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.

PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R.

PubMed

Grau, Jan; Grosse, Ivo; Keilwagen, Jens

2015-08-01

Precision-recall (PR) and receiver operating characteristic (ROC) curves are valuable measures of classifier performance. Here, we present the R-package PRROC, which allows for computing and visualizing both PR and ROC curves. In contrast to available R-packages, PRROC allows for computing PR and ROC curves and areas under these curves for soft-labeled data using a continuous interpolation between the points of PR curves. In addition, PRROC provides a generic plot function for generating publication-quality graphics of PR and ROC curves. © The Author 2015. Published by Oxford University Press.

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

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.

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.

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.

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.

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Obuchowski, Nancy A.; Bullen, Jennifer A.

2018-04-01

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

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.

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.

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2011-01-01

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

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

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

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.

Anxiety and Depression Screening for Youth in a Primary Care Population

PubMed Central

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

2008-01-01

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

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.

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.

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.

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.

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.

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

PubMed Central

1975-01-01

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

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.

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.

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…

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.

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

PubMed

Vexler, Albert; Yu, Jihnhee

2018-04-13

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

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.

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.

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 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

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.

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

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…

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.

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

PubMed Central

Edwards, Darrin C.; Metz, Charles E.

2012-01-01

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

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.

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.

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 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.

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

PubMed

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

The Belief Bias Effect Is Aptly Named: A Reply to Klauer and Kellen (2011)

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.; Heit, Evan

2011-01-01

In "Assessing the Belief Bias Effect With ROCs: It's a Response Bias Effect," Dube, Rotello, and Heit (2010) examined the form of receiver operating characteristic (ROC) curves for reasoning and the effects of belief bias on measurement indices that differ in whether they imply a curved or linear ROC function. We concluded that the ROC…

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.

On analyzing free-response data on location level

NASA Astrophysics Data System (ADS)

Bandos, Andriy I.; Obuchowski, Nancy A.

2017-03-01

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

A unified Bayesian semiparametric approach to assess discrimination ability in survival analysis

PubMed Central

Zhao, Lili; Feng, Dai; Chen, Guoan; Taylor, Jeremy M.G.

2015-01-01

Summary The discriminatory ability of a marker for censored survival data is routinely assessed by the time-dependent ROC curve and the c-index. The time-dependent ROC curve evaluates the ability of a biomarker to predict whether a patient lives past a particular time t. The c-index measures the global concordance of the marker and the survival time regardless of the time point. We propose a Bayesian semiparametric approach to estimate these two measures. The proposed estimators are based on the conditional distribution of the survival time given the biomarker and the empirical biomarker distribution. The conditional distribution is estimated by a linear dependent Dirichlet process mixture model. The resulting ROC curve is smooth as it is estimated by a mixture of parametric functions. The proposed c-index estimator is shown to be more efficient than the commonly used Harrell's c-index since it uses all pairs of data rather than only informative pairs. The proposed estimators are evaluated through simulations and illustrated using a lung cancer dataset. PMID:26676324

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.

An ROC-type measure of diagnostic accuracy when the gold standard is continuous-scale.

PubMed

Obuchowski, Nancy A

2006-02-15

ROC curves and summary measures of accuracy derived from them, such as the area under the ROC curve, have become the standard for describing and comparing the accuracy of diagnostic tests. Methods for estimating ROC curves rely on the existence of a gold standard which dichotomizes patients into disease present or absent. There are, however, many examples of diagnostic tests whose gold standards are not binary-scale, but rather continuous-scale. Unnatural dichotomization of these gold standards leads to bias and inconsistency in estimates of diagnostic accuracy. In this paper, we propose a non-parametric estimator of diagnostic test accuracy which does not require dichotomization of the gold standard. This estimator has an interpretation analogous to the area under the ROC curve. We propose a confidence interval for test accuracy and a statistical test for comparing accuracies of tests from paired designs. We compare the performance (i.e. CI coverage, type I error rate, power) of the proposed methods with several alternatives. An example is presented where the accuracies of two quick blood tests for measuring serum iron concentrations are estimated and compared.

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

PubMed

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

2011-03-15

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

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.

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

PubMed Central

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

2017-01-01

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

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

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.

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

PubMed

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

2016-01-01

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

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.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

PubMed

Rousson, Valentin; Zumbrunn, Thomas

2011-06-22

Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies

PubMed Central

2011-01-01

Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604

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.

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2014-01-01

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

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.

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.

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.

[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.

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

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

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

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

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.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Marghany, Maged

2016-10-01

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

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.

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…

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

PubMed

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

2014-09-01

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

Differentiating benign from malignant mediastinal lymph nodes visible at EBUS using grey-scale textural analysis.

PubMed

Edey, Anthony J; Pollentine, Adrian; Doody, Claire; Medford, Andrew R L

2015-04-01

Recent data suggest that grey-scale textural analysis on endobronchial ultrasound (EBUS) imaging can differentiate benign from malignant lymphadenopathy. The objective of studies was to evaluate grey-scale textural analysis and examine its clinical utility. Images from 135 consecutive clinically indicated EBUS procedures were evaluated retrospectively using MATLAB software (MathWorks, Natick, MA, USA). Manual node mapping was performed to obtain a region of interest and grey-scale textural features (range of pixel values and entropy) were analysed. The initial analysis involved 94 subjects and receiver operating characteristic (ROC) curves were generated. The ROC thresholds were then applied on a second cohort (41 subjects) to validate the earlier findings. A total of 371 images were evaluated. There was no difference in proportions of malignant disease (56% vs 53%, P = 0.66) in the prediction (group 1) and validation (group 2) sets. There was no difference in range of pixel values in group 1 but entropy was significantly higher in the malignant group (5.95 vs 5.77, P = 0.03). Higher entropy was seen in adenocarcinoma versus lymphoma (6.00 vs 5.50, P < 0.05). An ROC curve for entropy gave an area under the curve of 0.58 with 51% sensitivity and 71% specificity for entropy greater than 5.94 for malignancy. In group 2, the entropy threshold phenotyped only 47% of benign cases and 20% of malignant cases correctly. These findings suggest that use of EBUS grey-scale textural analysis for differentiation of malignant from benign lymphadenopathy may not be accurate. Further studies are required. © 2015 Asian Pacific Society of Respirology.

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.

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

Dynamic thresholds and a summary ROC curve: Assessing prognostic accuracy of longitudinal markers.

PubMed

Saha-Chaudhuri, P; Heagerty, P J

2018-04-19

Cancer patients, chronic kidney disease patients, and subjects infected with HIV are routinely monitored over time using biomarkers that represent key health status indicators. Furthermore, biomarkers are frequently used to guide initiation of new treatments or to inform changes in intervention strategies. Since key medical decisions can be made on the basis of a longitudinal biomarker, it is important to evaluate the potential accuracy associated with longitudinal monitoring. To characterize the overall accuracy of a time-dependent marker, we introduce a summary ROC curve that displays the overall sensitivity associated with a time-dependent threshold that controls time-varying specificity. The proposed statistical methods are similar to concepts considered in disease screening, yet our methods are novel in choosing a potentially time-dependent threshold to define a positive test, and our methods allow time-specific control of the false-positive rate. The proposed summary ROC curve is a natural averaging of time-dependent incident/dynamic ROC curves and therefore provides a single summary of net error rates that can be achieved in the longitudinal setting. Copyright © 2018 John Wiley & Sons, Ltd.

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.

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

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.

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.

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.

Reader strategies: variability and error- methodology, findings, and health policy implications from a study of the U.S. population of mammographers

NASA Astrophysics Data System (ADS)

Beam, Craig A.

2002-04-01

Each year, approximately 60% of all US women over the age of 40 utilize mammography. Through the matrix of an imaging technology, this Population of Patients (POP) interacts with a population of approximately 20,000 physicians who interpret mammograms in the US. This latter Population of Diagnosticians (POD) operationally serves as the interface between an image-centric healthcare technology system and patient. Methods: using data collected from a large POD and POP based study, I evaluate the distribution of several ROC curve-related parameters in the POD and explore the health policy implications of a population ROC curve for mammography. Results and Conclusions: Principal Components Analysis suggests that two Binormal parameters are sufficient to explain variation in the POD and implies that the Binormal model is foundational to Health Policy Research in Mammography. A population ROC curve based on percentiles of the POD can be used to set targets to achieve national health policy goals. Medical Image Perception science provides the framework. Alternatively, a restrictive policy can be envisioned using performance criteria based on area. However, the data suggests this sort of policy would be too costly in terms of reduced healthcare service capacity in the US in the face of burgeoning demands.

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.

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.

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.

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.

[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.

The ROC Curves of Fused Independent Classification Systems

DTIC Science & Technology

2008-09-01

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

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).

Binary ROCs in Perception and Recognition Memory Are Curved

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.

2012-01-01

In recognition memory, a classic finding is that receiver operating characteristics (ROCs) are curvilinear. This has been taken to support the fundamental assumptions of signal detection theory (SDT) over discrete-state models such as the double high-threshold model (2HTM), which predicts linear ROCs. Recently, however, Broder and Schutz (2009)…

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.

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…

Developing a clinical utility framework to evaluate prediction models in radiogenomics

NASA Astrophysics Data System (ADS)

Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.

2015-03-01

Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.

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

PubMed

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

2018-04-09

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

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.

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

Diagnostic value of fibronectin discriminant score for predicting liver fibrosis stages in chronic hepatitis C virus patients.

PubMed

Attallah, Abdelfattah M; Abdallah, Sanaa O; Attallah, Ahmed A; Omran, Mohamed M; Farid, Khaled; Nasif, Wesam A; Shiha, Gamal E; Abdel-Aziz, Abdel-Aziz F; Rasafy, Nancy; Shaker, Yehia M

2013-01-01

Several noninvasive predictive models were developed to substitute liver biopsy for fibrosis assessment. To evaluate the diagnostic value of fibronectin which reflect extracellular matrix metabolism and standard liver functions tests which reflect alterations in hepatic functions. Chronic hepatitis C (CHC) patients (n = 145) were evaluated using ROC curves and stepwise multivariate discriminant analysis (MDA) and was validated in 180 additional patients. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, albumin, complete blood count were estimated. Fibronectin concentration was determined using monoclonal antibody and ELISA. A novel index named fibronectin discriminant score (FDS) based on fibronectin, APRI and albumin was developed. FDS produced areas under ROC curves (AUC) of 0.91 for significant fibrosis and 0.81 for advanced fibrosis. The FDS correctly classified 79% of the significant liver fibrosis patients (F2-F4) with 87% sensitivity and 75% specificity. The relative risk [odds ratio (OR)] of having significant liver fibrosis using the cut-off values determined by ROC curve analyses were 6.1 for fibronectin, 4.9 for APRI, and 4.2 for albumin. FDS predicted liver fibrosis with an OR of 16.8 for significant fibrosis and 8.6 for advanced fibrosis. The FDS had similar AUC and OR in the validation group to the estimation group without statistically significant difference. FDS predicted liver fibrosis with high degree of accuracy, potentially decreasing the number of liver biopsy required.

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.

Validating a biometric authentication system: sample size requirements.

PubMed

Dass, Sarat C; Zhu, Yongfang; Jain, Anil K

2006-12-01

Authentication systems based on biometric features (e.g., fingerprint impressions, iris scans, human face images, etc.) are increasingly gaining widespread use and popularity. Often, vendors and owners of these commercial biometric systems claim impressive performance that is estimated based on some proprietary data. In such situations, there is a need to independently validate the claimed performance levels. System performance is typically evaluated by collecting biometric templates from n different subjects, and for convenience, acquiring multiple instances of the biometric for each of the n subjects. Very little work has been done in 1) constructing confidence regions based on the ROC curve for validating the claimed performance levels and 2) determining the required number of biometric samples needed to establish confidence regions of prespecified width for the ROC curve. To simplify the analysis that address these two problems, several previous studies have assumed that multiple acquisitions of the biometric entity are statistically independent. This assumption is too restrictive and is generally not valid. We have developed a validation technique based on multivariate copula models for correlated biometric acquisitions. Based on the same model, we also determine the minimum number of samples required to achieve confidence bands of desired width for the ROC curve. We illustrate the estimation of the confidence bands as well as the required number of biometric samples using a fingerprint matching system that is applied on samples collected from a small population.

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

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.

Enhancement of the Daytime MODIS Based Aircraft Icing Potential Algorithm Using Mesoscale Model Data

DTIC Science & Technology

2006-03-01

January, 15, 2006 ...... 37 x Figure 25. ROC curves using 3 hour PIREPs and Alexander Tmap with symbols plotted at the 0.5 threshold values...42 Figure 26. ROC curves using 3 hour PIREPs and Alexander Tmap with symbols plotted at the 0.5 threshold values...Table 4. Results using T icing potential values from the Alexander Tmap , and 3 Hour PIREPs

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.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

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.

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.

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.

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.

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.

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.

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.

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

PubMed

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

2018-05-23

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

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.

14-3-3η Autoantibodies: Diagnostic Use in Early Rheumatoid Arthritis.

PubMed

Maksymowych, Walter P; Boire, Gilles; van Schaardenburg, Dirkjan; Wichuk, Stephanie; Turk, Samina; Boers, Maarten; Siminovitch, Katherine A; Bykerk, Vivian; Keystone, Ed; Tak, Paul Peter; van Kuijk, Arno W; Landewé, Robert; van der Heijde, Desiree; Murphy, Mairead; Marotta, Anthony

2015-09-01

To describe the expression and diagnostic use of 14-3-3η autoantibodies in early rheumatoid arthritis (RA). 14-3-3η autoantibody levels were measured using an electrochemiluminescent multiplexed assay in 500 subjects (114 disease-modifying antirheumatic drug-naive patients with early RA, 135 with established RA, 55 healthy, 70 autoimmune, and 126 other non-RA arthropathy controls). 14-3-3η protein levels were determined in an earlier analysis. Two-tailed Student t tests and Mann-Whitney U tests compared differences among groups. Receiver-operator characteristic (ROC) curves were generated and diagnostic performance was estimated by area under the curve (AUC), as well as specificity, sensitivity, and likelihood ratios (LR) for optimal cutoffs. Median serum 14-3-3η autoantibody concentrations were significantly higher (p < 0.0001) in patients with early RA (525 U/ml) when compared with healthy controls (235 U/ml), disease controls (274 U/ml), autoimmune disease controls (274 U/ml), patients with osteoarthritis (259 U/ml), and all controls (265 U/ml). ROC curve analysis comparing early RA with healthy controls demonstrated a significant (p < 0.0001) AUC of 0.90 (95% CI 0.85-0.95). At an optimal cutoff of ≥ 380 U/ml, the ROC curve yielded a sensitivity of 73%, a specificity of 91%, and a positive LR of 8.0. Adding 14-3-3η autoantibodies to 14-3-3η protein positivity enhanced the identification of patients with early RA from 59% to 90%; addition of 14-3-3η autoantibodies to anticitrullinated protein antibodies (ACPA) and/or rheumatoid factor (RF) increased identification from 72% to 92%. Seventy-two percent of RF- and ACPA-seronegative patients were positive for 14-3-3η autoantibodies. 14-3-3η autoantibodies, alone and in combination with the 14-3-3η protein, RF, and/or ACPA identified most patients with early RA.

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

PubMed Central

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

2016-01-01

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

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.

Using BIRADS categories in ROC experiments

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Hersh, Marla R.; Thomas, Jerry A.

2002-04-01

This paper investigated the use of the Breast Imaging Reporting And Data System (BIRADS) Lexicon in ROC mammography experiments. Analysis was based on data from parallel ROC experiments performed at two Institutions with different readers and databases to compare film to digitized mammography. Seven readers participated in the studies and read approximately 200 cases each in two formats: film and digital or softcopy. Reporting was done using BIRADS categories 1 through 5. Training was done with a separate set of cases and included detailed review of the relationship between BIRADS and a standard ROC discrete 5-point rating scale. The results from both sites showed equivalency between film and softcopy mammography. Decisions using the BIRADS categories showed no unsampled ROC regions and no degenerate data. Fits yielded smooth ROC curves that correlated to clinical practice. In a qualitative evaluation, all observers indicated preference in using the BIRADS classes instead of a discrete or continuous rating scheme. Familiarity with the rating process seems to relieve some of the bias associated with the interpretation of digitized mammograms from computer monitors (softcopy reading). Our results suggested that BIRADS categories can be used in comparative ROC studies because they represent a scale familiar to the reader that can be followed consistently and they provide a rating approach that accounts for both positive and negative cases to be evaluated and categorized.

Describing three-class task performance: three-class linear discriminant analysis and three-class ROC analysis

NASA Astrophysics Data System (ADS)

He, Xin; Frey, Eric C.

