ROC curve 0.95). According to ROC curve, 65 U/ml may be the optimal operational cut-off level to predict impending graft rejection (specificity 91.8%, sensitivity 87.1%). Measurement of soluble CD30 on day 5 post-transplantation might offer a noninvasive means to recognize patients at risk of impending acute graft rejection during early post-transplantation period.

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.

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.

Class-specific Error Bounds for Ensemble Classifiers

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

Prenger, R; Lemmond, T; Varshney, K

2009-10-06

The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missedmore » detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.« less

Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy

PubMed Central

McGee, Sasha; Mardirossian, Vartan; Elackattu, Alphi; Mirkovic, Jelena; Pistey, Robert; Gallagher, George; Kabani, Sadru; Yu, Chung-Chieh; Wang, Zimmern; Badizadegan, Kamran; Grillone, Gregory; Feld, Michael S.

2010-01-01

Objectives We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc). Methods In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative parameters related to tissue morphology and biochemistry were extracted from the spectra. Diagnostic algorithms specific for combinations of sites with similar spectral properties were developed. Results Discrimination of benign from dysplastic/malignant lesions was most successful when algorithms were designed for individual sites (area under the receiver operator characteristic curve [ROC-AUC], 0.75 for the lateral surface of the tongue) and was least accurate when all sites were combined (ROC-AUC, 0.60). The combination of sites with similar spectral properties (floor of mouth and lateral surface of the tongue) yielded an ROC-AUC of 0.71. Conclusions Accurate spectroscopic detection of oral disease must account for spectral variations among anatomic sites. Anatomy-based algorithms for single sites or combinations of sites demonstrated good diagnostic performance in distinguishing benign lesions from dysplastic/malignant lesions and consistently performed better than algorithms developed for all sites combined. PMID:19999369

Ultrasound bladder wall thickness measurement in diagnosis of recurrent urinary tract infections and cystitis cystica in prepubertal girls.

PubMed

Milošević, Danko; Trkulja, Vladimir; Turudić, Daniel; Batinić, Danica; Spajić, Borislav; Tešović, Goran

2013-12-01

To evaluate urinary bladder wall thickness (BWT) assessed by ultrasound as a diagnostic tool for cystitis cystica. This was a 9-year prospective study comprising 120 prepubertal girls. Sixty subjects of whom half underwent cystoscopy represented cases while the other 60 (those with a single urinary tract infection and healthy subjects) represented controls. Based on receiver operating characteristics (ROC) analysis, BWT discriminated very well between cases and controls with area under the ROC curve close to 1.0. At the optimum cut-off defined at 3.9 mm, negative predictive value (NPV) was 100% leaving no probability of cystic cystitis with BWT <3.9 mm. Positive predictive value (PPV) was also very high (95.2%), indicating only around 4.82% probability of no cystic cystitis in patients with BWT values ≥3.9 mm. BWT could also distinguish between healthy subjects and those with a cured single urinary tract infection, although discriminatory properties were moderate (area under ROC 86.7%, PPV 78.8%, NPV 85.2%). Ultrasound mucosal bladder wall measurement is a non-invasive, simple and quite reliable method in diagnosis of cystitis cystica in prepubertal girls with recurrent urinary tract infections. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Is the MARS questionnaire a reliable measure of medication adherence in childhood asthma?

PubMed

Garcia-Marcos, Patricia W; Brand, Paul L P; Kaptein, Adrian A; Klok, Ted

2016-12-01

To assess the reliability of the Medication Adherence Report Scale (MARS-5) for assessing adherence in clinical practice and research. Prospective cohort study following electronically measured inhaled corticosteroids (ICS) adherence for 1 year in 2-13-year-old children with persistent asthma. The relationship between electronically measured adherence and MARS-5 scores (ranging from 5 to 25) was assessed by Spearman's rank correlation coefficient. A ROC (receiver operating characteristic) curve was performed testing MARS-5 against electronically measured adherence. Sensitivity, specificity, positive and negative likelihood ratios of the closest MARS-5 cut-off values to the top left-hand corner of the ROC curve were calculated. High MARS scores were obtained (median 24, interquartile range 22-24). Despite a statistically significant correlation between MARS-5 and electronically assessed adherence (Spearman's rho = 0.47; p < 0.0001), there was considerable variation of adherence rates at every MARS-5 score. The area under the ROC curve was 0.7188. A MARS-5 score ≥23 had the best predictive ability for electronically assessed adherence, but positive and negative likelihood ratios were too small to be useful (1.65 and 0.27, respectively). Self-report using MARS-5 is too inaccurate to be a useful measure of adherence in children with asthma, both in clinical practice and in research.

A transfer of technology from engineering: use of ROC curves from signal detection theory to investigate information processing in the brain during sensory difference testing.

PubMed

Wichchukit, Sukanya; O'Mahony, Michael

2010-01-01

This article reviews a beneficial effect of technology transfer from Electrical Engineering to Food Sensory Science. Specifically, it reviews the recent adoption in Food Sensory Science of the receiver operating characteristic (ROC) curve, a tool that is incorporated in the theory of signal detection. Its use allows the information processing that takes place in the brain during sensory difference testing to be studied and understood. The review deals with how Signal Detection Theory, also called Thurstonian modeling, led to the adoption of a more sophisticated way of analyzing the data from sensory difference tests, by introducing the signal-to-noise ratio, d', as a fundamental measure of perceived small sensory differences. Generally, the method of computation of d' is a simple matter for some of the better known difference tests like the triangle, duo-trio and 2-AFC. However, there are occasions when these tests are not appropriate and other tests like the same-different and the A Not-A test are more suitable. Yet, for these, it is necessary to understand how the brain processes information during the test before d' can be computed. It is for this task that the ROC curve has a particular use. © 2010 Institute of Food Technologists®

Morphological and wavelet features towards sonographic thyroid nodules evaluation.

PubMed

Tsantis, Stavros; Dimitropoulos, Nikos; Cavouras, Dionisis; Nikiforidis, George

2009-03-01

This paper presents a computer-based classification scheme that utilized various morphological and novel wavelet-based features towards malignancy risk evaluation of thyroid nodules in ultrasonography. The study comprised 85 ultrasound images-patients that were cytological confirmed (54 low-risk and 31 high-risk). A set of 20 features (12 based on nodules boundary shape and 8 based on wavelet local maxima located within each nodule) has been generated. Two powerful pattern recognition algorithms (support vector machines and probabilistic neural networks) have been designed and developed in order to quantify the power of differentiation of the introduced features. A comparative study has also been held, in order to estimate the impact speckle had onto the classification procedure. The diagnostic sensitivity and specificity of both classifiers was made by means of receiver operating characteristics (ROC) analysis. In the speckle-free feature set, the area under the ROC curve was 0.96 for the support vector machines classifier whereas for the probabilistic neural networks was 0.91. In the feature set with speckle, the corresponding areas under the ROC curves were 0.88 and 0.86 respectively for the two classifiers. The proposed features can increase the classification accuracy and decrease the rate of missing and misdiagnosis in thyroid cancer control.

Operating characteristics of six response distortion indicators for the personality assessment inventory.

PubMed

Morey, L C; Lanier, V W

1998-09-01

The characteristics of six different indicators of response distortion on the Personality Assessment Inventory (PAI; Morey, 1991) were evaluated by having college students complete the PAI under positive impression management, malingering, and honest responding conditions. The six indicators were the PAI Positive Impression (PIM) and Negative Impression (NIM) scales, the Malingering and Defensiveness Indexes, and two discriminant functions, one developed by Cashel and the other by Rogers. Protocols of students asked to malinger were compared with those of actual clinical patients, while protocols of students asked to manage their impression in a positive direction were compared with those of students asked to respond honestly. Comparisons between groups were accomplished through the examination of effect sizes and receiver operating characteristic (ROC) curves. All six indicators demonstrated the ability to distinguish between actual and feigned responding. The Rogers function was particularly effective in identifying malingering. The Cashel function was less effective than other measures in identifying positive impression management, although it appears to also have promise as an indicator of malingering.

Can technical characteristics predict clinical performance in PET/CT imaging? A correlation study for thyroid cancer diagnosis

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Menychtas, Dimitrios; Georgakopoulos, Alexandros; Pianou, Nikoletta; Metaxas, Marinos; Chatziioannou, Sofia

2013-03-01

The purpose of this study was to determine whether image characteristics could be used to predict the outcome of ROC studies in PET/CT imaging. Patients suspected for recurrent thyroid cancer underwent a standard whole body (WB) examination and an additional high-resolution head-and-neck (HN) F18-FDG PET/CT scan. The value of the latter was determined with an ROC study, the results of which showed that the WB+HN combination was better than WB alone for thyroid cancer detection and diagnosis. Following the ROC experiment, the WB and HN images of confirmed benign or malignant thyroid disease were analyzed and first and second order textural features were determined. Features included minimum, mean, and maximum intensity, as well as contrast in regions of interest encircling the thyroid lesions. Lesion size and standard uptake values (SUV) were also determined. Bivariate analysis was applied to determine relationships between WB and HN features and between observer ROC responses and the various feature values. The two sets showed significant associations in the values of SUV, contrast, and lesion size. They were completely different when the intensities were considered; no relationship was found between the WB minimum, maximum, and mean ROI values and their HN counterparts. SUV and contrast were the strongest predictors of ROC performance on PET/CT examinations of thyroid cancer. The high resolution HN images seem to enhance these relationships but without a single dramatic effect as was projected from the ROC results. A combination of features from both WB and HN datasets may possibly be a more robust predictor of ROC performance.

Computed Tomography Angiography Evaluation of Risk Factors for Unstable Intracranial Aneurysms.

PubMed

Wang, Guang-Xian; Gong, Ming-Fu; Wen, Li; Liu, Lan-Lan; Yin, Jin-Bo; Duan, Chun-Mei; Zhang, Dong

2018-03-19

To evaluate risk factors for instability in intracranial aneurysms (IAs) using computed tomography angiography (CTA). A total of 614 consecutive patients diagnosed with 661 IAs between August 2011 and February 2016 were reviewed. Patients and IAs were divided into stable and unstable groups. Along with clinical characteristics, IA characteristics were evaluated by CTA. Multiple logistic regression analysis was used to identify the independent risk factors associated with unstable IAs. Receiver operating characteristic (ROC) curve analysis was performed on the final model, and optimal thresholds were obtained. Patient age (odds ratio [OR], 0.946), cerebral atherosclerosis (CA; OR, 0.525), and IAs located at the middle cerebral artery (OR, 0.473) or internal carotid artery (OR, 0.512) were negatively correlated with instability, whereas IAs with irregular shape (OR, 2.157), deep depth (OR, 1.557), or large flow angle (FA; OR, 1.015) were more likely to be unstable. ROC analysis revealed threshold values of age, depth, and FA of 59.5 years, 4.25 mm, and 87.8°, respectively. The stability of IAs is significantly affected by several factors, including patient age and the presence of CA. IA shape and location also have an impact on the stability of IAs. Growth into an irregular shape, with a deep depth, and a large FA are risk factors for a change in IAs from stable to unstable. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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

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

Factors associated with excessive bleeding after cardiac surgery: A prospective cohort study.

PubMed

Lopes, Camila Takao; Brunori, Evelise Fadini Reis; Cavalcante, Agueda Maria Ruiz Zimmer; Moorhead, Sue Ann; Swanson, Elizabeth; Lopes, Juliana de Lima; de Barros, Alba Lucia Bottura Leite

2016-01-01

To identify factors associated with excessive bleeding (ExB) after cardiac surgery in adults. Excessive bleeding after cardiac surgery must be anticipated for implementation of timely interventions. A prospective cohort study with 323 adults requiring open-chest cardiac surgery. Potential factors associated with ExB were investigated through univariate analysis and logistic regression. The accuracy of the relationship between the independent variables and the outcome was depicted through the receiver-operating characteristic (ROC) curve. The factors associated with ExB included gender, body mass index (BMI), preoperative platelet count, intraoperative heparin doses and intraoperative platelet transfusion. The ROC curve cut-off points were 26.35 for the BMI; 214,000 for the preoperative platelet count, and 6.25 for intraoperative heparin dose. This model had an accuracy = 77.3%, a sensitivity = 81%, and a specificity = 62%. Male gender, BMI, preoperative platelet count, dose of intraoperative heparin >312.5 mg without subsequent platelet transfusion, are factors associated with ExB. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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

Learning the ideal observer for SKE detection tasks by use of convolutional neural networks (Cum Laude Poster Award)

NASA Astrophysics Data System (ADS)

Zhou, Weimin; Anastasio, Mark A.

2018-03-01

It has been advocated that task-based measures of image quality (IQ) should be employed to evaluate and optimize imaging systems. Task-based measures of IQ quantify the performance of an observer on a medically relevant task. The Bayesian Ideal Observer (IO), which employs complete statistical information of the object and noise, achieves the upper limit of the performance for a binary signal classification task. However, computing the IO performance is generally analytically intractable and can be computationally burdensome when Markov-chain Monte Carlo (MCMC) techniques are employed. In this paper, supervised learning with convolutional neural networks (CNNs) is employed to approximate the IO test statistics for a signal-known-exactly and background-known-exactly (SKE/BKE) binary detection task. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are compared to those produced by the analytically computed IO. The advantages of the proposed supervised learning approach for approximating the IO are demonstrated.

Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

PubMed

Kim, Eunhee; Zhang, Zheng; Wang, Youdan; Zeng, Donglin

2014-12-01

Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure. © 2014, The International Biometric Society.

Application of the Hotelling and ideal observers to detection and localization of exoplanets.

PubMed

Caucci, Luca; Barrett, Harrison H; Devaney, Nicholas; Rodríguez, Jeffrey J

2007-12-01

The ideal linear discriminant or Hotelling observer is widely used for detection tasks and image-quality assessment in medical imaging, but it has had little application in other imaging fields. We apply it to detection of planets outside of our solar system with long-exposure images obtained from ground-based or space-based telescopes. The statistical limitations in this problem include Poisson noise arising mainly from the host star, electronic noise in the image detector, randomness or uncertainty in the point-spread function (PSF) of the telescope, and possibly a random background. PSF randomness is reduced but not eliminated by the use of adaptive optics. We concentrate here on the effects of Poisson and electronic noise, but we also show how to extend the calculation to include a random PSF. For the case where the PSF is known exactly, we compare the Hotelling observer to other observers commonly used for planet detection; comparison is based on receiver operating characteristic (ROC) and localization ROC (LROC) curves.

Application of the Hotelling and ideal observers to detection and localization of exoplanets

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Devaney, Nicholas; Rodríguez, Jeffrey J.

2008-01-01

The ideal linear discriminant or Hotelling observer is widely used for detection tasks and image-quality assessment in medical imaging, but it has had little application in other imaging fields. We apply it to detection of planets outside of our solar system with long-exposure images obtained from ground-based or space-based telescopes. The statistical limitations in this problem include Poisson noise arising mainly from the host star, electronic noise in the image detector, randomness or uncertainty in the point-spread function (PSF) of the telescope, and possibly a random background. PSF randomness is reduced but not eliminated by the use of adaptive optics. We concentrate here on the effects of Poisson and electronic noise, but we also show how to extend the calculation to include a random PSF. For the case where the PSF is known exactly, we compare the Hotelling observer to other observers commonly used for planet detection; comparison is based on receiver operating characteristic (ROC) and localization ROC (LROC) curves. PMID:18059905

Comparison of performance of computer display monitors for radiological diagnosis; "diagnostic" high brightness monochrome LCD, 3MP vs "clinical review" colour LCD, 2MP.

PubMed

Sim, L; Manthey, K; Stuckey, S

2007-06-01

A study to compare performance of the following display monitors for application as PACS CR diagnostic workstations is described. 1. Diagnostic quality, 3 Mega Pixel, 21 inch monochrome LCD monitors--Planar C3i. 2. Clinical review quality, 2 Mega Pixel, 21 inch colour LCD monitors--Planar PX212. Two sets of seventy radiological studies were presented to four senior radiologists on two occasions, using different displays on each occasion. The clinical condition used for this investigation was to query for the presence of a solitary pulmonary nodule. Receiver Operating Characteristic (ROC) curves were constructed for diagnostic performance for each presentation. Areas under the ROC curves (AUC) for diagnosis using different monitors were compared and the following results obtained: Monochrome AUC = 0.813 +/- 0.02, Colour AUC = 0.801 +/- 0.021. These results indicate that there is no statistically significant difference in the performance of these monitor types at a 95% confidence level.

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

PubMed

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

Likelihood Ratio, Optimal Decision Rules, and Relationship between Proportion Correct and d' in the Dual-Pair AB vs BA identification Paradigm

PubMed Central

Micheyl, Christophe; Dai, Huanping

2010-01-01

The equal-variance Gaussian signal-detection-theory (SDT) decision model for the dual-pair change-detection (or “4IAX”) paradigm has been described in earlier publications. In this note, we consider the equal-variance Gaussian SDT model for the related dual-pair AB vs BA identification paradigm. The likelihood ratios, optimal decision rules, receiver operating characteristics (ROCs), and relationships between d' and proportion-correct (PC) are analyzed for two special cases: that of statistically independent observations, which is likely to apply in constant-stimuli experiments, and that of highly correlated observations, which is likely to apply in experiments where stimuli are roved widely across trials or pairs. A surprising outcome of this analysis is that although these two situations lead to different optimal decision rules, the predicted ROCs and proportions of correct responses (PCs) for these two cases are not substantially different, and are either identical or similar to those observed in the basic Yes-No paradigm. PMID:19633356

Pharmacologic study of calcium influx pathways in rabbit aortic smooth muscle

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

Lukeman, D.S.

1987-01-01

Functional characteristics and pharmacologic domains of receptor-operated and potential-sensitive calcium (Ca/sup 2 +/) channels (ROCs and PSCs, respectively) were derived via measurements of /sup 45/Ca/sup 2 +/ influx (M/sup Ca/) during activation by the neurotransmitters norepinephrine (NE), histamine (HS), and serotonin (5-HT) and by elevated extracellular potassium (K/sup +/) in the individual or combined presence of organic Ca/sup 2 +/ channel antagonists (CAts), calmodulin antagonists (Calm-ants), lanthanum (La/sup 3 +/), and agents that increase intracellular levels of cyclic AMP.

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.

The "surprise question" for predicting death in seriously ill patients: a systematic review and meta-analysis.

PubMed

Downar, James; Goldman, Russell; Pinto, Ruxandra; Englesakis, Marina; Adhikari, Neill K J

2017-04-03

The surprise question - "Would I be surprised if this patient died in the next 12 months?" - has been used to identify patients at high risk of death who might benefit from palliative care services. Our objective was to systematically review the performance characteristics of the surprise question in predicting death. We searched multiple electronic databases from inception to 2016 to identify studies that prospectively screened patients with the surprise question and reported on death at 6 to 18 months. We constructed models of hierarchical summary receiver operating characteristics (sROCs) to determine prognostic performance. Sixteen studies (17 cohorts, 11 621 patients) met the selection criteria. For the outcome of death at 6 to 18 months, the pooled prognostic characteristics were sensitivity 67.0% (95% confidence interval [CI] 55.7%-76.7%), specificity 80.2% (73.3%-85.6%), positive likelihood ratio 3.4 (95% CI 2.8-4.1), negative likelihood ratio 0.41 (95% CI 0.32-0.54), positive predictive value 37.1% (95% CI 30.2%-44.6%) and negative predictive value 93.1% (95% CI 91.0%-94.8%). The surprise question had worse discrimination in patients with noncancer illness (area under sROC curve 0.77 [95% CI 0.73-0.81]) than in patients with cancer (area under sROC curve 0.83 [95% CI 0.79-0.87; p = 0.02 for difference]). Most studies had a moderate to high risk of bias, often because they had a low or unknown participation rate or had missing data. The surprise question performs poorly to modestly as a predictive tool for death, with worse performance in noncancer illness. Further studies are needed to develop accurate tools to identify patients with palliative care needs and to assess the surprise question for this purpose. © 2017 Canadian Medical Association or its licensors.

Validation of the German Diabetes Risk Score among the general adult population: findings from the German Health Interview and Examination Surveys

PubMed Central

Paprott, Rebecca; Mühlenbruch, Kristin; Mensink, Gert B M; Thiele, Silke; Schulze, Matthias B; Scheidt-Nave, Christa; Heidemann, Christin

2016-01-01

Objective To evaluate the German Diabetes Risk Score (GDRS) among the general adult German population for prediction of incident type 2 diabetes and detection of prevalent undiagnosed diabetes. Methods The longitudinal sample for prediction of incident diagnosed type 2 diabetes included 3625 persons who participated both in the examination survey in 1997–1999 and the examination survey in 2008–2011. Incident diagnosed type 2 diabetes was defined as first-time physician diagnosis or antidiabetic medication during 5 years of follow-up excluding potential incident type 1 and gestational diabetes. The cross-sectional sample for detection of prevalent undiagnosed diabetes included 6048 participants without diagnosed diabetes of the examination survey in 2008–2011. Prevalent undiagnosed diabetes was defined as glycated haemoglobin ≥6.5% (48 mmol/mol). We assessed discrimination as area under the receiver operating characteristic curve (ROC-AUC (95% CI)) and calibration through calibration plots. Results In longitudinal analyses, 82 subjects with incident diagnosed type 2 diabetes were identified after 5 years of follow-up. For prediction of incident diagnosed diabetes, the GDRS yielded an ROC-AUC of 0.87 (0.83 to 0.90). Calibration plots indicated excellent prediction for low diabetes risk and overestimation for intermediate and high diabetes risk. When considering the entire follow-up period of 11.9 years (ROC-AUC: 0.84 (0.82 to 0.86)) and including incident undiagnosed diabetes (ROC-AUC: 0.81 (0.78 to 0.84)), discrimination decreased somewhat. A previously simplified paper version of the GDRS yielded a similar predictive ability (ROC-AUC: 0.86 (0.82 to 0.89)). In cross-sectional analyses, 128 subjects with undiagnosed diabetes were identified. For detection of prevalent undiagnosed diabetes, the ROC-AUC was 0.84 (0.81 to 0.86). Again, the simplified version yielded a similar result (ROC-AUC: 0.83 (0.80 to 0.86)). Conclusions The GDRS might be applied for public health monitoring of diabetes risk in the German adult population. Future research needs to evaluate whether the GDRS is useful to improve diabetes risk awareness and prevention among the general population. PMID:27933187

Linguistic adaptation, validation and comparison of 3 routinely used neuropathic pain questionnaires.

PubMed

Li, Jun; Feng, Yi; Han, Jisheng; Fan, Bifa; Wu, Dasheng; Zhang, Daying; Du, Dongping; Li, Hui; Lim, Jian; Wang, Jiashuang; Jin, Yi; Fu, Zhijian

2012-01-01

Neuropathic pain questionnaires are efficient diagnostic tools for neuropathic pain and play an important role in neuropathic pain epidemiologic studies in China. No comparison data was available in regards to the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS), the Neuropathic Pain Questionnaire (NPQ) and ID Pain within and among the same population. To achieve a linguistic adaptation, validation, and comparison of Chinese versions of the 3 neuropathic pain questionnaires (LANSS, NPQ and ID Pain). A nonrandomized, controlled, prospective, multicenter trial. Ten pain centers in China. Two forward translations followed by comparison and reconciliation of the translations. Comparison of the 2 backward translations with the original version was made to establish consistency and accuracy of the translations. Pilot testing and pain specialists' evaluations were also required. A total of 140 patients were enrolled in 10 centers throughout China: 70 neuropathic pain patients and 70 nociceptive pain patients. Reliability (Cronbach's alpha coefficients and Guttman split-half coefficients) and validity (sensitivity, specificity, positive and negative predictive values, receiver operating characteristic [ROC] curves and the area under the ROC curves) of the 3 questionnaires were determined. ROC curves and the area under the ROC curves of the 3 questionnaires were also compared. Chinese versions of LANSS, NPQ and ID Pain had a good reliability (Cronbach's alpha coefficients and Guttman split-half coefficients were greater than 0.7). Sensitivity, specificity, positive and negative predictive values of the Chinese versions of LANSS and ID Pain were considerably high ( > 80%). The area under the ROC curves of LANSS and ID Pain was significantly higher than that of NPQ (P < 0.05). There was no statistically significant difference between the area under the ROC curves of LANSS and ID Pain (P > 0.05). The study was based on patients with a high school degree or above, which limited the application of the 3 neuropathic pain questionnaires to patients with lower educational levels. The Chinese versions of LANSS and ID Pain developed and validated by this study can be used as a diagnostic tool in differentiating neuropathic pain in patients whose native language is Chinese (Mandarin).

Promotion by humus-reducing bacteria for the degradation of UV254 absorbance in reverse-osmosis concentrates pretreated with O3-assisted UV-Fenton method.

PubMed

Xia, Jiaohui; Zhang, Hui; Ding, Shaoxuan; Li, Changyu; Ding, Jincheng; Lu, Jie

2017-07-12

The primary pollutants in reverse-osmosis concentrates (ROC) are the substances with the UV absorbance at 254 nm (UV 254 ), which is closely related to humic substances that can be degraded by humus-reducing bacteria. This work studied the degradation characteristics of humus-reducing bacteria in ROC treatment. The physiological and biochemical characteristics of humus-reducing bacteria were investigated, and the effects of pH values and electron donors on the reduction of humic analog, antraquinone-2, 6-disulfonate were explored to optimize the degradation. Furthermore, the O 3 -assisted UV-Fenton method was applied for the pretreatment of ROC, and the degradation of UV 254 absorbance was apparently promoted with their removal rate, reaching 84.2% after 10 days of degradation by humus-reducing bacteria.

Validation of the modified Ranson versus Glasgow score for pancreatitis in a Singaporean population.

PubMed

Tan, Yong Hui Alvin; Rafi, Shumaila; Tyebally Fang, Mirriam; Hwang, Stephen; Lim, Ee Wen; Ngu, James; Tan, Su-Ming

2017-09-01

The characteristics of patients with acute pancreatitis in multi-ethnic Singapore differ from that of the populations used in formulating the modified Ranson and Glasgow scores. The use of these scoring systems has not previously been validated in the Singaporean setting. This study aims to validate and compare the prognostic use of the modified Ranson and Glasgow scores, and to determine the superiority of one score over the other in predicting the outcome for acute pancreatitis in the Singaporean population. This is a 3-year retrospective study of patients diagnosed with acute pancreatitis at our centre. Patients with chronic pancreatitis, acute on chronic pancreatitis, iatrogenic pancreatitis, pancreatic cancer as well as those with incomplete Ranson or Glasgow scores were excluded from the study. Case notes and computer records were reviewed for local complications of pancreatitis and organ failure. Receiver operator characteristic (ROC) curves of the Ranson and Glasgow scores were plotted for the prediction of severity and mortality. Between January 2010 and December 2012, 230 cases were diagnosed with acute pancreatitis. A majority of the patients had mild pancreatitis (n = 194, 84.3%), and the overall 30-day mortality rate was 3.5% (n = 8). ROC of the Ranson and Glasgow scoring systems for mortality showed an area under curve (AUC) of 0.854 (P = 0.001) and 0.776 (P = 0.008), respectively. For severity, the AUC for the modified Ranson and Glasgow score was calculated to be 0.694 and 0.668, respectively. The ROC curves of Ranson and Glasgow scores for mortality are comparable with that published in earlier studies. In a Singaporean population, the Ranson score is more accurate in the prediction of mortality. However, both scoring systems are poor predictors for severity of acute pancreatitis. © 2015 Royal Australasian College of Surgeons.

Cumulative lactate and hospital mortality in ICU patients

PubMed Central

2013-01-01

Background Both hyperlactatemia and persistence of hyperlactatemia have been associated with bad outcome. We compared lactate and lactate-derived variables in outcome prediction. Methods Retrospective observational study. Case records from 2,251 consecutive intensive care unit (ICU) patients admitted between 2001 and 2007 were analyzed. Baseline characteristics, all lactate measurements, and in-hospital mortality were recorded. The time integral of arterial blood lactate levels above the upper normal threshold of 2.2 mmol/L (lactate-time-integral), maximum lactate (max-lactate), and time-to-first-normalization were calculated. Survivors and nonsurvivors were compared and receiver operating characteristic (ROC) analysis were applied. Results A total of 20,755 lactate measurements were analyzed. Data are srpehown as median [interquartile range]. In nonsurvivors (n = 405) lactate-time-integral (192 [0–1881] min·mmol/L) and time-to-first normalization (44.0 [0–427] min) were higher than in hospital survivors (n = 1846; 0 [0–134] min·mmol/L and 0 [0–75] min, respectively; all p < 0.001). Normalization of lactate <6 hours after ICU admission revealed better survival compared with normalization of lactate >6 hours (mortality 16.6% vs. 24.4%; p < 0.001). AUC of ROC curves to predict in-hospital mortality was the largest for max-lactate, whereas it was not different among all other lactate derived variables (all p > 0.05). The area under the ROC curves for admission lactate and lactate-time-integral was not different (p = 0.36). Conclusions Hyperlactatemia is associated with in-hospital mortality in a heterogeneous ICU population. In our patients, lactate peak values predicted in-hospital mortality equally well as lactate-time-integral of arterial blood lactate levels above the upper normal threshold. PMID:23446002

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.

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.

The pre-operative levels of haemoglobin in the blood can be used to predict the risk of allogenic blood transfusion after total knee arthroplasty.

PubMed

Maempel, J F; Wickramasinghe, N R; Clement, N D; Brenkel, I J; Walmsley, P J

2016-04-01

The pre-operative level of haemoglobin is the strongest predictor of the peri-operative requirement for blood transfusion after total knee arthroplasty (TKA). There are, however, no studies reporting a value that could be considered to be appropriate pre-operatively. This study aimed to identify threshold pre-operative levels of haemoglobin that would predict the requirement for blood transfusion in patients who undergo TKA. Analysis of receiver operator characteristic (ROC) curves of 2284 consecutive patients undergoing unilateral TKA was used to determine gender specific thresholds predicting peri-operative transfusion with the highest combined sensitivity and specificity (area under ROC curve 0.79 for males; 0.78 for females). Threshold levels of 13.75 g/dl for males and 12.75 g/dl for females were identified. The rates of transfusion in males and females, respectively above these levels were 3.37% and 7.11%, while below these levels, they were 16.13% and 28.17%. Pre-operative anaemia increased the rate of transfusion by 6.38 times in males and 6.27 times in females. Blood transfusion was associated with an increased incidence of early post-operative confusion (odds ratio (OR) = 3.44), cardiac arrhythmia (OR = 5.90), urinary catheterisation (OR = 1.60), the incidence of deep infection (OR = 4.03) and mortality (OR = 2.35) one year post-operatively, and increased length of stay (eight days vs six days, p < 0.001). Uncorrected low pre-operative levels of haemoglobin put patients at potentially modifiable risk and attempts should be made to correct this before TKA. Target thresholds for the levels of haemoglobin pre-operatively in males and females are proposed. Low pre-operative haemoglobin levels put patients at unnecessary risk and should be corrected prior to surgery. ©2016 The British Editorial Society of Bone & Joint Surgery.

NASA Ares I Launch Vehicle First Stage Roll Control System Cold Flow Development Test Program Overview

NASA Technical Reports Server (NTRS)

Butt, Adam; Popp, Christopher G.; Holt, Kimberly A.; Pitts, Hank M.

2010-01-01

The Ares I launch vehicle is the selected design, chosen to return humans to the moon, Mars, and beyond. It is configured in two inline stages: the First Stage is a Space Shuttle derived five-segment Solid Rocket Booster and the Upper Stage is powered by a Saturn V derived J-2X engine. During launch, roll control for the First Stage (FS) is handled by a dedicated Roll Control System (RoCS) located on the connecting Interstage. That system will provide the Ares I with the ability to counteract induced roll torque while any induced yaw or pitch moments are handled by vectoring of the booster nozzle. This paper provides an overview of NASA s Ares I FS RoCS cold flow development test program including detailed test objectives, types of tests run to meet those objectives, an overview of the results, and applicable lessons learned. The test article was built and tested at the NASA Marshall Space Flight Center in Huntsville, AL. The FS RoCS System Development Test Article (SDTA) is a full scale, flight representative water flow test article whose primary objective was to obtain fluid system performance data to evaluate integrated system level performance characteristics and verify analytical models. Development testing and model correlation was deemed necessary as there is little historical precedent for similar large flow, pulsing systems such as the FS RoCS. The cold flow development test program consisted of flight-similar tanks, pressure regulators, and thruster valves, as well as plumbing simulating flight geometries, combined with other facility grade components and structure. Orifices downstream of the thruster valves were used to simulate the pressure drop through the thrusters. Additional primary objectives of this test program were to: evaluate system surge pressure (waterhammer) characteristics due to thruster valve operation over a range of mission duty cycles at various feed system pressures, evaluate temperature transients and heat transfer in the pressurization system, including regulator blowdown and propellant ullage performance, measure system pressure drops for comparison to analysis of tubing and components, and validate system activation and re-activation procedures for the helium pressurant system. Secondary objectives included: validating system processes for loading, unloading, and purging, validating procedures and system response for multiple failure scenarios, including relief valve operation, and evaluating system performance for contingency scenarios. The test results of the cold flow development test program are essential in validating the performance and interaction of the Roll Control System and anchoring analysis tools and results to a Critical Design Review level of fidelity.