2007-03-01

Binary ROC analysis has solid decision-theoretic foundations and a close relationship to linear discriminant analysis (LDA). In particular, for the case of Gaussian equal covariance input data, the area under the ROC curve (AUC) value has a direct relationship to the Hotelling trace. Many attempts have been made to extend binary classification methods to multi-class. For example, Fukunaga extended binary LDA to obtain multi-class LDA, which uses the multi-class Hotelling trace as a figure-of-merit, and we have previously developed a three-class ROC analysis method. This work explores the relationship between conventional multi-class LDA and three-class ROC analysis. First, we developed a linear observer, the three-class Hotelling observer (3-HO). For Gaussian equal covariance data, the 3- HO provides equivalent performance to the three-class ideal observer and, under less strict conditions, maximizes the signal to noise ratio for classification of all pairs of the three classes simultaneously. The 3-HO templates are not the eigenvectors obtained from multi-class LDA. Second, we show that the three-class Hotelling trace, which is the figureof- merit in the conventional three-class extension of LDA, has significant limitations. Third, we demonstrate that, under certain conditions, there is a linear relationship between the eigenvectors obtained from multi-class LDA and 3-HO templates. We conclude that the 3-HO based on decision theory has advantages both in its decision theoretic background and in the usefulness of its figure-of-merit. Additionally, there exists the possibility of interpreting the two linear features extracted by the conventional extension of LDA from a decision theoretic point of view.

Prognostic Significance of the Short Physical Performance Battery in Older Patients Discharged from Acute Care Hospitals

PubMed Central

Lattanzio, Fabrizia; Pedone, Claudio; Garasto, Sabrina; Laino, Irma; Bustacchini, Silvia; Pranno, Luigi; Mazzei, Bruno; Passarino, Giuseppe; Incalzi, Raffaele Antonelli

2012-01-01

Abstract We investigated the prognostic role of the Short Physical Performance Battery (SPPB) in elderly patients discharged from the acute care hospital. Our series consisted of 506 patients aged 70 years or more enrolled in a multicenter collaborative observational study. We considered three main outcomes: 1-year survival after discharge, functional decline, and hospitalization during follow-up. Independent predictors/correlates of the outcomes were investigated by Cox regression or logistic regression analysis when appropriate. The diagnostic accuracy of SPPB in relation to study outcomes was investigated by receiver operating characteristic (ROC) curve. SPPB score was associated with reduced mortality (hazard ratio [HR]=0.86, 95% confidence interval [CI] 0.78–0.95). When the analysis was adjusted for functional status at discharge, such an association was still near significant only for SPPB values >8 (HR=0.51; 95% CI 0.30–1.05). An SPPB score<5 could identify patients who died during follow-up with fair sensitivity (0.66), specificity (0.62), and area under the ROC curve (0.66). SPPB also qualified as independent correlate of functional decline (odds ratio [OR]=0.82; 95% CI 0.70–0.96), but not of rehospitalization or combined end-point death or rehospitalization. An SPPB score <5 could identify patients experiencing functional decline during follow-up with lower sensitivity (0.60), but higher specificity (0.69), and area under the ROC curve (0.69) with respect to mortality. In conclusion, SPPB can be considered a valid instrument to identify patients at major risk of functional decline and death after discharge from acute care hospital. However, it could more efficiently target patients at risk of functional decline than those at risk of death. PMID:22004280

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.

Estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers.

PubMed

Li, Shanshan; Ning, Yang

2015-09-01

Covariate-specific time-dependent ROC curves are often used to evaluate the diagnostic accuracy of a biomarker with time-to-event outcomes, when certain covariates have an impact on the test accuracy. In many medical studies, measurements of biomarkers are subject to missingness due to high cost or limitation of technology. This article considers estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers. To incorporate the covariate effect, we assume a proportional hazards model for the failure time given the biomarker and the covariates, and a semiparametric location model for the biomarker given the covariates. In the presence of missing biomarkers, we propose a simple weighted estimator for the ROC curves where the weights are inversely proportional to the selection probability. We also propose an augmented weighted estimator which utilizes information from the subjects with missing biomarkers. The augmented weighted estimator enjoys the double-robustness property in the sense that the estimator remains consistent if either the missing data process or the conditional distribution of the missing data given the observed data is correctly specified. We derive the large sample properties of the proposed estimators and evaluate their finite sample performance using numerical studies. The proposed approaches are illustrated using the US Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. © 2015, The International Biometric Society.

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.

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

[Application of decision curve on evaluation of MRI predictive model for early assessing pathological complete response to neoadjuvant therapy in breast cancer].

PubMed

He, Y J; Li, X T; Fan, Z Q; Li, Y L; Cao, K; Sun, Y S; Ouyang, T

2018-01-23

Objective: To construct a dynamic enhanced MR based predictive model for early assessing pathological complete response (pCR) to neoadjuvant therapy in breast cancer, and to evaluate the clinical benefit of the model by using decision curve. Methods: From December 2005 to December 2007, 170 patients with breast cancer treated with neoadjuvant therapy were identified and their MR images before neoadjuvant therapy and at the end of the first cycle of neoadjuvant therapy were collected. Logistic regression model was used to detect independent factors for predicting pCR and construct the predictive model accordingly, then receiver operating characteristic (ROC) curve and decision curve were used to evaluate the predictive model. Results: ΔArea(max) and Δslope(max) were independent predictive factors for pCR, OR =0.942 (95% CI : 0.918-0.967) and 0.961 (95% CI : 0.940-0.987), respectively. The area under ROC curve (AUC) for the constructed model was 0.886 (95% CI : 0.820-0.951). Decision curve showed that in the range of the threshold probability above 0.4, the predictive model presented increased net benefit as the threshold probability increased. Conclusions: The constructed predictive model for pCR is of potential clinical value, with an AUC>0.85. Meanwhile, decision curve analysis indicates the constructed predictive model has net benefit from 3 to 8 percent in the likely range of probability threshold from 80% to 90%.

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

PubMed

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

2017-01-01

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

Bioimpedance spectroscopy can precisely discriminate human breast carcinoma from benign tumors

PubMed Central

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

2017-01-01

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

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.

Differential gene expression profiles of peripheral blood mononuclear cells in childhood asthma.

PubMed

Kong, Qian; Li, Wen-Jing; Huang, Hua-Rong; Zhong, Ying-Qiang; Fang, Jian-Pei

2015-05-01

Asthma is a common childhood disease with strong genetic components. This study compared whole-genome expression differences between asthmatic young children and healthy controls to identify gene signatures of childhood asthma. Total RNA extracted from peripheral blood mononuclear cells (PBMC) was subjected to microarray analysis. QRT-PCR was performed to verify the microarray results. Classification and functional characterization of differential genes were illustrated by hierarchical clustering and gene ontology analysis. Multiple logistic regression (MLR) analysis, receiver operating characteristic (ROC) curve analysis, and discriminate power were used to scan asthma-specific diagnostic markers. For fold-change>2 and p < 0.05, there were 758 named differential genes. The results of QRT-PCR confirmed successfully the array data. Hierarchical clustering divided 29 highly possible genes into seven categories and the genes in the same cluster were likely to possess similar expression patterns or functions. Gene ontology analysis presented that differential genes primarily enriched in immune response, response to stress or stimulus, and regulation of apoptosis in biological process. MLR and ROC curve analysis revealed that the combination of ADAM33, Smad7, and LIGHT possessed excellent discriminating power. The combination of ADAM33, Smad7, and LIGHT would be a reliable and useful childhood asthma model for prediction and diagnosis.

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

PubMed Central

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

2014-01-01

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

Quantity of Candida Colonies in Saliva: 
A Diagnostic Evaluation for Oral Candidiasis.

PubMed

Zhou, Pei Ru; Hua, Hong; Liu, Xiao Song

To investigate the relationship between the quantity of Candida colonies in saliva and oral candidiasis (OC), as well as to identify the threshold for distinguishing oral candidiasis from healthy carriage. A diagnostic test was conducted in 197 patients with different oral problems. The diagnosis of OC was established based on clinical features. Whole saliva samples from the subjects were cultured for Candida species. Receiver operating characteristic (ROC) curve analysis was used in this study. OC patients had significantly more Candida colony-forming units per millilitre saliva (795 cfu/ml) than asymptomatic carriers (40 cfu/ml; P < 0.05). Among different types of candidiasis, the quantity of Candida colonies differed. The number of Candida colonies in pseudomembranous type was significantly higher than that in the erythematous type (P < 0.05). Candida albicans was the predominant species of Candida. The cut-off point with the best fit for OC diagnosis was calculated to be 266 cfu/ml. The sensitivity and specificity were 0.720 and 0.825, respectively. Analysis of the ROC curve indicated that Candida colonies had a high diagnostic value for OC, as demonstrated by the area under the curve (AUC = 0.873). Based on this study, the value of 270 cfu/ml was considered a threshold for distinguishing OC from carriage.

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.

[Identification of cutoff points for Homeostatic Model Assessment for Insulin Resistance index in adolescents: systematic review].

PubMed

Andrade, Maria Izabel Siqueira de; Oliveira, Juliana Souza; Leal, Vanessa Sá; Lima, Niedja Maria da Silva; Costa, Emília Chagas; Aquino, Nathalia Barbosa de; Lira, Pedro Israel Cabral de

2016-06-01

To identify cutoff points of the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index established for adolescents and discuss their applicability for the diagnosis of insulin resistance in Brazilian adolescents. A systematic review was performed in the PubMed, Lilacs and SciELO databases, using the following descriptors: "Adolescents", "insulin resistance" and "ROC curve". Original articles carried out with adolescents published between 2005 and 2015 in Portuguese, English or Spanish languages, which included the statistical analysis using ROC curve to determine the index cutoff (HOMA-IR) were included. A total of 184 articles were identified and after the study phases were applied, seven articles were selected for the review. All selected studies established their cutoffs using a ROC curve, with the lowest observed cutoff of 1.65 for girls and 1.95 for boys and the highest of 3.82 for girls and 5.22 for boys. Of the studies analyzed, one proposed external validity, recommending the use of the HOMA-IR cutoff >2.5 for both genders. The HOMA-IR index constitutes a reliable method for the detection of insulin resistance in adolescents, as long as it uses cutoffs that are more adequate for the reality of the study population, allowing early diagnosis of insulin resistance and enabling multidisciplinary interventions aiming at health promotion of this population. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

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).…

Development of a gambling addictive behavior scale for adolescents in Korea.

PubMed

Park, Hyun Sook; Jung, Sun Young

2012-12-01

This study was conducted to develop a gambling addictive behavior scale for adolescents. The process involved construction of a conceptual framework, initial item search, verification of content validity, selection of secondary items, and extraction of final items. The participants were 299 adolescents from two middle schools and four high schools. Item analysis, factor analysis, criterion validity, internal consistency, and ROC curve were used to analyze the data. For the final scale, 25 items were selected, and categorized into 4 factors which accounted for 54.9% of the total variance. The factors were labeled as loss of control, life dysfunction from gambling addiction, gambling experience, and social dysfunction from problem gambling. The scores for the scale were significantly correlated with addictive personality, irrational gambling belief, and adolescent's gambling addictive behavior. Cronbach's alpha coefficient for the 25 items was .94. Scale scores identified adolescents as being in a problem gambling group, a non-problem gambling group, and a non-gambling group by the ROC curve. The above findings indicate that the gambling addictive behavior scale has good validity and reliability and can be used with adolescents in Korea.

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.

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.

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

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.

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

PubMed Central

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

2017-01-01

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

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.

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.

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.

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

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.

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.

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.

Predicting extracapsular involvement in prostate cancer through the tumor contact length and the apparent diffusion coefficient.

PubMed

Granja, M F; Pedraza, C M; Flórez, D C; Romero, J A; Palau, M A; Aguirre, D A

To evaluate the diagnostic performance of the length of the tumor contact with the capsule (LTC) and the apparent diffusion coefficient (ADC) map in the prediction of microscopic extracapsular extension in patients with prostate cancer who are candidates for radical prostatectomy. We used receiver operating curves to retrospectively study the diagnostic performance of the ADC map and the LTC as predictors of microscopic extracapsular extension in 92 patients with prostate cancer and moderate to high risk who were examined between May 2011 and December 2013. The optimal cutoff for the ADC map was 0.87× 10 -3 mm 2 /s, which yielded an area under the ROC curve of 72% (95% CI: 57%-86%), corresponding to a sensitivity of 83% and a specificity of 61%. The optimal cutoff for the LTC was 17.5mm, which yielded an area under the ROC curve of 74% (95% CI: 61%-87%), corresponding to a sensitivity of 91% and a specificity of 57%. Combining the two criteria improved the diagnostic performance, yielding an area under the ROC curve of 77% (95% CI: 62%-92%), corresponding to a sensitivity of 77% and a specificity of 61%. We elaborated a logistic regression model, obtaining an area under the ROC curve of 82% (95% CI: 73%-93%). Using quantitative measures improves the diagnostic accuracy of multiparametric magnetic resonance imaging in the staging of prostate cancer. The values of the ADC and LTC were predictors of microscopic extracapsular extension, and the best results were obtained when both values were used in combination. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

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.

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

DTIC Science & Technology

2008-04-04

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

Waist circumference and insulin resistance: a cross-sectional study of Japanese men

PubMed Central

Tabata, Shinji; Yoshimitsu, Shinichiro; Hamachi, Tadamichi; Abe, Hiroshi; Ohnaka, Keizo; Kono, Suminori

2009-01-01

Background Visceral obesity is positively related to insulin resistance. The nature of the relationship between waist circumference and insulin resistance has not been known in Japanese populations. This study examined the relationship between waist circumference and insulin resistance and evaluated the optimal cutoff point for waist circumference in relation to insulin resistance in middle-aged Japanese men. Methods Study subjects included 4800 Japanese men aged 39 to 60 years. Insulin resistance was evaluated by the homeostasis model assessment of insulin resistance (HOMA-IR). The relationship of waist circumference with HOMA-IR was assessed by use of adjusted means of HOMA-IR and odds ratios of elevated HOMA-IR defined as the highest quintile (≥2.00). Receiver operating characteristics (ROC) curve analysis using Youden index and the area under curve (AUC) was employed to determine optimal cutoffs of waist circumference in relation to HOMA-IR. Results Adjusted geometric means of HOMA-IR and prevalence odds of elevated HOMA-IR were progressively higher with increasing levels of waist circumference. In the ROC curve analysis, the highest value of Youden index was obtained for a cutoff point of 85 cm in waist circumference across different values of HOMA-IR. Multiple logistic regression analysis also indicated that the AUC was consistently the largest for a waist circumference of 85 cm. Conclusion Waist circumference is linearly related to insulin resistance, and 85 cm in waist circumference is an optimal cutoff in predicting insulin resistance in middle-aged Japanese men. PMID:19138424

Optimizing Clinical Interpretation of Distortion Product Otoacoustic Emissions in Infants.

PubMed

Blankenship, Chelsea M; Hunter, Lisa L; Keefe, Douglas H; Feeney, M Patrick; Brown, David K; McCune, Annie; Fitzpatrick, Denis F; Lin, Li

2018-03-06

The purpose of this study was to analyze distortion product otoacoustic emission (DPOAE) level and signal to noise ratio in a group of infants from birth to 4 months of age to optimize prediction of hearing status. DPOAEs from infants with normal hearing (NH) and hearing loss (HL) were used to predict the presence of conductive HL (CHL), sensorineural HL (SNHL), and mixed HL (MHL). Wideband ambient absorbance was also measured and compared among the HL types. This is a prospective, longitudinal study of 279 infants with verified NH and HL, including conductive, sensorineural, and mixed types that were enrolled from a well-baby nursery and two neonatal intensive care units in Cincinnati, Ohio. At approximately 1 month of age, DPOAEs (1-8 kHz), wideband absorbance (0.25-8 kHz), and air and bone conduction diagnostic tone burst auditory brainstem response (0.5-4 kHz) thresholds were measured. Hearing status was verified at approximately 9 months of age with visual reinforcement audiometry (0.5-4 kHz). Auditory brainstem response air conduction thresholds were used to assign infants to an NH or HL group, and the efficacy of DPOAE data to classify ears as NH or HL was analyzed using receiver operating characteristic (ROC) curves. Two summary statistics of the ROC curve were calculated: the area under the ROC curve and the point of symmetry on the curve at which the sensitivity and specificity were equal. DPOAE level and signal to noise ratio cutoff values were defined at each frequency as the symmetry point on their respective ROC curve, and DPOAE results were combined across frequency in a multifrequency analysis to predict the presence of HL. Single-frequency test performance of DPOAEs was best at mid to high frequencies (3-8 kHz) with intermediate performance at 1.5 and 2 kHz and chance performance at 1 kHz. Infants with a conductive component to their HL (CHL and MHL combined) displayed significantly lower ambient absorbance values than the NH group. No differences in ambient absorbance were found between the NH and SNHL groups. Multifrequency analysis resulted in the best prediction of HL for the SNHL/MHL group with poorer sensitivity values when infants with CHL were included. Clinical interpretation of DPOAEs in infants can be improved by using age-appropriate normative ranges and optimized cutoff values. DPOAE interpretation is most predictive at higher F2 test frequencies in young infants (2-8 kHz) due to poor test performance at 1 to 1.5 kHz. Multifrequency rules can be used to improve sensitivity while balancing specificity. Last, a sensitive middle ear measure such as wideband absorbance should be included in the test battery to assess possibility of a conductive component to the HL.

Measurement properties of the Dizziness Handicap Inventory by cross-sectional and longitudinal designs

PubMed Central

2009-01-01

Background The impact of dizziness on quality of life is often assessed by the Dizziness Handicap Inventory (DHI), which is used as a discriminate and evaluative measure. The aim of the present study was to examine reliability and validity of a translated Norwegian version (DHI-N), also examining responsiveness to important change in the construct being measured. Methods Two samples (n = 92 and n = 27) included participants with dizziness of mainly vestibular origin. A cross-sectional design was used to examine the factor structure (exploratory factor analysis), internal consistency (Cronbach's α), concurrent validity (Pearson's product moment correlation r), and discriminate ability (ROC curve analysis). Longitudinal designs were used to examine test-retest reliability (intraclass correlation coefficient (ICC) statistics, smallest detectable difference (SDD)), and responsiveness (Pearson's product moment correlation, ROC curve analysis; area under the ROC curve (AUC), and minimally important change (MIC)). The DHI scores range from 0 to 100. Results Factor analysis revealed a different factor structure than the original DHI, resulting in dismissal of subscale scores in the DHI-N. Acceptable internal consistency was found for the total scale (α = 0.95). Concurrent correlations between the DHI-N and other related measures were moderate to high, highest with Vertigo Symptom Scale-short form-Norwegian version (r = 0.69), and lowest with preferred gait (r = - 0.36). The DHI-N demonstrated excellent ability to discriminate between participants with and without 'disability', AUC being 0.89 and best cut-off point = 29 points. Satisfactory test-retest reliability was demonstrated, and the change for an individual should be ≥ 20 DHI-N points to exceed measurement error (SDD). Correlations between change scores of DHI-N and other self-report measures of functional health and symptoms were high (r = 0.50 - 0.57). Responsiveness of the DHI-N was excellent, AUC = 0.83, discriminating between self-perceived 'improved' versus 'unchanged' participants. The MIC was identified as 11 DHI-N points. Conclusions The DHI-N total scale demonstrated satisfactory measurement properties. This is the first study that has addressed and demonstrated responsiveness to important change of the DHI, and provided values of SDD and MIC to help interpret change scores. PMID:20025754

A local equation for differential diagnosis of β-thalassemia trait and iron deficiency anemia by logistic regression analysis in Southeast Iran.

PubMed

Sargolzaie, Narjes; Miri-Moghaddam, Ebrahim

2014-01-01

The most common differential diagnosis of β-thalassemia (β-thal) trait is iron deficiency anemia. Several red blood cell equations were introduced during different studies for differential diagnosis between β-thal trait and iron deficiency anemia. Due to genetic variations in different regions, these equations cannot be useful in all population. The aim of this study was to determine a native equation with high accuracy for differential diagnosis of β-thal trait and iron deficiency anemia for the Sistan and Baluchestan population by logistic regression analysis. We selected 77 iron deficiency anemia and 100 β-thal trait cases. We used binary logistic regression analysis and determined best equations for probability prediction of β-thal trait against iron deficiency anemia in our population. We compared diagnostic values and receiver operative characteristic (ROC) curve related to this equation and another 10 published equations in discriminating β-thal trait and iron deficiency anemia. The binary logistic regression analysis determined the best equation for best probability prediction of β-thal trait against iron deficiency anemia with area under curve (AUC) 0.998. Based on ROC curves and AUC, Green & King, England & Frazer, and then Sirdah indices, respectively, had the most accuracy after our equation. We suggest that to get the best equation and cut-off in each region, one needs to evaluate specific information of each region, specifically in areas where populations are homogeneous, to provide a specific formula for differentiating between β-thal trait and iron deficiency anemia.

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.

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.

Bronchial lavage P 16INK4A gene promoter methylation and lung cancer diagnosis: A meta-analysis.

PubMed

Yifan, D; Qun, L; Yingshuang, H; Xulin, L; Jianjun, W; Qian, M; Yuman, Yu; Zhaoyang, R

2015-12-01

To evaluate the diagnostic value of bronchial lavage P16INK4A promoter methylation and lung cancer. The databases of PubMed, Medline, China National Knowledge Infrastructure, and Wanfang were electronically searched by two reviewers to find the suitable studies related to the association between P16INK4A promoter methylation and lung cancer. The P16INK4A promoter methylation rate was extracted from each included individual study. The diagnostic sensitivity, specificity, and area under the receiver operating characteristic ROC curve of bronchial lavage P16INK4Aas a biomarker for diagnosis of lung cancer were pooled by stata 11.0 software (Stata Corporation, College Station, TX, USA). At last, 10 publications were included in this meta-analysis. Of the included 10 studies, five are published in English with relatively high quality and other five papers published in Chinese have relatively low quality. The pooled sensitivity and specificity of bronchial lavage P16INK4A promoter methylation for lung cancer diagnosis were 0.61 (95% confidence interval [CI]: 0.57-0.65) and 0.81 (95% CI: 0.78-0.85), respectively, with random effect model. The ROC curve were calculated and drawn according to Bayes' theorem by stata 11.0 software. The systematic area under the ROC was 0.72 (95% CI: 0.68-0.76), which indicated that the diagnostic value of bronchial lavage P16INK4A promoter methylation for lung cancer was relatively high. Moreover, no significant publication bias was existed in this meta-analysis (t = 0.69, P > 0.05). Bronchial lavage P16INK4A promoter methylation can be a potential biomarker for diagnosis of lung cancer.

Quantitative Differentiation of LV Myocardium with and without Layer-Specific Fibrosis Using MRI in Hypertrophic Cardiomyopathy and Layer-Specific Strain TTE Analysis.

PubMed

Funabashi, Nobusada; Takaoka, Hiroyuki; Ozawa, Koya; Kamata, Tomoko; Uehara, Masae; Komuro, Issei; Kobayashi, Yoshio

2018-05-30

To achieve further risk stratification in hypertrophic cardiomyopathy (HCM) patients, we localized and quantified layer-specific LVM fibrosis on MRI in HCM patients using regional layer-specific peak longitudinal strain (PLS) and peak circumferential strain (PCS) in LV myocardium (LVM) on speckle tracking transthoracic echocardiography (TTE). A total of 18 HCM patients (14 males; 58 ± 17 years) underwent 1.5T-MRI and TTE. PLS and PCS in each layer of the LVM (endocardium, epicardium, and whole-layer myocardium) were calculated for 17 AHA-defined lesions. MRI assessment showed that fibrosis was classified as endocardial, epicardial, or whole-layer (= either or both of these). Regional PLS was smaller in fibrotic endocardial lesions than in non-fibrotic endocardial lesions (P = 0.004). To detect LV endocardial lesions with fibrosis, ROC curves of regional PLS revealed an area under the curve (AUC) of 0.609 and a best cut-off point of 13.5%, with sensitivity of 65.3% and specificity of 54.3%. Regional PLS was also smaller in fibrotic epicardial lesions than in non-fibrotic epicardial lesions (P < 0.001). To detect LV epicardial lesions with fibrosis, ROC curves of PLS revealed an AUC of 0.684 and a best cut-off point of 9.5%, with sensitivity of 73.5% and specificity of 55.5%. Using whole-layer myocardium analysis, PLS was smaller in fibrotic lesions than in non-fibrotic lesions (P < 0.001). To detect whole-layer LV lesions with fibrosis, ROC curves of regional PLS revealed an AUC of 0.674 and a best cut-off point of 12.5%, with sensitivity of 79.0% and specificity of 50.7%. There were no significant differences in PCS of LV myocardium (endocardium, epicardium, and whole-layer) between fibrotic and non-fibrotic lesions. Quantitative regional PLS but not PCS in LV endocardium, epicardium, and whole-layer myocardium provides useful non-invasive information for layer-specific localization of fibrosis in HCM patients.

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

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.

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.

Comparison of radiologist performance with photon-counting full-field digital mammography to conventional full-field digital mammography.

PubMed

Cole, Elodia B; Toledano, Alicia Y; Lundqvist, Mats; Pisano, Etta D

2012-08-01

The purpose of this study was to assess the performance of a MicroDose photon-counting full-field digital mammography (PCM) system in comparison to full-field digital mammography (FFDM) for area under the receiver-operating characteristic (ROC) curve (AUC), sensitivity, specificity, and feature analysis of standard-view mammography for women presenting for screening mammography, diagnostic mammography, or breast biopsy. A total of 133 women were enrolled in this study at two European medical centers, with 67 women who had a pre-existing 10-36 months FFDM enrolled prospectively into the study and 66 women who underwent breast biopsy and had screening PCM and diagnostic FFDM, including standard craniocaudal and mediolateral oblique views of the breast with the lesion, enrolled retrospectively. The case mix consisted of 49 cancers, 17 biopsy-benign cases, and 67 normal cases. Sixteen radiologists participated in the reader study and interpreted all 133 cases in both conditions, separated by washout period of ≥4 weeks. ROC curve and free-response ROC curve analyses were performed for noninferiority of PCM compared to FFDM using a noninferiority margin Δ value of 0.10. Feature analysis of the 66 cases with lesions was conducted with all 16 readers at the conclusion of the blinded reads. Mean glandular dose was recorded for all cases. The AUC for PCM was 0.947 (95% confidence interval [CI], 0.920-0.974) and for FFDM was 0.931 (95% CI, 0.898-0.964). Sensitivity per case for PCM was 0.936 (95% CI, 0.897-0.976) and for FFDM was 0.908 (95% CI, 0.856-0.960). Specificity per case for PCM was 0.764 (95% CI, 0.688-0.841) and for FFDM was 0.749 (95% CI, 0.668-0.830). Free-response ROC curve figures of merit were 0.920 (95% CI, 0.881-0.959) and 0.903 (95% CI, 0.858-0.948) for PCM and FFDM, respectively. Sensitivity per lesion was 0.903 (95% CI, 0.846-0.960) and 0.883 (95% CI, 0.823-0.944) for PCM and FFDM, respectively. The average false-positive marks per image of noncancer cases were 0.265 (95% CI, 0.171-0.359) and 0.281 (95% CI, 0.188-0.374) for PCM and FFDM, respectively. Noninferiority P values for AUC, sensitivity (per case and per lesion), specificity, and average false-positive marks per image were all statistically significant (P < .001). The noninferiority P value for free-response ROC was <.025, from the 95% CI for the difference. Feature analysis resulted in PCM being preferred to FFDM by the readers for ≥70% of the cases. The average mean glandular dose for PCM was 0.74 mGy (95% CI, 0.722-0.759 mGy) and for FFDM was 1.23 mGy (95% CI, 1.199-1.262 mGy). In this study, radiologist performance with PCM was not inferior to that with conventional FFDM at an average 40% lower mean glandular dose. Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

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

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.

Exploring the utility of narrative analysis in diagnostic decision making: picture-bound reference, elaboration, and fetal alcohol spectrum disorders.

PubMed

Thorne, John C; Coggins, Truman E; Carmichael Olson, Heather; Astley, Susan J

2007-04-01

To evaluate classification accuracy and clinical feasibility of a narrative analysis tool for identifying children with a fetal alcohol spectrum disorder (FASD). Picture-elicited narratives generated by 16 age-matched pairs of school-aged children (FASD vs. typical development [TD]) were coded for semantic elaboration and reference strategy by judges who were unaware of age, gender, and group membership of the participants. Receiver operating characteristic (ROC) curves were used to examine the classification accuracy of the resulting set of narrative measures for making 2 classifications: (a) for the 16 children diagnosed with FASD, low performance (n = 7) versus average performance (n = 9) on a standardized expressive language task and (b) FASD (n = 16) versus TD (n = 16). Combining the rates of semantic elaboration and pragmatically inappropriate reference perfectly matched a classification based on performance on the standardized language task. More importantly, the rate of ambiguous nominal reference was highly accurate in classifying children with an FASD regardless of their performance on the standardized language task (area under the ROC curve = .863, confidence interval = .736-.991). Results support further study of the diagnostic utility of narrative analysis using discourse level measures of elaboration and children's strategic use of reference.

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

PubMed

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

2013-01-01

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

Development and Validation Study of the Internet Overuse Screening Questionnaire

PubMed Central

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

2018-01-01

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

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

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…

[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.

Positive and negative remember judgments and ROCs in the plurals paradigm: Evidence for alternative decision strategies

PubMed Central

Kapucu, Aycan; Macmillan, Neil A.; Rotello, Caren M.

2010-01-01

Using old-new ratings and remember-know judgments we explored the plurals paradigm, in which studied words must be distinguished from plurality-changed lures. The paradigm allowed us to investigate negative remembering, that is, the remembering of a plural-altered study item; capacity for this judgment was found to be poorer than or equivalent to the conventional positive remembering. A response-bias manipulation affected positive but not negative remembering. The ratings were used to construct ROC curves and test the prediction of the most common dual-process theory of recognition memory (Yonelinas, 2001) that the amount of recollection can be independently estimated from ROC curves and from remember judgments. By fitting the individual data with pure signal-detection (SDT) models and dual-process models that combined SDT and threshold components (HTSDT), we identified two types of subjects. For those who were better described by HTSDT, the predicted convergence of remember-know and ROC measures was observed. For those who were better described by SDT the ROC intercept could not predict the remember rate. The data are consistent with the idea that all subjects rely on the same representation but base their decisions on different partitions of a decision space. PMID:20551335

Predictive value of modeled AUC(AFP-hCG), a dynamic kinetic parameter characterizing serum tumor marker decline in patients with nonseminomatous germ cell tumor.

PubMed

You, Benoit; Fronton, Ludivine; Boyle, Helen; Droz, Jean-Pierre; Girard, Pascal; Tranchand, Brigitte; Ribba, Benjamin; Tod, Michel; Chabaud, Sylvie; Coquelin, Henri; Fléchon, Aude

2010-08-01

The early decline profile of alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG) in patients with nonseminomatous germ cell tumors (NSGCT) treated with chemotherapy may be related to the risk of relapse. We assessed the predictive values of areas under the curve of hCG (AUC(hCG)) and AFP (AUC(AFP)) of modeled concentration-time equations on progression-free survival (PFS). Single-center retrospective analysis of hCG and AFP time-points from 65 patients with IGCCCG intermediate-poor risk NSGCT treated with 4 cycles of bleomycin-etoposide-cisplatin (BEP). To determine AUC(hCG) and AUC(AFP) for D0-D42, AUCs for D0-D7 were calculated using the trapezoid rule and AUCs for D7-D42 were calculated using the mathematic integrals of equations modeled with NONMEM. Combining AUC(AFP) and AUC(hCG) enabled us to define 2 predictive groups: namely, patients with favorable and unfavorable AUC(AFP-hCG). Survival analyses and ROC curves assessed the predictive values of AUC(AFP-hCG) groups regarding progression-free survival (PFS) and compared them with those of half-life (HL) and time-to-normalization (TTN). Mono-exponential models best fit the patterns of marker decreases. Patients with a favorable AUC(AFP-hCG) had a significantly better PFS (100% vs 71.5%, P = .014). ROC curves confirmed the encouraging predictive accuracy of AUC(AFP-hCG) against HL or TTN regarding progression risk (ROC AUCs = 79.6 vs 71.9 and 70.2 respectively). Because of the large number of patients with missing data, multivariate analysis could not be performed. AUC(AFP-hCG) is a dynamic parameter characterizing tumor marker decline in patients with NSGCT during BEP treatment. Its value as a promising predictive factor should be validated. Copyright 2010 Elsevier Inc. All rights reserved.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

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

2014-01-01

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

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

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.

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.

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

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient.