A receiver operated curve-based evaluation of change in sensitivity and specificity of cotinine urinalysis for detecting active tobacco use.

PubMed

Balhara, Yatan Pal Singh; Jain, Raka

2013-01-01

Tobacco use has been associated with various carcinomas including lung, esophagus, larynx, mouth, throat, kidney, bladder, pancreas, stomach, and cervix. Biomarkers such as concentration of cotinine in the blood, urine, or saliva have been used as objective measures to distinguish nonusers and users of tobacco products. A change in the cut-off value of urinary cotinine to detect active tobacco use is associated with a change in sensitivity and sensitivity of detection. The current study aimed at assessing the impact of using different cut-off thresholds of urinary cotinine on sensitivity and specificity of detection of smoking and smokeless tobacco product use among psychiatric patients. All the male subjects attending the psychiatry out-patient department of the tertiary care multispecialty teaching hospital constituted the sample frame for the current study in a cross-sectionally. Quantitative urinary cotinine assay was done by using ELISA kits of Calbiotech. Inc., USA. We used the receiver operating characteristic (ROC) curve to assess the sensitivity and specificity of various cut-off values of urinary cotinine to identify active smokers and users of smokeless tobacco products. ROC analysis of urinary cotinine levels in detection of self-reported smoking provided the area under curve (AUC) of 0.434. Similarly, the ROC analysis of urinary cotinine levels in detection of self-reported smoking revealed AUC of 0.44. The highest sensitivity and specificity of 100% for smoking were detected at the urinary cut-off value greater than or equal to 2.47 ng/ml. The choice of cut-off value of urinary cotinine used to distinguish nonusers form active users of tobacco products impacts the sensitivity as well as specificity of detection.

A comparative study of fire weather indices in a semiarid south-eastern Europe region. Case of study: Murcia (Spain).

PubMed

Pérez-Sánchez, Julio; Senent-Aparicio, Javier; Díaz-Palmero, José María; Cabezas-Cerezo, Juan de Dios

2017-07-15

Forest fires are an important distortion in forest ecosystems, linked to their development and whose effects proceed beyond the destruction of ecosystems and material properties, especially in semiarid regions. Prevention of forest fires has to lean on indices based on available parameters that quantify fire risk ignition and spreading. The present study was conducted to compare four fire weather indices in a semiarid region of 11,314km 2 located in southern Spain, characterised as being part of the most damaged area by fire in the Iberian Peninsula. The studied period comprises 3033 wildfires in the region during 15years (2000-2014), of which 80% are >100m 2 and 14% >1000m 2 , resulting around 40km 2 of burnt area in this period. The indices selected have been Angström Index, Forest Fire Drought Index, Forest Moisture Index and Fire Weather Index. Likewise, four selection methods have been applied to compare the results of the studied indices: Mahalanobis distance, percentile method, ranked percentile method and Relative Operating Characteristic curves (ROC). Angström index gives good results in the coastal areas with higher temperatures, low rainfall and wider range of variations while Fire Weather Index has better results in inland areas with higher rainfall, dense forest mass and fewer changes in meteorological conditions throughout the year. ROC space rejects all the indices except Fire Weather Index with good performance all over the region. ROC analysis ratios can be used to assess the success (or lack thereof) of fire indices; thus, it benefits operational wildfire predictions in semiarid regions similar to that of the case study. Copyright © 2017 Elsevier B.V. All rights reserved.

East London Modified-Broset as Decision-Making Tool to Predict Seclusion in Psychiatric Intensive Care Units.

PubMed

Loi, Felice; Marlowe, Karl

2017-01-01

Seclusion is a last resort intervention for management of aggressive behavior in psychiatric settings. There is no current objective and practical decision-making instrument for seclusion use on psychiatric wards. Our aim was to test the predictive and discriminatory characteristics of the East London Modified-Broset (ELMB), to delineate its decision-making profile for seclusion of adult psychiatric patients, and second to benchmark it against the psychometric properties of the Broset Violence Checklist (BVC). ELMB, an 8-item modified version of the 6-item BVC, was retrospectively employed to evaluate the seclusion decision-making process on two Psychiatric Intensive Care Units (patients n  = 201; incidents n  = 2,187). Data analyses were carried out using multivariate regression and Receiver Operating Characteristic (ROC) curves. Predictors of seclusion were: physical violence toward staff/patients OR = 24.2; non-compliance with PRN (pro re nata) medications OR = 9.8; and damage to hospital property OR = 2.9. ROC analyses indicated that ELMB was significantly more accurate that BVC, with higher sensitivity, specificity, and positive likelihood ratio. Results were similar across gender. The ELMB is a sensitive and specific instrument that can be used to guide the decision-making process when implementing seclusion.

East London Modified-Broset as Decision-Making Tool to Predict Seclusion in Psychiatric Intensive Care Units

PubMed Central

Loi, Felice; Marlowe, Karl

2017-01-01

Seclusion is a last resort intervention for management of aggressive behavior in psychiatric settings. There is no current objective and practical decision-making instrument for seclusion use on psychiatric wards. Our aim was to test the predictive and discriminatory characteristics of the East London Modified-Broset (ELMB), to delineate its decision-making profile for seclusion of adult psychiatric patients, and second to benchmark it against the psychometric properties of the Broset Violence Checklist (BVC). ELMB, an 8-item modified version of the 6-item BVC, was retrospectively employed to evaluate the seclusion decision-making process on two Psychiatric Intensive Care Units (patients n = 201; incidents n = 2,187). Data analyses were carried out using multivariate regression and Receiver Operating Characteristic (ROC) curves. Predictors of seclusion were: physical violence toward staff/patients OR = 24.2; non-compliance with PRN (pro re nata) medications OR = 9.8; and damage to hospital property OR = 2.9. ROC analyses indicated that ELMB was significantly more accurate that BVC, with higher sensitivity, specificity, and positive likelihood ratio. Results were similar across gender. The ELMB is a sensitive and specific instrument that can be used to guide the decision-making process when implementing seclusion. PMID:29046647

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.

Screening for type 2 diabetes and prediabetes in obese youth: evaluating alternate markers of glycemia - 1,5-anhydroglucitol, fructosamine, and glycated albumin.

PubMed

Chan, Christine L; Pyle, Laura; Kelsey, Megan; Newnes, Lindsey; Zeitler, Philip S; Nadeau, Kristen J

2016-05-01

Hemoglobin A1c (HbA1c) is increasingly performed over the oral glucose tolerance test (OGTT) as the initial screening test for type 2 diabetes in youth. However, the optimal strategy for identifying type 2 diabetes in youth remains controversial. Alternate glycemic markers have been proposed as potentially useful tools for diabetes screening. We examined the relationships among fructosamine (FA), glycated albumin (GA), and 1,5-anhydroglucitol (1,5-AG) with traditional screening tests, HbA1c and OGTT. Youth 10-18 yrs, BMI ≥85th‰, and HbA1c <7.5% had a single visit with measurement of HbA1c, 1,5-AG, FA, GA, and a standard OGTT. Distributions of FA, GA, and 1,5-AG by HbA1c and 2-hour glucose (2hG) categories were compared. Receiver operating characteristic (ROC)-curves were generated to determine the cut points at which alternate markers maximized sensitivity and specificity for predicting prediabetes and diabetes. One hundred and seventeen, 62% female, 59% Hispanic, 22% White, 17% black, median 14.1 yr, and body mass index (BMI) z-score 2.3 participated. Median values of each alternate marker differed significantly between prediabetes and diabetes HbA1c and 2hG categories (p < 0.017). Only GA medians differed (p = 0.006) between normal and prediabetes HbA1c. Area under the receiver operating characteristic curves (ROC-AUCs) for alternate markers as predictors of prediabetes (0.5-0.66) were low; however, alternate marker ROC-AUCs for identifying diabetes (0.82-0.98) were excellent. Although the alternate markers were poor predictors of prediabetes, they all performed well predicting diabetes by 2hG and HbA1c. Whereas the usefulness of these markers for identifying prediabetes is limited, they may be useful in certain scenarios as second line screening tools for diabetes in overweight/obese youth. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

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.

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.

The diagnostic efficiency of the extended German Brøset Violence Checklist to assess the risk of violence.

PubMed

Rechenmacher, Josef; Müller, Gerhard; Abderhalden, Christoph; Schulc, Eva

2014-01-01

The prevention of aggression and violence of patients is part of the challenge for the psychiatric inpatient care. Resources needed are a systematic risk assessment and taking preventive measures according to the risk. The extended Brøset Violence Checklist (BVC-CH) is an assessment instrument for the short-term assessment of the risk of violence for physical attacks toward medical staff and other patients. Until now, the instrument was only validated in the context of the development phase of the instrument. The aim of this study was to investigate how valid the BVC-CH scale is for adult psychiatry in acute inpatient care facilities. In a prospective cohort study, 232 consecutively admitted patients were assessed using the BVC-CH. The calculation of the predictive values was based on a contingency table. The discriminatory power of the instrument and the determination of the cutoff point were done using the receiver operating characteristic (ROC) curve analysis. Physical attacks were registered with the Staff Observation of Aggression Scale-Revised (SOAS-R). The sensitivity was 58.8% and the specificity was 96.8% by a cutoff point of > or = 7. By choosing a cutoff point of > or = 6, the sensitivity was 64.7% and the specificity was 95.1%. A value of .93 was determined for the area under the curve receiver operating characteristic (AUC(ROC)). Overall, the BVC-CH is a valid instrument for the short-term prediction of physical attacks. Further research of the BVC-CH is recommended but in particular for the cutoff point.

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

PubMed

Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L

2016-02-01

Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

Acute respiratory distress syndrome in blunt trauma: identification of independent risk factors.

PubMed

Miller, Preston R; Croce, Martin A; Kilgo, Patrick D; Scott, John; Fabian, Timothy C

2002-10-01

Acute respiratory distress syndrome (ARDS) is a major contributor to morbidity and mortality in trauma patients. Although many injuries and conditions are believed to be associated with ARDS independent risk factors in trauma patients and their relative importance in development of the syndrome are undefined. The aim of this project is to identify independent risk factors for the development of ARDS in blunt trauma patients and to examine the contributions of each factor to ARDS development. Patients with ARDS were identified from the registry of a Level I trauma center over a 4.5-year period. Records were reviewed for demographics, injury characteristics, transfusion requirements, and hospital course. Variables examined included age >65 years, Injury Severity Score (ISS) >25, hypotension on admission (systolic blood pressure <90), significant metabolic acidosis (base deficit <-5.0), severe brain injury as shown by a Glasgow Coma Scale score (GCS) <8 on admission, 24-hour transfusion requirement >10 units packed red blood cells, pulmonary contusion (PC), femur fracture, and major infection (pneumonia, empyema, or intra-abdominal abscess). Both univariate and stepwise logistic regression were used to identify independent risk factors, and receiver operating characteristic curve (ROC) analysis was used to determine the relative contribution of each risk factor. A total of 4397 patients having sustained blunt trauma were admitted to the intensive care unit and survived >24 hours between October 1995 and May 2000. Of these patients 200 (4.5%) developed ARDS. All studied variables were significantly associated with ARDS in univariate analyses. Stepwise logistic regression, however, demonstrated age >65 years, ISS >25, hypotension on admission, 24-hour transfusion requirement >10 units, and pulmonary contusion as independent risk factors, whereas admission metabolic acidosis, femur fracture, infection, and severe brain injury were not. Using a model based on the logistic regression equation derived yields better than 80 per cent discrimination in ARDS patients. The risk factors providing the greatest contribution to ARDS development were ISS >25 (ROC area 0.72) and PC (ROC area 0.68) followed by large transfusion requirement (ROC area 0.56), admission hypotension (ROC area 0.57), and age >65 (ROC area 0.54). Independent risk factors for ARDS in blunt trauma include ISS >25, PC, age >65 years, hypotension on admission, and 24-hour transfusion requirement >10 units but not admission metabolic acidosis, femur fracture, infection, or severe brain injury. Assessment of these variables allows accurate estimate of risk in the majority of cases, and the most potent contributors to the predictive value of the model are ISS >25 and PC. Improvement in understanding of which patients are actually at risk may allow for advances in treatment as well as prevention in the future.

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.

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

The first Latin-American risk stratification system for cardiac surgery: can be used as a graphic pocket-card score.

PubMed

Carosella, Victorio C; Navia, Jose L; Al-Ruzzeh, Sharif; Grancelli, Hugo; Rodriguez, Walter; Cardenas, Cesar; Bilbao, Jorge; Nojek, Carlos

2009-08-01

This study aims to develop the first Latin-American risk model that can be used as a simple, pocket-card graphic score at bedside. The risk model was developed on 2903 patients who underwent cardiac surgery at the Spanish Hospital of Buenos Aires, Argentina, between June 1994 and December 1999. Internal validation was performed on 708 patients between January 2000 and June 2001 at the same center. External validation was performed on 1087 patients between February 2000 and January 2007 at three other centers in Argentina. In the development dataset the area under receiver operating characteristics (ROC) curve was 0.73 and the Hosmer-Lemeshow (HL) test was P=0.88. In the internal validation ROC curve was 0.77. In the external validation ROC curve was 0.81, but imperfect calibration was detected because the observed in-hospital mortality (3.96%) was significantly lower than the development dataset (8.20%) (P<0.0001). Recalibration was done in 2007, showing excellent level of agreement between the observed and predicted mortality rates on all patients (P=0.92). This is the first risk model for cardiac surgery developed in a population of Latin-America with both internal and external validation. A simple graphic pocket-card score allows an easy bedside application with acceptable statistic precision.

External validation of the ability of the DRAGON score to predict outcome after thrombolysis treatment.

PubMed

Ovesen, C; Christensen, A; Nielsen, J K; Christensen, H

2013-11-01

Easy-to-perform and valid assessment scales for the effect of thrombolysis are essential in hyperacute stroke settings. Because of this we performed an external validation of the DRAGON scale proposed by Strbian et al. in a Danish cohort. All patients treated with intravenous recombinant plasminogen activator between 2009 and 2011 were included. Upon admission all patients underwent physical and neurological examination using the National Institutes of Health Stroke Scale along with non-contrast CT scans and CT angiography. Patients were followed up through the Outpatient Clinic and their modified Rankin Scale (mRS) was assessed after 3 months. Three hundred and three patients were included in the analysis. The DRAGON scale proved to have a good discriminative ability for predicting highly unfavourable outcome (mRS 5-6) (area under the curve-receiver operating characteristic [AUC-ROC]: 0.89; 95% confidence interval [CI] 0.81-0.96; p<0.001) and good outcome (mRS 0-2) (AUC-ROC: 0.79; 95% CI 0.73-0.85; p<0.001). When only patients with M1 occlusions were selected the DRAGON scale provided good discriminative capability (AUC-ROC: 0.89; 95% CI 0.78-1.0; p=0.003) for highly unfavourable outcome. We confirmed the validity of the DRAGON scale in predicting outcome after thrombolysis treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings.

PubMed

Cowling, Benjamin J; Muller, Matthew P; Wong, Irene O L; Ho, Lai-Ming; Lo, Su-Vui; Tsang, Thomas; Lam, Tai Hing; Louie, Marie; Leung, Gabriel M

2006-07-24

An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.

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

Cerebrospinal fluid cytokines in the diagnosis of bacterial meningitis in infants.

PubMed

Srinivasan, Lakshmi; Kilpatrick, Laurie; Shah, Samir S; Abbasi, Soraya; Harris, Mary C

2016-10-01

Bacterial meningitis poses diagnostic challenges in infants. Antibiotic pretreatment and low bacterial density diminish cerebrospinal fluid (CSF) culture yield, while laboratory parameters do not reliably identify bacterial meningitis. Pro and anti-inflammatory cytokines are elevated in bacterial meningitis and may be useful diagnostic adjuncts when CSF cultures are negative. In a prospective cohort study of infants, we used cytometric bead arrays to measure tumor necrosis factor alpha (TNF-α), interleukin 1 (IL-1), IL-6, IL-8, IL-10, and IL-12 in CSF. Receiver operating characteristic (ROC) analyses and Principal component analysis (PCA) were used to determine cytokine combinations that identified bacterial meningitis. Six hundred and eighty four infants < 6 mo were included; 11 had culture-proven bacterial meningitis. IL-6 and IL-10 were the individual cytokines possessing greatest accuracy in diagnosis of culture proven bacterial meningitis (ROC analyses; area under the concentration-time curve (AUC) 0.91; 0.9103 respectively), and performed as well as, or better than combinations identified using ROC and PCA. CSF cytokines were highly correlated with each other and with CSF white blood cell count (WBC) counts in infants with meningitis. A subset of antibiotic pretreated culture-negative subjects demonstrated cytokine patterns similar to culture positive subjects. CSF cytokine levels may aid diagnosis of bacterial meningitis, and facilitate decision-making regarding treatment for culture negative meningitis.

A new approach of objective quality evaluation on JPEG2000 lossy-compressed lung cancer CT images

NASA Astrophysics Data System (ADS)

Cai, Weihua; Tan, Yongqiang; Zhang, Jianguo

2007-03-01

Image compression has been used to increase the communication efficiency and storage capacity. JPEG 2000 compression, based on the wavelet transformation, has its advantages comparing to other compression methods, such as ROI coding, error resilience, adaptive binary arithmetic coding and embedded bit-stream. However it is still difficult to find an objective method to evaluate the image quality of lossy-compressed medical images so far. In this paper, we present an approach to evaluate the image quality by using a computer aided diagnosis (CAD) system. We selected 77 cases of CT images, bearing benign and malignant lung nodules with confirmed pathology, from our clinical Picture Archiving and Communication System (PACS). We have developed a prototype of CAD system to classify these images into benign ones and malignant ones, the performance of which was evaluated by the receiver operator characteristics (ROC) curves. We first used JPEG 2000 to compress these cases of images with different compression ratio from lossless to lossy, and used the CAD system to classify the cases with different compressed ratio, then compared the ROC curves from the CAD classification results. Support vector machine (SVM) and neural networks (NN) were used to classify the malignancy of input nodules. In each approach, we found that the area under ROC (AUC) decreases with the increment of compression ratio with small fluctuations.

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia

PubMed Central

Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Purpose Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Methods Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. Results We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Conclusion Learning curve seems to complete after performing 16 cases. PMID:28686640

Monthly and seasonally verification of precipitation in Poland

NASA Astrophysics Data System (ADS)

Starosta, K.; Linkowska, J.

2009-04-01

The national meteorological service of Poland - the Institute of Meteorology and Water Management (IMWM) joined COSMO - The Consortium for Small Scale Modelling on July 2004. In Poland, the COSMO _PL model version 3.5 had run till June 2007. Since July 2007, the model version 4.0 has been running. The model runs in an operational mode at 14-km grid spacing, twice a day (00 UTC, 12 UTC). For scientific research also model with 7-km grid spacing is ran. Monthly and seasonally verification for the 24-hours (06 UTC - 06 UTC) accumulated precipitation is presented in this paper. The precipitation field of COSMO_LM had been verified against rain gauges network (308 points). The verification had been made for every month and all seasons from December 2007 to December 2008. The verification was made for three forecast days for selected thresholds: 0.5, 1, 2.5, 5, 10, 20, 25, 30 mm. Following indices from contingency table were calculated: FBI (bias), POD (probability of detection), PON (probability of detection of non event), FAR (False alarm rate), TSS (True sill statistic), HSS (Heidke skill score), ETS (Equitable skill score). Also percentile ranks and ROC-relative operating characteristic are presented. The ROC is a graph of the hit rate (Y-axis) against false alarm rate (X-axis) for different decision thresholds

Monthly and seasonally verification of precipitation in Poland

NASA Astrophysics Data System (ADS)

Starosta, K.; Linkowska, J.

2009-04-01

The national meteorological service of Poland - the Institute of Meteorology and Water Management (IMWM) joined COSMO - The Consortium for Small Scale Modelling on July 2004. In Poland, the COSMO _PL model version 3.5 had run till June 2007. Since July 2007, the model version 4.0 has been running. The model runs in an operational mode at 14-km grid spacing, twice a day (00 UTC, 12 UTC). For scientific research also model with 7-km grid spacing is ran. Monthly and seasonally verification for the 24-hours (06 UTC - 06 UTC) accumulated precipitation is presented in this paper. The precipitation field of COSMO_LM had been verified against rain gauges network (308 points). The verification had been made for every month and all seasons from December 2007 to December 2008. The verification was made for three forecast days for selected thresholds: 0.5, 1, 2.5, 5, 10, 20, 25, 30 mm. Following indices from contingency table were calculated: FBI (bias), POD (probability of detection), PON (probability of detection of non event), FAR (False alarm rate), TSS (True sill statistic), HSS (Heidke skill score), ETS (Equitable skill score). Also percentile ranks and ROC-relative operating characteristic are presented. The ROC is a graph of the hit rate (Y-axis) against false alarm rate (X-axis) for different decision thresholds.

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia.

PubMed

Yano, Fumiaki; Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Learning curve seems to complete after performing 16 cases.

Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS.

PubMed

Golkarian, Ali; Naghibi, Seyed Amir; Kalantar, Bahareh; Pradhan, Biswajeet

2018-02-17

Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.

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.

Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

NASA Astrophysics Data System (ADS)

Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Adler, Dorit D.; Blane, Caroline E.; Joynt, Lynn K.; Paramagul, Chintana; Roubidoux, Marilyn A.; Wilson, Todd E.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

1999-05-01

A receiver operating characteristic (ROC) experiment was conducted to evaluate the effects of pixel size on the characterization of mammographic microcalcifications. Digital mammograms were obtained by digitizing screen-film mammograms with a laser film scanner. One hundred twelve two-view mammograms with biopsy-proven microcalcifications were digitized at a pixel size of 35 micrometer X 35 micrometer. A region of interest (ROI) containing the microcalcifications was extracted from each image. ROI images with pixel sizes of 70 micrometers, 105 micrometers, and 140 micrometers were derived from the ROI of 35 micrometer pixel size by averaging 2 X 2, 3 X 3, and 4 X 4 neighboring pixels, respectively. The ROI images were printed on film with a laser imager. Seven MQSA-approved radiologists participated as observers. The likelihood of malignancy of the microcalcifications was rated on a 10-point confidence rating scale and analyzed with ROC methodology. The classification accuracy was quantified by the area, Az, under the ROC curve. The statistical significance of the differences in the Az values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz (DBM) method for multi-reader, multi-case ROC data. It was found that five of the seven radiologists demonstrated a higher classification accuracy with the 70 micrometer or 105 micrometer images. The average Az also showed a higher classification accuracy in the range of 70 to 105 micrometer pixel size. However, the differences in A(subscript z/ between different pixel sizes did not achieve statistical significance. The low specificity of image features of microcalcifications an the large interobserver and intraobserver variabilities may have contributed to the relatively weak dependence of classification accuracy on pixel size.

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.

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.

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

PubMed

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

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.

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.

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

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

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

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.

Decision making for pancreatic resection in patients with intraductal papillary mucinous neoplasms.

PubMed

Xu, Bin; Ding, Wei-Xing; Jin, Da-Yong; Wang, Dan-Song; Lou, Wen-Hui

2013-03-07

To identify a practical approach for preoperative decision-making in patients with intraductal papillary mucinous neoplasms (IPMNs) of the pancreas. Between March 1999 and November 2006, the clinical characteristics, pathological data and computed tomography/magnetic resonance imaging (CT/MRI) of 54 IPMNs cases were retrieved and analyzed. The relationships between the above data and decision-making for pancreatic resection were analyzed using SPSS 13.0 software. Univariate analysis of risk factors for malignant or invasive IPMNs was performed with regard to the following variables: carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9) and the characteristics from CT/MRI images. Receiver operating characteristic (ROC) curve analysis for pancreatic resection was performed using significant factors from the univariate analysis. CT/MRI images, including main and mixed duct IPMNs, tumor size > 30 mm or a solid component appearance in the lesion, and preoperative serum CA19-9 > 37 U/mL had good predictive value for determining pancreatic resection (P < 0.05), but with limitations. Combining the above factors (CT/MRI images and CA19-9) improved the accuracy and sensitivity for determining pancreatic resection in IPMNs. Using ROC analysis, the area under the curve reached 0.893 (P < 0.01, 95%CI: 0.763-1.023), with a sensitivity, specificity, positive predictive value and negative predictive value of 95.2%, 83.3%, 95.2% and 83.3%, respectively. Combining preoperative CT/MRI images and CA19-9 level may provide useful information for surgical decision-making in IPMNs.

Clinical Decision Making Following Disasters: Efficient Identification of PTSD Risk in Adolescents

PubMed Central

Danielson, Carla Kmett; Cohen, Joseph; Adams, Zachary; Youngstrom, Eric A.; Soltis, Kathryn; Amstadter, Ananda B.; Ruggiero, Kenneth J.

2016-01-01

The present study aimed to utilize a Receiver Operating Characteristic (ROC) approach in order to improve clinical decision-making for adolescents at risk for the development of psychopathology in the aftermath of a natural disaster. Specifically we assessed theoretically-driven individual, interpersonal, and event-related vulnerability factors to determine which indices were most accurate in forecasting PTSD. Furthermore, we aimed to translate these etiological findings by identifying clinical cut-off recommendations for relevant vulnerability factors. Our study consisted of structured phone-based clinical interviews with 2,000 adolescent-parent dyads living within a 5-mile radius of tornados that devastated Joplin, MO, and northern Alabama in Spring 2011. Demographics, tornado incident characteristics, prior trauma, mental health, and family support and conflict were assessed. A subset of youth completed two behavioral assessment tasks online to assess distress tolerance and risk taking behavior. ROC analyses indicated four variables that significantly improved PTSD diagnostic efficiency: Lifetime depression (AUC=.90), trauma history (AUC=.76), social support (AUC=.70), and family conflict (AUC=.72). Youth were 2–3 times more likely to have PTSD if they had elevated scores on any of these variables. Of note, event-related characteristics (e.g., property damage) were not related to PTSD diagnostic status. The present study adds to the literature by making specific recommendations for empirically-based, efficient disaster-related PTSD assessment for adolescents following a natural disaster. Implications for practice and future trauma-related developmental psychopathology research are discussed. PMID:27103002

Validation of a Chichewa version of the self-reporting questionnaire (SRQ) as a brief screening measure for maternal depressive disorder in Malawi, Africa.

PubMed

Stewart, Robert C; Kauye, Felix; Umar, Eric; Vokhiwa, Maclean; Bunn, James; Fitzgerald, Margaret; Tomenson, Barbara; Rahman, Atif; Creed, Francis

2009-01-01

Depressive disorder affecting women during the perinatal period is common in low-income countries. The detection and study of maternal depression in a resource-poor setting requires a brief screening tool that is both accurate and practical to administer. A Chichewa version of the Self Reporting Questionnaire (SRQ) was developed through a rigorous process of forward and back translation, focus-group discussion and piloting. Criterion validation was conducted as part of a larger study in a sample of women who had brought their infants to a child health clinic in rural Malawi, using DSM-IV major and minor depressive episode as the gold standard diagnoses. The criterion validation was conducted on 114 subjects who did not differ on health and sociodemographic characteristics from the total study sample (n=501). Test characteristics for each possible SRQ cut-off were calculated and Receiver Operator Characteristic (ROC) curves derived. Area under the ROC curve (AUROC) for detection of current major depressive disorder was 0.856 (95% CI 0.813 to 0.900), and for current major or minor depressive disorder was 0.826 (95% CI 0.783 to 0.869). Internal consistency of the SRQ was high (Cronbach's alpha 0.85). Inter-rater reliability testing was not conducted. This Chichewa version of the SRQ shows utility as a brief screening measure for detection of probable maternal depression in rural Malawi.

Clinical Decision-Making Following Disasters: Efficient Identification of PTSD Risk in Adolescents.

PubMed

Danielson, Carla Kmett; Cohen, Joseph R; Adams, Zachary W; Youngstrom, Eric A; Soltis, Kathryn; Amstadter, Ananda B; Ruggiero, Kenneth J

2017-01-01

The present study aimed to utilize a Receiver Operating Characteristic (ROC) approach in order to improve clinical decision-making for adolescents at risk for the development of psychopathology in the aftermath of a natural disaster. Specifically we assessed theoretically-driven individual, interpersonal, and event-related vulnerability factors to determine which indices were most accurate in forecasting PTSD. Furthermore, we aimed to translate these etiological findings by identifying clinical cut-off recommendations for relevant vulnerability factors. Our study consisted of structured phone-based clinical interviews with 2000 adolescent-parent dyads living within a 5-mile radius of tornados that devastated Joplin, MO, and northern Alabama in Spring 2011. Demographics, tornado incident characteristics, prior trauma, mental health, and family support and conflict were assessed. A subset of youth completed two behavioral assessment tasks online to assess distress tolerance and risk-taking behavior. ROC analyses indicated four variables that significantly improved PTSD diagnostic efficiency: Lifetime depression (AUC = .90), trauma history (AUC = .76), social support (AUC = .70), and family conflict (AUC = .72). Youth were 2-3 times more likely to have PTSD if they had elevated scores on any of these variables. Of note, event-related characteristics (e.g., property damage) were not related to PTSD diagnostic status. The present study adds to the literature by making specific recommendations for empirically-based, efficient disaster-related PTSD assessment for adolescents following a natural disaster. Implications for practice and future trauma-related developmental psychopathology research are discussed.

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.

A study on risk factors and diagnostic efficiency of posthepatectomy liver failure in the nonobstructive jaundice.

PubMed

Wang, He; Lu, Shi-Chun; He, Lei; Dong, Jia-Hong

2018-02-01

Liver failure remains as the most common complication and cause of death after hepatectomy, and continues to be a challenge for doctors.t test and χ test were used for single factor analysis of data-related variables, then results were introduced into the model to undergo the multiple factors logistic regression analysis. Pearson correlation analysis was performed for related postoperative indexes, and a diagnostic evaluation was performed using the receiver operating characteristic (ROC) of postoperative indexes.Differences in age, body mass index (BMI), portal vein hypertension, bile duct cancer, total bilirubin, alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), operation time, cumulative portal vein occlusion time, intraoperative blood volume, residual liver volume (RLV)/entire live rvolume, ascites volume at postoperative day (POD)3, supplemental albumin amount at POD3, hospitalization time after operation, and the prothrombin activity (PTA) were statistically significant. Furthermore, there were significant differences in total bilirubin and the supplemental albumin amount at POD3. ROC analysis of the average PTA, albumin amounts, ascites volume at POD3, and their combined diagnosis were performed, which had diagnostic value for postoperative liver failure (area under the curve (AUC): 0.895, AUC: 0.798, AUC: 0.775, and AUC: 0.903).Preoperative total bilirubin level and the supplemental albumin amount at POD3 were independent risk factors. PTA can be used as the index of postoperative liver failure, and the combined diagnosis of the indexes can improve the early prediction of postoperative liver failure.

Change in end-tidal carbon dioxide outperforms other surrogates for change in cardiac output during fluid challenge.

PubMed

Lakhal, K; Nay, M A; Kamel, T; Lortat-Jacob, B; Ehrmann, S; Rozec, B; Boulain, T

2017-03-01

During fluid challenge, volume expansion (VE)-induced increase in cardiac output (Δ VE CO) is seldom measured. In patients with shock undergoing strictly controlled mechanical ventilation and receiving VE, we assessed minimally invasive surrogates for Δ VE CO (by transthoracic echocardiography): fluid-induced increases in end-tidal carbon dioxide (Δ VE E'CO2 ); pulse (Δ VE PP), systolic (Δ VE SBP), and mean systemic blood pressure (Δ VE MBP); and femoral artery Doppler flow (Δ VE FemFlow). In the absence of arrhythmia, fluid-induced decrease in heart rate (Δ VE HR) and in pulse pressure respiratory variation (Δ VE PPV) were also evaluated. Areas under the receiver operating characteristic curves (AUC ROC s) reflect the ability to identify a response to VE (Δ VE CO ≥15%). In 86 patients, Δ VE E'CO2 had an AUC ROC =0.82 [interquartile range 0.73-0.90], significantly higher than the AUC ROC for Δ VE PP, Δ VE SBP, Δ VE MBP, and Δ VE FemFlow (AUC ROC =0.61-0.65, all P  <0.05). A value of Δ VE E'CO2  >1 mm Hg (>0.13 kPa) had good positive (5.0 [2.6-9.8]) and fair negative (0.29 [0.2-0.5]) likelihood ratios. The 16 patients with arrhythmia had similar relationships between Δ VE E'CO2 and Δ VE CO to patients with regular rhythm ( r 2 =0.23 in both subgroups). In 60 patients with no arrhythmia, Δ VE E'CO2 (AUC ROC =0.84 [0.72-0.92]) outperformed Δ VE HR (AUC ROC =0.52 [0.39-0.66], P <0.05) and tended to outperform Δ VE PPV (AUC ROC =0.73 [0.60-0.84], P =0.21). In the 45 patients with no arrhythmia and receiving ventilation with tidal volume <8 ml kg -1 , Δ VE E'CO2 performed better than Δ VE PPV, with AUC ROC =0.86 [0.72-0.95] vs 0.66 [0.49-0.80], P =0.02. Δ VE E'CO2 outperformed Δ VE PP, Δ VE SBP, Δ VE MBP, Δ VE FemFlow, and Δ VE HR and, during protective ventilation, arrhythmia, or both, it also outperformed Δ VE PPV. A value of Δ VE E'CO2 >1 mm Hg (>0.13 kPa) indicated a likely response to VE. © The Author 2017. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Gender differences in the accuracy of time-dependent blood pressure indices for predicting coronary heart disease: A random-effects modeling approach.