PubMed

Xu, Xiao-Quan; Li, Yan; Hong, Xun-Ning; Wu, Fei-Yun; Shi, Hai-Bin

2017-02-01

To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). Diffusion-weighted (DW) images (b = 0 and 1000 s/mm 2 ) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC mean ), median ADC (ADC median ), 10th/25th/75th/90th percentile ADC (ADC 10 , ADC 25 , ADC 75 and ADC 90 ), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. Significant differences were found on the ADC mean , ADC median , ADC 10 , ADC 25 , ADC 75 and ADC 90 between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10 -3 mm 2 /s for the ADC 90 value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%). Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC 90 value was the most promising parameter for differentiating these two entities.

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.

Diagnostic performance of FDG PET or PET/CT in prosthetic infection after arthroplasty: a meta-analysis.

PubMed

Jin, H; Yuan, L; Li, C; Kan, Y; Hao, R; Yang, J

2014-03-01

The purpose of this study was to systematically review and perform a meta-analysis of published data regarding the diagnostic performance of positron emission tomography (PET) or PET/computed tomography (PET/CT) in prosthetic infection after arthroplasty. A comprehensive computer literature search of studies published through May 31, 2012 regarding PET or PET/CT in patients suspicious of prosthetic infection was performed in PubMed/MEDLINE, Embase and Scopus databases. Pooled sensitivity and specificity of PET or PET/CT in patients suspicious of prosthetic infection on a per prosthesis-based analysis were calculated. The area under the receiver-operating characteristic (ROC) curve was calculated to measure the accuracy of PET or PET/CT in patients with suspicious of prosthetic infection. Fourteen studies comprising 838 prosthesis with suspicious of prosthetic infection after arthroplasty were included in this meta-analysis. The pooled sensitivity of PET or PET/CT in detecting prosthetic infection was 86% (95% confidence interval [CI] 82-90%) on a per prosthesis-based analysis. The pooled specificity of PET or PET/CT in detecting prosthetic infection was 86% (95% CI 83-89%) on a per prosthesis-based analysis. The area under the ROC curve was 0.93 on a per prosthesis-based analysis. In patients suspicious of prosthetic infection, FDG PET or PET/CT demonstrated high sensitivity and specificity. FDG PET or PET/CT are accurate methods in this setting. Nevertheless, possible sources of false positive results and influcing factors should kept in mind.

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.

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

PubMed

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

2018-01-01

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

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.

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).

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.

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

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.

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

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.

Accuracy of optical spectroscopy for the detection of cervical intraepithelial neoplasia: Testing a device as an adjunct to colposcopy.

PubMed

Cantor, Scott B; Yamal, Jose-Miguel; Guillaud, Martial; Cox, Dennis D; Atkinson, E Neely; Benedet, John L; Miller, Dianne; Ehlen, Thomas; Matisic, Jasenka; van Niekerk, Dirk; Bertrand, Monique; Milbourne, Andrea; Rhodes, Helen; Malpica, Anais; Staerkel, Gregg; Nader-Eftekhari, Shahla; Adler-Storthz, Karen; Scheurer, Michael E; Basen-Engquist, Karen; Shinn, Eileen; West, Loyd A; Vlastos, Anne-Therese; Tao, Xia; Beck, J Robert; Macaulay, Calum; Follen, Michele

2011-03-01

Testing emerging technologies involves the evaluation of biologic plausibility, technical efficacy, clinical effectiveness, patient satisfaction, and cost-effectiveness. The objective of this study was to select an effective classification algorithm for optical spectroscopy as an adjunct to colposcopy and obtain preliminary estimates of its accuracy for the detection of CIN 2 or worse. We recruited 1,000 patients from screening and prevention clinics and 850 patients from colposcopy clinics at two comprehensive cancer centers and a community hospital. Optical spectroscopy was performed, and 4,864 biopsies were obtained from the sites measured, including abnormal and normal colposcopic areas. The gold standard was the histologic report of biopsies, read 2 to 3 times by histopathologists blinded to the cytologic, histopathologic, and spectroscopic results. We calculated sensitivities, specificities, receiver operating characteristic (ROC) curves, and areas under the ROC curves. We identified a cutpoint for an algorithm based on optical spectroscopy that yielded an estimated sensitivity of 1.00 [95% confidence interval (CI) = 0.92-1.00] and an estimated specificity of 0.71 [95% CI = 0.62-0.79] in a combined screening and diagnostic population. The positive and negative predictive values were 0.58 and 1.00, respectively. The area under the ROC curve was 0.85 (95% CI = 0.81-0.89). The per-patient and per-site performance were similar in the diagnostic and poorer in the screening settings. Like colposcopy, the device performs best in a diagnostic population. Alternative statistical approaches demonstrate that the analysis is robust and that spectroscopy works as well as or slightly better than colposcopy for the detection of CIN 2 to cancer. Copyright © 2010 UICC.

Deriving the reference value from the circadian motor active patterns in the "non-dementia" population, compared to the "dementia" population: What is the amount of physical activity conducive to the good circadian rhythm.

PubMed

Kodama, Ayuto; Kume, Yu; Tsugaruya, Megumi; Ishikawa, Takashi

2016-01-01

The circadian rhythm in older adults is commonly known to change with a decrease in physical activity. However, the association between circadian rhythm metrics and physical activity remains unclear. The objective of this study was to examine circadian activity patterns in older people with and without dementia and to determine the amount of physical activity conducive to a good circadian measurement. Circadian parameters were collected from 117 older community-dwelling people (66 subjects without dementia and 52 subjects with dementia); the parameters were measured continuously using actigraphy for 7 days. A receiver operating characteristic (ROC) curve was applied to determine reference values for the circadian rhythm parameters, consisting of interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA), in older subjects. The ROC curve revealed reference values of 0.55 for IS, 1.10 for IV, and 0.82 for RA. In addition, as a result of the ROC curve in the moderate-to-vigorous physical Activity (MVPA) conducive to the reference value of the Non-parametric Circadian Rhythm Analysis per day, the optimal reference values were 51 minutes for IV and 55 minutes for RA. However, the IS had no classification accuracy. Our results demonstrated the reference values derived from the circadian parameters of older Japanese population with or without dementia. Also, we determined the MVPA conducive to a good circadian rest-active pattern. This reference value for physical activity conducive to a good circadian rhythm might be useful for developing a new index for health promotion in the older community-dwelling population.

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

PubMed

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

2016-02-01

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

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…

Matched Filter Stochastic Background Characterization for Hyperspectral Target Detection

DTIC Science & Technology

2005-09-30

and Pre- Clustering MVN Test.....................126 4.2.3 Pre- Clustering Detection Results.................................................130...4.2.4 Pre- Clustering Target Influence..................................................134 4.2.5 Statistical Distance Exclusion and Low Contrast...al, 2001] Figure 2.7 ROC Curve Comparison of RX, K-Means, and Bayesian Pre- Clustering Applied to Anomaly Detection [Ashton, 1998] Figure 2.8 ROC

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

PubMed

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

2018-01-01

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

Bishop score and ultrasound assessment of the cervix for prediction of time to onset of labor and time to delivery in prolonged pregnancy.

PubMed

Strobel, E; Sladkevicius, P; Rovas, L; De Smet, F; Karlsson, E Dejin; Valentin, L

2006-09-01

To determine the ability of Bishop score and sonographic cervical length to predict time to spontaneous onset of labor and time to delivery in prolonged pregnancy. Ninety-seven women underwent transvaginal ultrasound examination and palpation of the cervix at 291-296 days' gestation according to ultrasound fetometry at 12-20 weeks' gestation. Sonographic cervical length and Bishop score were recorded. Multivariate logistic regression analysis was used to determine which variables were independent predictors of the onset of labor/delivery < or = 24 h, < or = 48 h, and < or = 96 h. Receiver-operating characteristics (ROC) curves were drawn to assess diagnostic performance. In nulliparous women (n = 45), both Bishop score and sonographic cervical length predicted the onset of labor/delivery < or = 24 h and < or = 48 h (area under ROC curve for the onset of labor < or = 24 h 0.79 vs. 0.80, P = 0.94; for delivery < or = 24 h 0.81 vs. 0.85, P = 0.64; for the onset of labor < or = 48 h 0.73 vs. 0.74, P = 0.90; for delivery < or = 48 h 0.77 vs. 0.71, P = 0.50). Only Bishop score discriminated between nulliparous women who went into labor/delivered < or = 96 h or > 96 h. A logistic regression model including Bishop score and cervical length was superior to Bishop score alone in predicting delivery < or = 24 h (area under ROC curve 0.93 vs. 0.81, P = 0.03) and superior to Bishop score alone and cervical length alone in predicting the onset of labor < or = 24 h (area under ROC curve 0.90 vs. 0.79, P = 0.06; and 0.90 vs. 0.80, P = 0.06). In parous women (n = 52), Bishop score and sonographic cervical length predicted the onset of labor/delivery < or = 24 h (area under ROC curve for the onset of labor 0.75 vs. 0.69, P = 0.49; for delivery 0.74 vs. 0.70, P = 0.62), but only Bishop score discriminated between women who went into labor/delivered < or = 48 h and > 48 h. Three parous women had not gone into labor and six had not given birth at 96 h. In parous women logistic regression models including both Bishop score and cervical length did not substantially improve prediction of the time to onset of labor/delivery. In prolonged pregnancy Bishop score and sonographic cervical length have a similar ability to predict the time to the onset of labor and delivery. In nulliparous women the use of logistic regression models including Bishop score and cervical length is likely to offer better prediction of the onset of labor/delivery < or = 24 h than the use of the Bishop score alone. Copyright 2006 ISUOG. Published by John Wiley & Sons, Ltd.

A Perceptual Repetition Blindness Effect

NASA Technical Reports Server (NTRS)

Hochhaus, Larry; Johnston, James C.; Null, Cynthia H. (Technical Monitor)

1994-01-01

Before concluding Repetition Blindness is a perceptual phenomenon, alternative explanations based on memory retrieval problems and report bias must be rejected. Memory problems were minimized by requiring a judgment about only a single briefly displayed field. Bias and sensitivity effects were empirically measured with an ROC-curve analysis method based on confidence ratings. Results from five experiments support the hypothesis that Repetition Blindness can be a perceptual phenomenon.

The Incorporation of ICT in Higher Education. The Contribution of ROC Curves in the Graphic Visualization of Differences in the Analysis of the Variables

ERIC Educational Resources Information Center

Munoz-Repiso, Ana Garcia-Valcarcel; Tejedor, Francisco Javier Tejedor

2012-01-01

This paper has focused on the productive use of information and communications technology (ICT) by university students and its influence on academic performance. The objective is to determine whether a comparison of successful and non-successful students (in relation to academic achievements) versus the variables studied (linked to the process of…

Urine colorimetry for therapeutic drug monitoring of pyrazinamide during tuberculosis treatment.

PubMed

Zentner, Isaac; Modongo, Chawangwa; Zetola, Nicola M; Pasipanodya, Jotam G; Srivastava, Shashikant; Heysell, Scott K; Mpagama, Stellah; Schlect, Hans P; Gumbo, Tawanda; Bisson, Gregory P; Vinnard, Christopher

2018-03-01

Pyrazinamide is a key drug in the first-line treatment regimen for tuberculosis, with a potent sterilizing effect. Although low pyrazinamide peak serum concentrations (C max ) are associated with poor treatment outcomes, many resource-constrained settings do not have sufficient laboratory capacity to support therapeutic drug monitoring (TDM). The objective of this study was to determine whether a colorimetric test of urine can identify tuberculosis patients with adequate pyrazinamide exposures, as defined by serum C max above a target threshold. In the derivation study of healthy volunteers, three dose sizes of pyrazinamide were evaluated, and intensive pharmacokinetic blood sampling was performed over an 8-h period, with a timed urine void at 4h post-dosing. Pyrazinamide in urine was isolated by spin column centrifugation with an exchange resin, followed by colorimetric analysis; the absorbance peak at 495nm was measured. The urine assay was then evaluated in a study of 39 HIV/tuberculosis patients in Botswana enrolled in an intensive pharmacokinetic study. Receiver operating characteristics (ROC) curves were used to measure diagnostic accuracy. The guideline-recommended pyrazinamide serum C max target of 35mg/l was evaluated in the primary analysis; this target was found to be predictive of favorable outcomes in a clinical study. Following this, a higher serum C max target of 58mg/l was evaluated in the secondary analysis. At the optimal cut-off identified in the derivation sample, the urine colorimetric assay was 97% sensitive and 50% specific to identify 35 of 39 HIV/tuberculosis patients with pharmacokinetic target attainment, with an area under the ROC curve of 0.81 (95% confidence interval 0.60-0.97). Diagnostic accuracy was lower at the 58mg/l serum C max target, with an area under the ROC curve of 0.68 (95% confidence interval 0.48-0.84). Men were less likely than women to attain either serum pharmacokinetic target. The urine colorimetric assay was sensitive but not specific for the detection of adequate pyrazinamide pharmacokinetic exposures among HIV/tuberculosis patients in a high-burden setting. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Diagnostic value of the plasmatic ADM level for early ectopic pregnancy.

PubMed

Yan, Qi; Lu, Qi; Tao, Yu; Wang, Yu-Dong; Zhao, Wen-Xia

2015-01-01

To analyze the plasmatic ADM level in early pregnancy and to investigate the diagnostic value of ADM in early ectopic pregnancy (EP). 70 patients with EP who had menopause for 5~8 weeks were included as study group, while 155 women with normal intrauterine pregnancy were also included as control group. The correlation between ADM level and menopause weeks was statistically analyzed and ROC curve was used to identify the diagnostic value of ADM. (1) In 155 cases of normal intrauterine pregnancy, the plasmatic ADM level was increased with menopause weeks in linear relationship, and the correlation coefficient (R) was 0.991 (P<0.05). In 70 patients with EP, no significant increase was found with menopause weeks and no linear relationship can be found between ADM level and menopause weeks in EP group. The correlation coefficient (R) was 0.744 (P>0.05). (2) The multiple of median of plasmatic ADM level in EP group of menopause for 8 weeks was obviously lower than the intrauterine control group (P<0.01). (3) ROC curve was used to analyze the cut-off value of ADM level in the diagnosis of EP, and the area under the ROC curve was 0.523 (P>0.05) regardless of menopause weeks, however, the area under the ROC curve was 0.702 (P<0.05) at 8 weeks after menopause with sensitivity of 53.50% and specificity of 85.00%. Different from normal intrauterine pregnancy, plasmatic ADM level in early EP was relatively lower and no significant increase was found with menopause weeks; further studies are still needed for plasmatic ADM level as an indicator in the early diagnosis of EP.

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.

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.

Application of texture analysis method for classification of benign and malignant thyroid nodules in ultrasound images.

PubMed

Abbasian Ardakani, Ali; Gharbali, Akbar; Mohammadi, Afshin

2015-01-01

The aim of this study was to evaluate computer aided diagnosis (CAD) system with texture analysis (TA) to improve radiologists' accuracy in identification of thyroid nodules as malignant or benign. A total of 70 cases (26 benign and 44 malignant) were analyzed in this study. We extracted up to 270 statistical texture features as a descriptor for each selected region of interests (ROIs) in three normalization schemes (default, 3s and 1%-99%). Then features by the lowest probability of classification error and average correlation coefficients (POE+ACC), and Fisher coefficient (Fisher) eliminated to 10 best and most effective features. These features were analyzed under standard and nonstandard states. For TA of the thyroid nodules, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA) were applied. First Nearest-Neighbour (1-NN) classifier was performed for the features resulting from PCA and LDA. NDA features were classified by artificial neural network (A-NN). Receiver operating characteristic (ROC) curve analysis was used for examining the performance of TA methods. The best results were driven in 1-99% normalization with features extracted by POE+ACC algorithm and analyzed by NDA with the area under the ROC curve ( Az) of 0.9722 which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Our results indicate that TA is a reliable method, can provide useful information help radiologist in detection and classification of benign and malignant thyroid nodules.

Acoustic cue weighting in the singleton vs geminate contrast in Lebanese Arabic: The case of fricative consonants.

PubMed

Al-Tamimi, Jalal; Khattab, Ghada

2015-07-01

This paper is the first reported investigation of the role of non-temporal acoustic cues in the singleton-geminate contrast in Lebanese Arabic, alongside the more frequently reported temporal cues. The aim is to explore the extent to which singleton and geminate consonants show qualitative differences in a language where phonological length is prominent and where moraic structure governs segment timing and syllable weight. Twenty speakers (ten male, ten female) were recorded producing trochaic disyllables with medial singleton and geminate fricatives preceded by phonologically short and long vowels. The following acoustic measures were applied on the medial fricative and surrounding vowels: absolute duration; intensity; fundamental frequency; spectral peak and shape, dynamic amplitude, and voicing patterns of medial fricatives; and vowel quality and voice quality correlates of surrounding vowels. Discriminant analysis and receiver operating characteristics (ROC) curves were used to assess each acoustic cue's contribution to the singleton-geminate contrast. Classification rates of 89% and ROC curves with an area under the curve rate of 96% confirmed the major role played by temporal cues, with non-temporal cues contributing to the contrast but to a much lesser extent. These results confirm that the underlying contrast for gemination in Arabic is temporal, but highlight [+tense] (fortis) as a secondary feature.