PubMed

Brant, Larry J; Ferrucci, Luigi; Sheng, Shan L; Concin, Hans; Zonderman, Alan B; Kelleher, Cecily C; Longo, Dan L; Ulmer, Hanno; Strasak, Alexander M

2010-12-01

Previous studies on blood pressure (BP) indices as a predictor of coronary heart disease (CHD) have provided equivocal results and generally relied on Cox proportional hazards regression methodology, with age and sex accounting for most of the predictive capability of the model. The aim of the present study was to use serially collected BP measurements to examine age-and gender-related differences in BP indices for predicting CHD. The predictive accuracy of time-dependent BP indices for CHD was investigated using a method of risk prediction based on posterior probabilities calculated from mixed-effects regression to utilize intraindividual differences in serial BP measurements according to age changes within gender groups. Data were collected prospectively from 2 community-dwelling cohort studies in the United States (Baltimore Longitudinal Study of Aging [BLSA]) and Europe (Vorarlberg Health Monitoring and Promotion Program [VHM&PP]). The study comprised 152,633 participants (aged 30-74 years) and 610,061 BP measurements. During mean follow-up of 7.5 years, 2457 nonfatal and fatal CHD events were observed. In both study populations, pulse pressure (PP) and systolic blood pressure (SBP) performed best as individual predictors of CHD in women (area under the receiver operating characteristic curve [AUC(ROC)] was between 0.83 and 0.85 for PP, and between 0.77 and 0.81 for SBP). Mean arterial pressure (MAP) and diastolic blood pressure (DBP) performed better for men (AUC(ROC) = 0.67 and 0.65 for MAP and DBP, respectively, in the BLSA; AUC(ROC) = 0.77 and 0.75 in the VHM&PP) than for women (AUC(ROC) = 0.60 for both MAP and DBP in the BLSA; AUC(ROC) = 0.75 and 0.52, respectively, in the VHM&PP). The degree of discrimination in both populations was overall greater but more varied for all BP indices for women (AUC(ROC) estimates between 0.85 [PP in the VHM&PP] and 0.52 [DBP in the VHM&PP]) than for men (AUC(ROC) estimates between 0.78 [MAP + PP in the VHM&PP] and 0.63 [PP in the BLSA]). Our findings indicate differences in discrimination between women and men in the accuracy of longitudinally collected BP measurements for predicting CHD, implicating the usefulness of gender-specific BP indices to assess individual CHD risk. Copyright © 2010. Published by EM Inc USA.

Evaluation of the Aristotle complexity models in adult patients with congenital heart disease.

PubMed

Hörer, Jürgen; Vogt, Manfred; Wottke, Michael; Cleuziou, Julie; Kasnar-Samprec, Jelena; Lange, Rüdiger; Schreiber, Christian

2013-01-01

The adult congenital heart disease (CHD) population has surpassed the paediatric CHD population. Half of all mortality caused by CHD occurs in adulthood; in some patients, it occurs during surgery. We sought to assess the potential risk factors for adverse outcome after cardiac operations in adults with CHD, and to evaluate the predictive power of the Aristotle score models for hospital mortality. Procedure-dependent and independent factors, as well as the outcome factors of all consecutive patients aged 16 or more who underwent surgery for CHD between 2005 and 2008 at our institution were evaluated according to the European Association for Cardio-Thoracic Surgery Congenital Database nomenclature. An Aristotle basic complexity (ABC) and an Aristotle comprehensive complexity (ACC) score were assigned to each operation. The discriminatory power of the scores was assessed using the area under the receiver operating characteristics (AuROC) curve. During 542 operations, 773 procedures were performed. The early mortality rate was 2.4%, and the early complication rate was 53.7%. Tricuspid valve replacement (P = 0.009), mitral valve replacement (P < 0.001), elevated lung resistances (P = 0.002), hypothyroidism (P = 0.002) and redosternotomy (P = 0.003) emerged as risk factors for 30-day mortality. Tricuspid valve replacement (P < 0.001), tricuspid valvuloplasty (P = 0.006), mitral valve replacement (P = 0.003), shunt implantation (P = 0.009), surgical ablation (P = 0.024), myocardial dysfunction (P = 0.014), elevated lung resistances (P = 0.004), hypothyroidism (P = 0.002) and redosternotomy (P < 0.001) emerged as risk factors for complications. Mean ABC and ACC scores were 6.6 ± 2.3, and 9.0 ± 3.7, respectively. The AuROCs of the ABC and the ACC scores for 30-day mortality were 0.663 (P = 0.044), and 0.755 (P = 0.002), respectively. The AuROCs of the ABC and the ACC scores for complications were 0.634 (P < 0.001), and 0.670 (P < 0.001), respectively. Surgery for adults with CHD can be performed with low early mortality. However, complications are frequent, especially in patients who require repeat operations for atrioventricular valve incompetence. The ACC score may be helpful to estimate the risk of early mortality.

Big endothelin-1 as a tumour marker for canine haemangiosarcoma.

PubMed

Fukumoto, Shinya; Miyasho, Taku; Hanazono, Kiwamu; Saida, Kaname; Kadosawa, Tsuyoshi; Iwano, Hidetomo; Uchide, Tsuyoshi

2015-06-01

Haemangiosarcoma (HSA) is an important malignant neoplasm of dogs that originates from vascular endothelial cells. This study explored the suitability of using serum big endothelin-1 (ET-1) as a tumour marker for canine spontaneous HSA. Serum big ET-1 was measured in dogs with splenic HSA (n = 14), splenic malignant tumours other than HSA (n = 10), benign splenic lesions (n = 11) and normal healthy dogs (n = 17) by ELISA. Serum big ET-1 levels in dogs with HSA were significantly (P < 0.01) higher than in other dogs. High sensitivity (100%, 95% confidence interval 86-100%) and specificity (95%, 95% confidence interval 86-95%) for HSA diagnosis were obtained using a cut-off of 17 pg/mL according to receiver operating characteristic (ROC) curves (area under ROC curve 0.93). PPET1, ETA, VEGF and Hif1-α mRNA expression, measured by real-time PCR, were elevated in HSA compared with normal tissues. These findings suggest that elevated serum big ET-1 could be used as a diagnostic marker for canine HSA. Copyright © 2015 Elsevier Ltd. All rights reserved.

Highly predictive and interpretable models for PAMPA permeability.

PubMed

Sun, Hongmao; Nguyen, Kimloan; Kerns, Edward; Yan, Zhengyin; Yu, Kyeong Ri; Shah, Pranav; Jadhav, Ajit; Xu, Xin

2017-02-01

Cell membrane permeability is an important determinant for oral absorption and bioavailability of a drug molecule. An in silico model predicting drug permeability is described, which is built based on a large permeability dataset of 7488 compound entries or 5435 structurally unique molecules measured by the same lab using parallel artificial membrane permeability assay (PAMPA). On the basis of customized molecular descriptors, the support vector regression (SVR) model trained with 4071 compounds with quantitative data is able to predict the remaining 1364 compounds with the qualitative data with an area under the curve of receiver operating characteristic (AUC-ROC) of 0.90. The support vector classification (SVC) model trained with half of the whole dataset comprised of both the quantitative and the qualitative data produced accurate predictions to the remaining data with the AUC-ROC of 0.88. The results suggest that the developed SVR model is highly predictive and provides medicinal chemists a useful in silico tool to facilitate design and synthesis of novel compounds with optimal drug-like properties, and thus accelerate the lead optimization in drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validation of "Signs of Inflammation in Children that Kill" (SICK) score for immediate non-invasive assessment of severity of illness.

PubMed

Gupta, Manoj A; Chakrabarty, Anjan; Halstead, Ruth; Sahni, Mohit; Rangasami, Jayanti; Puliyel, Ashish; Sreenivas, Vishnubhatla; Green, David A; Puliyel, Jacob M

2010-04-26

To validate the SICK scoring system's ability to differentiate between individuals with higher and lower probabilities of death We performed a one year two-centre prospective evaluation of all children aged between one month and 12 years referred to the Paediatric team at St Stephens Hospital in Delhi and admitted to the Paediatric Department at West Middlesex University Hospital in London. We calculated SICK scores at presentation and correlated them with subsequent in-hospital mortality. We used discrimination by areas under receiver operating characteristic (ROC) curves to measure performance. We prospectively evaluated 3895 children in Delhi and 1473 children in London. The areas under the ROC curves were 84.8% in Delhi, 81.0% in London and 84.1% (95% CI 77.4-90.8%) for combined data. Hosmer-Lemeshow goodness of fit for the combined data was good (Hosmer-Lemeshow Chi-square=2.13 (p=0.345). We propose the SICK score as a useful triage tool at initial presentation and highlight its particular suitability for resource poor settings.

[Support vector machine?assisted diagnosis of human malignant gastric tissues based on dielectric properties].

PubMed

Zhang, Sa; Li, Zhou; Xin, Xue-Gang

2017-12-20

To achieve differential diagnosis of normal and malignant gastric tissues based on discrepancies in their dielectric properties using support vector machine. The dielectric properties of normal and malignant gastric tissues at the frequency ranging from 42.58 to 500 MHz were measured by coaxial probe method, and the Cole?Cole model was used to fit the measured data. Receiver?operating characteristic (ROC) curve analysis was used to evaluate the discrimination capability with respect to permittivity, conductivity, and Cole?Cole fitting parameters. Support vector machine was used for discriminating normal and malignant gastric tissues, and the discrimination accuracy was calculated using k?fold cross? The area under the ROC curve was above 0.8 for permittivity at the 5 frequencies at the lower end of the measured frequency range. The combination of the support vector machine with the permittivity at all these 5 frequencies combined achieved the highest discrimination accuracy of 84.38% with a MATLAB runtime of 3.40 s. The support vector machine?assisted diagnosis is feasible for human malignant gastric tissues based on the dielectric properties.

Extraction of Capillary Non-perfusion from Fundus Fluorescein Angiogram

NASA Astrophysics Data System (ADS)

Sivaswamy, Jayanthi; Agarwal, Amit; Chawla, Mayank; Rani, Alka; Das, Taraprasad

Capillary Non-Perfusion (CNP) is a condition in diabetic retinopathy where blood ceases to flow to certain parts of the retina, potentially leading to blindness. This paper presents a solution for automatically detecting and segmenting CNP regions from fundus fluorescein angiograms (FFAs). CNPs are modelled as valleys, and a novel technique based on extrema pyramid is presented for trough-based valley detection. The obtained valley points are used to segment the desired CNP regions by employing a variance-based region growing scheme. The proposed algorithm has been tested on 40 images and validated against expert-marked ground truth. In this paper, we present results of testing and validation of our algorithm against ground truth and compare the segmentation performance against two others methods.The performance of the proposed algorithm is presented as a receiver operating characteristic (ROC) curve. The area under this curve is 0.842 and the distance of ROC from the ideal point (0,1) is 0.31. The proposed method for CNP segmentation was found to outperform the watershed [1] and heat-flow [2] based methods.

A dual-process account of auditory change detection.

PubMed

McAnally, Ken I; Martin, Russell L; Eramudugolla, Ranmalee; Stuart, Geoffrey W; Irvine, Dexter R F; Mattingley, Jason B

2010-08-01

Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed objects with those predicted by change-detection models based on signal detection theory (SDT) and high-threshold theory (HTT). Detected changes were not identified as accurately as predicted by models based on either theory, suggesting that some changes are detected by a process that does not support change identification. Undetected changes were identified as accurately as predicted by the HTT model but much less accurately than predicted by the SDT models. The process underlying change detection was investigated further by determining receiver-operating characteristics (ROCs). ROCs did not conform to those predicted by either a SDT or a HTT model but were well modeled by a dual-process that incorporated HTT and SDT components. The dual-process model also accurately predicted the rates at which detected and undetected changes were correctly identified.

Diagnostic performance of the EMIT-tox benzodiazepine immunoassay, FPIA serum benzodiazepine immunoassay, and radioreceptor assay in suspected acute poisoning.

PubMed

Verstraete, A G; Belpaire, F M; Leroux-Roels, G G

1998-01-01

We evaluated the diagnostic performance of the EMIT-tox serum benzodiazepine assay adapted to a Hitachi 717 analyzer (EMIT), the Abbott ADx serum benzodiazepine fluorescence polarization immunoassay (FPIA), and a radioreceptor assay (RRA) in 113 patients with suspected acute poisoning. The reference method was high-performance liquid chromatography with ultraviolet detection after solid-phase extraction. For the discrimination between negative and positive samples, the areas under the receiver-operating characteristic (ROC) curves were 0.976, 0.991, and 0.991 for EMIT (cutoff, 50-ng/mL diazepam), FPIA (cutoff, 12-ng/mL nordiazepam), and RRA (cutoff, 50-ng/mL diazepam), respectively. For the discrimination between non-toxic and toxic concentrations, the areas under the ROC curves were 0.896, 0.893, and 0.933, respectively. EMIT (with the cutoff lowered to 50 ng/mL), FPIA, and RRA can be reliably used to screen for the presence of benzodiazepines in serum, but in many cases they cannot discriminate between toxic and nontoxic concentrations.

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.

Detection of discontinuous patterns in spontaneous brain activity of neonates and fetuses.

PubMed

Vairavan, Srinivasan; Eswaran, Hari; Haddad, Naim; Rose, Douglas F; Preissl, Hubert; Wilson, James D; Lowery, Curtis L; Govindan, Rathinaswamy B

2009-11-01

The discontinuous patterns in neonatal magnetoencephalographic (MEG) data are quantified with a novel Hilbert phase (HP) based approach. The expert neurologists' scores were used as the gold standard. The performance of this approach was analyzed using a receiver operating characteristic (ROC) curve, and it was compared with two other approaches, namely spectral ratio (SR) and discrete wavelet transform (DWT) that have been proposed for the detection of discontinuous patterns in neonatal EEG. The area under the ROC curve (AUC) was used as a performance measure. AUCs obtained for SR, HP, and DWT were 0.87, 0.80, and 0.56, respectively. Although the performance of HP was lower than SR, it carries information about the frequency content of the signal that helps to distinguish brain patterns from artifacts such as cardiac residuals. Based on this property, the HP approach was extended to fetal MEG data. Further, using the frequency property of the HP approach, burst duration and interburst interval were computed for the discontinuous patterns detected and they are in agreement with reported values.

Validation of "Signs of Inflammation in Children that Kill" (SICK) score for immediate non-invasive assessment of severity of illness

PubMed Central

2010-01-01

Objective To validate the SICK scoring system's ability to differentiate between individuals with higher and lower probabilities of death Method We performed a one year two-centre prospective evaluation of all children aged between one month and 12 years referred to the Paediatric team at St Stephens Hospital in Delhi and admitted to the Paediatric Department at West Middlesex University Hospital in London. We calculated SICK scores at presentation and correlated them with subsequent in-hospital mortality. We used discrimination by areas under receiver operating characteristic (ROC) curves to measure performance. Results We prospectively evaluated 3895 children in Delhi and 1473 children in London. The areas under the ROC curves were 84.8% in Delhi, 81.0% in London and 84.1% (95% CI 77.4 - 90.8%) for combined data. Hosmer-Lemeshow goodness of fit for the combined data was good (Hosmer-Lemeshow Chi-square = 2.13 (p = 0.345). Conclusions We propose the SICK score as a useful triage tool at initial presentation and highlight its particular suitability for resource poor settings. PMID:20420670

Cognitive Vulnerabilities and Depression in Young Adults: An ROC Curves Analysis.

PubMed

Balsamo, Michela; Imperatori, Claudio; Sergi, Maria Rita; Belvederi Murri, Martino; Continisio, Massimo; Tamburello, Antonino; Innamorati, Marco; Saggino, Aristide

2013-01-01

Objectives and Methods. The aim of the present study was to evaluate, by means of receiver operating characteristic (ROC) curves, whether cognitive vulnerabilities (CV), as measured by three well-known instruments (the Beck Hopelessness Scale, BHS; the Life Orientation Test-Revised, LOT-R; and the Attitudes Toward Self-Revised, ATS-R), independently discriminate between subjects with different severities of depression. Participants were 467 young adults (336 females and 131 males), recruited from the general population. The subjects were also administered the Beck Depression Inventory-II (BDI-II). Results. Four first-order (BHS Optimism/Low Standard; BHS Pessimism; Generalized Self-Criticism; and LOT Optimism) and two higher-order factors (Pessimism/Negative Attitudes Toward Self, Optimism) were extracted using Principal Axis Factoring analysis. Although all first-order and second-order factors were able to discriminate individuals with different depression severities, the Pessimism factor had the best performance in discriminating individuals with moderate to severe depression from those with lower depression severity. Conclusion. In the screening of young adults at risk of depression, clinicians have to pay particular attention to the expression of pessimism about the future.

Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis.

PubMed

Hillis, Stephen L; Berbaum, Kevin S; Metz, Charles E

2008-05-01

The Dorfman-Berbaum-Metz (DBM) method has been one of the most popular methods for analyzing multireader receiver-operating characteristic (ROC) studies since it was proposed in 1992. Despite its popularity, the original procedure has several drawbacks: it is limited to jackknife accuracy estimates, it is substantially conservative, and it is not based on a satisfactory conceptual or theoretical model. Recently, solutions to these problems have been presented in three papers. Our purpose is to summarize and provide an overview of these recent developments. We present and discuss the recently proposed solutions for the various drawbacks of the original DBM method. We compare the solutions in a simulation study and find that they result in improved performance for the DBM procedure. We also compare the solutions using two real data studies and find that the modified DBM procedure that incorporates these solutions yields more significant results and clearer interpretations of the variance component parameters than the original DBM procedure. We recommend using the modified DBM procedure that incorporates the recent developments.

Statistical evidence of seismo-ionospheric precursors of the GPS total electron content in China

NASA Astrophysics Data System (ADS)

Chen, Yuh-Ing; Huang, Chi-Shen; Liu, Jann-Yenq

2015-04-01

Evidence of the seismo-ionospheric precursor (SIP) is reported by statistically investigating the relationship between the total electron content (TEC) in global ionosphere map (GIM) and 56 M≥6.0 earthquakes during 1998-2013 in China. A median-based method together with the z test is employed to examine the TEC variations 30 days before and after the earthquake. It is found that the TEC significantly decreases 0600-1000 LT 1-6 days before the earthquake, and anomalously increases in 3 time periods of 1300-1700 LT 12-15 days; 0000-0500 LT 15-17 days; and 0500-0900 LT 22-28 days before the earthquake. The receiver operating characteristic (ROC) curve is then used to evaluate the efficiency of TEC for predicting M≥6.0 earthquakes in China during a specified time period. Statistical results suggest that the SIP is the significant TEC reduction in the morning period of 0600-1000 LT. The SIP is further confirmed since the area under the ROC curve is positively associated with the earthquake magnitude.

Visual inspection versus spectrophotometry in detecting bilirubin in cerebrospinal fluid

PubMed Central

Linn, F; Voorbij, H; Rinkel, G; Algra, A; van Gijn, J

2005-01-01

Methods: Clinicians and students assessed CSF specimens with seven degrees of extinction between 0.00 and 0.09 at 450–460 nm as "yellow," "doubtful," or "colourless" after random presentation under standard conditions. The assessments were compared with spectrophotometry, with 0.05 being taken as the cut off level for the presence of bilirubin. Results were compared between the two groups and explored by means of receiver operating characteristic (ROC) curves. Results: All 51 clinicians and 50 of 51 students scored the tubes with extinction of 0.06 or higher as "yellow" or "doubtful." Tubes without any bilirubin were scored as "yellow" by three of the students only. The ROC curves confirmed that the diagnostic properties of the visual inspection versus spectrophotometry were slightly better for the clinicians than for the students. Conclusions: If CSF is considered colourless, the extinction of bilirubin is too low to be compatible with a diagnosis of recent subarachnoid haemorrhage. If CSF is not considered colourless, spectrophotometry should be carried out to determine the level of extinction of bilirubin. PMID:16170095

No special K! A signal detection framework for the strategic regulation of memory accuracy.

PubMed

Higham, Philip A

2007-02-01

Two experiments investigated criterion setting and metacognitive processes underlying the strategic regulation of accuracy on the Scholastic Aptitude Test (SAT) using Type-2 signal detection theory (SDT). In Experiment 1, report bias was manipulated by penalizing participants either 0.25 (low incentive) or 4 (high incentive) points for each error. Best guesses to unanswered items were obtained so that Type-2 signal detection indices of discrimination and bias could be calculated. The same incentive manipulation was used in Experiment 2, only the test was computerized, confidence ratings were taken so that receiver operating characteristic (ROC) curves could be generated, and feedback was manipulated. The results of both experiments demonstrated that SDT provides a viable alternative to A. Koriat and M. Goldsmith's (1996c) framework of monitoring and control and reveals information about the regulation of accuracy that their framework does not. For example, ROC analysis indicated that the threshold model implied by formula scoring is inadequate. Instead, performance on the SAT should be modeled with an equal-variance Gaussian, Type-2 signal detection model. ((c) 2007 APA, all rights reserved).

Prediction of Fetal Growth Restriction by Analyzing the Messenger RNAs of Angiogenic Factor in the Plasma of Pregnant Women.

PubMed

Takenaka, Shin; Ventura, Walter; Sterrantino, Anna Freni; Kawashima, Akihiro; Koide, Keiko; Hori, Kyoko; Farina, Antonio; Sekizawa, Akihiko

2015-06-01

To predict the occurrence of fetal growth restriction (FGR) by analyzing messenger RNA (mRNA) expression levels of vascular endothelial growth factor receptor 1 (fms-like tyrosine kinase 1 [Flt-1]) in maternal blood. Eleven women with FGR were matched with 88 controls. Plasma samples were obtained during each trimester. The Flt-1 mRNA expression levels were compared between groups. Predicted probabilities were calculated, and sensitivity-specificity (receiver-operating characteristic [ROC]) curves were assessed based on regression models for each trimester measurement and possible combinations of measurements. The mRNA levels of the FGR group during all trimesters were significantly higher than those of the control group. The ROC curve of combined first and second trimester data yielded a detection rate of 60% at a 10% false-positive rate, with an area under curve of 0.79. The Flt-1 mRNA expression in maternal blood can be used as a marker to predict the development of FGR, long before a clinical diagnosis is made. © The Author(s) 2014.

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.

Electrodiagnosis of ulnar neuropathy at the elbow (Une): a Bayesian approach.

PubMed

Logigian, Eric L; Villanueva, Raissa; Twydell, Paul T; Myers, Bennett; Downs, Marlene; Preston, David C; Kothari, Milind J; Herrmann, David N

2014-03-01

In ulnar neuropathy at the elbow (UNE), we determined how electrodiagnostic cutoffs [across-elbow ulnar motor conduction velocity slowing (AECV-slowing), drop in across-elbow vs. forearm CV (AECV-drop)] depend on pretest probability (PreTP). Fifty clinically defined UNE patients and 50 controls underwent ulnar conduction testing recording abductor digiti minimi (ADM) and first dorsal interosseous (FDI), stimulating wrist, below-elbow, and 6-, 8-, and 10-cm more proximally. For various PreTPs of UNE, the cutoffs required to confirm UNE (defined as posttest probability = 95%) were determined with receiver operator characteristic (ROC) curves and Bayes Theorem. On ROC and Bayesian analyses, the ADM 10-cm montage was optimal. For PreTP = 0.25, the confirmatory cutoffs were >23 m/s (AECV-drop), and <38 m/s (AECV-slowing); for PreTP = 0.75, they were much less conservative: >14 m/s, and <47 m/s, respectively. (1) In UNE, electrodiagnostic cutoffs are critically dependent on PreTP; rigid cutoffs are problematic. (2) AE distances should be standardized and at least 10 cm. Copyright © 2013 Wiley Periodicals, Inc.

Specific and social fears in children and adolescents: separating normative fears from problem indicators and phobias.

PubMed

Laporte, Paola P; Pan, Pedro M; Hoffmann, Mauricio S; Wakschlag, Lauren S; Rohde, Luis A; Miguel, Euripedes C; Pine, Daniel S; Manfro, Gisele G; Salum, Giovanni A

2017-01-01

To distinguish normative fears from problematic fears and phobias. We investigated 2,512 children and adolescents from a large community school-based study, the High Risk Study for Psychiatric Disorders. Parent reports of 18 fears and psychiatric diagnosis were investigated. We used two analytical approaches: confirmatory factor analysis (CFA)/item response theory (IRT) and nonparametric receiver operating characteristic (ROC) curve. According to IRT and ROC analyses, social fears are more likely to indicate problems and phobias than specific fears. Most specific fears were normative when mild; all specific fears indicate problems when pervasive. In addition, the situational fear of toilets and people who look unusual were highly indicative of specific phobia. Among social fears, those not restricted to performance and fear of writing in front of others indicate problems when mild. All social fears indicate problems and are highly indicative of social phobia when pervasive. These preliminary findings provide guidance for clinicians and researchers to determine the boundaries that separate normative fears from problem indicators in children and adolescents, and indicate a differential severity threshold for specific and social fears.

Estimating time-dependent ROC curves using data under prevalent sampling.

PubMed

Li, Shanshan

2017-04-15

Prevalent sampling is frequently a convenient and economical sampling technique for the collection of time-to-event data and thus is commonly used in studies of the natural history of a disease. However, it is biased by design because it tends to recruit individuals with longer survival times. This paper considers estimation of time-dependent receiver operating characteristic curves when data are collected under prevalent sampling. To correct the sampling bias, we develop both nonparametric and semiparametric estimators using extended risk sets and the inverse probability weighting techniques. The proposed estimators are consistent and converge to Gaussian processes, while substantial bias may arise if standard estimators for right-censored data are used. To illustrate our method, we analyze data from an ovarian cancer study and estimate receiver operating characteristic curves that assess the accuracy of the composite markers in distinguishing subjects who died within 3-5 years from subjects who remained alive. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Application of receiver operating characteristic curve in the assessment of the value of body mass index, waist circumference and percentage of body fat in the Diagnosis of Polycystic Ovary Syndrome in childbearing women.

PubMed

Dou, Pan; Ju, Huiyan; Shang, Jing; Li, Xueying; Xue, Qing; Xu, Yang; Guo, Xiaohui

2016-08-24

There are various parameters to analyze obesity, however, no standard reference to predict, screen or diagnose PCOS with various obesity parameters has been established, and the accuracy of these parameters still needs to be studied.This study was to use the receiver operating characteristic (ROC) curve to explore the different values of three obesity parameters, body mass index (BMI), waist circumference (WC) and percentage of body fat (PBF) in the diagnosis of polycystic ovary syndrome (PCOS) in Chinese childbearing women. Three hundred patients who were diagnosed with PCOS at Center of Reproductive Medicine and Genetics of Peking University First Hospital were enrolled in this study, and 110 healthy age-matched women were enrolled as controls. The characteristics of BMI, WC and PBF in PCOS patients were analyzed. Compared with the control group, all the three obesity parameters were significantly increased in PCOS group. In terms of ROC area under the curve, WC > PBF > BMI, and they were all significantly different from those of the control. At a cut-off point of 80.5 cm, WC has a sensitivity of 73.6 % and a specificity of 85 % in diagnosis of PCOS; At a cut-off point of 29 %, PBF has a sensitivity of 88.2 % and a specificity of 57.7 % in diagnosis of PCOS; and at a cut-off point of 26.6 kg/m(2), BMI has a sensitivity of 54.5 % and a specificity of 98 % in diagnosis of PCOS. WC, BMI and PBF are valuable in screening and diagnosis of PCOS in Chinese childbearing women. PBF can be used to screen PCOS as it has a better sensitivity, while BMI can be used in the diagnosis of PCOS as it has a better specificity.

Global detection approach for clustered microcalcifications in mammograms using a deep learning network.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-04-01

In computerized detection of clustered microcalcifications (MCs) from mammograms, the traditional approach is to apply a pattern detector to locate the presence of individual MCs, which are subsequently grouped into clusters. Such an approach is often susceptible to the occurrence of false positives (FPs) caused by local image patterns that resemble MCs. We investigate the feasibility of a direct detection approach to determining whether an image region contains clustered MCs or not. Toward this goal, we develop a deep convolutional neural network (CNN) as the classifier model to which the input consists of a large image window ([Formula: see text] in size). The multiple layers in the CNN classifier are trained to automatically extract image features relevant to MCs at different spatial scales. In the experiments, we demonstrated this approach on a dataset consisting of both screen-film mammograms and full-field digital mammograms. We evaluated the detection performance both on classifying image regions of clustered MCs using a receiver operating characteristic (ROC) analysis and on detecting clustered MCs from full mammograms by a free-response receiver operating characteristic analysis. For comparison, we also considered a recently developed MC detector with FP suppression. In classifying image regions of clustered MCs, the CNN classifier achieved 0.971 in the area under the ROC curve, compared to 0.944 for the MC detector. In detecting clustered MCs from full mammograms, at 90% sensitivity, the CNN classifier obtained an FP rate of 0.69 clusters/image, compared to 1.17 clusters/image by the MC detector. These results indicate that using global image features can be more effective in discriminating clustered MCs from FPs caused by various sources, such as linear structures, thereby providing a more accurate detection of clustered MCs on mammograms.

Clinical value and indication for the dissection of lymph nodes posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma.

PubMed

Luo, Ding-Cun; Xu, Xiao-Cheng; Ding, Jin-Wang; Zhang, Yu; Peng, You; Pan, Gang; Zhang, Wo

2017-10-03

Lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) are common sites of nodal recurrence after the resection of papillary thyroid carcinoma (PTC). However, the indication for LN-prRLN dissection remains debatable. We therefore studied the relationships between LN-prRLN metastasis and the clinicopathological characteristics in 306 patients with right or bilateral PTC who underwent LN-prRLN dissection. We found that LN-prRLN metastasis occurred in 16.67% of PTC and was associated with a number of the clinicopathological features. The receiver-operator characteristic (ROC) analysis showed that the areas under the ROC curves for the prediction of LN-prRLN metastasis by the risk factors age < 35.5 years, right tumor size > 0.85 cm, lymph node (right cervical central VI-1) number > 1.5, metastatic lymph node (right cervical central VI-1) size > 0.45 cm, and lymph node number in the right cervical lateral compartment > 0.5 were 0.601, 0.815, 0.813, 0.725, and 0.743, respectively. In conclusion, the risk factors for LN-prRLN metastasis in patients suffering right thyroid lobe or bilateral PTC include age ≤ 35.5 years, right tumor size ≥ 0.85 cm, capsular invasion, metastatic lymph node (right cervical central VI-1) number ≥ 2, metastatic lymph node (right cervical central VI-1) size ≥ 0.45 cm, and metastatic lymph node number in the right cervical lateral compartment ≥ 1. In patients whose risk factors can be identified pre-operatively or intraoperatively, the dissection of LN-pr-RLN should be considered during right cervical central compartment dissection.

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.

Critical thresholds of liver function parameters for ketosis prediction in dairy cows using receiver operating characteristic (ROC) analysis.