GPU-based prompt gamma ray imaging from boron neutron capture therapy.

PubMed

Yoon, Do-Kun; Jung, Joo-Young; Jo Hong, Key; Sil Lee, Keum; Suk Suh, Tae

2015-01-01

The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU). Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray image reconstruction using the GPU computation for BNCT simulations.

Assessment of single-item literacy questions, age, and education level in the prediction of low health numeracy.

PubMed

Johnson, Tim V; Abbasi, Ammara; Kleris, Renee S; Ehrlich, Samantha S; Barthwaite, Echo; DeLong, Jennifer; Master, Viraj A

2013-08-01

Determining a patient's health literacy is important to optimum patient care. Single-item questions exist for screening written health literacy. We sought to assess the predictive potential of three common screening questions, along with patient age and education level, in the prediction of low health numerical literacy (numeracy). After demographic and educational information was obtained, 441 patients were administered three health literacy screening questions. The three-item Schwartz-Woloshin Numeracy Scale was then administered to assess for low health numeracy (score of 0 out of 3). This score served as the reference standard for Receiver Operating Characteristics (ROC) curve analysis. ROC curves were constructed and used to determine the area under the curve (AUC); a higher AUC suggests increased statistical significance. None of the three screening questions were significant predictors of low health numeracy. However, education level was a significant predictor of low health numeracy, with an AUC (95% CI) of 0.811 (0.720-0.902). This measure had a specificity of 95.3% at the cutoff of 12 years of education (<12 versus > or = 12 years of education) but was non-sensitive. Common single-item questions used to screen for written health literacy are ineffective screening tools for health numeracy. However, low education level is a specific predictor of low health numeracy.

Screening for Sleep Apnoea in Mild Cognitive Impairment: The Utility of the Multivariable Apnoea Prediction Index

PubMed Central

Wilson, Georgina; Terpening, Zoe; Wong, Keith; Grunstein, Ron; Norrie, Louisa; Lewis, Simon J. G.; Naismith, Sharon L.

2014-01-01

Purpose. Mild cognitive impairment (MCI) is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA) is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI), a patient self-report survey, to assess OSA in MCI. Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG). Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI). Receiver-operating characteristics (ROC) curve analyses were performed using various cut-off scores for apnoea severity. Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI: r = 0.47, P = 0.017). However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC) in the MCI sample compared to the controls across all AHI severity cut-off scores. Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI. PMID:24551457

The Total Urine Protein-to-Creatinine Ratio Can Predict the Presence of Microalbuminuria

PubMed Central

Yamamoto, Kyoko; Yamamoto, Hiroyuki; Yoshida, Katsumi; Niwa, Koichiro; Nishi, Yutaro; Mizuno, Atsushi; Kuwabara, Masanari; Asano, Taku; Sakoda, Kunihiro; Niinuma, Hiroyuki; Nakahara, Fumiko; Takeda, Kyoko; Shindoh, Chiyohiko; Komatsu, Yasuhiro

2014-01-01

Background The Kidney Disease: Improving Global Outcomes chronic kidney disease (CKD) guidelines recommend that CKD be classified based on the etiology, glomerular filtration rate (GFR) and degree of albuminuria. The present study aimed to establish a method that predicts the presence of microalbuminuria by measuring the total urine protein-to-creatinine ratio (TPCR) in patients with cardiovascular disease (CVD) risk factors. Methods and Results We obtained urine samples from 1,033 patients who visited the cardiovascular clinic at St. Luke's International Hospital from February 2012 to August 2012. We measured the TPCR and the urine albumin-to-creatinine ratio (ACR) from random spot urine samples. We performed correlation, receiver operating characteristic (ROC) curve, sensitivity, and subgroup analyses. There was a strong positive correlation between the TPCR and ACR (R2 = 0.861, p<0.001). A ROC curve analysis for the TPCR revealed a sensitivity of 94.4%, a specificity of 86.1%, and an area under the curve of 0.903 for detecting microalbuminuria for a TPCR cut-off value of 84 mg/g of creatinine. The subgroup analysis indicated that the cut-off value could be used for patients with CVD risk factors. Conclusions These results suggest that the TPCR with an appropriate cut-off value could be used to screen for the presence of microalbuminuria in patients with CVD risk factors. This simple, inexpensive measurement has broader applications, leading to earlier intervention and public benefit. PMID:24614247

Is being female a risk factor for shallow anterior chamber? The associations between anterior chamber depth and age, sex, and body height

PubMed Central

Hsu, Wei-Cherng; Shen, Elizabeth P; Hsieh, Yi-Ting

2014-01-01

Aim of Study: To analyze the association between anterior chamber depth (ACD) and age, sex, and body height (BH). Materials and Methods: One thousand four hundred eighty eyes of 1480 adults 40 years of age and older receiving preoperative evaluation for cataract surgery were recruited consecutively from June 1, 2006, to December 31, 2010. ACD was measured with the Zeiss IOLMaster. Univariate and multivariate linear regression models were used to analyze the correlations, and receiving operator characteristic (ROC) curves and the area under the curve (AUC) were used for evaluating the predictability of an ACD less than 2.70 mm. Results: ACD was negatively correlated with age and positively correlated with BH in both univariate and multivariate regression analysis (P < 0.001). Sex was associated with ACD in univariate analysis, but not after adjustment with age and BH. In predicting an ACD less than 2.70 mm, the AUCs of ROC curves for ‘age and sex’, ‘age and BH’, and ‘age, sex, and BH’ were 0.687, 0.689, and 0.689, respectively. Conclusion: Age and BH were independent associating factors of ACD; however, sex was not. Older people and shorter ones likely had shallower ACD, and therefore were predisposed to Primary angle closure glaucoma (PACG). The predictability of ACD by age and BH solely was low, and adding sex did not increase it. PMID:24145564

[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.

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.

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

Peripheral Venous Waveform Analysis for Detecting Hemorrhage and Iatrogenic Volume Overload in a Porcine Model.

PubMed

Hocking, Kyle M; Sileshi, Ban; Baudenbacher, Franz J; Boyer, Richard B; Kohorst, Kelly L; Brophy, Colleen M; Eagle, Susan S

2016-10-01

Unrecognized hemorrhage and unguided resuscitation is associated with increased perioperative morbidity and mortality. The authors investigated peripheral venous waveform analysis (PIVA) as a method for quantitating hemorrhage as well as iatrogenic fluid overload during resuscitation. The authors conducted a prospective study on Yorkshire Pigs (n = 8) undergoing hemorrhage, autologous blood return, and administration of balanced crystalloid solution beyond euvolemia. Intra-arterial blood pressure, electrocardiogram, and pulse oximetry were applied to each subject. Peripheral venous pressure was measured continuously through an upper extremity standard peripheral IV catheter and analyzed with LabChart. The primary outcome was comparison of change in the first fundamental frequency (f1) of PIVA with standard and invasive monitoring and shock index (SI). Hemorrhage, return to euvolemia, and iatrogenic fluid overload resulted in significantly non-zero slopes of f1 amplitude. There were no significant differences in heart rate or mean arterial pressure, and a late change in SI. For the detection of hypovolemia the PIVA f1 amplitude change generated an receiver operator curves (ROC) curve with an area under the curve (AUC) of 0.93; heart rate AUC = 0.61; mean arterial pressure AUC = 0.48, and SI AUC = 0.72. For hypervolemia the f1 amplitude generated an ROC curve with an AUC of 0.85, heart rate AUC = 0.62, mean arterial pressure AUC = 0.63, and SI AUC = 0.65. In this study, PIVA demonstrated a greater sensitivity for detecting acute hemorrhage, return to euvolemia, and iatrogenic fluid overload compared with standard monitoring and SI. PIVA may provide a low-cost, minimally invasive monitoring solution for monitoring and resuscitating patients with perioperative hemorrhage.

Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

NASA Astrophysics Data System (ADS)

Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

2017-08-01

We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  <  0.0001). Survival analysis on immunohistochemical subgroups shows significant separation for the estrogen-receptor subtype tumors (P  <  0.0001) and the triple-negative subtype tumors (P  =  0.0039), but not for tumors of the HER2 subtype (P  =  0.41). The results of this retrospective study show the potential of early-stage pre-treatment eigentumors for use in prediction of treatment failure of breast cancer.

Usefulness of Cellular Analysis of Bronchoalveolar Lavage Fluid for Predicting the Etiology of Pneumonia in Critically Ill Patients

PubMed Central

Hong, Hyo-Lim; Kim, Sung-Han; Huh, Jin Won; Sung, Heungsup; Lee, Sang-Oh; Kim, Mi-Na; Jeong, Jin-Yong; Lim, Chae-Man; Kim, Yang Soo; Woo, Jun Hee; Koh, Younsuck

2014-01-01

Background The usefulness of bronchoalveolar lavage (BAL) fluid cellular analysis in pneumonia has not been adequately evaluated. This study investigated the ability of cellular analysis of BAL fluid to differentially diagnose bacterial pneumonia from viral pneumonia in adult patients who are admitted to intensive care unit. Methods BAL fluid cellular analysis was evaluated in 47 adult patients who underwent bronchoscopic BAL following less than 24 hours of antimicrobial agent exposure. The abilities of BAL fluid total white blood cell (WBC) counts and differential cell counts to differentiate between bacterial and viral pneumonia were evaluated using receiver operating characteristic (ROC) curve analysis. Results Bacterial pneumonia (n = 24) and viral pneumonia (n = 23) were frequently associated with neutrophilic pleocytosis in BAL fluid. BAL fluid median total WBC count (2,815/µL vs. 300/µL, P<0.001) and percentage of neutrophils (80.5% vs. 54.0%, P = 0.02) were significantly higher in the bacterial pneumonia group than in the viral pneumonia group. In ROC curve analysis, BAL fluid total WBC count showed the best discrimination, with an area under the curve of 0.855 (95% CI, 0.750–0.960). BAL fluid total WBC count ≥510/µL had a sensitivity of 83.3%, specificity of 78.3%, positive likelihood ratio (PLR) of 3.83, and negative likelihood ratio (NLR) of 0.21. When analyzed in combination with serum procalcitonin or C-reactive protein, sensitivity was 95.8%, specificity was 95.7%, PLR was 8.63, and NLR was 0.07. BAL fluid total WBC count ≥510/µL was an independent predictor of bacterial pneumonia with an adjusted odds ratio of 13.5 in multiple logistic regression analysis. Conclusions Cellular analysis of BAL fluid can aid early differential diagnosis of bacterial pneumonia from viral pneumonia in critically ill patients. PMID:24824328

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

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

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

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

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

2014-01-15

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

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

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.

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.

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

PubMed

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

2017-02-01

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

Corneal Structural Changes in Nonneoplastic and Neoplastic Monoclonal Gammopathies.

PubMed

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

2016-05-01

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

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Association between Serum Cystatin C and Diabetic Foot Ulceration in Patients with Type 2 Diabetes: A Cross-Sectional Study

PubMed Central

Zhao, Jie; Deng, Wuquan; Zhang, Yuping; Zheng, Yanling; Zhou, Lina; Boey, Johnson; Armstrong, David G.; Yang, Gangyi

2016-01-01

Serum cystatin C (CysC) has been identified as a possible potential biomarker in a variety of diabetic complications, including diabetic peripheral neuropathy and peripheral artery disease. We aimed to examine the association between CysC and diabetic foot ulceration (DFU) in patients with type 2 diabetes (T2D). 411 patients with T2D were enrolled in this cross-sectional study at a university hospital. Clinical manifestations and biochemical parameters were compared between DFU group and non-DFU group. The association between serum CysC and DFU was explored by binary logistic regression analysis. The cut point of CysC for DFU was also evaluated by receiver operating characteristic (ROC) curve. The prevalence of coronary artery disease, diabetic nephropathy (DN), and DFU dramatically increased with CysC (P < 0.01) in CysC quartiles. Multivariate logistic regression analysis indicated that the significant risk factors for DFU were serum CysC, coronary artery disease, hypertension, insulin use, the differences between supine and sitting TcPO2, and hypertension. ROC curve analysis revealed that the cut point of CysC for DFU was 0.735 mg/L. Serum CysC levels correlated with DFU and severity of tissue loss. Our study results indicated that serum CysC was associated with a high prevalence of DFU in Chinese T2D subjects. PMID:27668262

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Responsiveness of SF-36 and Lower Extremity Functional Scale for assessing outcomes in traumatic injuries of lower extremities.

PubMed

Pan, Shin-Liang; Liang, Huey-Wen; Hou, Wen-Hsuan; Yeh, Tian-Shin

2014-11-01

To assess the responsiveness of one generic questionnaire, Medical Outcomes Study Short Form-36 (SF-36), and one region-specific outcome measure, Lower Extremity Functional Scale (LEFS), in patients with traumatic injuries of lower extremities. A prospective and observational study of patients after traumatic injuries of lower extremities. Assessments were performed at baseline and 3 months later. In-patients and out-patients in two university hospitals in Taiwan. A convenience sample of 109 subjects were evaluated and 94 (86%) were followed. Not applicable. Assessments of responsiveness with distribution-based approach (effect size, standardized response mean [SRM], minimal detectable change) and anchor-based approach (receiver's operating curve analysis, ROC analysis). LEFS and physical component score (PCS) of SF-36 were all responsive to global improvement, with fair-to-good accuracy in discriminating between participants with and without improvement. The area under curve gained by ROC analysis for LEFS and SF-36 PCS was similar (0.65 vs. 0.70, p=0.26). Our findings revealed comparable responsiveness of LEFS and PCS of SF-36 in a sample of subjects with traumatic injuries of lower limbs. Either type of functional measure would be suitable for use in clinical trials where improvement in function was an endpoint of interest. Copyright © 2014 Elsevier Ltd. All rights reserved.

Can unaided non-linguistic measures predict cochlear implant candidacy?

PubMed Central

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

2014-01-01

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

Factors associated with an inadequate hypoglycemia in the insulin tolerance test in Japanese patients with suspected or proven hypopituitarism.

PubMed

Takahashi, Kiyohiko; Nakamura, Akinobu; Miyoshi, Hideaki; Nomoto, Hiroshi; Kameda, Hiraku; Cho, Kyu Yong; Nagai, So; Shimizu, Chikara; Taguri, Masataka; Terauchi, Yasuo; Atsumi, Tatsuya

2017-04-29

We attempted to identify the predictors of an inadequate hypoglycemia in insulin tolerance test (ITT), defined as a blood glucose level higher than 2.8 mmol/L after insulin injection, in Japanese patients with suspected or proven hypopituitarism. A total of 78 patients who had undergone ITT were divided into adequate and inadequate hypoglycemia groups. The relationships between the subjects' clinical parameters and inadequate hypoglycemia in ITT were analyzed. Stepwise logistic regression analysis identified high systolic blood pressure (SBP) and high homeostasis model assessment of insulin resistance (HOMA-IR) as being independent factors associated with inadequate hypoglycemia in ITT. Receiver operating characteristic (ROC) curve analysis revealed the cutoff value for inadequate hypoglycemia was 109 mmHg for SBP and 1.4 for HOMA-IR. The areas under ROC curve for SBP and HOMA-IR were 0.72 and 0.86, respectively. We confirmed that high values of SBP and HOMA-IR were associated with inadequate hypoglycemia in ITT, regardless of the degree of reduction of pituitary hormone levels. Furthermore, the strongest predictor of inadequate hypoglycemia was obtained by using the cutoff value of HOMA-IR. Our results suggest that HOMA-IR is a useful pre-screening tool for ITT in these populations.

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

PubMed

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

2018-06-01

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

Quantitative analysis of iris parameters in keratoconus patients using optical coherence tomography.