PubMed

Sun, Yuhang; Wang, Bo; Shu, Shi; Zhang, Hongyou; Xu, Chuang; Wu, Ling; Xia, Cheng

2015-01-01

Fatty liver syndrome and ketosis are important metabolic disorders in high-producing cows during early lactation with fatty liver usually preceding ketosis. To date, parameters for early prediction of the risk of ketosis have not been investigated in China. To determine the predictive value of some parameters on the risk of ketosis in China. In a descriptive study, 48 control and 32 ketotic Holstein Friesian cows were randomly selected from one farm with a serum β-hydroxybutyrate (BHBA) concentration of 1.20 mmol/L as cutoff point. The risk prediction thresholds for ketosis were determined by receiver operating characteristic (ROC) analysis. In line with a high BHBA concentration, blood glucose concentration was significantly lower in ketotic cows compared to control animals (2.77 ± 0.24 versus 3.34 ± 0.03 mmol/L; P = 0.02). Thresholds were more than 0.76 mmol/L for nonesterified fatty acids (NEFA, with 65% sensitivity and 92% specificity), more than 104 U/L for aspartate aminotransferase (AST, 74% and 85%, respectively), less than 140 U/L for cholinesterase (CHE, 75% and 59%, respectively), and more than 3.3 µmol/L for total bilirubin (TBIL, 58% and 83%, respectively). There were significant correlations between BHBA and glucose (R = -4.74), or CHE (R = -0.262), BHBA and NEFA (R = 0.520), or AST (R = 0.525), or TBIL (R = 0.278), or direct bilirubin (DBIL, R = 0.348). AST, CHE, TBIL and NEFA may be useful parameters for risk prediction of ketosis. This study might be of value in addressing novel directions for future research on the connection between ketosis and liver dysfunction.

Receiver-operating characteristic curves for somatic cell scores and California mastitis test in Valle del Belice dairy sheep.

PubMed

Riggio, Valentina; Pesce, Lorenzo L; Morreale, Salvatore; Portolano, Baldassare

2013-06-01

Using receiver-operating characteristic (ROC) curve methodology this study was designed to assess the diagnostic effectiveness of somatic cell count (SCC) and the California mastitis test (CMT) in Valle del Belice sheep, and to propose and evaluate threshold values for those tests that would optimally discriminate between healthy and infected udders. Milk samples (n=1357) were collected from 684 sheep in four flocks. The prevalence of infection, as determined by positive bacterial culture was 0.36, 87.7% of which were minor and 12.3% major pathogens. Of the culture negative samples, 83.7% had an SCC<500,000/mL and 97.4% had <1,000,000cells/mL. When the associations between SC score (SCS) and whole sample status (culture negative vs. infected), minor pathogen status (culture negative vs. infected with minor pathogens), major pathogen status (culture negative vs. infected with major pathogens), and CMT results were evaluated, the estimated area under the ROC curve was greater for glands infected with major compared to minor pathogens (0.88 vs. 0.73), whereas the area under the curve considering all pathogens was similar to the one for minor pathogens (0.75). The estimated optimal thresholds were 3.00 (CMT), 2.81 (SCS for the whole sample), 2.81 (SCS for minor pathogens), and 3.33 (SCS for major pathogens). These correctly classified, respectively, 69.0%, 73.5%, 72.6% and 91.0% of infected udders in the samples. The CMT appeared only to discriminate udders infected with major pathogens. In this population, SCS appeared to be the best indirect test of the bacteriological status of the udder. Copyright © 2012 Elsevier Ltd. All rights reserved.

Regional Cerebral Blood Flow In Dementia: Receiver-Operating-Characteristic Analysis

NASA Astrophysics Data System (ADS)

Zemcov, Alexander; Barclay, Laurie; Sansone, Joseph; Blass, John P.; Metz, Charles E.

1985-06-01

The coupling of mentation to regional cerebral blood flow (rCBF) has prompted the application of the Xe-133 inhalation method of measuring rCBF in the differential diagnosis of the two most common dementing diseases, Alzheimer's disease and multi-infarct dementia (MID). In this study receiver-operating-characteristic (ROC) curve analysis was used to assess the effectiveness of a 32 detector Xe-133 inhalation system in discriminating between patients with Alzheimer's disease and normal controls, MID patients and normal controls and between patients with Alzheimer's disease and MID. The populations were clinically evaluated as 1) normal (age 63.1 + 13.1, n=23), 2) Alzheimer's disease (age 72.7 + 7.0, n=82), 3) MID (age 76.4 + 7.6, n=27): The mean flow values for all detectors were lowest for the Alzheimer's disease group, larger for the MID group and largest for the normal controls. The dynamic relationship between the correct identifications (true posi-tives) versus incorrect identifications (false positives) per detector for any 2 pairs of clinical groups varies as the cutoff value of flow is changed over the range of experimental blood flow values. Therefore a quantitative characterization of the "decision" or ROC curve (TP vs FP) for each detector and for each pair of clinical groups provides a measure of the overall diagnostic efficacy of the detector. Detectors directed approximately toward the speech, auditory and association cortices were most effective in disciminatinq between each of the dementia groups and the controls. Frontal detectors were diagnostically inefficient. The Xe-133 inhalation system provided virtually no diagnostic power in discriminating between the two forms of dementia, however. Therefore this imaging technology is most useful when assessing the general diagnostic state of dementia (Alz-heimer's disease and MID) from normal cognitive function.

Relation of Monocyte/High-Density Lipoprotein Cholesterol Ratio with Coronary Artery Disease in Type 2 Diabetes Mellitus.

PubMed

Ya, Gao; Qiu, Zhang; Tianrong, Pan

2018-06-01

Atherosclerotic cardiovascular disease is the leading cause of mortality of patients with type 2 diabetes mellitus, and both coronary artery disease (CAD) and diabetes mellitus are associated with inflammation. Emerging evidence suggests a relationship of the monocyte to high-density lipoprotein cholesterol ratio (MHR) with the incidence and severity of CAD. The aim of the present study was to examine the association of MHR with CAD in patients with type 2 diabetes mellitus. A total of 458 consecutive individuals were enrolled, comprising 178 type 2 diabetic patients, 124 type 2 diabetes with CAD, and 156 healthy volunteers as the controls. A multivariable logistic regression model was used to evaluate the relationship between the MHR and CAD in type 2 diabetes, and the receiver operating characteristic (ROC) curve of MHR was used for predicting the presence of CAD in type 2 diabetic patients. Values of MHR were significantly higher in type 2 diabetic patients with CAD compared with those without CAD and the control group. Moreover, multivariate logistic regression analysis showed that MHR was an independent predictor of the presence of CAD in type 2 diabetic patients (OR = 1.361, 95% CI 1.245 - 1.487, p < 0.0001). Based on the receiver operating characteristic (ROC) curve, the cutoff value of MHR (> 8.2) in predicting the presence of CAD in type 2 diabetic patients yields a sensitivity and specificity of 83.74% and 62.15%, respectively, with an area under the curve of 0.795 (95% CI: 0.745 - 0.840). The MHR is strongly associated with CAD in type 2 diabetes and might be a potential biomarker to predict the presence of CAD in type 2 diabetic patients.

Decreased expression of hsa_circ_0137287 predicts aggressive clinicopathologic characteristics in papillary thyroid carcinoma.

PubMed

Lan, Xiabin; Cao, Jun; Xu, Jiajie; Chen, Chao; Zheng, Chuanming; Wang, Jiafeng; Zhu, Xuhang; Zhu, Xin; Ge, Minghua

2018-05-22

Circular RNA (circRNA) is a new type of noncoding RNA that can serve as ideal biomarkers. Evidence has showed that circRNAs play an important role in carcinogenesis and cancer development. However, little is known about the diagnostic value of circRNAs in papillary thyroid carcinoma (PTC) as well as their associations with clinicopathologic characteristics of patients with PTC. The expression levels of hsa_circ_0137287 were detected in 120 PTC and 60 adjacent noncancerous thyroid tissues by quantitative real-time polymerase chain reaction. The relationships between the expression of hsa_circ_0137287 in PTC and the clinicopathologic factors were analyzed. Finally, receiver operating characteristic (ROC) curves were generated to assess the diagnostic value of hsa_circ_0137287 as a biomarker for PTC. The expression of hsa_circ_0137287 was significantly downregulated in PTC tissues compared with adjacent noncancerous tissues (P < .0001). Downregulation of hsa_circ_0137287 correlated with aggressive clinicopathologic characteristics of PTC such as extrathyroidal extension (P < .001), lymph node metastasis (P = .022), advanced T stage (P < .001) and larger tumor size (P < .001). The ROC curves revealed that hsa_circ_0137287 had a potential diagnostic value in predicting malignancy, extrathyroidal extension and lymph node metastasis. The area under curves were 0.8973 (95% CI = 0.8452-0.9494, P < .0001), 0.6885 (95%CI = 0.5908-0.7862, P = .0009), and 0.6691(95%CI = 0.5641-0.7742, P = .0034), respectively. Our findings suggest that hsa_circ_0137287 may serve as a novel biomarker for PTC. © 2018 Wiley Periodicals, Inc.

Maladaptive interpersonal schemas as sensitive and specific markers of borderline personality disorder among psychiatric inpatients.

PubMed

Cohen, Lisa J; Tanis, Thachell; Ardalan, Firouz; Yaseen, Zimri; Galynker, Igor

2016-08-30

Diagnostic criteria for borderline personality disorder (BPD) and mood and psychotic disorders characterized by major mood episodes (i.e., major depressive, bipolar and schizoaffective disorder) share marked overlap in symptom presentation, complicating differential diagnosis. The current study tests the hypothesis that maladaptive interpersonal schemas (MIS) are characteristic of BPD, but not of the major mood disorders. One hundred psychiatric inpatients were assessed by SCID I, SCID II and the Young Schema Questionnaire (YSQ-S2). Logistic regression analyses tested the association between MIS (measured by the YSQ-S2) and BPD, bipolar, major depressive and schizoaffective disorder. Receiver operator characteristic (ROC) curve analyses assessed the sensitivity and specificity of MIS as a marker of BPD. After covariation for comorbidity with each of the 3 mood disorders, BPD was robustly associated with 4 out of 5 schema domains. In contrast, only one of fifteen regression analyses demonstrated a significant association between any mood disorder and schema domain after covariation for comorbid BPD. ROC analyses of the 5 schema domains suggested Disconnection/Rejection had the greatest power for identification of BPD cases. These data support the specific role of maladaptive interpersonal schemas in BPD and potentially contribute to greater conceptual clarity about the distinction between BPD and the major mood disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Prognostic factors of Bell's palsy: prospective patient collected observational study.

PubMed

Fujiwara, Takashi; Hato, Naohito; Gyo, Kiyofumi; Yanagihara, Naoaki

2014-07-01

The purpose of this study was to evaluate various parameters potentially influencing poor prognosis in Bell's palsy and to assess the predictive value for Bell's palsy. A single-center prospective patient collected observation and validation study was conducted. To evaluate the correlation between patient characteristics and poor prognosis, we performed univariate and multivariate analyzes of age, gender, side of palsy, diabetes mellitus, hypertension, and facial grading score 1 week after onset. To evaluate the accuracy of the facial grading score, we prepared a receiver operating characteristic (ROC) curve and calculated the area under the ROC curve (AUROC). We also calculated sensitivity, specificity, positive/negative likelihood ratio, and positive/negative predictive value. We included Bell's palsy patients who attended Ehime University Hospital within 1 week after onset between 1977 and 2011. We excluded patients who were less than 15 years old and lost-to-follow-up within 6 months. The main outcome was defined as non-recovery at 6 months after onset. In total, 679 adults with Bell's palsy were included. The facial grading score at 1 week showed a correlation with non-recovery in the multivariate analysis, although age, gender, side of palsy, diabetes mellitus, and hypertension did not. The AUROC of the facial grading score was 0.793. The Y-system score at 1 week moderate accurately predicted non-recovery at 6 months in Bell's palsy.

A Colombian diabetes risk score for detecting undiagnosed diabetes and impaired glucose regulation.

PubMed

Barengo, Noël Christopher; Tamayo, Diana Carolina; Tono, Teresa; Tuomilehto, Jaakko

2017-02-01

(i) To develop a diabetes mellitus risk score model for the Colombian population (ColDRISC); and (ii) to evaluate the accuracy of the ColDRISC unknown Type 2 diabetes mellitus METHODS: Cross-sectional screening study of the 18-74 years-old population of a health-care insurance company (n=2060) in northern Colombia. Lifestyle habits and risk factors for diabetes mellitus were assessed by an interview using a questionnaire consisting of information regarding sociodemographic factors, history of diabetes mellitus, tobacco consumption, hypertension, nutritional and physical activity habits. Anthropometric measurements and an oral glucose tolerance test were taken. The sensitivity and the specificity, receiver-operating characteristic (ROC) curves, were calculated for the ColDRISC and FINDRISC. The area under the ROC curve for unknown Type 2 diabetes mellitus was 0.74 (95% CI: 0.70-0.79) for the ColDRISC and 0.73 for the FINDRISC (95% confidence intervals [CI] 0.69-0.78). Using the risk score cutoff value of 4 in the ColDRISC to detect Type 2 diabetes mellitus resulted in a sensitivity of 73% and specificity of 67%. The characteristics of the ColDRISC show that it can be used as a simple, safe, and inexpensive test to identify people at high risk for Type 2 diabetes mellitus in Colombia. Copyright © 2016 Primary Care Diabetes Europe. Published by Elsevier Ltd. 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.

Performance characteristics of the PTSD Checklist in retired firefighters exposed to the World Trade Center disaster.

PubMed

Chiu, Sydney; Webber, Mayris P; Zeig-Owens, Rachel; Gustave, Jackson; Lee, Roy; Kelly, Kerry J; Rizzotto, Linda; McWilliams, Rita; Schorr, John K; North, Carol S; Prezant, David J

2011-05-01

Since the World Trade Center (WTC) attacks on September 11, 2001, the Fire Department, City of New York Monitoring Program has provided physical and mental health screening services to rescue/recovery workers. This study evaluated performance of the self-report PTSD Checklist (PCL) as a screening tool for risk of posttraumatic stress disorder (PTSD) in firefighters who worked at Ground Zero, compared with the interviewer-administered Diagnostic Interview Schedule (DIS). From December 2005 to July 2007, all retired firefighter enrollees completed the PCL and DIS on the same day. Sensitivity, specificity, receiver operating characteristic (ROC) curves, and Youden index (J) were used to assess properties of the PCL and to identify an optimum cutoff score. Six percent of 1,915 retired male firefighters were diagnosed with PTSD using the DIS to assess DSM-IV criteria. Depending on the PCL cutoff, the prevalence of elevated risk relative to DSM-IV criteria varied from 16% to 22%. Youden index identified an optimal cutoff score of 39, in contrast with the frequently recommended cutoff of 44. At 39, PCL sensitivity was 0.85, specificity was 0.82, and the area under the ROC curve was 0.91 relative to DIS PTSD diagnosis. This is the first study to validate the PCL in retired firefighters and determine the optimal cutoff score to maximize opportunities for PTSD diagnosis and treatment.

A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging

NASA Astrophysics Data System (ADS)

Solomon, Justin; Samei, Ehsan

2014-11-01

Realistic three-dimensional (3D) mathematical models of subtle lesions are essential for many computed tomography (CT) studies focused on performance evaluation and optimization. In this paper, we develop a generic mathematical framework that describes the 3D size, shape, contrast, and contrast-profile characteristics of a lesion, as well as a method to create lesion models based on CT data of real lesions. Further, we implemented a technique to insert the lesion models into CT images in order to create hybrid CT datasets. This framework was used to create a library of realistic lesion models and corresponding hybrid CT images. The goodness of fit of the models was assessed using the coefficient of determination (R2) and the visual appearance of the hybrid images was assessed with an observer study using images of both real and simulated lesions and receiver operator characteristic (ROC) analysis. The average R2 of the lesion models was 0.80, implying that the models provide a good fit to real lesion data. The area under the ROC curve was 0.55, implying that the observers could not readily distinguish between real and simulated lesions. Therefore, we conclude that the lesion-modeling framework presented in this paper can be used to create realistic lesion models and hybrid CT images. These models could be instrumental in performance evaluation and optimization of novel CT systems.

Predicting serious bacterial infection in young children with fever without apparent source.

PubMed

Bleeker, S E; Moons, K G; Derksen-Lubsen, G; Grobbee, D E; Moll, H A

2001-11-01

The aim of this study was to design a clinical rule to predict the presence of a serious bacterial infection in children with fever without apparent source. Information was collected from the records of children aged 1-36 mo who attended the paediatric emergency department because of fever without source (temperature > or = 38 degrees C and no apparent source found after evaluation by a general practitioner or history by a paediatrician). Serious bacterial infection included bacterial meningitis, sepsis, bacteraemia, pneumonia, urinary tract infection, bacterial gastroenteritis, osteomyelitis and ethmoiditis. Using multivariate logistic regression and the area under the receiver operating characteristic curve (ROC area), the diagnostic value of predictors for serious bacterial infection was judged, resulting in a risk stratification. Twenty-five percent of the 231 patients enrolled in the study (mean age 1.1 y) had a serious bacterial infection. Independent predictors from history and examination included duration of fever, poor micturition, vomiting, age, temperature < 36.7 degrees C or > or = 40 degrees C at examination, chest-wall retractions and poor peripheral circulation (ROC area: 0.75). Independent predictors from laboratory tests were white blood cell count, serum C-reactive protein and the presence of >70 white blood cells in urinalysis (ROC area: 0.83). The risk stratification for serious bacterial infection ranged from 6% to 92%. The probability of a serious bacterial infection in the individual patient with fever without source can be estimated more precisely by using a limited number of symptoms, signs and laboratory tests.

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.

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.

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.

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

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.

Usefulness of the UCSD Performance-based Skills Assessment (UPSA) for Predicting Residential Independence in Patients with Chronic Schizophrenia

PubMed Central

Mausbach, Brent T.; Bowie, Christopher R.; Harvey, Philip D.; Twamley, Elizabeth W.; Goldman, Sherrill R.; Jeste, Dilip V.; Patterson, Thomas L.

2009-01-01

The objective of this study was to examine the sensitivity and specificity of a performance-based measure of functional capacity, the UCSD Performance-Based Skills Assessment (UPSA) for the prediction of independent living status in patients with chronic schizophrenia-related conditions. A sample of 434 adults with schizophrenia or schizoaffective disorder was administered the UPSA and assessed for independent living status. Participants were classified as “independent” if they were living alone in an apartment, house, or single-resident occupancy (e.g., hotel room) and non-independent if they resided in a care facility (e.g., Board-and-Care home, Skilled Nursing Facility). Receiver Operator Characteristic (ROC) curves were calculated with the UPSA and Mattis’ Dementia Rating Scale (DRS) scores as predictor variables and residential independence as the state variable. Of the 434 participants, 99 (23%) were living independently at the time of assessment. The discriminant validity of the UPSA was adequate (ROC area under the curve = 0.74; 95% CI: 0.68–0.79), with greatest dichotomization for the UPSA at a cutoff score of 75 (68% accuracy, 69% sensitivity, 66% specificity), or 80 (68% accuracy, 59% sensitivity, 76% specificity). The UPSA was also a significantly better predictor of living status than was the DRS, based on ROC (z = 2.43, p = .015). The UPSA is a brief measure of functional capacity that predicts the ability of patients with schizophrenia to reside independently in the community. PMID:17303168

DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment.

PubMed

Scholz, Christoph; Knorr, Sabine; Hamacher, Kay; Schmidt, Boris

2015-02-23

The formation of a covalent bond with the target is essential for a number of successful drugs, yet tools for covalent docking without significant restrictions regarding warhead or receptor classes are rare and limited in use. In this work we present DOCKTITE, a highly versatile workflow for covalent docking in the Molecular Operating Environment (MOE) combining automated warhead screening, nucleophilic side chain attachment, pharmacophore-based docking, and a novel consensus scoring approach. The comprehensive validation study includes pose predictions of 35 protein/ligand complexes which resulted in a mean RMSD of 1.74 Å and a prediction rate of 71.4% with an RMSD below 2 Å, a virtual screening with an area under the curve (AUC) for the receiver operating characteristics (ROC) of 0.81, and a significant correlation between predicted and experimental binding affinities (ρ = 0.806, R(2) = 0.649, p < 0.005).

Accuracy of Seattle Heart Failure Model and HeartMate II Risk Score in Non-Inotrope-Dependent Advanced Heart Failure Patients: Insights From the ROADMAP Study (Risk Assessment and Comparative Effectiveness of Left Ventricular Assist Device and Medical Management in Ambulatory Heart Failure Patients).

PubMed

Lanfear, David E; Levy, Wayne C; Stehlik, Josef; Estep, Jerry D; Rogers, Joseph G; Shah, Keyur B; Boyle, Andrew J; Chuang, Joyce; Farrar, David J; Starling, Randall C

2017-05-01

Timing of left ventricular assist device (LVAD) implantation in advanced heart failure patients not on inotropes is unclear. Relevant prediction models exist (SHFM [Seattle Heart Failure Model] and HMRS [HeartMate II Risk Score]), but use in this group is not established. ROADMAP (Risk Assessment and Comparative Effectiveness of Left Ventricular Assist Device and Medical Management in Ambulatory Heart Failure Patients) is a prospective, multicenter, nonrandomized study of 200 advanced heart failure patients not on inotropes who met indications for LVAD implantation, comparing the effectiveness of HeartMate II support versus optimal medical management. We compared SHFM-predicted versus observed survival (overall survival and LVAD-free survival) in the optimal medical management arm (n=103) and HMRS-predicted versus observed survival in all LVAD patients (n=111) using Cox modeling, receiver-operator characteristic (ROC) curves, and calibration plots. In the optimal medical management cohort, the SHFM was a significant predictor of survival (hazard ratio=2.98; P <0.001; ROC area under the curve=0.71; P <0.001) but not LVAD-free survival (hazard ratio=1.41; P =0.097; ROC area under the curve=0.56; P =0.314). SHFM showed adequate calibration for survival but overestimated LVAD-free survival. In the LVAD cohort, the HMRS had marginal discrimination at 3 (Cox P =0.23; ROC area under the curve=0.71; P =0.026) and 12 months (Cox P =0.036; ROC area under the curve=0.62; P =0.122), but calibration was poor, underestimating survival across time and risk subgroups. In non-inotrope-dependent advanced heart failure patients receiving optimal medical management, the SHFM was predictive of overall survival but underestimated the risk of clinical worsening and LVAD implantation. Among LVAD patients, the HMRS had marginal discrimination and underestimated survival post-LVAD implantation. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01452802. © 2017 American Heart Association, Inc.

D-dimer, factor VIII and von Willebrand factor predict a non-dipping pattern of blood pressure in hypertensive patients.

PubMed

Agorasti, Athanasia; Trivellas, Theodoros; Mourvati, Efthimia; Papadopoulos, Vasilios; Tsatalas, Konstantinos; Vargemezis, Vasilios; Passadakis, Ploumis

2013-06-01

The aim of this study is to assess whether the haemostatic markers D-dimer, factor VIII (FVIII) and von Willebrand factor (VWF) are predictive of non-dipping status in treated hypertensive patients; so, as easy available laboratory data can predict non-dipping pattern and help with the selection of the patients whom circadian blood pressure should be re-examined. Forty treated hypertensive patients with essential hypertension were included in the study. Twenty-four-hour ambulatory blood pressure monitoring was performed in all patients. Daytime and nocturnal average systolic, diastolic and mean blood pressures were calculated. Patients were characterised as "non-dippers" on the basis of a less than 10 % decline in nocturnal blood pressure (BP); either systolic or diastolic or mean (MAP). D-dimer as marker of fibrinolytic function, FVIII activity and VWF antigen as marker of endothelial dysfunction were measured on plasma. The predictive efficiency was analysed by receiver operating characteristic (ROC) curves. Youden index was used for the estimation of the cut-off points and the associated values for sensitivity and 1-specificity. Plasma levels of D-dimer, FVIII and VWF were significantly higher in non-dippers as compared with dippers, irrespective of the classification used (BP index); all P < 0.05. The ROC curves indicated a good diagnostic efficiency for D-dimer (AUC(ROC) = 0.697, 0.715 and 0.774), FVIII (AUC(ROC) = 0.714, 0.692 and 0.755) and VWF (AUC(ROC) = 0.706, 0.740 and 0.708) in distinguishing non-dipping pattern (systolic, diastolic or mean) in the study population; all P < 0.05. Among the three haemostatic markers, D-dimer presents the most satisfactory sensitivity/1-specificity for the differentiation of non-dippers, with a cut-off point >168 ng/ml (sensitivity/1-specificity for systolic BP non-dippers of 0.789/0.381, for diastolic BP non-dippers 0.923/0.444 and for MAP non-dippers 0.875/0.375). In conclusion, D-dimer has a good predictive value for non-dipping pattern and the decision for the 24-h ambulatory blood pressure re-monitoring among dippers could rely on its values.

Interrelationships Between Receiver/Relative Operating Characteristics Display, Binomial, Logit, and Bayes' Rule Probability of Detection Methodologies

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2014-01-01

Unknown risks are introduced into failure critical systems when probability of detection (POD) capabilities are accepted without a complete understanding of the statistical method applied and the interpretation of the statistical results. The presence of this risk in the nondestructive evaluation (NDE) community is revealed in common statements about POD. These statements are often interpreted in a variety of ways and therefore, the very existence of the statements identifies the need for a more comprehensive understanding of POD methodologies. Statistical methodologies have data requirements to be met, procedures to be followed, and requirements for validation or demonstration of adequacy of the POD estimates. Risks are further enhanced due to the wide range of statistical methodologies used for determining the POD capability. Receiver/Relative Operating Characteristics (ROC) Display, simple binomial, logistic regression, and Bayes' rule POD methodologies are widely used in determining POD capability. This work focuses on Hit-Miss data to reveal the framework of the interrelationships between Receiver/Relative Operating Characteristics Display, simple binomial, logistic regression, and Bayes' Rule methodologies as they are applied to POD. Knowledge of these interrelationships leads to an intuitive and global understanding of the statistical data, procedural and validation requirements for establishing credible POD estimates.

Teaching a Machine to Feel Postoperative Pain: Combining High-Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain

PubMed Central

Tighe, Patrick J.; Harle, Christopher A.; Hurley, Robert W.; Aytug, Haldun; Boezaart, Andre P.; Fillingim, Roger B.

2015-01-01

Background Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain. Methods Here, we report on the application of machine learning algorithms to predict postoperative pain outcomes in a retrospective cohort of 8071 surgical patients using 796 clinical variables. Five algorithms were compared in terms of their ability to forecast moderate to severe postoperative pain: Least Absolute Shrinkage and Selection Operator (LASSO), gradient-boosted decision tree, support vector machine, neural network, and k-nearest neighbor, with logistic regression included for baseline comparison. Results In forecasting moderate to severe postoperative pain for postoperative day (POD) 1, the LASSO algorithm, using all 796 variables, had the highest accuracy with an area under the receiver-operating curve (ROC) of 0.704. Next, the gradient-boosted decision tree had an ROC of 0.665 and the k-nearest neighbor algorithm had an ROC of 0.643. For POD 3, the LASSO algorithm, using all variables, again had the highest accuracy, with an ROC of 0.727. Logistic regression had a lower ROC of 0.5 for predicting pain outcomes on POD 1 and 3. Conclusions Machine learning algorithms, when combined with complex and heterogeneous data from electronic medical record systems, can forecast acute postoperative pain outcomes with accuracies similar to methods that rely only on variables specifically collected for pain outcome prediction. PMID:26031220

High level of distress in long-term survivors of thyroid carcinoma: results of rapid screening using the distress thermometer.

PubMed

Roerink, Sean H P P; de Ridder, Mischa; Prins, Judith; Huijbers, Angelique; de Wilt, Hans J H; Marres, Henri; Repping-Wuts, Han; Stikkelbroeck, Nike M M L; Timmers, Henri J; Hermus, Ad R M M; Netea-Maier, Romana T

2013-01-01

Cancer patients are at increased risk for distress. The Distress Thermometer (DT) and problem list (PL) are short-tools validated and recommended for distress screening in cancer patients. To investigate the level of distress and problems experienced by survivors of differentiated non-medullary thyroid carcinoma (DTC), using the DT and PL and whether this correlates with clinical and demographical variables. All 205 DTC patients, under follow-up at the outpatient clinic of our university hospital, were asked to fill in the DT and PL, hospital anxiety and depression scale (HADS), illness cognition questionnaire (ICQ) and an ad hoc questionnaire. Receiver Operator Characteristic analysis (ROC) was used to establish the optimal DT cut-off score according to HADS. Correlations of questionnaires scores with data on diagnosis, treatment and follow-up collected from medical records were analyzed. Of the 159 respondents, 145 agreed to participate [118 in remission, median follow-up 7.2 years (range 3 months-41 years)]. Of these, 34.3% rated their distress score ≥5, indicating clinically relevant distress according to ROC analysis. Patients reported physical (86%) over emotional problems (76%) as sources of distress. DT scores correlated with HADS scores and ICQ subscales. No significant correlations were found between DT scores and clinical or demographical characteristics except for employment status. Prevalence of distress is high among patients with DTC even after long-term remission and cannot be predicted by clinical and demographical characteristics. DT and PL are useful screening instruments for distress in DTC patients and could easily be incorporated into daily practice.

Value of combining serum carcinoembryonic antigen and PET/CT in predicting EGFR mutation in non-small cell lung cancer.

PubMed

Gu, Jincui; Xu, Siqi; Huang, Lixia; Li, Shaoli; Wu, Jian; Xu, Junwen; Feng, Jinlun; Liu, Baomo; Zhou, Yanbin

2018-02-01

We sought to investigate the associations between pretreatment serum Carcinoembryonic antigen (CEA) level, 18 F-Fluoro-2-deoxyglucose ( 18 F-FDG) uptake value of primary tumor and epidermal growth factor receptor ( EGFR ) mutation status in non-small cell lung cancer (NSCLC). We retrospectively reviewed medical records of 210 NSCLC patients who underwent EGFR mutation test and 18 F-FDG positron emission tomography/computed tomography (PET/CT) scan before anti-tumor therapy. The associations between EGFR mutations and patients' characteristics, serum CEA, PET/CT imaging characteristics maximal standard uptake value (SUVmax) of the primary tumor were analyzed. Receiver-operating characteristic (ROC) curve was used to assess the predictive value of these factors. EGFR mutations were found in 70 patients (33.3%). EGFR mutations were more common in high CEA group (CEA ≥7.0 ng/mL) than in low CEA group (CEA <7.0 ng/mL) (40.4% vs . 27.6%; P=0.05). Females (P<0.001), non-smokers (P<0.001), patients with adenocarcinoma (P<0.001) and SUVmax <9.0 (P=0.001) were more likely to be EGFR mutation-positive. Multivariate analysis revealed that gender, tumor histology, pretreatment serum CEA level, and SUVmax were the most significant predictors for EGFR mutations. The ROC curve revealed that combining these four factors yielded a higher calculated AUC (0.80). Gender, histology, pretreatment serum CEA level and SUVmax are significant predictors for EGFR mutations in NSCLC. Combining these factors in predicting EGFR mutations has a moderate diagnostic accuracy, and is helpful in guiding anti-tumor treatment.

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models.

PubMed

Lindor, Noralane M; Lindor, Rachel A; Apicella, Carmel; Dowty, James G; Ashley, Amanda; Hunt, Katherine; Mincey, Betty A; Wilson, Marcia; Smith, M Cathie; Hopper, John L

2007-01-01

Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear. To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women; BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by Myriad Genetics Laboratories. Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory. For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of accuracy and dispersion. Cases "missed" by one or more models (model predicted less than 10% probability of mutation when a mutation was actually found) were compared across models. All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted the numbers of carriers. All models were too dispersed. In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided.

RocKeTeria restaurant

NASA Technical Reports Server (NTRS)

2000-01-01

When StenniSphere at John C. Stennis Space Center in Hancock County, Miss., opened in May 2000, it introduced the RocKeTeria, a new 1960s-style, space-themed restaurant located in the newly expanded visitor center. The restaurant, operated by the owners of Mary's Drive Inn of Biloxi, features an extensive collection of space-related photos from that era, as well as a full menu of home-style cooking.

Implications of dynamic changes in miR-192 expression in ischemic acute kidney injury.

PubMed

Zhang, Lulu; Xu, Yuan; Xue, Song; Wang, Xudong; Dai, Huili; Qian, Jiaqi; Ni, Zhaohui; Yan, Yucheng

2017-03-01

Ischemia-reperfusion injury (IRI) is a major cause of acute kidney injury (AKI) with poor outcomes. While many important functions of microRNAs (miRNAs) have been identified in various diseases, few studies reported miRNAs in acute kidney IRI, especially the dynamic changes in their expression and their implications during disease progression. The expression of miR-192, a specific kidney-enriched miRNA, was assessed in both the plasma and kidney of IRI rats at different time points after kidney injury and compared to renal function and kidney histological changes. The results were validated in the plasma of the selected patients with AKI after cardiac surgery compared with those matched patients without AKI. The performance characteristics of miR-192 were summarized using area under the receiver operator characteristic (ROC) curves (AUC-ROC). MiRNA profiling in plasma led to the identification of 42 differentially expressed miRNAs in the IRI group compared to the sham group. MiR-192 was kidney-enriched and chosen for further validation. Real-time PCR showed that miR-192 levels increased by fourfold in the plasma and decreased by about 40% in the kidney of IRI rats. Plasma miR-192 expression started increasing at 3 h and peaked at 12 h, while kidney miR-192 expression started decreasing at 6 h and remained at a low level for 7 days after reperfusion. Plasma miR-192 level in patients with AKI increased at the time of ICU admission, was stable for 2 h and decreased after 24 h. AUC-ROC was 0.673 (95% CI: 0.540-0.806, p = 0.014). Plasma miR-192 expression was induced in a time-dependent manner after IRI in rats and patients with AKI after cardiac surgery, comparably to the kidney injury development and recovery process, and may be useful for the detection of AKI.