PubMed

Bonfadini, Gustavo; Arora, Karun; Vianna, Lucas M; Campos, Mauro; Friedman, David; Muñoz, Beatriz; Jun, Albert S

2015-01-01

To investigate the relationship between quantitative iris parameters and the presence of keratoconus. Cross-sectional observational study that included 15 affected eyes of 15 patients with keratoconus and 26 eyes of 26 normal age- and sex-matched controls. Iris parameters (area, thickness, and pupil diameter) of affected and unaffected eyes were measured under standardized light and dark conditions using anterior segment optical coherence tomography (AS-OCT). To identify optimal iris thickness cutoff points to maximize the sensitivity and specificity when discriminating keratoconus eyes from normal eyes, the analysis included the use of receiver operating characteristic (ROC) curves. Iris thickness and area were lower in keratoconus eyes than in normal eyes. The mean thickness at the pupillary margin under both light and dark conditions was found to be the best parameter for discriminating normal patients from keratoconus patients. Diagnostic performance was assessed by the area under the ROC curve (AROC), which had a value of 0.8256 with 80.0% sensitivity and 84.6% specificity, using a cutoff of 0.4125 mm. The sensitivity increased to 86.7% when a cutoff of 0.4700 mm was used. In our sample, iris thickness was lower in keratoconus eyes than in normal eyes. These results suggest that tomographic parameters may provide novel adjunct approaches for keratoconus screening.

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.

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.

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.

3D quantitative breast ultrasound analysis for differentiating fibroadenomas and carcinomas smaller than 1cm.

PubMed

Meel-van den Abeelen, A S S; Weijers, G; van Zelst, J C M; Thijssen, J M; Mann, R M; de Korte, C L

2017-03-01

In (3D) ultrasound, accurate discrimination of small solid masses is difficult, resulting in a high frequency of biopsies for benign lesions. In this study, we investigate whether 3D quantitative breast ultrasound (3DQBUS) analysis can be used for improving non-invasive discrimination between benign and malignant lesions. 3D US studies of 112 biopsied solid breast lesions (size <1cm), were included (34 fibroadenomas and 78 invasive ductal carcinomas). The lesions were manually delineated and, based on sonographic criteria used by radiologists, 3 regions of interest were defined in 3D for analysis: ROI (ellipsoid covering the inside of the lesion), PER (peritumoural surrounding: 0.5mm around the lesion), and POS (posterior-tumoural acoustic phenomena: region below the lesion with the same size as delineated for the lesion). After automatic gain correction (AGC), the mean and standard deviation of the echo level within the regions were calculated. For the ROI and POS also the residual attenuation coefficient was estimated in decibel per cm [dB/cm]. The resulting eight features were used for classification of the lesions by a logistic regression analysis. The classification accuracy was evaluated by leave-one-out cross-validation. Receiver operating characteristic (ROC) curves were constructed to assess the performance of the classification. All lesions were delineated by two readers and results were compared to assess the effect of the manual delineation. The area under the ROC curve was 0.86 for both readers. At 100% sensitivity, a specificity of 26% and 50% was achieved for reader 1 and 2, respectively. Inter-reader variability in lesion delineation was marginal and did not affect the accuracy of the technique. The area under the ROC curve of 0.86 was reached for the second reader when the results of the first reader were used as training set yielding a sensitivity of 100% and a specificity of 40%. Consequently, 3DQBUS would have achieved a 40% reduction in biopsies for benign lesions for reader 2, without a decrease in sensitivity. This study shows that 3DQBUS is a promising technique to classify suspicious breast lesions as benign, potentially preventing unnecessary biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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.

Bayes’ theorem, the ROC diagram and reference values: Definition and use in clinical diagnosis

PubMed Central

Kallner, Anders

2017-01-01

Medicine is diagnosis, treatment and care. To diagnose is to consider the probability of the cause of discomfort experienced by the patient. The physician may face many options and all decisions are liable to uncertainty to some extent. The rational action is to perform selected tests and thereby increase the pre-test probability to reach a superior post-test probability of a particular option. To draw the right conclusions from a test, certain background information about the performance of the test is necessary. We set up a partially artificial dataset with measured results obtained from the laboratory information system and simulated diagnosis attached. The dataset is used to explore the use of contingency tables with a unique graphic design and software to establish and compare ROC graphs. The loss of information in the ROC curve is compensated by a cumulative data analysis (CDA) plot linked to a display of the efficiency and predictive values. A standard for the contingency table is suggested and the use of dynamic reference intervals discussed. PMID:29209139

Influence of optic disc size on the diagnostic performance of macular ganglion cell complex and peripapillary retinal nerve fiber layer analyses in glaucoma.

PubMed

Cordeiro, Daniela Valença; Lima, Verônica Castro; Castro, Dinorah P; Castro, Leonardo C; Pacheco, Maria Angélica; Lee, Jae Min; Dimantas, Marcelo I; Prata, Tiago Santos

2011-01-01

To evaluate the influence of optic disc size on the diagnostic accuracy of macular ganglion cell complex (GCC) and conventional peripapillary retinal nerve fiber layer (pRNFL) analyses provided by spectral domain optical coherence tomography (SD-OCT) in glaucoma. Eighty-two glaucoma patients and 30 healthy subjects were included. All patients underwent GCC (7 × 7 mm macular grid, consisting of RNFL, ganglion cell and inner plexiform layers) and pRNFL thickness measurement (3.45 mm circular scan) by SD-OCT. One eye was randomly selected for analysis. Initially, receiver operating characteristic (ROC) curves were generated for different GCC and pRNFL parameters. The effect of disc area on the diagnostic accuracy of these parameters was evaluated using a logistic ROC regression model. Subsequently, 1.5, 2.0, and 2.5 mm(2) disc sizes were arbitrarily chosen (based on data distribution) and the predicted areas under the ROC curves (AUCs) and sensitivities were compared at fixed specificities for each. Average mean deviation index for glaucomatous eyes was -5.3 ± 5.2 dB. Similar AUCs were found for the best pRNFL (average thickness = 0.872) and GCC parameters (average thickness = 0.824; P = 0.19). The coefficient representing disc area in the ROC regression model was not statistically significant for average pRNFL thickness (-0.176) or average GCC thickness (0.088; P ≥ 0.56). AUCs for fixed disc areas (1.5, 2.0, and 2.5 mm(2)) were 0.904, 0.891, and 0.875 for average pRNFL thickness and 0.834, 0.842, and 0.851 for average GCC thickness, respectively. The highest sensitivities - at 80% specificity for average pRNFL (84.5%) and GCC thicknesses (74.5%) - were found with disc sizes fixed at 1.5 mm(2) and 2.5 mm(2). Diagnostic accuracy was similar between pRNFL and GCC thickness parameters. Although not statistically significant, there was a trend for a better diagnostic accuracy of pRNFL thickness measurement in cases of smaller discs. For GCC analysis, an inverse effect was observed.

The Prognostic Role of Angiotensin II Type 1 Receptor Autoantibody in Non-Gravid Hypertension and Pre-eclampsia

PubMed Central

Lei, Jinghui; Li, Yafeng; Zhang, Suli; Wu, Ye; Wang, Pengli; Liu, Huirong

2016-01-01

Abstract Angiotensin II type 1 receptor autoantibody (AT1-AA) is found in patients with non-gravid hypertension or pre-eclampsia, but the relationship is uncertain. The aim of the present study was to assess the association between AT1-AA and high blood pressure using meta-analysis, and to evaluate the prognosis value of AT1-AA for hypertensive diseases. Literature search from PubMed, Embase, and Cochrane databases were conducted using keywords “hypertension” or “pre-eclampsia,” “angiotensin II receptor type 1 autoantibody,” and its aliases from April 1999 to December 2015. Studies evaluating the association between AT1-AA and non-gravid hypertension or pre-eclampsia were included in this analysis. The quality of the eligible studies was assessed based on the Newcastle–Ottawa Scale with some modifications. Two researchers then independently reviewed all included studies and extracted all relevant data. Association between AT1-AA and hypertension was tested with pooled odds ratios (ORs) and 95% confidence intervals (CIs). Finally, we evaluated whether AT1-AA predicted the prognosis of hypertension by using a summary receiver-operating characteristic (ROC) curve and sensitivity analysis. Ten studies were finally included in this meta-analysis. AT1-AA showed more significant association with pre-eclampsia than that with non-gravid hypertension (pooled OR 32.84, 95% CI 17.19–62.74; and pooled OR 4.18, 95% CI 2.20–7.98, respectively). Heterogeneity among studies was also detected probably due to different hypertensive subtypes and AT1-AA measuring methods. Area under summary ROC curve (AUC) of pre-eclampsia was 0.92 (sensitivity 0.76; specificity 0.86). Area under the ROC curve of overall hypertensive diseases or non-gravid hypertension was lower than that of pre-eclampsia (0.86 and 0.72, respectively) with lower sensitivities (0.46 and 0.26, respectively). The major limitation of this analysis was the publication bias due to lack of unpublished data and the language limitation during literature search. Prospective study with large simple size and specific measuring data collection are needed to enhance our findings in the future. Our analysis confirms that elevated AT1-AA in serum is significantly associated with hypertensive disorder, especially pre-eclampsia. AT1-AA may be a valuable indicator for poorer prognosis of patients with pre-eclampsia, and could be used in patients with hypertensive disease for risk evaluation and making individual treatment decision. PMID:27124051

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.

Preoperative serum alkaline phosphatase: a predictive factor for early hypocalcaemia following parathyroidectomy of primary hyperparathyroidism.

PubMed

Sun, Longhao; He, Xianghui; Liu, Tong

2014-01-01

Postoperative hypocalcemia is one of the most common complications following parathyroidectomy for primary hyperparathyroidism (PHPT). The aim of this study was to analyze the predictive value of biochemical parameters as indicators for episodes of hypocalcemia in patients undergoing parathyroidectomy for PHPT. The patients with PHPT who underwent parathyroidectomy between February 2004 and February 2014 were studied retrospectively at a single medical center. The patients were divided into biochemical, clinical, and no postoperative hypocalcemia groups, based on different clinical manifestations. Potential risk factors for postoperative hypocalcemia were identified and investigated by univariate and multivariate Logistic regression analysis. Of the 139 cases, 25 patients (18.0%) were diagnosed with postoperative hypocalcemia according to the traditional criterion. Univariate analysis revealed only alkaline phosphatase (ALP) and the small area under the curve (AUC) of receiver operating characteristics (ROC) curve for ALP demonstrates low accuracy in predicting the occurrence of postoperative hypocalcemia. Based on new criteria, 22 patients were added to the postoperative hypocalcemia group and similar biochemical parameters were compared. The serum ALP was a significant independent risk factor for postoperative hypocalcemia (P = 0.000) and its AUC of ROC curve was 0.783. The optimal cutoff point was 269 U/L and the sensitivity and specificity for prediction were 89.2% and 64.3%, respectively. The risk of postoperative hypocalcemia after parathyroidectomy should be emphasized for patients with typical symptoms of hypocalcemia despite their serum calcium level is in normal or a little higher range. Serum ALP is a predictive factor for the occurrence of postoperative hypocalcemia.

The prognostic value of preoperative inflammation-based prognostic scores and nutritional status for overall survival in resected patients with nonmetastatic Siewert type II/III adenocarcinoma of esophagogastric junction.

PubMed

Zhang, Lixiang; Su, Yezhou; Chen, Zhangming; Wei, Zhijian; Han, Wenxiu; Xu, Aman

2017-07-01

Immune and nutritional status of patients have been reported to predict postoperative complications, recurrence, and prognosis of patients with cancer. Therefore, this retrospective study aimed to explore the prognostic value of preoperative inflammation-based prognostic scores [neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR)] and nutritional status [prognostic nutritional index (PNI), body mass index (BMI), hemoglobin, albumin, and prealbumin] for overall survival (OS) in adenocarcinoma of esophagogastric junction (AEG) patients. A total of 355 patients diagnosed with Siewert type II/III AEG and underwent surgery between October 2010 and December 2011 were followed up until October 2016. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff values of NLR, PLR, and PNI. Kaplan-Meier curves and Cox regression analyses were used to calculate the OS characteristics. The ideal cutoff values for predicting OS were 3.5 for NLR, 171 for PLR, and 51.3 for PNI according to the ROC curve. The patients with hemoglobin <120 g/L (P = .001), prealbumin <180 mg/L (P = .000), PNI <51.3 (P = .010), NLR >3.5 (P = .000), PLR >171 (P = .006), and low BMI group (P = .000) had shorter OS. And multivariate survival analysis using the Cox proportional hazards model showed that the tumor-node-metastasis stage, BMI, NLR, and prealbumin levels were independent risk factors for the OS. Our study demonstrated that preoperative prealbumin, BMI, and NLR were independent prognostic factors of AEG patients.

Diagnostic performance of procalcitonin for hospitalised children with acute pyelonephritis presenting to the paediatric emergency department.

PubMed

Chen, Shan-Ming; Chang, Hung-Ming; Hung, Tung-Wei; Chao, Yu-Hua; Tsai, Jeng-Dau; Lue, Ko-Huang; Sheu, Ji-Nan

2013-05-01

Urinary tract infection (UTI) is a common bacterial infection in children that can result in permanent renal damage. This study prospectively assessed the diagnostic performance of procalcitonin (PCT) for predicting acute pyelonephritis (APN) among children with febrile UTI presenting to the paediatric emergency department (ED). Children aged ≤10 years with febrile UTI admitted to hospital from the paediatric ED were prospectively studied. Blood PCT, C reactive protein (CRP) and white blood cell (WBC) count were measured in the ED. Sensitivity, specificity, predictive values, multilevel likelihood ratios, receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were used to assess quantitative variables for diagnosing APN. The 136 enrolled patients (56 boys and 80 girls; age range 1 month to 10 years) were divided into APN (n=87) and lower UTI (n=49) groups according to (99m)Tc-dimercaptosuccinic acid scan results. The cut-off value for maximum diagnostic performance of PCT was 1.3 ng/ml (sensitivity 86.2%, specificity 89.8%). By multivariate regression analysis, only PCT and CRP were retained as significant predictors of APN. Comparing ROC curves, PCT had a significantly greater area under the curve than CRP, WBC count and fever for differentiating between APN and lower UTI. PCT has better sensitivity and specificity than CRP and WBC count for distinguishing between APN and lower UTI. PCT is a valuable marker for predicting APN in children with febrile UTI. It may be considered in the initial investigation and therapeutic strategies for children presenting to the ED.

GPU-based prompt gamma ray imaging from boron neutron capture therapy

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

Yoon, Do-Kun; Jung, Joo-Young; Suk Suh, Tae, E-mail: suhsanta@catholic.ac.kr

Purpose: The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. Methods: To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU).more » Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. Results: The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). Conclusions: The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray image reconstruction using the GPU computation for BNCT simulations.« less

TU-FG-BRB-07: GPU-Based Prompt Gamma Ray Imaging From Boron Neutron Capture Therapy

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

Kim, S; Suh, T; Yoon, D

Purpose: The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. Methods: To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU).more » Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. Results: The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). Conclusion: The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray reconstruction using the GPU computation for BNCT simulations.« less

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

PubMed

Esmaily, Habibollah; Tayefi, Maryam; Doosti, Hassan; Ghayour-Mobarhan, Majid; Nezami, Hossein; Amirabadizadeh, Alireza

2018-04-24

We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. A cross-sectional study. The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

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®

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

PubMed

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

2008-01-01

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

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.

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.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Diagnostic performance of Fluorine-18-Fluorodeoxyglucose positron emission tomography for the diagnosis of osteomyelitis related to diabetic foot: a systematic review and a meta-analysis.

PubMed

Treglia, Giorgio; Sadeghi, Ramin; Annunziata, Salvatore; Zakavi, Seyed Rasoul; Caldarella, Carmelo; Muoio, Barbara; Bertagna, Francesco; Ceriani, Luca; Giovanella, Luca

2013-12-01

To systematically review and meta-analyse published data about the diagnostic performance of Fluorine-18-Fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) and PET/computed tomography (PET/CT) in osteomyelitis related to diabetic foot. A comprehensive literature search of studies on (18)F-FDG-PET and PET/CT in patients with diabetic foot was performed. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR+ and LR-) and diagnostic odds ratio (DOR) and area under the summary ROC curve of (18)F-FDG-PET and PET/CT in patients with osteomyelitis related to diabetic foot were calculated. Nine studies comprising 299 patients with diabetic foot were included in the qualitative analysis (systematic review) and discussed. The quantitative analysis (meta-analysis) of four selected studies provided the following results on a per patient-based analysis: sensitivity was 74% [95% confidence interval (95%CI): 60-85%], specificity 91% (95%CI: 85-96%), LR+ 5.56 (95%CI: 2.02-15.27), LR- 0.37 (95%CI: 0.10-1.35), and DOR 16.96 (95%CI: 2.06-139.66). The area under the summary ROC curve was 0.874. In patients with suspected osteomyelitis related to diabetic foot (18)F-FDG-PET and PET/CT demonstrated a high specificity, being potentially useful tools if combined with other imaging methods such as MRI. Nevertheless, the literature focusing on the use of (18)F-FDG-PET and PET/CT in this setting remains still limited. Copyright © 2013 Elsevier Ltd. All rights reserved.

Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers.

PubMed

Zangwill, Linda M; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N; Sejnowski, Terrence J; Goldbaum, Michael H

2004-09-01

To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240 degrees and 300 degrees, had the largest area under the ROC curve (0.85-0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. Copyright Association for Research in Vision and Ophthalmology

Heidelberg Retina Tomograph Measurements of the Optic Disc and Parapapillary Retina for Detecting Glaucoma Analyzed by Machine Learning Classifiers

PubMed Central

Zangwill, Linda M.; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N.; Sejnowski, Terrence J.; Goldbaum, Michael H.

2010-01-01

Purpose To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. Methods One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. Results The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240° and 300°, had the largest area under the ROC curve (0.85–0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Conclusions Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. PMID:15326133

[Value of sepsis single-disease manage system in predicting mortality in patients with sepsis].

PubMed

Chen, J; Wang, L H; Ouyang, B; Chen, M Y; Wu, J F; Liu, Y J; Liu, Z M; Guan, X D

2018-04-03

Objective: To observe the effect of sepsis single-disease manage system on the improvement of sepsis treatment and the value in predicting mortality in patients with sepsis. Methods: A retrospective study was conducted. Patients with sepsis admitted to the Department of Surgical Intensive Care Unit of Sun Yat-Sen University First Affiliated Hospital from September 22, 2013 to May 5, 2015 were enrolled in this study. Sepsis single-disease manage system (Rui Xin clinical data manage system, China data, China) was used to monitor 25 clinical quality parameters, consisting of timeliness, normalization and outcome parameters. Based on whether these quality parameters could be completed or not, the clinical practice was evaluated by the system. The unachieved quality parameter was defined as suspicious parameters, and these suspicious parameters were used to predict mortality of patients with receiver operating characteristic curve (ROC). Results: A total of 1 220 patients with sepsis were enrolled, included 805 males and 415 females. The mean age was (59±17) years, and acute physiology and chronic health evaluation (APACHE Ⅱ) scores was 19±8. The area under ROC curve of total suspicious numbers for predicting 28-day mortality was 0.70; when the suspicious parameters number was more than 6, the sensitivity was 68.0% and the specificity was 61.0% for predicting 28-day mortality. In addition, the area under ROC curve of outcome suspicious number for predicting 28-day mortality was 0.89; when the suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 78.0% for predicting 28-day mortality. Moreover, the area under ROC curve of total suspicious number for predicting 90-day mortality was 0.73; when the total suspicious parameters number was more than 7, the sensitivity was 60.0% and the specificity was 74.0% for predicting 90-day mortality. Finally, the area under ROC curve of outcome suspicious numbers for predicting 90-day mortality was 0.92; when suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 81.0% for predicting 90-day mortality. Conclusion: The single center study suggests that this sepsis single-disease manage system could be used to monitor the completion of clinical practice for intensivist in managing sepsis, and the number of quality parameters failed to complete could be used to predict the mortality of the patients.

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.

Sensitivity of A1C to diagnose diabetes is decreased in high-risk older Southeast Asians.

PubMed

Khoo, Joan; Tay, Tunn-Lin; Foo, Joo-Pin; Tan, Eberta; Soh, Shui-Boon; Chen, Richard; Au, Vanessa; Jen-Min Ng, Ben; Cho, Li-Wei

2012-01-01

To determine the effect of ageing on the performance of glycosylated haemoglobin A1C (A1C) for the diagnosis of diabetes mellitus (DM) in Southeast Asians. A1C was measured in 511 subjects (mean age of 52.4 years; range 14-93) undergoing the 75-g oral glucose tolerance test (OGTT). Using receiver operating curve (ROC) analysis, the performance of A1C for the diagnosis of diabetes (using different standard criteria) was compared between 4 groups: <45 (n=156), 45-54 (n=132), 55-64 (n=122), ≥65 years (n=101). Subjects aged ≥65 years had the highest false-negative rates with fasting plasma glucose (60.8%) and A1C (35.1%), the smallest area under ROC curve (0.723, 95% CI 0.627-0.820), the lowest sensitivity (58.7%, 95% CI 50.4-65.7) and specificity (71.1%, 95% CI 57.3-82.6) of A1C 6.5%, compared to the younger age groups. OGTT is preferable for diagnosis of DM in older Southeast Asian adults. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

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.

Estimation of AUC or Partial AUC under Test-Result-Dependent Sampling.

PubMed

Wang, Xiaofei; Ma, Junling; George, Stephen; Zhou, Haibo

2012-01-01

The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.

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.

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.

Assessment of intracranial pressure with ultrasonographic retrobulbar optic nerve sheath diameter measurement.

PubMed

Liu, Dachuan; Li, Zhen; Zhang, Xuxiang; Zhao, Liping; Jia, Jianping; Sun, Fei; Wang, Yaxing; Ma, Daqing; Wei, Wenbin

2017-09-29

Ultrasonograpic retrobulbar optic nerve sheath diameter (ONSD) measurement is considered to be an alternative noninvasive method to estimate intracranial pressure,but the further validation is urgently needed. The aim of the current study was to investigate the association of the ultrasonographic ONSD and intracranial pressure (ICP) in patients. One hundred and ten patients whose intracranial pressure measured via lumbar puncture were enrolled in the study. Their retrobulbar ONSD with B-scan ultrasound was determined just before lumber puncture. The correlation between the ICP and the body mass index (BMI), ONSD or age was established respectively with the Pearson correlation coefficient analysis. The discriminant analysis was used to obtain a discriminant formula for predicting ICP with the ONSD、BMI、gender and age. Another 20 patients were recruited for further validation the efficiency of this discriminant equation. The mean ICP was 215.3 ± 81.2 mmH 2 O. ONSD was 5.70 ± 0.80 mm in the right eye and 5.80 ± 0.77 mm in the left eye. A significant correlation was found between ICP and BMI (r = 0.554, p < 0.001), the mean ONSD (r = 0.61, P < 0.001), but not with age (r = -0.131, p = 0.174) and gender (r = 0.03, p = 0.753). Using receiver operating characteristic (ROC) curve analysis, the critical value for the risk mean-ONSD was 5.6 mm from the ROC curve, with the sensitivity of 86.2% and specificity of 73.1%. With 200 mmH 2 O as the cutoff point for a high or low ICP, stepwise discriminant was applied, the sensitivity and specificity of ONSD predicting ICP was 84.5%-85.7% and 86.5%-92.3%. Ophthalmic ultrasound measurement of ONSD may be a good surrogate of invasive ICP measurement. This non-invasive method may be an alternative approach to predict the ICP value of patients whose ICP measurement via lumbar puncture are in high risk. The discriminant formula, which incorporated the factor of BMI, had similar sensitivity and higher specificity than the ROC curve.

Development and Validation of a Short Version of the Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) Scale

PubMed Central

Webster, Kate E.; Feller, Julian A.

2018-01-01

Background: The Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) scale was developed to measure an athlete’s psychological readiness to return to sport after anterior cruciate ligament (ACL) injury and reconstruction surgery. The scale is being used with increasing frequency in both research and clinical settings. Purpose: To generate and validate a short version of the ACL-RSI scale. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: The ACL-RSI scale was administered to 535 patients who had undergone ACL reconstruction surgery. Reliability (Cronbach alpha) was determined and factor analysis of the full scale was undertaken along with a process of item selection and elimination. A second group of 250 patients participated in a predictive validation analysis. This group completed the ACL-RSI scale at 6 months and reported return-to-sport outcomes 12 months following ACL reconstruction surgery. The predictive validity of both scales (full and short versions) was assessed by use of receiver operating characteristic (ROC) curve statistics. Results: The scale was found to have high internal consistency (Cronbach alpha, 0.96), which suggested that item redundancy was present. After an item selection process, the scale was reduced to a 6-item format. Cronbach alpha for the short version was 0.92, and factor analysis confirmed the presence of 1 factor accounting for 71% of the total variance. Scores for the short version were significantly different between patients who had and those who had not returned to sport. Six-month ACL-RSI scores for both the full and short versions had fair to good predictive ability for 12-month return-to-sport outcomes (full version: area under ROC curve, 0.77 [95% CI, 0.7-0.8]; short version: area under ROC curve, 0.75 [95% CI, 0.7-0.8]). Conclusion: A 6-item short version of the ACL-RSI scale was developed from a large cohort of patients undergoing ACL reconstruction. The short version appears to be as robust as the full version for discriminating between and predicting return-to-sport outcomes. The short version of the ACL-RSI may be of use in busy clinical settings to help identify athletes who may find return to sport challenging. PMID:29662909

Correlation between laboratory coagulation testing and thromboelastometry is modified during management of trauma patients.

PubMed

David, Jean-Stéphane; Durand, Maeva; Levrat, Albrice; Lefevre, Mathilde; Rugeri, Lucia; Geay-Baillat, Marie-Odile; Inaba, Kenji; Bouzat, Pierre

2016-08-01

Thromboelastometry (ROTEM, Pentapharm GmbH, Munich, Germany) is increasingly being used to make a diagnosis of coagulopathy and to guide hemostatic therapy (HT). Although ROTEM parameters and standard laboratory test (SLT) correlated well before administration of HT, it is not known if this correlation persists after hemostatic resuscitation. A retrospective analysis of prospectively collected data from a trauma registry (2011-2014) was performed. All patients having a ROTEM analysis were included. ROTEM parameters (clotting time and clot amplitude at 5 minutes) were determined after activation with tissue factor (EXTEM) or platelet inhibition with cytochalasin D (FIBTEM). Spearman rank correlation coefficient was calculated for the correlation between SLT and thromboelastometry parameters, and thresholds were determined with receiver operating characteristic (ROC) curve analysis for the diagnosis of an international normalized ratio (INR) greater than 1.5, fibrinogen 1.5 g/L or less, and platelet count of less than 100.10/L. Of the 358 patients included, 533 thromboelastometry results were obtained (335 at admission, 198 during care). Correlation between INR and EXTEM-clotting time was good at admission (r = 0.617) in the whole cohort but decreased in the subgroup of patients having an Injury Severity Score of less than 25 (r = 0.399) or a base excess of less than 6 mmol/L (r = 0.489). During care, correlation was impaired after the administration of fibrinogen concentrates in the whole cohort (r = 0.430), as well as in the subgroup of patients having an Injury Severity Score greater than 24 (r = 0.465). As well, for the diagnosis of increased INR, sensitivity and the area under the ROC curve decreased from 75% and 0.894 (no treatment) to 20% and 0.653 (fibrinogen concentrate). Areas under the ROC curve for the prediction of a fibrinogen or platelet decrease were not significantly altered regardless of the treatment group. A decrease in the correlation between SLTs and ROTEM parameters was observed at admission or during care, which could be in relation with injury severity, base deficit, or the administration of blood products, particularly fibrinogen concentrate. Further work will be necessary to better understand which tool is the most suitable for guiding HT. Therapeutic study, level IV; diagnostic study, level IV.

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.

The Percent of Positive Biopsy Cores Improves Prediction of Prostate Cancer-Specific Death in Patients Treated With Dose-Escalated Radiotherapy

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

Qian Yushen; Feng, Felix Y.; Veterans Administration Medical Center, Ann Arbor, MI

2011-11-01

Purpose: To examine the prognostic utility of the percentage of positive cores (PPC) at the time of prostate biopsy for patients treated with dose-escalated external beam radiation therapy. Methods and Materials: We performed a retrospective analysis of patients treated at University of Michigan Medical Center to at least 75 Gy. Patients were stratified according to PPC by quartile, and freedom from biochemical failure (nadir + 2 ng/mL), freedom from metastasis (FFM), cause-specific survival (CSS), and overall survival (OS) were assessed by log-rank test. Receiver operator characteristic (ROC) curve analysis was used to determine the optimal cut point for PPC stratification.more » Finally, Cox proportional hazards multivariate regression was used to assess the impact of PPC on clinical outcome when adjusting for National Comprehensive Cancer Network (NCCN) risk group and androgen deprivation therapy. Results: PPC information was available for 651 patients. Increasing-risk features including T stage, prostate-specific antigen, Gleason score, and NCCN risk group were all directly correlated with increasing PPC. On log-rank evaluation, all clinical endpoints, except for OS, were associated with PPC by quartile, with worse clinical outcomes as PPC increased, with the greatest impact seen in the highest quartile (>66.7% of cores positive). ROC curve analysis confirmed that a cut point using two-thirds positive cores was most closely associated with CSS (p = 0.002; area under ROC curve, 0.71). On univariate analysis, stratifying patients according to PPC less than or equal to 66.7% vs. PPC greater than 66.7% was prognostic for freedom from biochemical failure (p = 0.0001), FFM (p = 0.0002), and CSS (p = 0.0003) and marginally prognostic for OS (p = 0.055). On multivariate analysis, after adjustment for NCCN risk group and androgen deprivation therapy use, PPC greater than 66.7% increased the risk for biochemical failure (p = 0.0001; hazard ratio [HR], 2.1 [95% confidence interval (CI), 1.4-3.0]) and FFM (p = 0.05; HR, 1.7 [95% CI, 1.1-2.9]) and marginally increased the risk for CSS (p = 0.057; HR, 2.1 [95% CI, 1.0-4.6]). Conclusion: PPC at the time of biopsy adds prognostic value for clinically meaningful endpoints for patients treated with dose-escalated radiation therapy. This was particularly true for NCCN-defined intermediate- and high-risk patients.« less

Mortality prediction using TRISS methodology in the Spanish ICU Trauma Registry (RETRAUCI).

PubMed

Chico-Fernández, M; Llompart-Pou, J A; Sánchez-Casado, M; Alberdi-Odriozola, F; Guerrero-López, F; Mayor-García, M D; Egea-Guerrero, J J; Fernández-Ortega, J F; Bueno-González, A; González-Robledo, J; Servià-Goixart, L; Roldán-Ramírez, J; Ballesteros-Sanz, M Á; Tejerina-Alvarez, E; Pino-Sánchez, F I; Homar-Ramírez, J

2016-10-01

To validate Trauma and Injury Severity Score (TRISS) methodology as an auditing tool in the Spanish ICU Trauma Registry (RETRAUCI). A prospective, multicenter registry evaluation was carried out. Thirteen Spanish Intensive Care Units (ICUs). Individuals with traumatic disease and available data admitted to the participating ICUs. Predicted mortality using TRISS methodology was compared with that observed in the pilot phase of the RETRAUCI from November 2012 to January 2015. Discrimination was evaluated using receiver operating characteristic (ROC) curves and the corresponding areas under the curves (AUCs) (95% CI), with calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test. A value of p<0.05 was considered significant. Predicted and observed mortality. A total of 1405 patients were analyzed. The observed mortality rate was 18% (253 patients), while the predicted mortality rate was 16.9%. The area under the ROC curve was 0.889 (95% CI: 0.867-0.911). Patients with blunt trauma (n=1305) had an area under the ROC curve of 0.887 (95% CI: 0.864-0.910), and those with penetrating trauma (n=100) presented an area under the curve of 0.919 (95% CI: 0.859-0.979). In the global sample, the HL test yielded a value of 25.38 (p=0.001): 27.35 (p<0.0001) in blunt trauma and 5.91 (p=0.658) in penetrating trauma. TRISS methodology underestimated mortality in patients with low predicted mortality and overestimated mortality in patients with high predicted mortality. TRISS methodology in the evaluation of severe trauma in Spanish ICUs showed good discrimination, with inadequate calibration - particularly in blunt trauma. Copyright © 2015 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Accuracy and reliability of the Pfeffer Questionnaire for the Brazilian elderly population

PubMed Central

Dutra, Marina Carneiro; Ribeiro, Raynan dos Santos; Pinheiro, Sarah Brandão; de Melo, Gislane Ferreira; Carvalho, Gustavo de Azevedo

2015-01-01

The aging population calls for instruments to assess functional and cognitive impairment in the elderly, aiming to prevent conditions that affect functional abilities. Objective To verify the accuracy and reliability of the Pfeffer (FAQ) scale for the Brazilian elderly population and to evaluate the reliability and reproducibility of the translated version of the Pfeffer Questionnaire. Methods The Brazilian version of the FAQ was applied to 110 elderly divided into two groups. Both groups were assessed by two blinded investigators at baseline and again after 15 days. In order to verify the accuracy and reliability of the instrument, sensitivity and specificity measurements for the presence or absence of functional and cognitive decline were calculated for various cut-off points and the ROC curve. Intra and inter-examiner reliability were assessed using the Interclass Correlation Coefficient (ICC) and Bland-Altman plots. Results For the occurrence of cognitive decline, the ROC curve yielded an area under the curve of 0.909 (95%CI of 0.845 to 0.972), sensitivity of 75.68% (95%CI of 93.52% to 100%) and specificity of 97.26%. For the occurrence of functional decline, the ROC curve yielded an area under the curve of 0.851 (95%CI of 64.52% to 87.33%) and specificity of 80.36% (95%CI of 69.95% to 90.76%). The ICC was excellent, with all values exceeding 0.75. On the Bland-Altman plot, intra-examiner agreement was good, with p>0.05consistently close to 0. A systematic difference was found for inter-examiner agreement. Conclusion The Pfeffer Questionnaire is applicable in the Brazilian elderly population and showed reliability and reproducibility compared to the original test. PMID:29213959

Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System.