Transmural ultrasound imaging of thermal lesion and action potential changes in perfused canine cardiac wedge preparations by high intensity focused ultrasound ablation.

PubMed

Wu, Ziqi; Gudur, Madhu S R; Deng, Cheri X

2013-01-01

Intra-procedural imaging is important for guiding cardiac arrhythmia ablation. It is difficult to obtain intra-procedural correlation of thermal lesion formation with action potential (AP) changes in the transmural plane during ablation. This study tested parametric ultrasound imaging for transmural imaging of lesion and AP changes in high intensity focused ultrasound (HIFU) ablation using coronary perfused canine ventricular wedge preparations (n = 13). The preparations were paced from epi/endocardial surfaces and subjected to HIFU application (3.5 MHz, 11 Hz pulse-repetition-frequency, 70% duty cycle, duration 4 s, 3500 W/cm(2)), during which simultaneous optical mapping (1 kframes/s) using di-4-ANEPPS and ultrasound imaging (30 MHz) of the same transmural surface of the wedge were performed. Spatiotemporally correlated AP measurements and ultrasound imaging allowed quantification of the reduction of AP amplitude (APA), shortening of AP duration at 50% repolarization, AP triangulation, decrease of optical AP rise, and change of conduction velocity along tissue depth direction within and surrounding HIFU lesions. The threshold of irreversible change in APA correlating to lesions was determined to be 43 ± 1% with a receiver operating characteristic (ROC) area under curve (AUC) of 0.96 ± 0.01 (n = 13). Ultrasound imaging parameters such as integrated backscatter, Rayleigh (α) and log-normal (σ) parameters, cumulative extrema of σ were tested, with the cumulative extrema of σ performing the best in detecting lesion (ROC AUC 0.89 ± 0.01, n = 13) and change of APA (ROC AUC 0.79 ± 0.03, n = 13). In conclusion, characteristic tissue and AP changes in HIFU ablation were identified and spatiotemporally correlated using optical mapping and ultrasound imaging. Parametric ultrasound imaging using cumulative extrema of σ can detect HIFU lesion and APA reduction.

Transmural Ultrasound Imaging of Thermal Lesion and Action Potential Changes in Perfused Canine Cardiac Wedge Preparations by High Intensity Focused Ultrasound Ablation

PubMed Central

Wu, Ziqi; Gudur, Madhu S. R.; Deng, Cheri X.

2013-01-01

Intra-procedural imaging is important for guiding cardiac arrhythmia ablation. It is difficult to obtain intra-procedural correlation of thermal lesion formation with action potential (AP) changes in the transmural plane during ablation. This study tested parametric ultrasound imaging for transmural imaging of lesion and AP changes in high intensity focused ultrasound (HIFU) ablation using coronary perfused canine ventricular wedge preparations (n = 13). The preparations were paced from epi/endocardial surfaces and subjected to HIFU application (3.5 MHz, 11 Hz pulse-repetition-frequency, 70% duty cycle, duration 4 s, 3500 W/cm2), during which simultaneous optical mapping (1 kframes/s) using di-4-ANEPPS and ultrasound imaging (30 MHz) of the same transmural surface of the wedge were performed. Spatiotemporally correlated AP measurements and ultrasound imaging allowed quantification of the reduction of AP amplitude (APA), shortening of AP duration at 50% repolarization, AP triangulation, decrease of optical AP rise, and change of conduction velocity along tissue depth direction within and surrounding HIFU lesions. The threshold of irreversible change in APA correlating to lesions was determined to be 43±1% with a receiver operating characteristic (ROC) area under curve (AUC) of 0.96±0.01 (n = 13). Ultrasound imaging parameters such as integrated backscatter, Rayleigh (α) and log-normal (σ) parameters, cumulative extrema of σ were tested, with the cumulative extrema of σ performing the best in detecting lesion (ROC AUC 0.89±0.01, n = 13) and change of APA (ROC AUC 0.79±0.03, n = 13). In conclusion, characteristic tissue and AP changes in HIFU ablation were identified and spatiotemporally correlated using optical mapping and ultrasound imaging. Parametric ultrasound imaging using cumulative extrema of σ can detect HIFU lesion and APA reduction. PMID:24349337

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.

Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge.

PubMed

Reynolds, Alexandra S; Guo, Xiaotao; Matthews, Elizabeth; Brodie, Daniel; Rabbani, Leroy E; Roh, David J; Park, Soojin; Claassen, Jan; Elkind, Mitchell S V; Zhao, Binsheng; Agarwal, Sachin

2017-08-01

Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam. We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome. Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10 -6 m 2 /s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10 -6 mm 2 /s and ≤650×10 -6 mm 2 /s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10 -6 m 2 /s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10 -6 mm 2 /s had an AUC of 0.737 (0.574-0.899, p=0.04). Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge. Copyright © 2017 Elsevier B.V. All rights reserved.

Cerebrospinal fluid ferritin and albumin index: potential candidates for scoring system to differentiate between bacterial and viral meningitis in children.

PubMed

Jebamalar, Angelin A; Prabhat; Balakrishnapillai, Agiesh K; Parmeswaran, Narayanan; Dhiman, Pooja; Rajendiran, Soundravally

2016-07-01

To evaluate the diagnostic role of cerebrospinal fluid (CSF) ferritin and albumin index (AI = CSF albumin/serum albumin × 1000) in differentiating acute bacterial meningitis (ABM) from acute viral meningitis (AVM) in children. The study included 42 cases each of ABM and AVM in pediatric age group. Receiver operating characteristic (ROC) analysis was carried out for CSF ferritin and AI. Binary logistic regression was also done. CSF ferritin and AI were found significantly higher in ABM compared to AVM. Model obtained using AI and CSF ferritin along with conventional criteria is better than existing models.

The suicide assessment scale: an instrument assessing suicide risk of suicide attempters.

PubMed

Niméus, A; Alsén, M; Träskman-Bendz, L

2000-11-01

The Suicide Assessment Scale (SUAS), a scale constructed to measure suicidality over time, was administered to 191 suicide attempters. Its predictive validity was tested. SUAS ratings were compared to ratings from other scales, and related to age and psychiatric diagnoses including co-morbidity. Eight patients committed suicide within 12 months after the SUAS assessment. Apart from advanced age, high scores in the SUAS were significant predictors of suicide. From a receiver operating characteristic (ROC) analysis, we identified cutoff SUAS scores which alone and in combination with certain diagnostic and demographic factors are of apparent value in the clinical evaluation of suicide risk after a suicide attempt.

Waist-to-Height Ratio and Triglycerides/High-Density Lipoprotein Cholesterol Were the Optimal Predictors of Metabolic Syndrome in Uighur Men and Women in Xinjiang, China.

PubMed

Chen, Bang-Dang; Yang, Yi-Ning; Ma, Yi-Tong; Pan, Shuo; He, Chun-Hui; Liu, Fen; Ma, Xiang; Fu, Zhen-Yan; Li, Xiao-Mei; Xie, Xiang; Zheng, Ying-Ying

2015-06-01

This study aimed to identify the best single predictor of metabolic syndrome by comparing the predictive ability of various anthropometric and atherogenic parameters among a Uighur population in Xinjiang, northwest China. A total of 4767 Uighur participants were selected from the Cardiovascular Risk Survey (CRS), which was carried out from October, 2007, to March, 2010. Anthropometric data, blood pressure, serum concentration of serum total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and fasting glucose were documented. Prevalence of metabolic syndrome and its individual components were confirmed according to International Diabetes Federation (IDF) criteria. Area under the receiver operating characteristic curve (AUC) of each variable for the presence of metabolic syndrome was compared. The sensitivity (Sen), specificity (Spe), distance in the receiver operating characteristic (ROC) curve, and cutoffs of each variable for the presence of metabolic syndrome were calculated. In all, 23.7% of men had the metabolic syndrome, whereas 40.1% of women had the metabolic syndrome in a Uighur population in Xinjiang; the prevalence of metabolic syndrome in women was significantly higher than that in men (P<0.001). In men, the waist-to-height ratio (WHtR) had the highest AUC value (AUC=0.838); it was followed by TGs/HDL-C (AUC=0.826), body mass index (BMI) (AUC=0.812), waist-to-hip ratio (WHR) (AUC=0.781), and body adiposity index (BAI) (AUC=0.709). In women, the TGs/HDL-C had the highest AUC value (AUC=0.815); it was followed by WHtR (AUC=0.780), WHR (AUC=0.730), BMI (AUC=0.719), and BAI (AUC=0.699). Similarly, among all five anthropometric and atherogenic parameters, the WHtR had the shortest ROC distance of 0.32 (Sen=85.40%, Spe=71.6%), and the optimal cutoff for WHtR was 0.55 in men. In women, TGs/HDL-C had the shortest ROC distance of 0.35 (Sen=75.29%, Spe=75.18%), and the optimal cutoff of TGs/HDL-C was 1.22. WHtR was the best predictor of metabolic syndrome in Uighur men, whereas TGs/HDL-C was the best predictor of metabolic syndrome in Uighur women in Xinjiang.

Variable ranking based on the estimated degree of separation for two distributions of data by the length of the receiver operating characteristic curve.

PubMed

Maswadeh, Waleed M; Snyder, A Peter

2015-05-30

Variable responses are fundamental for all experiments, and they can consist of information-rich, redundant, and low signal intensities. A dataset can consist of a collection of variable responses over multiple classes or groups. Usually some of the variables are removed in a dataset that contain very little information. Sometimes all the variables are used in the data analysis phase. It is common practice to discriminate between two distributions of data; however, there is no formal algorithm to arrive at a degree of separation (DS) between two distributions of data. The DS is defined herein as the average of the sum of the areas from the probability density functions (PDFs) of A and B that contain a≥percentage of A and/or B. Thus, DS90 is the average of the sum of the PDF areas of A and B that contain ≥90% of A and/or B. To arrive at a DS value, two synthesized PDFs or very large experimental datasets are required. Experimentally it is common practice to generate relatively small datasets. Therefore, the challenge was to find a statistical parameter that can be used on small datasets to estimate and highly correlate with the DS90 parameter. Established statistical methods include the overlap area of the two data distribution profiles, Welch's t-test, Kolmogorov-Smirnov (K-S) test, Mann-Whitney-Wilcoxon test, and the area under the receiver operating characteristics (ROC) curve (AUC). The area between the ROC curve and diagonal (ACD) and the length of the ROC curve (LROC) are introduced. The established, ACD, and LROC methods were correlated to the DS90 when applied on many pairs of synthesized PDFs. The LROC method provided the best linear correlation with, and estimation of, the DS90. The estimated DS90 from the LROC (DS90-LROC) is applied to a database, as an example, of three Italian wines consisting of thirteen variable responses for variable ranking consideration. An important highlight of the DS90-LROC method is utilizing the LROC curve methodology to test all variables one-at-a-time with all pairs of classes in a dataset. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Perspectives of human verification via binary QRS template matching of single-lead and 12-lead electrocardiogram.

PubMed

Krasteva, Vessela; Jekova, Irena; Schmid, Ramun

2018-01-01

This study aims to validate the 12-lead electrocardiogram (ECG) as a biometric modality based on two straightforward binary QRS template matching characteristics. Different perspectives of the human verification problem are considered, regarding the optimal lead selection and stability over sample size, gender, age, heart rate (HR). A clinical 12-lead resting ECG database, including a population of 460 subjects with two-session recordings (>1 year apart) is used. Cost-effective strategies for extraction of personalized QRS patterns (100ms) and binary template matching estimate similarity in the time scale (matching time) and dissimilarity in the amplitude scale (mismatch area). The two-class person verification task, taking the decision to validate or to reject the subject identity is managed by linear discriminant analysis (LDA). Non-redundant LDA models for different lead configurations (I,II,III,aVF,aVL,aVF,V1-V6) are trained on the first half of 230 subjects by stepwise feature selection until maximization of the area under the receiver operating characteristic curve (ROC AUC). The operating point on the training ROC at equal error rate (EER) is tested on the independent dataset (second half of 230 subjects) to report unbiased validation of test-ROC AUC and true verification rate (TVR = 100-EER). The test results are further evaluated in groups by sample size, gender, age, HR. The optimal QRS pattern projection for single-lead ECG biometric modality is found in the frontal plane sector (60°-0°) with best (Test-AUC/TVR) for lead II (0.941/86.8%) and slight accuracy drop for -aVR (-0.017/-1.4%), I (-0.01/-1.5%). Chest ECG leads have degrading accuracy from V1 (0.885/80.6%) to V6 (0.799/71.8%). The multi-lead ECG improves verification: 6-chest (0.97/90.9%), 6-limb (0.986/94.3%), 12-leads (0.995/97.5%). The QRS pattern matching model shows stable performance for verification of 10 to 230 individuals; insignificant degradation of TVR in women by (1.2-3.6%), adults ≥70 years (3.7%), younger <40 years (1.9%), HR<60bpm (1.2%), HR>90bpm (3.9%), no degradation for HR change (0 to >20bpm).

A software system for the simulation of chest lesions

NASA Astrophysics Data System (ADS)

Ryan, John T.; McEntee, Mark; Barrett, Saoirse; Evanoff, Michael; Manning, David; Brennan, Patrick

2007-03-01

We report on the development of a novel software tool for the simulation of chest lesions. This software tool was developed for use in our study to attain optimal ambient lighting conditions for chest radiology. This study involved 61 consultant radiologists from the American Board of Radiology. Because of its success, we intend to use the same tool for future studies. The software has two main functions: the simulation of lesions and retrieval of information for ROC (Receiver Operating Characteristic) and JAFROC (Jack-Knife Free Response ROC) analysis. The simulation layer operates by randomly selecting an image from a bank of reportedly normal chest x-rays. A random location is then generated for each lesion, which is checked against a reference lung-map. If the location is within the lung fields, as derived from the lung-map, a lesion is superimposed. Lesions are also randomly selected from a bank of manually created chest lesion images. A blending algorithm determines which are the best intensity levels for the lesion to sit naturally within the chest x-ray. The same software was used to run a study for all 61 radiologists. A sequence of images is displayed in random order. Half of these images had simulated lesions, ranging from subtle to obvious, and half of the images were normal. The operator then selects locations where he/she thinks lesions exist and grades the lesion accordingly. We have found that this software was very effective in this study and intend to use the same principles for future studies.

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.

STIM1 converts TRPC1 from a receptor-operated to a store-operated channel: moving TRPC1 in and out of lipid rafts.

PubMed

Alicia, Sampieri; Angélica, Zepeda; Carlos, Saldaña; Alfonso, Salgado; Vaca, Luis

2008-11-01

While the role of members from the TRPC family of channels as receptor-operated channels (ROC) is well established and supported by numerous studies, the role of this family of channels as store-operated channels (SOC) has been the focus of a heated controversy over the last few years. In the present study, we have explored the modulation of STIM1 on human TRPC1 channel. We show that the association of STIM1 to TRPC1 favors the insertion of TRPC1 into lipid rafts, where TRPC1 functions as a SOC. In the absence of STIM1, TRPC1 associates to other members from the TRPC family of channels to form ROCs. A novel TIRFM-FRET method illustrates the relevance of the dynamic association between STIM1 and TRPC1 for the activation of SOC and the lipid raft localization of the STIM1-TRPC1 complex. This study provides new evidence about the dual activity of TRPC1 (forming ROC or SOC) and the partners needed to determine TRPC1 functional fate. It highlights also the role of plasma membrane microdomains and ER-PM junctions in modulating TRPC1 channel function and its association to STIM1.

[POP-Q indication points, Aa and Ba, involve in diagnosis and prognosis of occult stress urinary incontinence complicated with pelvic organ prolapse].

PubMed

Liu, Cheng; Wu, Wenying; Yang, Qing; Hu, Ming; Zhao, Yang; Hong, Li

2015-06-01

To investigate the correlation between pelvic organ prolapse quantitation (POP-Q) indication points and the incidence of occult stress urinary incontinence (OSUI) and its impact on prognosis. Retrospective study medical records of 93 patients with pelvic organ prolapse (POP) staged at III-IV, of which underwent pelvic reconstruction operations with Prolift system from Jan. 2007 to Sept. 2012. None of these patients had clinical manifestations of stress urinary incontinence (SUI) before surgery, and in which 44 patients were included in study group (POP complicated with OSUI) because they were identified with OSUI, another 49 patients as control group (simple POP). Follow-up and collecting datas including POP-Q, stress test, urodynamic recordings, incidence of de novo SUI, statistic analyzing by logistic regression and receiver operating characteristic curve (ROC). (1) The study group had a much higher incidence of 30% (13/44) on de novo SUI than that of control group (4%, 2/49; P < 0.01). (2) Vaginal delivery (OR = 5.327, 95% CI: 1.120-25.347), constipation (OR = 5.789, 95% CI: 1.492-22.459), preoperative OSUI (OR = 13.695, 95% CI: 2.980-62.944), anterior vaginal wall prolapse (OR = 6.115, 95% CI: 1.231-30.379) were identified as dependent risk factors for de novo SUI by logistic regression analysis. (3) For POP patients that complicated with OSUI, we chose a cutoff value of +1.5 cm for Aa point as the threshold to predicting incidence of de novo SUI according to ROC curve, area under the curve (AUC) was 0.889 (P < 0.05), the sensitivity reached 88.9% and specificity was 73.9%. According to ROC curve of Ba point, a cutoff value of +2.5 cm was chosen as the threshold to predicting incidence of de novo SUI post-operation, it had a sensitivity of 66.7% and specificity of 82.6%, AUC was 0.766 (P < 0.05). Pre-operative OSUI is a dependent risk factor of de novo SUI for advanced POP patients. Aa and Ba points are correlated with preoperative OSUI, and it is worthy to be considered as a risk predictor on forecasting the incidence of de novo SUI post pelvic reconstruction surgery.

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.

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.

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.

Comparison of accelerometer cut points for predicting activity intensity in youth.

PubMed

Trost, Stewart G; Loprinzi, Paul D; Moore, Rebecca; Pfeiffer, Karin A

2011-07-01

The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and V˙O2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). Across all four intensity levels, the EV (κ=0.68) and FT (κ=0.66) cut points exhibited significantly better agreement than TR (κ=0.62), MT (κ=0.54), and PU (κ=0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate- to vigorous-intensity physical activity (ROC-AUC=0.90) than TR, PU, or MT cut points (ROC-AUC=0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC=0.90). On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents.

External validation of blood eosinophils, FE(NO) and serum periostin as surrogates for sputum eosinophils in asthma.

PubMed

Wagener, A H; de Nijs, S B; Lutter, R; Sousa, A R; Weersink, E J M; Bel, E H; Sterk, P J

2015-02-01

Monitoring sputum eosinophils in asthma predicts exacerbations and improves management of asthma. Thus far, blood eosinophils and FE(NO) show contradictory results in predicting eosinophilic airway inflammation. More recently, serum periostin was proposed as a novel biomarker for eosinophilic inflammation. Quantifying the mutual relationships of blood eosinophils, FE(NO), and serum periostin with sputum eosinophils by external validation in two independent cohorts across various severities of asthma. The first cohort consisted of 110 patients with mild to moderate asthma (external validation cohort). The replication cohort consisted of 37 patients with moderate to severe asthma. Both cohorts were evaluated cross-sectionally. Sputum was induced for the assessment of eosinophils. In parallel, blood eosinophil counts, serum periostin concentrations and FENO were assessed. The diagnostic accuracy of these markers to identify eosinophilic asthma (sputum eosinophils ≥3%) was calculated using receiver operating characteristics area under the curve (ROC AUC). In the external validation cohort, ROC AUC for blood eosinophils was 89% (p<0.001) and for FE(NO) level 78% (p<0.001) to detect sputum eosinophilia ≥3%. Serum periostin was not able to distinguish eosinophilic from non-eosinophilic airway inflammation (ROC AUC=55%, p=0.44). When combining these three variables, no improvement was seen. The diagnostic value of blood eosinophils was confirmed in the replication cohort (ROC AUC 85%, p<0.001). In patients with mild to moderate asthma, as well as patients with more severe asthma, blood eosinophils had the highest accuracy in the identification of sputum eosinophilia in asthma. The use of blood eosinophils can facilitate individualised treatment and management of asthma. NTR1846 and NTR2364. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Rockall score in predicting outcomes of elderly patients with acute upper gastrointestinal bleeding

PubMed Central

Wang, Chang-Yuan; Qin, Jian; Wang, Jing; Sun, Chang-Yi; Cao, Tao; Zhu, Dan-Dan

2013-01-01

AIM: To validate the clinical Rockall score in predicting outcomes (rebleeding, surgery and mortality) in elderly patients with acute upper gastrointestinal bleeding (AUGIB). METHODS: A retrospective analysis was undertaken in 341 patients admitted to the emergency room and Intensive Care Unit of Xuanwu Hospital of Capital Medical University with non-variceal upper gastrointestinal bleeding. The Rockall scores were calculated, and the association between clinical Rockall scores and patient outcomes (rebleeding, surgery and mortality) was assessed. Based on the Rockall scores, patients were divided into three risk categories: low risk ≤ 3, moderate risk 3-4, high risk ≥ 4, and the percentages of rebleeding/death/surgery in each risk category were compared. The area under the receiver operating characteristic (ROC) curve was calculated to assess the validity of the Rockall system in predicting rebleeding, surgery and mortality of patients with AUGIB. RESULTS: A positive linear correlation between clinical Rockall scores and patient outcomes in terms of rebleeding, surgery and mortality was observed (r = 0.962, 0.955 and 0.946, respectively, P = 0.001). High clinical Rockall scores > 3 were associated with adverse outcomes (rebleeding, surgery and death). There was a significant correlation between high Rockall scores and the occurrence of rebleeding, surgery and mortality in the entire patient population (χ2 = 49.29, 23.10 and 27.64, respectively, P = 0.001). For rebleeding, the area under the ROC curve was 0.788 (95%CI: 0.726-0.849, P = 0.001); For surgery, the area under the ROC curve was 0.752 (95%CI: 0.679-0.825, P = 0.001) and for mortality, the area under the ROC curve was 0.787 (95%CI: 0.716-0.859, P = 0.001). CONCLUSION: The Rockall score is clinically useful, rapid and accurate in predicting rebleeding, surgery and mortality outcomes in elderly patients with AUGIB. PMID:23801840

Whole Body Magnetic Resonance Imaging Features in Diffuse Idiopathic Skeletal Hyperostosis in Conjunction with Clinical Variables to Whole Body MRI and Clinical Variables in Ankylosing Spondylitis.

PubMed

Weiss, Bettina G; Bachmann, Lucas M; Pfirrmann, Christian W A; Kissling, Rudolf O; Zubler, Veronika

2016-02-01

Discrimination of diffuse idiopathic skeletal hyperostosis (DISH) and ankylosing spondylitis (AS) can be challenging. Usefulness of whole-body magnetic resonance imaging (WB-MRI) in diagnosing spondyloarthritis has been recently proved. We assessed the value of clinical variables alone and in combination with WB-MRI to distinguish between DISH and AS. Diagnostic case-control study: 33 patients with AS and 15 patients with DISH were included. All patients underwent 1.5 Tesla WB-MRI scanning. MR scans were read by a blinded radiologist using the Canadian-Danish Working Group's recommendation. Imaging and clinical variables were identified using the bootstrap. The most important variables from MR and clinical history were assessed in a multivariate fashion resulting in 3 diagnostic models (MRI, clinical, and combined). The discriminative capacity was quantified using the area under the receiver-operating characteristic (ROC) curve. The strength of diagnostic variables was quantified with OR. Forty-eight patients provided 1545 positive findings (193 DISH/1352 AS). The final MR model contained upper anterior corner fat infiltration (32 DISH/181 AS), ankylosis on the vertebral endplate (4 DISH/60 AS), facet joint ankylosis (4 DISH/49 AS), sacroiliac joint edema (11 DISH/91 AS), sacroiliac joint fat infiltration (2 DISH/114 AS), sacroiliac joint ankylosis (2 DISH/119 AS); area under the ROC curve was 0.71, 95% CI 0.64-0.78. The final clinical model contained patient's age and body mass index (area under the ROC curve 0.90, 95% CI 0.89-0.91). The full diagnostic model containing clinical and MR information had an area under the ROC curve of 0.93 (95% CI 0.92-0.95). WB-MRI features can contribute to the correct diagnosis after a thorough conventional workup of patients with DISH and AS.

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.

The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of β-cell function in African American women.

PubMed

Maturu, Amita; DeWitt, Peter; Kern, Philip A; Rasouli, Neda

2015-05-01

The TG/HDL-C ratio is used as a marker of insulin resistance (IR) in Caucasians. However, there are conflicting data on TG/HDL-C ratio as a predictor of IR in African Americans. Compared to Caucasians, African Americans have lower TG levels and increased insulin levels despite a greater risk for diabetes. We hypothesized that the TG/HDL-C ratio is predictive of IR and/or β-cell function in African American (AA) women. Non-diabetic AA women (n = 41) with a BMI > 25 kg/m(2) underwent frequently sampled intravenous glucose tolerance test (FSIGTT). Insulin sensitivity (SI) and the acute insulin response to glucose (AIRg) were measured using minimal model and β-cell function was determined by disposition index (DI = S I*AIRg). IR was defined as the lowest tertile of SI (<1.8 × 10(-4)min(-1)/μU/ml) and inadequate β cell compensation was defined as the lowest tertile of DI (< 900). Data were analyzed using logistic regression models and area under the receiver operating characteristic curve (AUC-ROC). An AUC-ROC > 0.70 was defined as significant discrimination. The mean (± SD) age was 38.5 ± 11.3 years, with BMI of 33.5 ± 6.7 kg/m(2) and fasting glucose of 86.5 ± 10.5 mg/dL. The AUC-ROC for the prediction of DI < 900 was 0.74 indicating that a higher TG/HDL-C ratio was associated with decreased DI. However, the AUC-ROC for prediction of IR or low AIRg (<335 μU/ml) was not significant. This study confirmed that the TG/HDL-C ratio is a poor predictor of IR in AA women. However, we did show an inverse association between the TG/HDL-C ratio and β-cell function, suggesting that this simple tool may effectively identify AA women at risk for DM2. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.

"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.

Description of the ambulance services participating in the Aus-ROC Australian and New Zealand out-of-hospital cardiac arrest Epistry.

PubMed

Beck, Ben; Bray, Janet E; Smith, Karen; Walker, Tony; Grantham, Hugh; Hein, Cindy; Thorrowgood, Melanie; Smith, Anthony; Inoue, Madoka; Smith, Tony; Dicker, Bridget; Swain, Andy; Bosley, Emma; Pemberton, Katherine; McKay, Michael; Johnston-Leek, Malcolm; Cameron, Peter; Perkins, Gavin D; Finn, Judith

2016-12-01

The present study aimed to describe and examine similarities and differences in the current service provision and resuscitation protocols of the ambulance services participating in the Aus-ROC Australian and New Zealand out-of-hospital cardiac arrest (OHCA) Epistry. Understanding these similarities and differences is important in identifying ambulance service factors that might explain regional variation in survival of OHCA in the Aus-ROC Epistry. A structured questionnaire was completed by each of the ambulance services participating in the Aus-ROC Epistry. These ambulance services were SA Ambulance Service, Ambulance Victoria, St John Ambulance Western Australia, Queensland Ambulance Service, St John Ambulance NT, St John New Zealand and Wellington Free Ambulance. The survey aimed to describe ambulance service and dispatch characteristics, resuscitation protocols and details of cardiac arrest registries. We observed similarities between services with respect to the treatment of OHCA and dispatch systems. Differences between services were observed in the serviced population; the proportion of paramedics with basic life support, advanced life support or intensive care training skills; the number of OHCA cases attended; guidelines related to withholding or terminating resuscitation attempts; and the variables that might be used to define 'attempted resuscitation'. All seven participating ambulance services were noted to have existing OHCA registries. There is marked variation between ambulance services currently participating in the Aus-ROC Australian and New Zealand OHCA Epistry with respect to workforce characteristics and key variable definitions. This variation between ambulance services might account for a proportion of the regional variation in survival of OHCA. © 2016 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Improving the prediction of pathologic outcomes in patients undergoing radical prostatectomy: the value of prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine.

PubMed

Ferro, Matteo; Lucarelli, Giuseppe; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Perruolo, Giuseppe; Marino, Ada; Cosimato, Vincenzo; Giorgio, Emilia; Tagliamonte, Virginia; Bottero, Danilo; De Cobelli, Ottavio; Terracciano, Daniela

2015-02-01

Several efforts have been made to find biomarkers that could help clinicians to preoperatively determine prostate cancer (PCa) pathological characteristics and choose the best therapeutic approach, avoiding over-treatment. On this effort, prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine have been presented as promising tools. We evaluated the ability of these biomarkers to predict the pathologic PCa characteristics within a prospectively collected contemporary cohort of patients who underwent radical prostatectomy (RP) for clinically localized PCa at a single high-volume Institution. The prognostic performance of PCA3, phi and sarcosine were evaluated in 78 patients undergoing RP for biopsy-proven PCa. Receiver operating characteristic (ROC) curve analyses tested the accuracy (area under the curve (AUC)) in predicting PCa pathological characteristics. Decision curve analyses (DCA) were used to assess the clinical benefit of the three biomarkers. We found that PCA3, phi and sarcosine levels were significantly higher in patients with tumor volume (TV)≥0.5 ml, pathologic Gleason sum (GS)≥7 and pT3 disease (all p-values≤0.01). ROC curve analysis showed that phi is an accurate predictor of high-stage (AUC 0.85 [0.77-0.93]), high-grade (AUC 0.83 [0.73-0.93]) and high-volume disease (AUC 0.94 [0.88-0.99]). Sarcosine showed a comparable AUC (0.85 [0.76-0.94]) only for T3 stage prediction, whereas PCA3 score showed lower AUCs, ranging from 0.74 (for GS) to 0.86 (for TV). PCA3, phi and sarcosine are predictors of PCa characteristics at final pathology. Successful clinical translation of these findings would reduce the frequency of surveillance biopsies and may enhance acceptance of active surveillance (AS). Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

The logistic score: a criterion for hypothermia after perinatal asphyxia?

PubMed

Wayenberg, Jean-Louis

2010-05-01

To identify during the first hour of life the asphyxiated term neonates who further develop moderate or severe neonatal encephalopathy. In 75 asphyxiated term infants, we measured postnatal arterial base deficit (BD30), assigned an early neurological score (ENS) according to their level of consciousness, respiration pattern and neonatal reflexes at 30 min of life and calculated the logistic score (LS) = (0.33 x BD30) - ENS. The receiver operating characteristics (ROC) methodology was applied to analyze the ability of the LS to correctly classify patients into two groups: normal or mild encephalopathy (60 patients) versus moderate or severe encephalopathy (15 patients). The area under the ROC curve of the LS for moderate or severe encephalopathy (+/- standard error) was 94.4 +/- 3.6%. At the threshold value of 1.2, the LS provided 87.5% sensitivity and 73.7% positive predictive value (PPV). The PPV of LS reaches 100% for a value >3.2, but this threshold allowed only 53.3% sensitivity. The LS is predictive of the neonatal neurological evolution after birth asphyxia and may help to select the high risk patients who are potential candidates for hypothermia therapy.

Achievable Strength-Based Signal Detection in Quantity-Constrained PAM OOK Concentration-Encoded Molecular Communication.

PubMed

Mahfuz, Mohammad Upal

2016-10-01

In this paper, the expressions of achievable strength-based detection probabilities of concentration-encoded molecular communication (CEMC) system have been derived based on finite pulsewidth (FP) pulse-amplitude modulated (PAM) on-off keying (OOK) modulation scheme and strength threshold. An FP-PAM system is characterized by its duty cycle α that indicates the fraction of the entire symbol duration the transmitter remains on and transmits the signal. Results show that the detection performance of an FP-PAM OOK CEMC system significantly depends on the statistical distribution parameters of diffusion-based propagation noise and intersymbol interference (ISI). Analytical detection performance of an FP-PAM OOK CEMC system under ISI scenario has been explained and compared based on receiver operating characteristics (ROC) for impulse (i.e., spike)-modulated (IM) and FP-PAM CEMC schemes. It is shown that the effects of diffusion noise and ISI on ROC can be explained separately based on their communication range-dependent statistics. With full duty cycle, an FP-PAM scheme provides significantly worse performance than an IM scheme. The paper also analyzes the performance of the system when duty cycle, transmission data rate, and quantity of molecules vary.

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.

Unified Least Squares Methods for the Evaluation of Diagnostic Tests With the Gold Standard

PubMed Central

Tang, Liansheng Larry; Yuan, Ao; Collins, John; Che, Xuan; Chan, Leighton

2017-01-01

The article proposes a unified least squares method to estimate the receiver operating characteristic (ROC) parameters for continuous and ordinal diagnostic tests, such as cancer biomarkers. The method is based on a linear model framework using the empirically estimated sensitivities and specificities as input “data.” It gives consistent estimates for regression and accuracy parameters when the underlying continuous test results are normally distributed after some monotonic transformation. The key difference between the proposed method and the method of Tang and Zhou lies in the response variable. The response variable in the latter is transformed empirical ROC curves at different thresholds. It takes on many values for continuous test results, but few values for ordinal test results. The limited number of values for the response variable makes it impractical for ordinal data. However, the response variable in the proposed method takes on many more distinct values so that the method yields valid estimates for ordinal data. Extensive simulation studies are conducted to investigate and compare the finite sample performance of the proposed method with an existing method, and the method is then used to analyze 2 real cancer diagnostic example as an illustration. PMID:28469385

Time-dependent classification accuracy curve under marker-dependent sampling.

PubMed

Zhu, Zhaoyin; Wang, Xiaofei; Saha-Chaudhuri, Paramita; Kosinski, Andrzej S; George, Stephen L

2016-07-01

Evaluating the classification accuracy of a candidate biomarker signaling the onset of disease or disease status is essential for medical decision making. A good biomarker would accurately identify the patients who are likely to progress or die at a particular time in the future or who are in urgent need for active treatments. To assess the performance of a candidate biomarker, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are commonly used. In many cases, the standard simple random sampling (SRS) design used for biomarker validation studies is costly and inefficient. In order to improve the efficiency and reduce the cost of biomarker validation, marker-dependent sampling (MDS) may be used. In a MDS design, the selection of patients to assess true survival time is dependent on the result of a biomarker assay. In this article, we introduce a nonparametric estimator for time-dependent AUC under a MDS design. The consistency and the asymptotic normality of the proposed estimator is established. Simulation shows the unbiasedness of the proposed estimator and a significant efficiency gain of the MDS design over the SRS design. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Diagnostic value of Tg and TgAb for metastasis following ablation in patients with differentiated thyroid carcinoma coexistent with Hashimoto thyroiditis.

PubMed

Chai, Hong; Zhu, Zhao-Jin; Chen, Ze-Quan; Yu, Yong-Li

2016-08-01

This study was designed to investigate the clinical value of serum thyroglobulin (Tg) and antithyroglobulin antibody (TgAb) measurements and the cutoff value after ablation in differentiated thyroid carcinoma (DTC) complicated by Hashimoto thyroiditis (HT) with metastasis. We measured serum Tg and TgAb levels and evaluated the disease status in 164 cases of DTC coexistent with HT in pathologically confirmed patients after surgery and post-remnant ablation during a 3-year follow-up. All Tg and TgAb levels were assessed by chemiluminescent immunoassay (IMA). Receiver operating characteristic (ROC) curve analysis was used to evaluate the prognostic value of Tg and TgAb for disease metastasis. The relationship between Tg and TgAb was analyzed using the scatter diagram distribution method. We found that the cutoff values of Tg and TgAb were 1.48 µg/L and 45 kIU/L, respectively. The area under the ROC curve (AUC) of Tg and TgAb was 0.907 and 0.650, respectively. In DTC coexistent with HT patients, the optimal cutoff value correlated with metastasis in Tg and TgAb was 1.48 µg/L and 45 kIU/L, respectively.

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.

Optimization of a chemical identification algorithm

NASA Astrophysics Data System (ADS)

Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

2010-04-01

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

Associations Among Indicators of Depression in Medicaid-Eligible Community-Dwelling Older Adults

PubMed Central

Byma, Elizabeth A.

2013-01-01

Purpose: The purpose of this research was to examine associations among 2 separate Minimum Data Set-Home Care (MDS-HC) depression measures (the Depression Rating Scale [DRS] and medical diagnosis of depression) with billed antidepressant medications in Medicaid paid claim files. Design and Methods: The sample for this cross-sectional research included 3,041 Medicaid-eligible older adult participants in a Home and Community Based Waiver Program and used data from the MDS-HC, Version 1 and Medicaid Paid Claim Files. Sensitivity and specificity analyses, receiver operating characteristic (ROC) curve analysis, and t tests were utilized. Results: DRS scoring indicated that 15.4% of participants had behaviors indicative of depression, whereas 42% had a medical diagnosis of depression noted in the MDS-HC. Of those with a medical diagnosis of depression, 51% had a prescribed antidepressant medication. ROC analysis suggested that the DRS was a poor distinguisher of participants with and without a medical diagnosis of depression or prescribed antidepressant medications. Implications: Approximately half of Medicaid-eligible older adults medically diagnosed with depression were treated pharmacologically. Longitudinal research is recommended to assess responsiveness of the DRS over time to pharmacological and psychotherapeutic interventions for depression. PMID:23103523

Machine learning study for the prediction of transdermal peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Choi, Seung-Hoon; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Yun-Jaie; Shin, Jae-Min; Choi, Kihang; Jung, Dong Hyun

2011-04-01

In order to develop a computational method to rapidly evaluate transdermal peptides, we report approaches for predicting the transdermal activity of peptides on the basis of peptide sequence information using Artificial Neural Network (ANN), Partial Least Squares (PLS) and Support Vector Machine (SVM). We identified 269 transdermal peptides by the phage display technique and use them as the positive controls to develop and test machine learning models. Combinations of three descriptors with neural network architectures, the number of latent variables and the kernel functions are tried in training to make appropriate predictions. The capacity of models is evaluated by means of statistical indicators including sensitivity, specificity, and the area under the receiver operating characteristic curve (ROC score). In the ROC score-based comparison, three methods proved capable of providing a reasonable prediction of transdermal peptide. The best result is obtained by SVM model with a radial basis function and VHSE descriptors. The results indicate that it is possible to discriminate between transdermal peptides and random sequences using our models. We anticipate that our models will be applicable to prediction of transdermal peptide for large peptide database for facilitating efficient transdermal drug delivery through intact skin.

Dissociations of the number and precision of visual short-term memory representations in change detection.

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

The present study dissociated the number (i.e., quantity) and precision (i.e., quality) of visual short-term memory (STM) representations in change detection using receiver operating characteristic (ROC) and experimental manipulations. Across three experiments, participants performed both recognition and recall tests of visual STM using the change-detection task and the continuous color-wheel recall task, respectively. Experiment 1 demonstrated that the estimates of the number and precision of visual STM representations based on the ROC model of change-detection performance were robustly correlated with the corresponding estimates based on the mixture model of continuous-recall performance. Experiments 2 and 3 showed that the experimental manipulation of mnemonic precision using white-noise masking and the experimental manipulation of the number of encoded STM representations using consolidation masking produced selective effects on the corresponding measures of mnemonic precision and the number of encoded STM representations, respectively, in both change-detection and continuous-recall tasks. Altogether, using the individual-differences (Experiment 1) and experimental dissociation (Experiment 2 and 3) approaches, the present study demonstrated the some-or-none nature of visual STM representations across recall and recognition.

Recognition errors suggest fast familiarity and slow recollection in rhesus monkeys

PubMed Central

Basile, Benjamin M.; Hampton, Robert R.

2013-01-01

One influential model of recognition posits two underlying memory processes: recollection, which is detailed but relatively slow, and familiarity, which is quick but lacks detail. Most of the evidence for this dual-process model in nonhumans has come from analyses of receiver operating characteristic (ROC) curves in rats, but whether ROC analyses can demonstrate dual processes has been repeatedly challenged. Here, we present independent converging evidence for the dual-process model from analyses of recognition errors made by rhesus monkeys. Recognition choices were made in three different ways depending on processing duration. Short-latency errors were disproportionately false alarms to familiar lures, suggesting control by familiarity. Medium-latency responses were less likely to be false alarms and were more accurate, suggesting onset of a recollective process that could correctly reject familiar lures. Long-latency responses were guesses. A response deadline increased false alarms, suggesting that limiting processing time weakened the contribution of recollection and strengthened the contribution of familiarity. Together, these findings suggest fast familiarity and slow recollection in monkeys, that monkeys use a “recollect to reject” strategy to countermand false familiarity, and that primate recognition performance is well-characterized by a dual-process model consisting of recollection and familiarity. PMID:23864646

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

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

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

Comparison of computer display monitors for computed radiography diagnostic application in a radiology PACS.

PubMed

Sim, L; Manthey, K; Esdaile, P; Benson, M

2004-09-01

A study to compare the performance of the following display monitors for application as PACS CR diagnostic workstations is described. 1. Diagnostic quality, 3 megapixel, 21 inch monochrome LCD monitors. 2. Commercial grade, 2 megapixel, 20 inch colour LCD monitors. Two sets of fifty radiological studies each were presented separately to five radiologists on two occasions, using different displays on each occasion. The two sets of radiological studies were CR of the chest, querying the presence of pneumothorax, and CR of the wrist, querying the presence of a scaphoid fracture. Receiver Operating Characteristic (ROC) curves were constructed for diagnostic performance for each presentation. Areas under the ROC curves (AUC) for diagnosis using different monitors were compared for each image set and the following results obtained: Set 1: Monochrome AUC = 0.873 +/- 0.026; Colour AUC = 0.831 +/- 0.032; Set 2: Monochrome AUC = 0.945 +/- 0.014; Colour AUC = 0.931 +/- 0.019; Differences in AUC were attributed to the different monitors. While not significant at a 95% confidence level, the results have supported a cautious approach to consideration of the use of commercial grade LCD colour monitors for diagnostic application.

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.

Identification of Serum Periostin as a Potential Diagnostic and Prognostic Marker for Colorectal Cancer.

PubMed

Dong, Dong; Zhang, Lufang; Jia, Li; Ji, Wei; Wang, Zhiyong; Ren, Li; Niu, Ruifang; Zhou, Yunli

2018-06-01

Periostin (POSTN) plays an important role in numerous cancers, especially in gastrointestinal malignancy. The objective of this study was to investigate the diagnostic and prognostic role of serum POSTN in colorectal cancer (CRC). Serum periostin, together with CEA, CA19.9, CA72.4, and CA242 levels were measured in samples from 108 patients with CRC and 56 healthy controls, and their correlation with clinical characteristics was further analyzed. Receiver operating curves (ROC), Kaplan-Meier curves, and log-rank analyses were used to evaluate diagnostic and prognostic significance. Serum POSTN levels were significantly higher in patients with CRC compared with healthy controls (p < 0.0001) and associated with clinical stages (p < 0.001). ROC analysis revealed that POSTN was a biomarker comparable to CEA, CA19.9, and CA72.4 to distinguish all CRC from healthy controls (AUC = 0.75). Moreover, POSTN retained its diagnostic ability for CEA-negative (AUC = 0.69) and CA19.9-negative CRC patients (AUC = 0.71). Survival analysis revealed that patients with lower serum POSTN had longer overall survival than those with high serum POSTN (p = 0.0146). Serum POSTN might be a novel diagnostic and prognostic biomarker for patients with CRC.

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

Initial development of a computer-aided diagnosis tool for solitary pulmonary nodules

NASA Astrophysics Data System (ADS)

Catarious, David M., Jr.; Baydush, Alan H.; Floyd, Carey E., Jr.

2001-07-01

This paper describes the development of a computer-aided diagnosis (CAD) tool for solitary pulmonary nodules. This CAD tool is built upon physically meaningful features that were selected because of their relevance to shape and texture. These features included a modified version of the Hotelling statistic (HS), a channelized HS, three measures of fractal properties, two measures of spicularity, and three manually measured shape features. These features were measured from a difficult database consisting of 237 regions of interest (ROIs) extracted from digitized chest radiographs. The center of each 256x256 pixel ROI contained a suspicious lesion which was sent to follow-up by a radiologist and whose nature was later clinically determined. Linear discriminant analysis (LDA) was used to search the feature space via sequential forward search using percentage correct as the performance metric. An optimized feature subset, selected for the highest accuracy, was then fed into a three layer artificial neural network (ANN). The ANN's performance was assessed by receiver operating characteristic (ROC) analysis. A leave-one-out testing/training methodology was employed for the ROC analysis. The performance of this system is competitive with that of three radiologists on the same database.

Competitive Enzyme-Linked Immunosorbent Assay for Detection of Leptospira interrogans Serovar pomona Antibodies in Bovine Sera

PubMed Central

Surujballi, Om; Mallory, Maria

2001-01-01

A competitive enzyme-linked immunosorbent assay (ELISA) using a specific monoclonal antibody (M898) was developed for detection of bovine antibodies to Leptospira interrogans serovar pomona. This assay was evaluated using field sera (n = 190) with serovar pomona microscopic agglutination test (MAT) titers of ≥100 as the positive population (group A); field sera (n = 1,445) which were negative in the MAT (1:100 dilution) for serovar pomona (group B); and sera (from a specific-pathogen-free cattle herd [n = 210]) which were negative in the MAT (1:100 dilution) for serovars canicola, copenhageni, grippotyphosa, hardjo, pomona, and sejroe (group C). At the cutoff point recommended by receiver operating characteristic (ROC) curve analysis of the combined ELISA results of serum groups A, B, and C, the sensitivity and specificity values were 93.7 and 96.3%, respectively. The value for the area under this ROC curve was 0.977, indicating a high level of accuracy for the ELISA. Similar results were obtained from the analysis of the combined results of serum groups A and B and from the analysis of the combined results of serum groups A and C. PMID:11139193

Extent of agreement between the body fluid model of Sysmex XN-20 and the manual microscopy method.

PubMed

Huang, Wei-Hua; Lu, Lin-Peng; Wu, Kang; Guo, Fang-Yu; Guo, Jie; Yu, Jing-Long; Zhou, Dao-Yin; Sun, Yi; Deng, An-Mei

2017-09-01

Although the correlations concerning cellular component analysis between the Sysmex XN-20 body fluid (BF) model and manual microscopy have been investigated by several studies, the extent of agreement between these two methods has not been investigated. A total of 90 BF samples were prospectively collected and analyzed using the Sysmex XN-20 BF model and microscopy. The extent of agreement between these two methods was evaluated using the Bland-Altman approach. Receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic accuracy of high-fluorescence (HF) BF cells for malignant diseases. The agreements of white blood cell (WBC), red blood cell (RBC), and percentages of neutrophils, lymphocytes, and monocytes between the Sysmex XN-20 BF model and manual microscopy were imperfect. The areas under the ROC curves for absolute and relative HF cells were 0.67 (95% confidence interval [CI]: 0.56-0.78) and 0.60 (95% CI: 0.48-0.72), respectively. Due to the Sysmex XN-20 BF model's imperfect agreement with manual microscopy and its weak diagnostic accuracy for malignant diseases, the current evidence does not support replacing manual microscopy with this model in clinical practice. © 2016 Wiley Periodicals, Inc.

[Criterion Validity of the German Version of the CES-D in the General Population].

PubMed

Jahn, Rebecca; Baumgartner, Josef S; van den Nest, Miriam; Friedrich, Fabian; Alexandrowicz, Rainer W; Wancata, Johannes

2018-04-17

The "Center of Epidemiologic Studies - Depression scale" (CES-D) is a well-known screening tool for depression. Until now the criterion validity of the German version of the CES-D was not investigated in a sample of the adult general population. 508 study participants of the Austrian general population completed the CES-D. ICD-10 diagnoses were established by using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN). Receiver Operating Characteristics (ROC) analysis was conducted. Possible gender differences were explored. Overall discriminating performance of the CES-D was sufficient (ROC-AUC 0,836). Using the traditional cut-off values of 15/16 and 21/22 respectively the sensitivity was 43.2 % and 32.4 %, respectively. The cut-off value developed on the basis of our sample was 9/10 with a sensitivity of 81.1 % und a specificity of 74.3 %. There were no significant gender differences. This is the first study investigating the criterion validity of the German version of the CES-D in the general population. The optimal cut-off values yielded sufficient sensitivity and specificity, comparable to the values of other screening tools. © Georg Thieme Verlag KG Stuttgart · New York.

Multiparametric MRI Apparent Diffusion Coefficient (ADC) Accuracy in Diagnosing Clinically Significant Prostate Cancer.

PubMed

Pepe, Pietro; D'Urso, Davide; Garufi, Antonio; Priolo, Giandomenico; Pennisi, Michele; Russo, Giorgio; Sabini, Maria Gabriella; Valastro, Lucia Maria; Galia, Antonio; Fraggetta, Filippo

2017-01-01

To evaluate the accuracy of multiparametric magnetic resonance imaging apparent diffusion coefficient (mpMRI ADC) in the diagnosis of clinically significant prostate cancer (PCa). From January 2016 to December 2016, 44 patients who underwent radical prostatectomy for PCa and mpMRI lesions suggestive of cancer were retrospectively evaluated at definitive specimen. The accuracy of suspicious mpMRI prostate imaging reporting and data system (PI-RADS ≥3) vs. ADC values in the diagnosis of Gleason score ≥7 was evaluated. Receiver operating characteristics (ROC) curve analysis gave back an ADC threshold of 0.747×10 -3 mm 2 /s to separate between Gleason Score 6 and ≥7. The diagnostic accuracy of ADC value (cut-off 0.747×10 -3 mm 2 /s) vs. PI-RADS score ≥3 in diagnosing PCa with Gleason score ≥7 was equal to 84% vs. 63.6% with an area under the curve (AUC) ROC of 0.81 vs. 0.71, respectively. ADC evaluation could support clinicians in decision making of patients with PI-RADS score <3 at risk for PCa. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

PubMed Central

Wray, Naomi R.; Yang, Jian; Goddard, Michael E.; Visscher, Peter M.

2010-01-01

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator. PMID:20195508

The Glittre-ADL Test Cut-Off Point to Discriminate Abnormal Functional Capacity in Patients with COPD.

PubMed

Gulart, Aline Almeida; Munari, Anelise Bauer; Klein, Suelen Roberta; Santos da Silveira, Lucas; Mayer, Anamaria Fleig

2018-02-01

The study objective was to determine a cut-off point for the Glittre activities of daily living (ADL)test (TGlittre) to discriminate patients with normal and abnormal functional capacity. Fifty-nine patients with moderate to very severe COPD (45 males; 65 ± 8.84 years; BMI: 26 ± 4.78 kg/m 2 ; FEV 1 : 35.3 ± 13.4% pred) were evaluated for spirometry, TGlittre, 6-minute walk test (6 MWT), physical ADL, modified Medical Research Council scale (mMRC), BODE index, Saint George's Respiratory Questionnaire (SGRQ), and COPD Assessment Test (CAT). The receiver operating characteristic (ROC) curve was used to determine the cut-off point for TGlittre in order to discriminate patients with 6 MWT < 82% pred. The ROC curve indicated a cut-off point of 3.5 minutes for the TGlittre (sensitivity = 92%, specificity = 83%, and area under the ROC curve = 0.95 [95% CI: 0.89-0.99]). Patients with abnormal functional capacity had higher mMRC (median difference 1 point), CAT (mean difference: 4.5 points), SGRQ (mean difference: 12.1 points), and BODE (1.37 points) scores, longer time of physical activity <1.5 metabolic equivalent of task (mean difference: 47.9 minutes) and in sitting position (mean difference: 59.4 minutes) and smaller number of steps (mean difference: 1,549 minutes); p < 0.05 for all. In conclusion, the cut-off point of 3.5 minutes in the TGlittre is sensitive and specific to distinguish COPD patients with abnormal and normal functional capacity.

Proposing a Tentative Cut Point for the Compulsive Sexual Behavior Inventory

PubMed Central

Storholm, Erik David; Fisher, Dennis G.; Napper, Lucy E.; Reynolds, Grace L.

2015-01-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas. PMID:21203814

[Efficacy of storage phosphor-based digital mammography in diagnosis of breast cancer--comparison with film-screen mammography].

PubMed

Kitahama, H

1991-05-25

The aim of this study is to present efficacy of storage phosphor-based digital mammography (CR-mammography) in diagnosis of breast cancer. Ninety-seven cases with breast cancer including 44 cases less than 2 cm in macroscopic size (t1 cases) were evaluated using storage phosphor-based digital mammography (2000 x 2510 pixels by 10 bits). Abnormal findings on CR-mammography were detected in 86 cases (88.7%) of 97 women with breast cancer. Sensitivity of CR-mammography was 88.7%. It was superior to that of film-screen mammography. On t1 breast cancer cases, sensitivity on CR-mammography was 88.6%. False negative rate in t1 breast cancer cases was reduced by image processing using CR-mammography. To evaluate microcalcifications, CR-mammograms and film-screen mammograms were investigated in 22 cases of breast cancer proven pathologically the existence of microcalcifications and 11 paraffin tissue blocks of breast cancer. CR-mammography was superior to film-screen mammography in recognizing of microcalcifications. As regards the detectability for the number and the shape of microcalcifications, CR-mammography was equivalent to film-screen mammography. Receiver operating characteristic (ROC) analysis by eight observers was performed for CR-mammography and film-screen mammography with 54 breast cancer patients and 54 normal cases. The detectability of abnormal findings of breast cancer on CR-mammography (ROC area = 0.91) was better than that on film-screen mammography (ROC area = 0.88) (p less than 0.05). Efficacy of storage phosphor-based digital mammography in diagnosis of breast cancer was discussed and demonstrated in this study.

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.

Siemens Immulite Aspergillus-specific IgG assay for chronic pulmonary aspergillosis diagnosis.

PubMed

Page, Iain D; Richardson, Malcolm D; Denning, David W

2018-05-14

Chronic pulmonary aspergillosis (CPA) complicates underlying lung disease, including treated tuberculosis. Measurement of Aspergillus-specific immunoglobulin G (IgG) is a key diagnostic step. Cutoffs have been proposed based on receiver operating characteristic (ROC) curve analyses comparing CPA cases to healthy controls, but performance in at-risk populations with underlying lung disease is unclear. We evaluated optimal cutoffs for the Siemens Immulite Aspergillus-specific IgG assay for CPA diagnosis in relation to large groups of healthy and diseased controls with treated pulmonary tuberculosis. Sera from 241 patients with CPA attending the UK National Aspergillosis Centre, 299 Ugandan blood donors (healthy controls), and 398 Ugandans with treated pulmonary tuberculosis (diseased controls) were tested. Radiological screening removed potential CPA cases from diseased controls (234 screened diseased controls). ROC curve analyses were performed and optimal cutoffs identified by Youden J statistic. CPA versus control ROC area under curve (AUC) results were: healthy controls 0.984 (95% confidence interval 0.972-0.997), diseased controls 0.972 (0.959-0.985), screened diseased controls 0.979 (0.967-0.992). Optimal cutoffs were: healthy controls 15 mg/l (94.6% sensitivity, 98% specificity), unscreened diseased controls 15 mg/l (94.6% sensitivity, 94.5% specificity), screened diseased controls 25 mg/l (92.9% sensitivity, 98.7% specificity). Results were similar in healthy and diseased controls. We advocate a cutoff of 20 mg/l as this is the midpoint of the range of optimal cutoffs. Cutoffs calculated in relation to healthy controls for other assays are likely to remain valid for use in a treated tuberculosis population.

VIEWDEX: an efficient and easy-to-use software for observer performance studies.

PubMed

Håkansson, Markus; Svensson, Sune; Zachrisson, Sara; Svalkvist, Angelica; Båth, Magnus; Månsson, Lars Gunnar

2010-01-01

The development of investigation techniques, image processing, workstation monitors, analysing tools etc. within the field of radiology is vast, and the need for efficient tools in the evaluation and optimisation process of image and investigation quality is important. ViewDEX (Viewer for Digital Evaluation of X-ray images) is an image viewer and task manager suitable for research and optimisation tasks in medical imaging. ViewDEX is DICOM compatible and the features of the interface (tasks, image handling and functionality) are general and flexible. The configuration of a study and output (for example, answers given) can be edited in any text editor. ViewDEX is developed in Java and can run from any disc area connected to a computer. It is free to use for non-commercial purposes and can be downloaded from http://www.vgregion.se/sas/viewdex. In the present work, an evaluation of the efficiency of ViewDEX for receiver operating characteristic (ROC) studies, free-response ROC (FROC) studies and visual grading (VG) studies was conducted. For VG studies, the total scoring rate was dependent on the number of criteria per case. A scoring rate of approximately 150 cases h(-1) can be expected for a typical VG study using single images and five anatomical criteria. For ROC and FROC studies using clinical images, the scoring rate was approximately 100 cases h(-1) using single images and approximately 25 cases h(-1) using image stacks ( approximately 50 images case(-1)). In conclusion, ViewDEX is an efficient and easy-to-use software for observer performance studies.

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.

[AIMS65 score validation for upper gastrointestinal bleeding in the National Hospital Cayetano Heredia].

PubMed

Aguilar Sánchez, Víctor; Bravo Paredes, Eduar Alban; Pinto Valdivia, José Luis; Valenzuela Granados, Vanessa; Espinoza-Rios, Jorge Luis

2015-01-01

To validate the score AIMS65 in patients with upper gastrointestinal bleeding, in terms of mortality and rebleeding a 30-day event. Patients included were those with higher age to 18 years attending the Hospital Nacional Cayetano Heredia during the period May 2013 to December 2014, by upper gastrointestinal bleeding. Data were analyzed using ROC curve (Receiver Operating Characteristic) and the area was obtained under the curve (AUC) to properly qualify the score AIMS65. 209 patients were included, 66.03% were male, with an average age of 58.02 years. The mortality rate was 7.65%, the multiorgan failure the most common cause of death. Plus 3.82% of the patients had recurrent bleeding and 11% required a transfusion of more than 2 units of blood. When analyzing the ROC curve with AIMS65 and mortality score a value of 0.9122 is reported; identifying it as cutoff greater than or equal to 3 value in the score AIMS65 to discriminate patients at high risk of death, likewise the ROC curve was analyzed for recurrence of bleeding with a value of 0.6266 and the need to Transfusion of packed red blood cells over two a value of 0.7421. And it was determined the average hospital stay with a value of 4.8 days, however, no correlation was found with the score AIMS65. AIMS65 score is a good predictor of mortality, and is useful for predicting the need for transfusion of more than 2 globular packages. However it is not a good predictor for recurrence of bleeding, or hospital stay.

Proposing a tentative cut point for the Compulsive Sexual Behavior Inventory.

PubMed

Storholm, Erik David; Fisher, Dennis G; Napper, Lucy E; Reynolds, Grace L; Halkitis, Perry N

2011-12-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas.

Three tests and three corrections: Comment on Koen and Yonelinas (2010)

PubMed Central

Jang, Yoonhee; Mickes, Laura; Wixted, John T.

2012-01-01

The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory experiments is usually less than 1, which has long been interpreted to mean that the variance of the target distribution is greater than the variance of the lure distribution. The greater variance of the target distribution could arise because the different items on a list receive different increments in memory strength during study (the “encoding variability” hypothesis). In a test of that interpretation, J. Koen and A. Yonelinas (2010, K&Y) attempted to further increase encoding variability to see if it would further decrease the slope of the zROC. To do so, they presented items on a list for two different durations and then mixed the weak and strong targets together. After performing three tests on the mixed-strength data, K&Y concluded that encoding variability does not explain why the slope of the zROC is typically less than one. However, we show that their tests have no bearing on the encoding variability account. Instead, they bear on the mixture-UVSD model that corresponds to their experimental design. On the surface, the results reported by K&Y appear to be inconsistent with the predictions of the mixture-UVSD model (though they were taken to be inconsistent with the predictions of the encoding variability hypothesis). However, all three of the tests they performed contained errors. When those errors are corrected, the same three tests show that their data support, rather than contradict, the mixture-UVSD model (but they still have no bearing on the encoding variability hypothesis). PMID:22390323

Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles

PubMed Central

2016-01-01

Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2N). A recursive approximation to the optimal solution scales as O(N2), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets. PMID:27097522

[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.

Non-invasive assessment of liver fibrosis using two-dimensional shear wave elastography in patients with autoimmune liver diseases

PubMed Central

Zeng, Jie; Huang, Ze-Ping; Zheng, Jian; Wu, Tao; Zheng, Rong-Qin

2017-01-01

AIM To determine the diagnostic accuracy of two-dimensional shear wave elastography (2D-SWE) for the non-invasive assessment of liver fibrosis in patients with autoimmune liver diseases (AILD) using liver biopsy as the reference standard. METHODS Patients with AILD who underwent liver biopsy and 2D-SWE were consecutively enrolled. Receiver operating characteristic (ROC) curves were constructed to assess the overall accuracy and to identify optimal cut-off values. RESULTS The characteristics of the diagnostic performance were determined for 114 patients with AILD. The areas under the ROC curves for significant fibrosis, severe fibrosis, and cirrhosis were 0.85, 0.85, and 0.86, respectively, and the optimal cut-off values associated with significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 9.7 kPa, 13.2 kPa and 16.3 kPa, respectively. 2D-SWE showed sensitivity values of 81.7% for significant fibrosis, 83.0% for severe fibrosis, and 87.0% for cirrhosis, and the respective specificity values were 81.3%, 74.6%, and 80.2%. The overall concordance rate of the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages was 53.5%. CONCLUSION 2D-SWE showed promising diagnostic performance for assessing liver fibrosis stages and exhibited high cut-off values in patients with AILD. Low overall concordance rate was observed in the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages. PMID:28765706

Benign and malignant skull-involved lesions: discriminative value of conventional CT and MRI combined with diffusion-weighted MRI.

PubMed

Tu, Zhanhai; Xiao, Zebin; Zheng, Yingyan; Huang, Hongjie; Yang, Libin; Cao, Dairong

2018-01-01

Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10 -3 mm 2 /s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.

The Center for Epidemiologic Studies Depression Scale is an adequate screening instrument for depression and anxiety disorder in adults with congential heart disease.

PubMed

Moon, Ju Ryoung; Huh, June; Song, Jinyoung; Kang, I-Seok; Park, Seung Woo; Chang, Sung-A; Yang, Ji-Hyuk; Jun, Tae-Gook

2017-09-05

The Center for Epidemiological Studies Depression Scale (CES-D) is an instrument that is commonly used to screen for depression in patients with chronic disease, but the characteristics of the CES-D in adults with congenital heart disease (CHD) have not yet been studied. The aim of this study was to investigate the criterion validities and the predictive powers of the CES-D for depression and anxiety disorders in adults with CHD. Two hundred patients were screened with the CES-D and secondarily interviewed with a diagnostic instrument, i.e., the Mini International Neuropsychiatric Instrument. The sensitivity and specificity values of the CES-D were calculated by cross-tabulation at different cutoff scores. Receiver operating characteristic (ROC) curves were used to assess the optimal cutoff point for each disorder and to assess the predictive power of the instrument. The CES-D exhibited satisfactory criterion validities for depression and for all combinations of depression and/or anxiety. With a desired sensitivity of at least 80%, the optimal cutoff scores were 18. The predictive power of the CES-D in the patients was best for major depression and dysthymia (area under the ROC curve: 0.92) followed by the score for any combination of depression and/or anxiety (0.88). The use of CES-D to simultaneously screen for both depression and anxiety disorders may be useful in adults with CHD. CESDEP 212. Registered 2 March 2014 (retrospectively registered).

Usability verification of the Emergency Trauma Score (EMTRAS) and Rapid Emergency Medicine Score (REMS) in patients with trauma: A retrospective cohort study.

PubMed

Park, Hyun Oh; Kim, Jong Woo; Kim, Sung Hwan; Moon, Seong Ho; Byun, Joung Hun; Kim, Ki Nyun; Yang, Jun Ho; Lee, Chung Eun; Jang, In Seok; Kang, Dong Hun; Kim, Seong Chun; Kang, Changwoo; Choi, Jun Young

2017-11-01

Early estimation of mortality risk in patients with trauma is essential. In this study, we evaluate the validity of the Emergency Trauma Score (EMTRAS) and Rapid Emergency Medicine Score (REMS) for predicting in-hospital mortality in patients with trauma. Furthermore, we compared the REMS and the EMTRAS with 2 other scoring systems: the Revised Trauma Score (RTS) and Injury Severity score (ISS).We performed a retrospective chart review of 6905 patients with trauma reported between July 2011 and June 2016 at a large national university hospital in South Korea. We analyzed the associations between patient characteristics, treatment course, and injury severity scoring systems (ISS, RTS, EMTRAS, and REMS) with in-hospital mortality. Discriminating power was compared between scoring systems using the areas under the curve (AUC) of receiver operating characteristic (ROC) curves.The overall in-hospital mortality rate was 3.1%. Higher EMTRAS and REMS scores were associated with hospital mortality (P < .001). The ROC curve demonstrated adequate discrimination (AUC = 0.957 for EMTRAS and 0.9 for REMS). After performing AUC analysis followed by Bonferroni correction for multiple comparisons, EMTRAS was significantly superior to REMS and ISS in predicting in-hospital mortality (P < .001), but not significantly different from the RTS (P = .057). The other scoring systems were not significantly different from each other.The EMTRAS and the REMS are simple, accurate predictors of in-hospital mortality in patients with trauma.

Non-invasive assessment of liver fibrosis using two-dimensional shear wave elastography in patients with autoimmune liver diseases.

PubMed

Zeng, Jie; Huang, Ze-Ping; Zheng, Jian; Wu, Tao; Zheng, Rong-Qin

2017-07-14

To determine the diagnostic accuracy of two-dimensional shear wave elastography (2D-SWE) for the non-invasive assessment of liver fibrosis in patients with autoimmune liver diseases (AILD) using liver biopsy as the reference standard. Patients with AILD who underwent liver biopsy and 2D-SWE were consecutively enrolled. Receiver operating characteristic (ROC) curves were constructed to assess the overall accuracy and to identify optimal cut-off values. The characteristics of the diagnostic performance were determined for 114 patients with AILD. The areas under the ROC curves for significant fibrosis, severe fibrosis, and cirrhosis were 0.85, 0.85, and 0.86, respectively, and the optimal cut-off values associated with significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 9.7 kPa, 13.2 kPa and 16.3 kPa, respectively. 2D-SWE showed sensitivity values of 81.7% for significant fibrosis, 83.0% for severe fibrosis, and 87.0% for cirrhosis, and the respective specificity values were 81.3%, 74.6%, and 80.2%. The overall concordance rate of the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages was 53.5%. 2D-SWE showed promising diagnostic performance for assessing liver fibrosis stages and exhibited high cut-off values in patients with AILD. Low overall concordance rate was observed in the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages.

Cross-cultural difference and validation of the Chinese version of Montreal Cognitive Assessment in older adults residing in Eastern China: preliminary findings.

PubMed

Hu, Jian-bo; Zhou, Wei-hua; Hu, Shao-hua; Huang, Man-li; Wei, Ning; Qi, Hong-li; Huang, Jin-wen; Xu, Yi

2013-01-01

To evaluate the psychometric properties of the Chinese Montreal Cognitive Assessment (MoCA-C) and assess cross-cultural differences in a community-based cohort residing in the Eastern China. The study included 72 patients with Alzheimer's disease (AD), 84 patients with mild cognitive impairment (MCI) and 146 cognitively normal controls. Sensitivities and specificities were calculated using the recommended cut-off scores. Receiver operator characteristic (ROC) curve analyses were performed to determine optimal sensitivity and specificity. Criterion validity, inter-rater, test-retest reliability and internal consistencies of the MoCA-C were examined, and clinical observations made. The influence of age, education level and gender on MoCA score was examined. Using the recommended cut-off score of 26, the area under the ROC (AUC) for predicting MCI groups using the MoCA-C was 0.930 (95%CI: 0.894; 0.965). The MoCA-C demonstrated 92% sensitivity and 85% specificity in screening for MCI. Cultural differences from the original MoCA affected the test response rate. The MoCA-C appears to have utility as a cognitive screen for early detection of AD and for MCI and warrants further investigation regarding its applicability in primary care settings in elderly Chinese people. It will be necessary to revise the contents of the questionnaire to account for by local characteristics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Scene perception and memory revealed by eye movements and receiver-operating characteristic analyses: does a cultural difference truly exist?

PubMed

Evans, Kris; Rotello, Caren M; Li, Xingshan; Rayner, Keith

2009-02-01

Cultural differences have been observed in scene perception and memory: Chinese participants purportedly attend to the background information more than did American participants. We investigated the influence of culture by recording eye movements during scene perception and while participants made recognition memory judgements. Real-world pictures with a focal object on a background were shown to both American and Chinese participants while their eye movements were recorded. Later, memory for the focal object in each scene was tested, and the relationship between the focal object (studied, new) and the background context (studied, new) was manipulated. Receiver-operating characteristic (ROC) curves show that both sensitivity and response bias were changed when objects were tested in new contexts. However, neither the decrease in accuracy nor the response bias shift differed with culture. The eye movement patterns were also similar across cultural groups. Both groups made longer and more fixations on the focal objects than on the contexts. The similarity of eye movement patterns and recognition memory behaviour suggests that both Americans and Chinese use the same strategies in scene perception and memory.

SVM classification of microaneurysms with imbalanced dataset based on borderline-SMOTE and data cleaning techniques

NASA Astrophysics Data System (ADS)

Wang, Qingjie; Xin, Jingmin; Wu, Jiayi; Zheng, Nanning

2017-03-01

Microaneurysms are the earliest clinic signs of diabetic retinopathy, and many algorithms were developed for the automatic classification of these specific pathology. However, the imbalanced class distribution of dataset usually causes the classification accuracy of true microaneurysms be low. Therefore, by combining the borderline synthetic minority over-sampling technique (BSMOTE) with the data cleaning techniques such as Tomek links and Wilson's edited nearest neighbor rule (ENN) to resample the imbalanced dataset, we propose two new support vector machine (SVM) classification algorithms for the microaneurysms. The proposed BSMOTE-Tomek and BSMOTE-ENN algorithms consist of: 1) the adaptive synthesis of the minority samples in the neighborhood of the borderline, and 2) the remove of redundant training samples for improving the efficiency of data utilization. Moreover, the modified SVM classifier with probabilistic outputs is used to divide the microaneurysm candidates into two groups: true microaneurysms and false microaneurysms. The experiments with a public microaneurysms database shows that the proposed algorithms have better classification performance including the receiver operating characteristic (ROC) curve and the free-response receiver operating characteristic (FROC) curve.

Characteristics of time-activity curves obtained from dynamic 11C-methionine PET in common primary brain tumors.

PubMed

Nomura, Yuichi; Asano, Yoshitaka; Shinoda, Jun; Yano, Hirohito; Ikegame, Yuka; Kawasaki, Tomohiro; Nakayama, Noriyuki; Maruyama, Takashi; Muragaki, Yoshihiro; Iwama, Toru

2018-07-01

The aim of this study was to assess whether dynamic PET with 11 C-methionine (MET) (MET-PET) is useful in the diagnosis of brain tumors. One hundred sixty patients with brain tumors (139 gliomas, 9 meningiomas, 4 hemangioblastomas and 8 primary central nervous system lymphomas [PCNSL]) underwent dynamic MET-PET with a 3-dimensional acquisition mode, and the maximum tumor MET-standardized uptake value (MET-SUV) was measured consecutively to construct a time-activity curve (TAC). Furthermore, receiver operating characteristic (ROC) curves were generated from the time-to-peak (TTP) and the slope of the curve in the late phase (SLOPE). The TAC patterns of MET-SUVs (MET-TACs) could be divided into four characteristic types when MET dynamics were analyzed by dividing the MET-TAC into three phases. MET-SUVs were significantly higher in early and late phases in glioblastoma compared to anaplastic astrocytoma, diffuse astrocytoma and the normal frontal cortex (P < 0.05). The SLOPE in the late phase was significantly lower in tumors that included an oligodendroglial component compared to astrocytic tumors (P < 0.001). When we set the cutoff of the SLOPE in the late phase to - 0.04 h -1 for the differentiation of tumors that included an oligodendroglial component from astrocytic tumors, the diagnostic accuracy was 74.2% sensitivity and 64.9% specificity. The area under the ROC curve was 0.731. The results of this study show that quantification of the MET-TAC for each brain tumor identified by a dynamic MET-PET study could be helpful in the non-invasive discrimination of brain tumor subtypes, in particular gliomas.

Whole-Body Barometric Plethysmography Characterizes Upper Airway Obstruction in 3 Brachycephalic Breeds of Dogs.

PubMed

Liu, N-C; Adams, V J; Kalmar, L; Ladlow, J F; Sargan, D R

2016-05-01

A novel test using whole-body barometric plethysmography (WBBP) was developed recently to diagnose brachycephalic obstructive airway syndrome (BOAS) in unsedated French bulldogs. The hypotheses of this study were: (1) respiratory characteristics are different between healthy nonbrachycephalic dogs and brachycephalic dogs; and among pugs, French bulldogs, and bulldogs; and (2) obesity and stenotic nares are risk factors for BOAS. The main objective was to establish a diagnostic test for BOAS in these 3 breeds. A total of 266 brachycephalic dogs (100 pugs, 100 French bulldogs, and 66 bulldogs) and 28 nonbrachycephalic dogs. Prospective study. Exercise tolerance tests with respiratory functional grading, and WBBP were performed on all dogs. Data from WBBP were associated with functional grades to train quadratic discriminant analysis tools to assign dogs to BOAS+ and BOAS- groups. A BOAS index (0-100%) was calculated for each dog. Receiver operating characteristic (ROC) curves were used to evaluate classification ability. Minute volume was decreased significantly in asymptomatic pugs (P = .009), French bulldogs (P = .026), and bulldogs (P < .0001) when compared to nonbrachycephalic controls. Respiratory characteristics were different among breeds and affected dogs had a significant increase in trace variation. The BOAS index predicted BOAS status for each breed with 94-97% (95% confidence interval [CI], 88.9-100%) accuracy (area under the ROC curve). Both obesity (P = .04) and stenotic nares (P = .004) were significantly associated with BOAS. The WBBP can be used as a clinical tool to diagnose BOAS noninvasively and objectively. Copyright © 2016 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

A comparison of five surveys that identify individuals at risk for airflow obstruction and chronic obstructive pulmonary disease.

PubMed

Sogbetun, Folarin; Eschenbacher, William L; Welge, Jeffrey A; Panos, Ralph J

2016-11-01

The predictive characteristics of different screening surveys for the recognition of individuals at risk for airflow obstruction (AFO) have not been evaluated simultaneously in the same population. To compare five AFO/COPD screening questionnaires. 383 individuals completed the Veterans Airflow Obstruction Screening Questionnaire, Personal Level Screener for COPD (VAFOSQ), the 11-Q COPD Screening Questionnaire (11-Q), the COPD Population Screener (COPD-PS) and the Lung Function Questionnaire (LFQ) and performed spirometry. AFO was defined as forced expiratory volume in one second divided by the forced vital capacity (FEV 1 /FVC) < 0.7, fixed ratio (FR) or FEV 1 /FVC < lower limit of normal (LLN). The predictive characteristics of the five questionnaires were calculated and non-parametric receiver operating characteristic (ROC) curves estimated by logistic regression. 376 participants completed at least two of the questionnaires and performed technically acceptable spirometry. AFO was present in 102 (27.1%) and 150 (39.9%) based on LLN and FR, respectively. The number of individuals positively selected by the VAFOSQ was 227, PLS 128, 11-Q 236, COPD-PS 217, and LFQ 328. The area under the ROC curves for the questionnaires was between 0.60 and 0.66 (LLN) and 0.58 and 0.66 (FR). Although these screening surveys have acceptable and similar predictive ability for the identification of AFO, their published thresholds lead to substantially different classification rates. The choice of an appropriate threshold for the identification of individuals with possible AFO/COPD should consider the underlying prevalence of AFO/COPD in the target population and the relative costs of misclassifying affected and unaffected cases. None. Veterans Health Administration. Published by Elsevier Ltd.

A Korean multicenter study of prenatal risk factors for overt diabetes during the postpartum period after gestational diabetes mellitus.

PubMed

Shin, Na-Ri; Yoon, So-Yeon; Cho, Geum Joon; Choi, Suk-Joo; Kwon, Han-Sung; Hong, Soon Cheol; Kwon, Ja-Young; Oh, Soo-Young

2016-03-01

To identify prenatal risk factors for postpartum diabetes among pregnant women with gestational diabetes mellitus (GDM). In a retrospective study, baseline characteristics and data from a postpartum 75-g glucose tolerance test (GTT) were reviewed for patients with GDM who had delivered in four Korean tertiary institutions from 2006 to 2012. Clinical characteristics were compared between women with and those without postpartum diabetes. Cutoffs to predict postpartum diabetes and diagnostic values were calculated from receiver operating characteristic (ROC) curves. Of 1637 patients with GDM, 498 (30.4%) underwent a postpartum 75-g GTT. Postpartum diabetes was diagnosed in 40 (8.0%) patients and impaired glucose intolerance in 157 (31.5%). Women with postpartum diabetes had higher glycated hemoglobin (HbA1c) levels at GDM diagnosis (P=0.008) and higher 100-g GTT values (P<0.05 for all). In ROC curve analysis, optimal cutoffs for predicting postpartum diabetes were 0.058 for HbA1c level and 5.3 mmol/L (fasting), 10.9 mmol/L (1h), 10.2 mmol/L (2h), and 8.6 mmol/L (3h) for 100-g GTT. The highest sensitivity was observed for 3-h 100-g GTT (76.9%) and the highest positive predictive value was for HbA1c at diagnosis (15.2%). HbA1c level at GDM diagnosis and 100-g GTT values could be used to identify patients at high risk of postpartum diabetes who should undergo postpartum screening. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

The performance characteristics of prostate-specific antigen and prostate-specific antigen density in Chinese men.

PubMed

Teoh, Jeremy Yc; Yuen, Steffi Kk; Tsu, James Hl; Wong, Charles Kw; Ho, Brian Sh; Ng, Ada Tl; Ma, Wai-Kit; Ho, Kwan-Lun; Yiu, Ming-Kwong

2017-01-01

We investigated the performance characteristics of prostate-specific antigen (PSA) and PSA density (PSAD) in Chinese men. All Chinese men who underwent transrectal ultrasound-guided prostate biopsy (TRUS-PB) from year 2000 to 2013 were included. The receiver operating characteristic (ROC) curves for both PSA and PSAD were analyzed. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at different cut-off levels were calculated. A total of 2606 Chinese men were included. For the ROC, the area under curve was 0.770 for PSA (P < 0.001) and 0.823 for PSAD (P < 0.001). PSA of 4.5 ng ml-1 had sensitivity of 94.4%, specificity of 14.1%, PPV of 29.5%, and NPV of 86.9%; PSAD of 0.12 ng ml-1 cc-1 had sensitivity of 94.5%, specificity of 26.6%, PPV of 32.8%, and NPV of 92.7%. On multivariate logistic regression analyses, PSA cut-off at 4.5 ng ml-1 (OR 1.61, 95% CI 1.05-2.45, P= 0.029) and PSAD cut-off at 0.12 ng ml-1 cc-1 (OR 6.22, 95% CI 4.20-9.22, P< 0.001) were significant predictors for prostate cancer detection on TRUS-PB. In conclusion, the performances of PSA and PSAD at different cut-off levels in Chinese men were very different from those in Caucasians. PSA of 4.5 ng ml-1 and PSAD of 0.12 ng ml-1 cc-1 had near 95% sensitivity and were significant predictors of prostate cancer detection in Chinese men.

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

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.

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

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

Sahiner, B.; Chan, H.P.; Petrick, N.

1996-10-01

The authors investigated the classification of regions of interest (ROI`s) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI`s using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequentlymore » used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI`s containing biopsy-proven masses and 504 ROI`s containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms.« less

[Role of serum 25-hydroxyvitamin D in the diagnosis of vitamin D deficiency rickets].

PubMed

Wang, Xiao-Yan; Jin, Chun-Hua; Wu, Jian-Xin; Liu, Zhuo; Li, Mei; Li, Na

2012-10-01

To study the role of serum 25-hydroxyvitamin D in the early diagnosis of vitamin D deficiency rickets. Concentrations of serum 25(OH)D, calcium, phosphorus and alkaline phosphatase were measured in normal control (n=73), suspected rickets (n=45) and confirmed rickets groups (n=65). Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of serum 25(OH)D for rickets. Serum 25(OH)D levels in the suspected and confirmed rickets groups were 83±30 and 72±31 nmol/L respectively, which was lower than in the normal control group (112±37 nmol/L) (P<0.01). There was no significant difference between the suspected and confirmed rickets groups (P>0.05). Vitamin D deficiency rates in the suspected and confirmed rickets groups were higher than in the control group (P<0.01). The ROC curve area of serum 25(OH)D for the diagnosis of rickets was 0.760 (95%CI 0.692-0.820, P<0.01), and the optimal operating point was 90.70 nmol/L (sensitivity 68.49%, specificity 72.73%). There was no significant difference in levels of calcium, phosphorus and alkaline phosphatase between the three groups (P>0.05). Serum 25(OH)D levels in infants with suspected and confirmed rickets are significantly reduced and this may reflect vitamin D deficiency . Therefore, it may be useful to check serum 25(OH)D levels in screening for rickets.

Diffuse reflectance spectroscopy from 400-1600 nm to evaluate tumor resection margins during head and neck surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Brouwer de Koning, Susan G.; Baltussen, E. J. M.; Karakullukcu, M. Baris; Smit, L.; van Veen, R. L. P.; Hendriks, Benno H. W.; Sterenborg, H. J. C. M.; Ruers, Theo J. M.

2017-02-01

This ex vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy oral tissue, with the aim to develop a technique that can be used to determine a complete excision of tumor through intraoperative margin assessment. DRS spectra were acquired on fresh surgical specimens from patients with an oral squamous cell carcinoma. The spectra represent a measure of diffuse light reflectance (wavelength range of 400-1600 nm), detected after illuminating tissue with a source fiber at 1.0 and 2.0 mm distances from a detection fiber. Spectra were obtained from 23 locations of tumor tissue and 16 locations of healthy muscle tissue. Biopsies were taken from all measured locations to facilitate an optimal correlation between spectra and pathological information. The area under the spectrum was used as a parameter to classify spectra of tumor and healthy tissue. Next, a receiver operating characteristics (ROC) analysis was performed to provide the area under the receiver operating curve (AUROC) as a measure for discriminative power. The area under the spectrum between 650 and 750 nm was used in the ROC analysis and provided AUROC values of 0.99 and 0.97, for distances of 1 mm and 2 mm between source and detector fiber, respectively. DRS can discriminate tumor from healthy oral tissue in an ex vivo setting. More specimens are needed to further evaluate this technique with component analyses and classification methods, prior to in vivo patient measurements.

Optimizing the interpretation of CT for appendicitis: modeling health utilities for clinical practice.

PubMed

Blackmore, C Craig; Terasawa, Teruhiko

2006-02-01

Error in radiology can be reduced by standardizing the interpretation of imaging studies to the optimum sensitivity and specificity. In this report, the authors demonstrate how the optimal interpretation of appendiceal computed tomography (CT) can be determined and how it varies in different clinical scenarios. Utility analysis and receiver operating characteristic (ROC) curve modeling were used to determine the trade-off between false-positive and false-negative test results to determine the optimal operating point on the ROC curve for the interpretation of appendicitis CT. Modeling was based on a previous meta-analysis for the accuracy of CT and on literature estimates of the utilities of various health states. The posttest probability of appendicitis was derived using Bayes's theorem. At a low prevalence of disease (screening), appendicitis CT should be interpreted at high specificity (97.7%), even at the expense of lower sensitivity (75%). Conversely, at a high probability of disease, high sensitivity (97.4%) is preferred (specificity 77.8%). When the clinical diagnosis of appendicitis is equivocal, CT interpretation should emphasize both sensitivity and specificity (sensitivity 92.3%, specificity 91.5%). Radiologists can potentially decrease medical error and improve patient health by varying the interpretation of appendiceal CT on the basis of the clinical probability of appendicitis. This report is an example of how utility analysis can be used to guide radiologists in the interpretation of imaging studies and provide guidance on appropriate targets for the standardization of interpretation.

Estimating mortality risk in preoperative patients using immunologic, nutritional, and acute-phase response variables.

PubMed Central

Christou, N V; Tellado-Rodriguez, J; Chartrand, L; Giannas, B; Kapadia, B; Meakins, J; Rode, H; Gordon, J

1989-01-01

We measured the delayed type hypersensitivity (DTH) skin test response, along with additional variables of host immunocompetence in 245 preoperative patients to determine which variables are associated with septic-related deaths following operation. Of the 14 deaths (5.7%), 12 were related to sepsis and in 2 sepsis was contributory. The DTH response (p less than 0.00001), age (p less than 0.0002), serum albumin (p less than 0.003), hemoglobin (p less than 0.02), and total hemolytic complement (p less than 0.03), were significantly different between those who died and those who lived. By logistic regression analysis, only the DTH skin test response (log likelihood = 41.7, improvement X2 = 6.24, p less than 0.012) and the serum albumin (log likelihood = 44.8, improvement X2 = 17.7, p less than 0.001) were significantly and independently associated with the deaths. The resultant probability of mortality calculation equation was tested in a separate validation group of 519 patients (mortality = 5%) and yielded a good predictive capability as assessed by (1) X2 = 0.08 between observed and expected deaths, NS; (2) Goodman-Kruskall G statistic = 0.673) Receiver-Operating-Characteristic (ROC) curve analysis with an area under the ROC curve, Az = 0.79 +/- 0.05. We conclude that a reduced immune response (DTH skin test anergy) plus a nutritional deficit and/or acute-phase response change are both associated with increased septic-related deaths in elective surgical patients. PMID:2472781

Development and Testing of a Single Frequency Terahertz Imaging System for Breast Cancer Detection

PubMed Central

St. Peter, Benjamin; Yngvesson, Sigfrid; Siqueira, Paul; Kelly, Patrick; Khan, Ashraf; Glick, Stephen; Karellas, Andrew

2013-01-01

The ability to discern malignant from benign tissue in excised human breast specimens in Breast Conservation Surgery (BCS) was evaluated using single frequency terahertz radiation. Terahertz (THz) images of the specimens in reflection mode were obtained by employing a gas laser source and mechanical scanning. The images were correlated with optical histological micrographs of the same specimens, and a mean discrimination of 73% was found for five out of six samples using Receiver Operating Characteristic (ROC) analysis. The system design and characterization is discussed in detail. The initial results are encouraging but further development of the technology and clinical evaluation is needed to evaluate its feasibility in the clinical environment. PMID:25055306

Performance comparison of phenomenology-based features to generic features for false alarm reduction in UWB SAR imagery

NASA Astrophysics Data System (ADS)

Marble, Jay A.; Gorman, John D.

1999-08-01

A feature based approach is taken to reduce the occurrence of false alarms in foliage penetrating, ultra-wideband, synthetic aperture radar data. A set of 'generic' features is defined based on target size, shape, and pixel intensity. A second set of features is defined that contains generic features combined with features based on scattering phenomenology. Each set is combined using a quadratic polynomial discriminant (QPD), and performance is characterized by generating a receiver operating characteristic (ROC) curve. Results show that the feature set containing phenomenological features improves performance against both broadside and end-on targets. Performance against end-on targets, however, is especially pronounced.

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office. Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm, a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Bill Hrybyk Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office. Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. In this image, a gathering of Goddard employees watch the ribbon cutting. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm, a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Desiree Stover Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office. Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm, a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Chris Gunn Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office (SSCO). Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. Here, she receives an overview of a robotic console station used to practice satellite servicing activities. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm, a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Desiree Stover NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office. Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm (visible at top right), a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Bill Hrybyk Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2016-01-06

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office. Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm, a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... Credit: NASA/Goddard/Chris Gunn NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

Sen. Barbara Mikulski participated in a ribbon cutting at NASA’s Goddard Space Flight Center on January 6th, 2016, to officially open the new Robotic Operations Center (ROC) developed by the Satellite Servicing Capabilities Office (SSCO). Within the ROC's black walls, NASA is testing technologies and operational procedures for science and exploration missions, including the Restore-L satellite servicing mission and also the Asteroid Redirect Mission. During her tour of the ROC, Sen. Mikulski saw first-hand an early version of the NASA Servicing Arm (visible above, at right), a 2-meter-class robot with the dexterity to grasp and refuel a satellite on orbit. She also heard a description of Raven, a payload launching to the International Space Station that will demonstrate real-time, relative space navigation technology. The robotic technologies that NASA is developing within the ROC also support the Journey to Mars. Learn more about NASA’s satellite servicing technologies at ssco.gsfc.nasa.gov/. Image credit: NASA/Desiree Stover Read more: www.nasa.gov/feature/goddard/2016/maryland-sen-barbara-mi... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Accuracy of different diagnostic tests for early, delayed and late prosthetic joint infection.

PubMed

Fernández-Sampedro, M; Fariñas-Alvarez, C; Garces-Zarzalejo, C; Alonso-Aguirre, M A; Salas-Venero, C; Martínez-Martínez, L; Fariñas, M C

2017-08-25

A combination of laboratory, histopathological and microbiological tests for diagnosis of prosthetic joint infection (PJI) have been strongly recommended. This study aims to characterize the accuracy of individual or group tests, such as culture of sonicate fluid, synovial fluid and peri-implant tissue, C-reactive protein (CRP) and histopathology for detection of early, delayed and late PJI. A prospective study of patients undergoing hip or knee arthroplasty from February 2009 to February 2014 was performed in a Spanish tertiary health care hospital. The diagnostic accuracy of the different methods was evaluated constructing receiver-operating-characteristic (ROC) curve areas. One hundred thirty consecutive patients were included: 18 (13.8%) early PJI, 35 (27%) delayed PJI and 77 (59.2%) late PJI. For individual parameters, the area under the ROC curve for peri-implant tissue culture was larger for early (0.917) than for delayed (0.829) and late PJI (0.778), p = 0.033. There was a significantly larger difference for ROC area in the synovial fluid culture for delayed (0.803) than for early (0.781) and late infections (0.679), p = 0.039. The comparison of the areas under the ROC curves for the two microbiological tests showed that sonicate fluid was significantly different from peri-implant tissue in delayed (0.951 vs 0.829, p = 0.005) and late PJI (0.901 vs 0.778, p = 0.000). The conjunction of preoperative parameters, synovial fluid culture and CRP, improved the accuracy for late PJI (p = 0.01). The conjunction of histopathology and sonicate fluid culture increased the area under ROC curve of sonication in early (0.917 vs 1.000); p = 0.06 and late cases (0.901 vs 0.999); p < 0.001. For early PJI, sonicate fluid and peri-implant tissue cultures achieve the same best sensitivity. For delayed and late PJI, sonicate fluid culture is the most sensitive individual diagnostic method. By combining histopathology and peri-implant tissue, all early, 97% of delayed and 94.8% of late cases are diagnosed. The conjunction of histopathology and sonicate fluid culture yields a sensitivity of 100% for all types of infection.

[Identification of green tea brand based on hyperspectra imaging technology].

PubMed

Zhang, Hai-Liang; Liu, Xiao-Li; Zhu, Feng-Le; He, Yong

2014-05-01

Hyperspectral imaging technology was developed to identify different brand famous green tea based on PCA information and image information fusion. First 512 spectral images of six brands of famous green tea in the 380 approximately 1 023 nm wavelength range were collected and principal component analysis (PCA) was performed with the goal of selecting two characteristic bands (545 and 611 nm) that could potentially be used for classification system. Then, 12 gray level co-occurrence matrix (GLCM) features (i. e., mean, covariance, homogeneity, energy, contrast, correlation, entropy, inverse gap, contrast, difference from the second-order and autocorrelation) based on the statistical moment were extracted from each characteristic band image. Finally, integration of the 12 texture features and three PCA spectral characteristics for each green tea sample were extracted as the input of LS-SVM. Experimental results showed that discriminating rate was 100% in the prediction set. The receiver operating characteristic curve (ROC) assessment methods were used to evaluate the LS-SVM classification algorithm. Overall results sufficiently demonstrate that hyperspectral imaging technology can be used to perform classification of green tea.

Meta-analysis of oral water-soluble contrast agent in the management of adhesive small bowel obstruction.

PubMed

Abbas, S M; Bissett, I P; Parry, B R

2007-04-01

Adhesions are the leading cause of small bowel obstruction. Identification of patients who require surgery is difficult. This review analyses the role of Gastrografin as a diagnostic and therapeutic agent in the management of adhesive small bowel obstruction. A systematic search of Medline, Embase and Cochrane databases was performed to identify studies of the use of Gastrografin in adhesive small bowel obstruction. Studies that addressed the diagnostic role of water-soluble contrast agent were appraised, and data presented as sensitivity, specificity, and positive and negative likelihood ratios. Results were pooled and a summary receiver-operator characteristic (ROC) curve was constructed. A meta-analysis of the data from six therapeutic studies was performed using the Mantel-Haenszel test and both fixed- and random-effect models. The appearance of water-soluble contrast agent in the colon on an abdominal radiograph within 24 h of its administration predicted resolution of obstruction with a pooled sensitivity of 97 per cent and specificity of 96 per cent. The area under the summary ROC curve was 0.98. Water-soluble contrast agent did not reduce the need for surgical intervention (odds ratio 0.81, P = 0.300), but it did reduce the length of hospital stay for patients who did not require surgery compared with placebo (weighted mean difference--1.84 days; P < 0.001). Published data strongly support the use of water-soluble contrast medium as a predictive test for non-operative resolution of adhesive small bowel obstruction. Although Gastrografin does not reduce the need for operation, it appears to shorten the hospital stay for those who do not require surgery.

A Study on the Deriving Requirements of ARGO Operation System

NASA Astrophysics Data System (ADS)

Seo, Yoon-Kyung; Rew, Dong-Young; Lim, Hyung-Chul; Park, In-Kwan; Yim, Hong-Suh; Jo, Jung Hyun; Park, Jong-Uk

2009-12-01

Korea Astronomy and Space Science Institute (KASI) has been developing one mobile and one stationary SLR system since 2008 named as ARGO-M and ARGO-F, respectively. KASI finished the step of deriving the system requirements of ARGO. The requirements include definitions and scopes of various software and hardware components which are necessary for developing the ARGO-M operation system. And the requirements define function, performance, and interface requirements. The operation system consisting of ARGO-M site, ARGO-F site, and Remote Operation Center (ROC) inside KASI is designed for remote access and the automatic tracking and control system which are the main operation concept of ARGO system. To accomplish remote operation, we are considering remote access to ARGO-F and ARGO-M from ROC. The mobile-phone service allows us to access the ARGO-F remotely and to control the system in an emergency. To implement fully automatic tracking and control function in ARGO-F, we have investigated and described the requirements about the automatic aircraft detection system and the various meteorological sensors. This paper addresses the requirements of ARGO Operation System.

A statistical model for water quality predictions from a river discharge using coastal observations

NASA Astrophysics Data System (ADS)

Kim, S.; Terrill, E. J.

2007-12-01

Understanding and predicting coastal ocean water quality has benefits for reducing human health risks, protecting the environment, and improving local economies which depend on clean beaches. Continuous observations of coastal physical oceanography increase the understanding of the processes which control the fate and transport of a riverine plume which potentially contains high levels of contaminants from the upstream watershed. A data-driven model of the fate and transport of river plume water from the Tijuana River has been developed using surface current observations provided by a network of HF radar operated as part of a local coastal observatory that has been in place since 2002. The model outputs are compared with water quality sampling of shoreline indicator bacteria, and the skill of an alarm for low water quality is evaluated using the receiver operating characteristic (ROC) curve. In addition, statistical analysis of beach closures in comparison with environmental variables is also discussed.

Efficient generation of receiver operating characteristics for the evaluation of damage detection in practical structural health monitoring applications.

PubMed

Liu, Chang; Dobson, Jacob; Cawley, Peter

2017-03-01

Permanently installed guided wave monitoring systems are attractive for monitoring large structures. By frequently interrogating the test structure over a long period of time, such systems have the potential to detect defects much earlier than with conventional one-off inspection, and reduce the time and labour cost involved. However, for the systems to be accepted under real operational conditions, their damage detection performance needs to be evaluated in these practical settings. The receiver operating characteristic (ROC) is an established performance metric for one-off inspections, but the generation of the ROC requires many test structures with realistic damage growth at different locations and different environmental conditions, and this is often impractical. In this paper, we propose an evaluation framework using experimental data collected over multiple environmental cycles on an undamaged structure with synthetic damage signatures added by superposition. Recent advances in computation power enable examples covering a wide range of practical scenarios to be generated, and for multiple cases of each scenario to be tested so that the statistics of the performance can be evaluated. The proposed methodology has been demonstrated using data collected from a laboratory pipe specimen over many temperature cycles, superposed with damage signatures predicted for a flat-bottom hole growing at different rates at various locations. Three damage detection schemes, conventional baseline subtraction, singular value decomposition (SVD) and independent component analysis (ICA), have been evaluated. It has been shown that in all cases, the component methods perform significantly better than the residual method, with ICA generally the better of the two. The results have been validated using experimental data monitoring a pipe in which a flat-bottom hole was drilled and enlarged over successive temperature cycles. The methodology can be used to evaluate the performance of an installed monitoring system and to show whether it is capable of detecting particular damage growth at any given location. It will enable monitoring results to be evaluated rigorously and will be valuable in the development of safety cases.

Efficient generation of receiver operating characteristics for the evaluation of damage detection in practical structural health monitoring applications

PubMed Central

Dobson, Jacob; Cawley, Peter

2017-01-01

Permanently installed guided wave monitoring systems are attractive for monitoring large structures. By frequently interrogating the test structure over a long period of time, such systems have the potential to detect defects much earlier than with conventional one-off inspection, and reduce the time and labour cost involved. However, for the systems to be accepted under real operational conditions, their damage detection performance needs to be evaluated in these practical settings. The receiver operating characteristic (ROC) is an established performance metric for one-off inspections, but the generation of the ROC requires many test structures with realistic damage growth at different locations and different environmental conditions, and this is often impractical. In this paper, we propose an evaluation framework using experimental data collected over multiple environmental cycles on an undamaged structure with synthetic damage signatures added by superposition. Recent advances in computation power enable examples covering a wide range of practical scenarios to be generated, and for multiple cases of each scenario to be tested so that the statistics of the performance can be evaluated. The proposed methodology has been demonstrated using data collected from a laboratory pipe specimen over many temperature cycles, superposed with damage signatures predicted for a flat-bottom hole growing at different rates at various locations. Three damage detection schemes, conventional baseline subtraction, singular value decomposition (SVD) and independent component analysis (ICA), have been evaluated. It has been shown that in all cases, the component methods perform significantly better than the residual method, with ICA generally the better of the two. The results have been validated using experimental data monitoring a pipe in which a flat-bottom hole was drilled and enlarged over successive temperature cycles. The methodology can be used to evaluate the performance of an installed monitoring system and to show whether it is capable of detecting particular damage growth at any given location. It will enable monitoring results to be evaluated rigorously and will be valuable in the development of safety cases. PMID:28413339

Prognostic subgroups for remission and response in the Coordinated Anxiety Learning and Management (CALM) trial.

PubMed

Kelly, J MacLaren; Jakubovski, Ewgeni; Bloch, Michael H

2015-03-01

Most patients with anxiety disorders receive treatment in primary care settings. Limited moderator data are available to inform clinicians of likely prognostic outcomes for individual patients. We identify baseline characteristics associated with outcome in adults seeking treatment for anxiety disorders. We conducted an exploratory moderator analysis from the Coordinated Anxiety Learning and Management (CALM) trial. In the CALM trial, 1,004 adults who met DSM-IV criteria for generalized anxiety disorder (GAD), panic disorder, social anxiety disorder, and/or posttraumatic stress disorder (PTSD) were randomized to usual care (UC) or a collaborative care intervention (ITV) of cognitive-behavioral therapy and/or pharmacotherapy between June 2006 and April 2008. Logistic regression was used to examine baseline characteristics associated with remission and response overall and by treatment condition. Receiver operating curve (ROC) analyses identified subgroups associated with similar likelihood of response and remission of global anxiety symptoms. Remission was defined as score < 6 on the 12-item Brief Symptom Inventory (BSI-12) anxiety and somatization subscales. Response was defined as at least 50% reduction on BSI-12, or meeting remission criteria. Randomization to ITV over UC was often the strongest predictor of outcome. Several baseline patient characteristics were associated with poor treatment outcome including comorbid depression, increased severity of underlying anxiety disorder(s) (P < .001), low socioeconomic status (perceived [P < .001] and actual [P < .05]), and limited social support (P < .001). Patient characteristics associated with particular benefit from ITV were being female (P < .05), increased depression (P < .01)/GAD severity (P < .05), and low socioeconomic status (P < .05). ROC analysis demonstrated prognostic subgroups with large differences in response likelihood. Further research should focus on the effectiveness of implementing the ITV intervention of CALM in community treatment centers where patients typically are of low socioeconomic status and may particularly benefit from ITV. ClinicalTrials.gov identifier: NCT00347269. © Copyright 2015 Physicians Postgraduate Press, Inc.

SU-F-R-22: Malignancy Classification for Small Pulmonary Nodules with Radiomics and Logistic Regression

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

Huang, W; Tu, S

Purpose: We conducted a retrospective study of Radiomics research for classifying malignancy of small pulmonary nodules. A machine learning algorithm of logistic regression and open research platform of Radiomics, IBEX (Imaging Biomarker Explorer), were used to evaluate the classification accuracy. Methods: The training set included 100 CT image series from cancer patients with small pulmonary nodules where the average diameter is 1.10 cm. These patients registered at Chang Gung Memorial Hospital and received a CT-guided operation of lung cancer lobectomy. The specimens were classified by experienced pathologists with a B (benign) or M (malignant). CT images with slice thickness ofmore » 0.625 mm were acquired from a GE BrightSpeed 16 scanner. The study was formally approved by our institutional internal review board. Nodules were delineated and 374 feature parameters were extracted from IBEX. We first used the t-test and p-value criteria to study which feature can differentiate between group B and M. Then we implemented a logistic regression algorithm to perform nodule malignancy classification. 10-fold cross-validation and the receiver operating characteristic curve (ROC) were used to evaluate the classification accuracy. Finally hierarchical clustering analysis, Spearman rank correlation coefficient, and clustering heat map were used to further study correlation characteristics among different features. Results: 238 features were found differentiable between group B and M based on whether their statistical p-values were less than 0.05. A forward search algorithm was used to select an optimal combination of features for the best classification and 9 features were identified. Our study found the best accuracy of classifying malignancy was 0.79±0.01 with the 10-fold cross-validation. The area under the ROC curve was 0.81±0.02. Conclusion: Benign nodules may be treated as a malignant tumor in low-dose CT and patients may undergo unnecessary surgeries or treatments. Our study may help radiologists to differentiate nodule malignancy for low-dose CT.« less

A Novel Data-Driven Approach to Preoperative Mapping of Functional Cortex Using Resting-State Functional Magnetic Resonance Imaging

PubMed Central

Mitchell, Timothy J.; Hacker, Carl D.; Breshears, Jonathan D.; Szrama, Nick P.; Sharma, Mohit; Bundy, David T.; Pahwa, Mrinal; Corbetta, Maurizio; Snyder, Abraham Z.; Shimony, Joshua S.

2013-01-01

BACKGROUND: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping. OBJECTIVE: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks. METHODS: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy. RESULTS: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively. CONCLUSION: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions. ABBREVIATIONS: AUC, area under the curve BA, Brodmann area BOLD, blood oxygen level dependent ECS, electrocortical stimulation fMRI, functional magnetic resonance imaging ICA, independent component analysis MLP, multilayer perceptron MP-RAGE, magnetization-prepared rapid gradient echo ROC, receiver-operating characteristic rs-fMRI, resting-state functional magnetic resonance imaging RSN, resting-state network PMID:24264234

Exploratory metabolomics of biomarker identification for the internet gaming disorder in young Korean males.

PubMed

Cho, Yeo Ul; Lee, Deokjong; Lee, Jung-Eun; Kim, Kyoung Heon; Lee, Do Yup; Jung, Young-Chul

2017-07-01

The main aim of the current research is to characterize the molecular dynamics related to internet gaming disorder (IGD) using non-targeted plasma metabolite profiling based on gas-chromatography time-of-flight mass spectrometry (GC-TOF MS). IGD is a psychiatric disorder instigated by excessive and prolonged internet gaming, which shared many pathological symptoms with attention deficit hyperactivity disorder (ADHD). The prevalence of the disorder has been rapidly increased particularly in East Asia countries (5.9% in South Korea) compared to Europe or North America (0.3-1.0% in United States and 1.16% in Germany). Thus we comparably explored the correlation between plasma metabolites and internet addiction severity in IGD patients, and potential biomarker composite in combination with clinical parameters. The systematic metabolite profiling of 54 blood samples (normal user, N=28 and IGD, N=24) identified a total of 104 metabolites out of 1212 metabolic feature, and revealed unique relation of co-linearly regressed set of plasma metabolites (arabitol, myo-inositol, methionine, pyrrole-2-carboxylic acid, and aspartic acid) with internet addiction severity scale (R=0.795). In addition, orthogonal partial least squared discriminant analysis (OPLS-DA) and receiver operating characteristic (ROC) analysis identified the potential biomarker cluster that simultaneously discriminated the different types of the psychiatric status. The potential biomarker re-composite was comprehensively evaluated by a receiver operating characteristic (ROC) analysis where the AUCs were 0.890, 0.880, 1.000, and 0.935 for control, IGD, AD and IGD+AD, respectively (N=18, 19, 5, and 10) against the others. This exploratory method may provide robustness of predictive diagnosis in population screening of IGD. The identified metabolic features, the relatedness with clinical parameters, and the putative biochemical linkage will hopefully aid future pathological studies in IGD. Copyright © 2017. Published by Elsevier B.V.

Superoxide dismutase: a predicting factor for boar semen characteristics for short-term preservation.

PubMed

Zakošek Pipan, Maja; Mrkun, Janko; Kosec, Marjan; Nemec Svete, Alenka; Zrimšek, Petra

2014-01-01

Superoxide dismutase (SOD), total antioxidant capacity (TAC), and thiobarbituric acid reactive substances (TBARS) in seminal plasma were evaluated on the basis of receiver operating characteristics (ROC) analysis as predictors for distinguishing satisfactory from unsatisfactory boar semen samples after storage. SOD on day 0 correlated significantly with progressive motility (r=-0.686; P<0.05) and viability (r=-0.513; P<0.05) after storage; TBARS correlated only with motility (r=-0.480; P<0.05). Semen samples that, after 3 days of storage, fulfilled all criteria for semen characteristics (viability>85%, motility>70%, progressive motility>25%, and normal morphology>50%) had significantly lower SOD levels on the day 0 than those with at least one criterion not fulfilled (P<0.05) following storage. SOD levels of less than 1.05 U/mL predicted with 87.5% accuracy that fresh semen will suit the requirements for satisfactory semen characteristics after storage, while semen with SOD levels higher than 1.05 U/mL will not fulfill with 100% accuracy at least one semen characteristic after storage. These results support the proposal that SOD in fresh boar semen can be used as a predictor of semen quality after storage.

A method for identifying color vision deficiency malingering.

PubMed

Pouw, Andrew; Karanjia, Rustum; Sadun, Alfredo

2017-03-01

To propose a new test to identify color vision deficiency malingering. An online survey was distributed to 130 truly color vision deficient participants and 160 participants willing to simulate color vision deficiency. The survey contained three sets of six color-adjusted versions of the standard Ishihara color plates each, as well as one set of six control plates. The plates that best discriminated both participant groups were selected for a "balanced" test emphasizing both sensitivity and specificity. A "specific" test that prioritized high specificity was also created by selecting from these plates. Statistical measures of the test (sensitivity, specificity, and Youden index) were assessed at each possible cut-off threshold, and a receiver operating characteristic (ROC) function with its area under the curve (AUC) charted. The redshift plate set was identified as having the highest difference of means between groups (-58%, CI: -64 to -52%), as well as the widest gap between group modes. Statistical measures of the "balanced" test show an optimal cut-off of at least two incorrectly identified plates to suggest malingering (Youden index: 0.773, sensitivity: 83.3%, specificity: 94.0%, AUC of ROC 0.918). The "specific" test was able to identify color vision deficiency simulators with a specificity of 100% when using a cut-off of at least two incorrectly identified plates (Youden index 0.599, sensitivity 59.9%, specificity 100%, AUC of ROC 0.881). Our proposed test for identifying color vision deficiency malingering demonstrates a high degree of reliability with AUCs of 0.918 and 0.881 for the "balanced" and "specific" tests, respectively. A cut-off threshold of at least two missed plates on the "specific" test was able to identify color vision deficiency simulators with 100% specificity.

Clinical relevance of pulse pressure variations for predicting fluid responsiveness in mechanically ventilated intensive care unit patients: the grey zone approach.

PubMed

Biais, Matthieu; Ehrmann, Stephan; Mari, Arnaud; Conte, Benjamin; Mahjoub, Yazine; Desebbe, Olivier; Pottecher, Julien; Lakhal, Karim; Benzekri-Lefevre, Dalila; Molinari, Nicolas; Boulain, Thierry; Lefrant, Jean-Yves; Muller, Laurent

2014-11-04

Pulse pressure variation (PPV) has been shown to predict fluid responsiveness in ventilated intensive care unit (ICU) patients. The present study was aimed at assessing the diagnostic accuracy of PPV for prediction of fluid responsiveness by using the grey zone approach in a large population. The study pooled data of 556 patients from nine French ICUs. Hemodynamic (PPV, central venous pressure (CVP) and cardiac output) and ventilator variables were recorded. Responders were defined as patients increasing their stroke volume more than or equal to 15% after fluid challenge. The receiver operating characteristic (ROC) curve and grey zone were defined for PPV. The grey zone was evaluated according to the risk of fluid infusion in hypoxemic patients. Fluid challenge led to increased stroke volume more than or equal to 15% in 267 patients (48%). The areas under the ROC curve of PPV and CVP were 0.73 (95% confidence interval (CI): 0.68 to 0.77) and 0.64 (95% CI 0.59 to 0.70), respectively (P<0.001). A grey zone of 4 to 17% (62% of patients) was found for PPV. A tidal volume more than or equal to 8 ml.kg(-1) and a driving pressure (plateau pressure - PEEP) more than 20 cmH2O significantly improved the area under the ROC curve for PPV. When taking into account the risk of fluid infusion, the grey zone for PPV was 2 to 13%. In ventilated ICU patients, PPV values between 4 and 17%, encountered in 62% patients exhibiting validity prerequisites, did not predict fluid responsiveness.

ROC analysis of the accuracy of Noncycloplegic retinoscopy, Retinomax Autorefractor, and SureSight Vision Screener for preschool vision screening.

PubMed

Ying, Gui-shuang; Maguire, Maureen; Quinn, Graham; Kulp, Marjean Taylor; Cyert, Lynn

2011-12-28

To evaluate, by receiver operating characteristic (ROC) analysis, the accuracy of three instruments of refractive error in detecting eye conditions among 3- to 5-year-old Head Start preschoolers and to evaluate differences in accuracy between instruments and screeners and by age of the child. Children participating in the Vision In Preschoolers (VIP) Study (n = 4040), had screening tests administered by pediatric eye care providers (phase I) or by both nurse and lay screeners (phase II). Noncycloplegic retinoscopy (NCR), the Retinomax Autorefractor (Nikon, Tokyo, Japan), and the SureSight Vision Screener (SureSight, Alpharetta, GA) were used in phase I, and Retinomax and SureSight were used in phase II. Pediatric eye care providers performed a standardized eye examination to identify amblyopia, strabismus, significant refractive error, and reduced visual acuity. The accuracy of the screening tests was summarized by the area under the ROC curve (AUC) and compared between instruments and screeners and by age group. The three screening tests had a high AUC for all categories of screening personnel. The AUC for detecting any VIP-targeted condition was 0.83 for NCR, 0.83 (phase I) to 0.88 (phase II) for Retinomax, and 0.86 (phase I) to 0.87 (phase II) for SureSight. The AUC was 0.93 to 0.95 for detecting group 1 (most severe) conditions and did not differ between instruments or screeners or by age of the child. NCR, Retinomax, and SureSight had similar and high accuracy in detecting vision disorders in preschoolers across all types of screeners and age of child, consistent with previously reported results at specificity levels of 90% and 94%.

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.

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.

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.

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

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.

Frequency doubling technique perimetry and spectral domain optical coherence tomography in patients with early glaucoma.

PubMed

Horn, F K; Mardin, C Y; Bendschneider, D; Jünemann, A G; Adler, W; Tornow, R P

2011-01-01

To assess the combined diagnostic power of frequency-doubling technique (FDT)-perimetry and retinal nerve fibre layer (RNFL) thickness measurements with spectral domain optical coherence tomography (SDOCT). The study included 330 experienced participants in five age-related groups: 77 'preperimetric' open-angle glaucoma (OAG) patients, 52 'early' OAG, 50 'moderate' OAG, 54 ocular hypertensive patients, and 97 healthy subjects. For glaucoma assessment in all subjects conventional perimetry, evaluation of fundus photographs, FDT-perimetry and RNFL thickness measurement with SDOCT was done. Glaucomatous visual field defects were classified using the Glaucoma Staging System. FDT evaluation used a published method with casewise calculation of an 'FDT-score', including all missed localized probability levels. SDOCT evaluation used mean RNFL thickness and a new individual SDOCT-score considering normal confidence limits in 32 sectors of a peripapillary circular scan. To examine the joined value of both methods a combined score was introduced. Significance of the difference between Receiver-operating-characteristic (ROC) curves was calculated for a specificity of 96%. Sensitivity in the preperimetric glaucoma group was 44% for SDOCT-score, 25% for FDT-score, and 44% for combined score, in the early glaucoma group 83, 81, and 89%, respectively, and in the moderate glaucoma group 94, 94, and 98%, respectively, all at a specificity of 96%. ROC performance of the newly developed combined score is significantly above single ROC curves of FDT-score in preperimetric and early OAG and above RNFL thickness in moderate OAG. Combination of function and morphology by using the FDT-score and the SDOCT-score performs equal or even better than each single method alone.

Frequency doubling technique perimetry and spectral domain optical coherence tomography in patients with early glaucoma

PubMed Central

Horn, F K; Mardin, C Y; Bendschneider, D; Jünemann, A G; Adler, W; Tornow, R P

2011-01-01

Purpose To assess the combined diagnostic power of frequency-doubling technique (FDT)-perimetry and retinal nerve fibre layer (RNFL) thickness measurements with spectral domain optical coherence tomography (SDOCT). Methods The study included 330 experienced participants in five age-related groups: 77 ‘preperimetric' open-angle glaucoma (OAG) patients, 52 ‘early' OAG, 50 ‘moderate' OAG, 54 ocular hypertensivepatients, and 97 healthy subjects. For glaucoma assessment in all subjects conventional perimetry, evaluation of fundus photographs, FDT-perimetry and RNFL thickness measurement with SDOCT was done. Glaucomatous visual field defects were classified using the Glaucoma Staging System. FDT evaluation used a published method with casewise calculation of an ‘FDT-score', including all missed localized probability levels. SDOCT evaluation used mean RNFL thickness and a new individual SDOCT-score considering normal confidence limits in 32 sectors of a peripapillary circular scan. To examine the joined value of both methods a combined score was introduced. Significance of the difference between Receiver-operating-characteristic (ROC) curves was calculated for a specificity of 96%. Results Sensitivity in the preperimetric glaucoma group was 44% for SDOCT-score, 25% for FDT-score, and 44% for combined score, in the early glaucoma group 83, 81, and 89%, respectively, and in the moderate glaucoma group 94, 94, and 98%, respectively, all at a specificity of 96%. ROC performance of the newly developed combined score is significantly above single ROC curves of FDT-score in preperimetric and early OAG and above RNFL thickness in moderate OAG. Conclusion Combination of function and morphology by using the FDT-score and the SDOCT-score performs equal or even better than each single method alone. PMID:21102494

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.

Pulse oximeter oxygen saturation in prediction of arterial oxygen saturation in liver transplant candidates.

PubMed

Ghayumi, Seiyed Mohammad Ali; Khalafi-Nezhad, Abolfazl; Jowkar, Zahra

2014-04-01

Liver transplant is the only definitive treatment for many patients with end stage liver disease. Presence and severity of preoperative pulmonary disease directly affect the rate of postoperative complications of the liver transplantation. Arterial blood gas (ABG) measurement, performed in many transplant centers, is considered as a traditional method to diagnose hypoxemia. Because ABG measurement is invasive and painful, pulse oximetry, a bedside, noninvasive and inexpensive technique, has been recommended as an alternative source for the ABG measurement. The aim of this study was to evaluate the efficacy of pulse oximetry as a screening tool in hypoxemia detection in liver transplant candidates and to compare the results with ABGs. Three hundred and ninety transplant candidates (237 males and 153 females) participated in this study. Arterial blood gas oxyhemoglobin saturation (SaO2) was recorded and compared with pulse oximetry oxyhemoglobin saturation (SpO2) results for each participants. The area under the curve (AUC) of receiver operating characteristic (ROC) curves was calculated by means of nonparametric methods to evaluate the efficacy of pulse oximetry to detect hypoxemia. Roc-derived SpO2 threshold of ≤ 94% can predict hypoxemia (PaO2 < 60 mmHg) with a sensitivity of 100% and a specificity of 95%. Furthermore, there are associations between the ROC-derived SpO2 threshold of ≤ 97% and detection of hypoxemia (PaO2 < 70 mmHg) with a sensitivity of 100% and a specificity of 46%. The accuracy of pulse oximetry was not affected by the severity of liver disease in detection of hypoxemia. Provided that SpO2 is equal to or greater than 94%, attained from pulse oximetry can be used as a reliable and accurate substitute for the ABG measurements to evaluate hypoxemia in patients with end stage liver disease.

A completely automated CAD system for mass detection in a large mammographic database.

PubMed

Bellotti, R; De Carlo, F; Tangaro, S; Gargano, G; Maggipinto, G; Castellano, M; Massafra, R; Cascio, D; Fauci, F; Magro, R; Raso, G; Lauria, A; Forni, G; Bagnasco, S; Cerello, P; Zanon, E; Cheran, S C; Lopez Torres, E; Bottigli, U; Masala, G L; Oliva, P; Retico, A; Fantacci, M E; Cataldo, R; De Mitri, I; De Nunzio, G

2006-08-01

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

External validation and comparison of three pediatric clinical dehydration scales.

PubMed

Jauregui, Joshua; Nelson, Daniel; Choo, Esther; Stearns, Branden; Levine, Adam C; Liebmann, Otto; Shah, Sachita P

2014-01-01

To prospectively validate three popular clinical dehydration scales and overall physician gestalt in children with vomiting or diarrhea relative to the criterion standard of percent weight change with rehydration. We prospectively enrolled a non-consecutive cohort of children ≤ 18 years of age with an acute episode of diarrhea or vomiting. Patient weight, clinical scale variables and physician clinical impression, or gestalt, were recorded before and after fluid resuscitation in the emergency department and upon hospital discharge. The percent weight change from presentation to discharge was used to calculate the degree of dehydration, with a weight change of ≥ 5% considered significant dehydration. Receiver operating characteristics (ROC) curves were constructed for each of the three clinical scales and physician gestalt. Sensitivity and specificity were calculated based on the best cut-points of the ROC curve. We approached 209 patients, and of those, 148 were enrolled and 113 patients had complete data for analysis. Of these, 10.6% had significant dehydration based on our criterion standard. The Clinical Dehydration Scale (CDS) and Gorelick scales both had an area under the ROC curve (AUC) statistically different from the reference line with AUCs of 0.72 (95% CI 0.60, 0.84) and 0.71 (95% CI 0.57, 0.85) respectively. The World Health Organization (WHO) scale and physician gestalt had AUCs of 0.61 (95% CI 0.45, 0.77) and 0.61 (0.44, 0.78) respectively, which were not statistically significant. The Gorelick scale and Clinical Dehydration Scale were fair predictors of dehydration in children with diarrhea or vomiting. The World Health Organization scale and physician gestalt were not helpful predictors of dehydration in our cohort.

External Validation and Comparison of Three Pediatric Clinical Dehydration Scales

PubMed Central

Jauregui, Joshua; Nelson, Daniel; Choo, Esther; Stearns, Branden; Levine, Adam C.; Liebmann, Otto; Shah, Sachita P.

2014-01-01

Objective To prospectively validate three popular clinical dehydration scales and overall physician gestalt in children with vomiting or diarrhea relative to the criterion standard of percent weight change with rehydration. Methods We prospectively enrolled a non-consecutive cohort of children ≤ 18 years of age with an acute episode of diarrhea or vomiting. Patient weight, clinical scale variables and physician clinical impression, or gestalt, were recorded before and after fluid resuscitation in the emergency department and upon hospital discharge. The percent weight change from presentation to discharge was used to calculate the degree of dehydration, with a weight change of ≥ 5% considered significant dehydration. Receiver operating characteristics (ROC) curves were constructed for each of the three clinical scales and physician gestalt. Sensitivity and specificity were calculated based on the best cut-points of the ROC curve. Results We approached 209 patients, and of those, 148 were enrolled and 113 patients had complete data for analysis. Of these, 10.6% had significant dehydration based on our criterion standard. The Clinical Dehydration Scale (CDS) and Gorelick scales both had an area under the ROC curve (AUC) statistically different from the reference line with AUCs of 0.72 (95% CI 0.60, 0.84) and 0.71 (95% CI 0.57, 0.85) respectively. The World Health Organization (WHO) scale and physician gestalt had AUCs of 0.61 (95% CI 0.45, 0.77) and 0.61 (0.44, 0.78) respectively, which were not statistically significant. Conclusion The Gorelick scale and Clinical Dehydration Scale were fair predictors of dehydration in children with diarrhea or vomiting. The World Health Organization scale and physician gestalt were not helpful predictors of dehydration in our cohort. PMID:24788134

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.

Risk Factors for Prosthetic Pulmonary Valve Failure in Patients With Congenital Heart Disease.

PubMed

Oliver, Jose Maria; Garcia-Hamilton, Diego; Gonzalez, Ana Elvira; Ruiz-Cantador, Jose; Sanchez-Recalde, Angel; Polo, Maria Luz; Aroca, Angel

2015-10-15

The incidence and risk factors for prosthetic pulmonary valve failure (PPVF) should be considered when determining optimal timing for pulmonary valve replacement (PVR) in asymptomatic patients with congenital heart disease (CHD). The cumulative freedom for reintervention due to PPVF after 146 PVR in 114 patients with CHD was analyzed. Six potential risk factors (underlying cardiac defect, history of palliative procedures, number of previous cardiac interventions, hemodynamic indication for PVR, type of intervention, and age at intervention) were analyzed using Cox proportional hazard modeling. Receiver operating characteristic (ROC) curves were used for discrimination. Internal validation in patients with tetralogy of Fallot was also performed. Median age at intervention was 23 years. There were 60 reinterventions due to PPVF (41%). Median event-free survival was 14 years (95% confidence interval [CI] 12 to 16 years). The only independent risk factor was the age at intervention (hazard ratio [HR] 0.93, 95% CI 0.90 to 0.97; p = 0.001; area under the ROC curve 0.95, 95% CI 0.92 to 0.98; p <0.001). The best cut-off point was 20.5 years. Freedom from reintervention for PPVF 15 years after surgery was 70% when it was performed at age >20.5 years compared with 33% when age at intervention was <20.5 years (p = 0.004). Internal validation in 102 PVR in patient cohort with tetralogy of Fallot (ROC area 0.98, 95% CI 0.96 to 1.0; p <0.001) was excellent. In conclusion, age at intervention is the main risk factor of reintervention for PPVF. The risk of reintervention is 2-fold when PVR is performed before the age of 20.5 years. Copyright © 2015 Elsevier Inc. All rights reserved.

[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.

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.

Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Features

PubMed Central

Tamayo, Pablo; Cho, Yoon-Jae; Tsherniak, Aviad; Greulich, Heidi; Ambrogio, Lauren; Schouten-van Meeteren, Netteke; Zhou, Tianni; Buxton, Allen; Kool, Marcel; Meyerson, Matthew; Pomeroy, Scott L.; Mesirov, Jill P.

2011-01-01

Purpose Despite significant progress in the molecular understanding of medulloblastoma, stratification of risk in patients remains a challenge. Focus has shifted from clinical parameters to molecular markers, such as expression of specific genes and selected genomic abnormalities, to improve accuracy of treatment outcome prediction. Here, we show how integration of high-level clinical and genomic features or risk factors, including disease subtype, can yield more comprehensive, accurate, and biologically interpretable prediction models for relapse versus no-relapse classification. We also introduce a novel Bayesian nomogram indicating the amount of evidence that each feature contributes on a patient-by-patient basis. Patients and Methods A Bayesian cumulative log-odds model of outcome was developed from a training cohort of 96 children treated for medulloblastoma, starting with the evidence provided by clinical features of metastasis and histology (model A) and incrementally adding the evidence from gene-expression–derived features representing disease subtype–independent (model B) and disease subtype–dependent (model C) pathways, and finally high-level copy-number genomic abnormalities (model D). The models were validated on an independent test cohort (n = 78). Results On an independent multi-institutional test data set, models A to D attain an area under receiver operating characteristic (au-ROC) curve of 0.73 (95% CI, 0.60 to 0.84), 0.75 (95% CI, 0.64 to 0.86), 0.80 (95% CI, 0.70 to 0.90), and 0.78 (95% CI, 0.68 to 0.88), respectively, for predicting relapse versus no relapse. Conclusion The proposed models C and D outperform the current clinical classification schema (au-ROC, 0.68), our previously published eight-gene outcome signature (au-ROC, 0.71), and several new schemas recently proposed in the literature for medulloblastoma risk stratification. PMID:21357789

Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection.

PubMed

Kuroda, Daisuke; Sawayama, Hiroshi; Kurashige, Junji; Iwatsuki, Masaaki; Eto, Tsugio; Tokunaga, Ryuma; Kitano, Yuki; Yamamura, Kensuke; Ouchi, Mayuko; Nakamura, Kenichi; Baba, Yoshifumi; Sakamoto, Yasuo; Yamashita, Yoichi; Yoshida, Naoya; Chikamoto, Akira; Baba, Hideo

2018-03-01

Controlling Nutritional Status (CONUT), as calculated from serum albumin, total cholesterol concentration, and total lymphocyte count, was previously shown to be useful for nutritional assessment. The current study investigated the potential use of CONUT as a prognostic marker in gastric cancer patients after curative resection. Preoperative CONUT was retrospectively calculated in 416 gastric cancer patients who underwent curative resection at Kumamoto University Hospital from 2005 to 2014. The patients were divided into two groups: CONUT-high (≥4) and CONUT-low (≤3), according to time-dependent receiver operating characteristic (ROC) analysis. The associations of CONUT with clinicopathological factors and survival were evaluated. CONUT-high patients were significantly older (p < 0.001) and had a lower body mass index (p = 0.019), deeper invasion (p < 0.001), higher serum carcinoembryonic antigen (p = 0.037), and higher serum carbohydrate antigen 19-9 (p = 0.007) compared with CONUT-low patients. CONUT-high patients had significantly poorer overall survival (OS) compared with CONUT-low patients according to univariate and multivariate analyses (hazard ratio: 5.09, 95% confidence interval 3.12-8.30, p < 0.001). In time-dependent ROC analysis, CONUT had a higher area under the ROC curve (AUC) for the prediction of 5-year OS than the neutrophil lymphocyte ratio, the Modified Glasgow Prognostic Score, or pStage. When the time-dependent AUC curve was used to predict OS, CONUT tended to maintain its predictive accuracy for long-term survival at a significantly higher level for an extended period after surgery when compared with the other markers tested. CONUT is useful for not only estimating nutritional status but also for predicting long-term OS in gastric cancer patients after curative resection.

Contrast-enhanced spectral mammography vs. mammography and MRI - clinical performance in a multi-reader evaluation.

PubMed

Fallenberg, Eva M; Schmitzberger, Florian F; Amer, Heba; Ingold-Heppner, Barbara; Balleyguier, Corinne; Diekmann, Felix; Engelken, Florian; Mann, Ritse M; Renz, Diane M; Bick, Ulrich; Hamm, Bernd; Dromain, Clarisse

2017-07-01

To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) to digital mammography (MG) and magnetic resonance imaging (MRI) in a prospective two-centre, multi-reader study. One hundred seventy-eight women (mean age 53 years) with invasive breast cancer and/or DCIS were included after ethics board approval. MG, CESM and CESM + MG were evaluated by three blinded radiologists based on amended ACR BI-RADS criteria. MRI was assessed by another group of three readers. Receiver-operating characteristic (ROC) curves were compared. Size measurements for the 70 lesions detected by all readers in each modality were correlated with pathology. Reading results for 604 lesions were available (273 malignant, 4 high-risk, 327 benign). The area under the ROC curve was significantly larger for CESM alone (0.84) and CESM + MG (0.83) compared to MG (0.76) (largest advantage in dense breasts) while it was not significantly different from MRI (0.85). Pearson correlation coefficients for size comparison were 0.61 for MG, 0.69 for CESM, 0.70 for CESM + MG and 0.79 for MRI. This study showed that CESM, alone and in combination with MG, is as accurate as MRI but is superior to MG for lesion detection. Patients with dense breasts benefitted most from CESM with the smallest additional dose compared to MG. • CESM has comparable diagnostic performance (ROC-AUC) to MRI for breast cancer diagnostics. • CESM in combination with MG does not improve diagnostic performance. • CESM has lower sensitivity but higher specificity than MRI. • Sensitivity differences are more pronounced in dense and not significant in non-dense breasts. • CESM and MRI are significantly superior to MG, particularly in dense breasts.