PubMed

Chai, Rifai; Naik, Ganesh R; Nguyen, Tuan Nghia; Ling, Sai Ho; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-05-01

This paper presents a two-class electroencephal-ography-based classification for classifying of driver fatigue (fatigue state versus alert state) from 43 healthy participants. The system uses independent component by entropy rate bound minimization analysis (ERBM-ICA) for the source separation, autoregressive (AR) modeling for the features extraction, and Bayesian neural network for the classification algorithm. The classification results demonstrate a sensitivity of 89.7%, a specificity of 86.8%, and an accuracy of 88.2%. The combination of ERBM-ICA (source separator), AR (feature extractor), and Bayesian neural network (classifier) provides the best outcome with a p-value < 0.05 with the highest value of area under the receiver operating curve (AUC-ROC = 0.93) against other methods such as power spectral density as feature extractor (AUC-ROC = 0.81). The results of this study suggest the method could be utilized effectively for a countermeasure device for driver fatigue identification and other adverse event applications.

Diagnostic utility of attenuation measurement (Hounsfield units) in computed tomography stonogram in predicting the radio-opacity of urinary calculi in plain abdominal radiographs.

PubMed

Chua, Michael E; Gatchalian, Glenn T; Corsino, Michael Vincent; Reyes, Buenaventura B

2012-10-01

(1) To determine the best cut-off level of Hounsfield units (HU) in the CT stonogram that would predict the appearance of a urinary calculi in plain KUB X-ray; (2) to estimate the sensitivity and specificity of the best cut-off HU; and (3) to determine whether stone size and location affect the in vivo predictability. A prospective cross-sectional study of patients aged 18-85 diagnosed with urolithiases on CT stonogram with concurrent plain KUB radiograph was conducted. Appearance of stones was recorded, and significant difference between radiolucent and radio-opaque CT attenuation level was determined using ANOVA. Receiver operating characteristics (ROC) curve determined the best HU cut-off value. Stone size and location were used for factor variability analysis. A total of 184 cases were included in this study, and the average urolithiasis size on CT stonogram was 0.84 cm (0.3-4.9 cm). On KUB X-ray, 34.2 % of the urolithiases were radiolucent and 65.8 % were radio-opaque. Mean value of CT Hounsfield unit for radiolucent stones was 358.25 (±156), and that for radio-opaque stones was 816.51 (±274). ROC curve determined the best cut-off value of HU at 498.5, with the sensitivity of 89.3 % and specificity of 87.3 %. For >4 mm stones, the sensitivity was 91.3 % and the specificity was 81.8 %. On the other hand, for =<4 mm stones, the sensitivity was 60 % and the specificity was 89.5 %. Based on the constructed ROC curve, a threshold value of 498.5 HU in CT stonogram was established as cut-off in determining whether a calculus is radio-opaque or radiolucent. The determined overall sensitivity and specificity of the set cut-off HU value are optimal. Stone size but not location affects the sensitivity and specificity.

Can Shear-Wave Elastography be Used to Discriminate Obstructive Hydronephrosis from Nonobstructive Hydronephrosis in Children?

PubMed

Dillman, Jonathan R; Smith, Ethan A; Davenport, Matthew S; DiPietro, Michael A; Sanchez, Ramon; Kraft, Kate H; Brown, Richard K J; Rubin, Jonathan M

2015-10-01

To determine if ultrasonographic (US) renal shear-wave speed (SWS) measurements obtained either before or after intravenous diuretic administration can be used to discriminate obstructive hydronephrosis from unobstructive hydronephrosis in children, with diuretic renal scintigraphy as the reference standard. Institutional review board approval and parental informed consent were obtained for this HIPAA-compliant prospective cross-sectional blind comparison with a reference standard. Between November 2012 and September 2014, 37 children (mean age, 4.1 years; age range, 1 month to 17 years) underwent shear-wave elastography of the kidneys immediately before and immediately after diuretic renal scintigraphy (reference standard for presence of urinary tract obstruction). Median SWS measurements (in meters per second), as well as change in median SWS (median SWS after diuretic administration minus median SWS before diuretic administration) were correlated with the amount of time required for kidney radiotracer activity to fall by 50% after intravenous administration of the diuretic (T1/2). Median SWS measurements were compared with degree of obstruction and degree of hydronephrosis with analysis of variance. Receiver operating characteristic (ROC) curves were created. Radiotracer T1/2 values after diuretic administration did not correlate with median SWS measurements obtained before (r = -0.08, P = .53) or after (r = -0.0004, P >.99) diuretic administration, nor did they correlate with intraindividual change in median SWS (r = 0.07, P = .56). There was no significant difference in pre- or postdiuretic median SWS measurements between kidneys with scintigraphic evidence of no, equivocal, or definite urinary tract obstruction (P > .5) or for median SWS measurements between kidneys with increasing degree of hydronephrosis (P > .5). ROC curves showed poor diagnostic performance of median SWS in discerning no, equivocal, or definite urinary tract obstruction (area under the ROC curve ranged from 0.50 to 0.62). US SWS measurements did not enable discrimination of obstructive hydronephrosis from unobstructive hydronephrosis in children. (©) RSNA, 2015 Online supplemental material is available for this article.

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

PubMed

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

2016-02-11

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

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.

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.

Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients.

PubMed

Shen, Shutong; Gao, Rongrong; Bei, Yihua; Li, Jin; Zhang, Haifeng; Zhou, Yanli; Yao, Wenming; Xu, Dongjie; Zhou, Fang; Jin, Mengchao; Wei, Siqi; Wang, Kai; Xu, Xuejuan; Li, Yongqin; Xiao, Junjie; Li, Xinli

2017-01-01

Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed. © 2017 The Author(s). Published by S. Karger AG, Basel.

Direct Analysis of JV-Curves Applied to an Outdoor-Degrading CdTe Module (Presentation)

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

Jordan, D; Kurtz, S.; Ulbrich, C.

2014-03-01

We present the application of a phenomenological four parameter equation to fit and analyze regularly measured current density-voltage JV curves of a CdTe module during 2.5 years of outdoor operation. The parameters are physically meaningful, i.e. the short circuit current density Jsc, open circuit voltage Voc and differential resistances Rsc, and Roc. For the chosen module, the fill factor FF degradation overweighs the degradation of Jsc and Voc. Interestingly, with outdoor exposure, not only the conductance at short circuit, Gsc, increases but also the Gsc(Jsc)-dependence. This is well explained with an increase in voltage dependent charge carrier collection in CdTe.

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.

Hsa_circ_0001649: A circular RNA and potential novel biomarker for hepatocellular carcinoma.

PubMed

Qin, Meilin; Liu, Gang; Huo, Xisong; Tao, Xuemei; Sun, Xiaomeng; Ge, Zhouhong; Yang, Juan; Fan, Jia; Liu, Lei; Qin, Wenxin

2016-01-01

It has been shown that circular RNA (circRNA) is associated with human cancers, however, few studies have been reported in hepatocellular carcinoma (HCC). To estimate clinical values of a circular RNA, Hsa_circ_0001649, in HCC. Expression level of hsa_circ_0001649 was detected in HCC and paired adjacent liver tissues by real-time quantitative reverse transcription-polymerase chain reactions (qRT-PCRs). Differences in expression level of hsa_circ_0001649 were analyzed using the paired t-test. Tests were performed between clinical information and hsa_circ_0001649 expression level by analysis of variance (ANOVA) or welch t-test and a receiver operating characteristics (ROC) curve was established to estimate the value of hsa_circ_0001649 expression as a biomarker in HCC. hsa_circ_0001649 expression was significantly downregulated in HCC tissues (p = 0.0014) based on an analysis of 89 paired samples of HCC and adjacent liver tissues and the area under the ROC curve (AUC) was 0.63. Furthermore, hsa_circ_0001649 expression was correlated with tumor size (p = 0.045) and the occurrence of tumor embolus (p = 0.017) in HCC. We first found hsa_circ_0001649 was significantly downregulated in HCC. Our findings indicate hsa_circ_0001649 might serve as a novel potential biomarker for HCC and may function in tumorigenesis and metastasis of HCC.

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

PubMed

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

2016-02-01

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

Diagnostic Validity of High-Density Barium Sulfate in Gastric Cancer Screening: Follow-up of Screenees by Record Linkage with the Osaka Cancer Registry

PubMed Central

Yamamoto, Kenyu; Yamazaki, Hideo; Kuroda, Chikazumi; Kubo, Tsugio; Oshima, Akira; Katsuda, Toshizo; Kuwano, Tadao; Takeda, Yoshihiro

2010-01-01

Background The use of high-density barium sulfate was recommended by the Japan Society of Gastroenterological Cancer Screening (JSGCS) in 2004. We evaluated the diagnostic validity of gastric cancer screening that used high-density barium sulfate. Methods The study subjects were 171 833 residents of Osaka, Japan who underwent gastric cancer screening tests at the Osaka Cancer Prevention and Detection Center during the period from 1 January 2000 through 31 December 2001. Screening was conducted using either high-density barium sulfate (n = 48 336) or moderate-density barium sulfate (n = 123 497). The subjects were followed up and their medical records were linked to those of the Osaka Cancer Registry through 31 December 2002. The results of follow-up during 1 year were defined as the gold standard, and test performance values were calculated. Results The sensitivity and specificity of the screening test using moderate-density barium sulfate were 92.3% and 91.0%, respectively, while the sensitivity and specificity of the high-density barium test were 91.8% and 91.4%, respectively. The results of area under receiver-operating-characteristic (ROC) curve analysis revealed no significant difference between the 2 screening tests. Conclusions Screening tests using high- and moderate-density barium sulfate had similar validity, as determined by sensitivity, specificity, and ROC curve analysis. PMID:20551581

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

PubMed

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

2016-01-01

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

Evaluation of erythrocyte dysmorphism by light microscopy with lowering of the condenser lens: A simple and efficient method.

PubMed

Barros Silva, Gyl Eanes; Costa, Roberto Silva; Ravinal, Roberto Cuan; Saraiva e Silva, Jucélia; Dantas, Marcio; Coimbra, Terezila Machado

2010-03-01

To demonstrate that the evaluation of erythrocyte dysmorphism by light microscopy with lowering of the condenser lens (LMLC) is useful to identify patients with a haematuria of glomerular or non-glomerular origin. A comparative double-blind study between phase contrast microscopy (PCM) and LMLC is reported to evaluate the efficacy of these techniques. Urine samples of 39 patients followed up for 9 months were analyzed, and classified as glomerular and non-glomerular haematuria. The different microscopic techniques were compared using receiver-operator curve (ROC) analysis and area under curve (AUC). Reproducibility was assessed by coefficient of variation (CV). Specific cut-offs were set for each method according to their best rate of specificity and sensitivity as follows: 30% for phase contrast microscopy and 40% for standard LMLC, reaching in the first method the rate of 95% and 100% of sensitivity and specificity, respectively, and in the second method the rate of 90% and 100% of sensitivity and specificity, respectively. In ROC analysis, AUC for PCM was 0.99 and AUC for LMLC was 0.96. The CV was very similar in glomerular haematuria group for PCM (35%) and LMLC (35.3%). LMLC proved to be effective in contributing to the direction of investigation of haematuria, toward the nephrological or urological side. This method can substitute PCM when this equipment is not available.

In vitro culture increases mechanical stability of human tissue engineered cartilage constructs by prevention of microscale scaffold buckling.

PubMed

Middendorf, Jill M; Shortkroff, Sonya; Dugopolski, Caroline; Kennedy, Stephen; Siemiatkoski, Joseph; Bartell, Lena R; Cohen, Itai; Bonassar, Lawrence J

2017-11-07

Many studies have measured the global compressive properties of tissue engineered (TE) cartilage grown on porous scaffolds. Such scaffolds are known to exhibit strain softening due to local buckling under loading. As matrix is deposited onto these scaffolds, the global compressive properties increase. However the relationship between the amount and distribution of matrix in the scaffold and local buckling is unknown. To address this knowledge gap, we studied how local strain and construct buckling in human TE constructs changes over culture times and GAG content. Confocal elastography techniques and digital image correlation (DIC) were used to measure and record buckling modes and local strains. Receiver operating characteristic (ROC) curves were used to quantify construct buckling. The results from the ROC analysis were placed into Kaplan-Meier survival function curves to establish the probability that any point in a construct buckled. These analysis techniques revealed the presence of buckling at early time points, but bending at later time points. An inverse correlation was observed between the probability of buckling and the total GAG content of each construct. This data suggests that increased GAG content prevents the onset of construct buckling and improves the microscale compressive tissue properties. This increase in GAG deposition leads to enhanced global compressive properties by prevention of microscale buckling. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-03-10

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

Predictive value of preoperative inflammatory response biomarkers for metabolic syndrome and post-PCNL systemic inflammatory response syndrome in patients with nephrolithiasis.

PubMed

Tang, Kun; Liu, Haoran; Jiang, Kehua; Ye, Tao; Yan, Libin; Liu, Peijun; Xia, Ding; Chen, Zhiqiang; Xu, Hua; Ye, Zhangqun

2017-10-17

Neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) were promising biomarkers used to predict diagnosis and prognosis in various inflammatory responses diseases and cancers. However, there have been no reports regarding these biomarkers in kidney stone patients. This study aimed to evaluate the predictive value of inflammatory biomarkers for metabolic syndrome (MetS) and post-PCNL SIRS in nephrolithiasis patients. We retrospectively enrolled 513 patients with nephrolithiasis and 204 healthy controls. NLR, dNLR, LMR and PLR in nephrolithiasis patients were significantly higher than control group. Patients with renal stone have higher NLR, dNLR, LMR and PLR than those without. ROC curve analysis indicated NLR, dNLR, LMR and PLR for predicting patients with nephrolithiasis and MetS, displayed AUC of 0.730, 0.717, 0.627 and 0.606. Additionally, ROC curves, using post-PCNL SIRS as the end-point for NLR, dNLR, LMR and PLR with AUC of 0.831, 0.813, 0.723 and 0.685. Multivariate analysis revealed that NLR, dNLR represented independent factors for predicting post-PCNL SIRS. While LMR independently associated with MetS. These resluts demonstrate preoperative NLR, dNLR and LMR appears to be effective predictors of post-PCNL SIRS and LMR of MetS in nephrolithiasis patients.

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

PubMed

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

2013-01-01

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

Computer-aided diagnosis with textural features for breast lesions in sonograms.

PubMed

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

"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.

User-friendly tools on handheld devices for observer performance study

NASA Astrophysics Data System (ADS)

Matsumoto, Takuya; Hara, Takeshi; Shiraishi, Junji; Fukuoka, Daisuke; Abe, Hiroyuki; Matsusako, Masaki; Yamada, Akira; Zhou, Xiangrong; Fujita, Hiroshi

2012-02-01

ROC studies require complex procedures to select cases from many data samples, and to set confidence levels in each selected case to generate ROC curves. In some observer performance studies, researchers have to develop software with specific graphical user interface (GUI) to obtain confidence levels from readers. Because ROC studies could be designed for various clinical situations, it is difficult task for preparing software corresponding to every ROC studies. In this work, we have developed software for recording confidence levels during observer studies on tiny personal handheld devices such as iPhone, iPod touch, and iPad. To confirm the functions of our software, three radiologists performed observer studies to detect lung nodules by using public database of chest radiograms published by Japan Society of Radiological Technology. The output in text format conformed to the format for the famous ROC kit from the University of Chicago. Times required for the reading each case was recorded very precisely.

Verification of a model for the detection of intrauterine growth restriction (IUGR) by receiver operating characteristics (ROC)

NASA Astrophysics Data System (ADS)

Liu, Pengbo; Mongelli, Max; Mondry, Adrian

2004-07-01

The purpose of this study is to verify by Receiver Operating Characteristics (ROC) a mathematical model supporting the hypothesis that IUGR can be diagnosed by estimating growth velocity. The ROC compare computerized simulation results with clinical data from 325 pregnant British women. Each patient had 6 consecutive ultrasound examinations for fetal abdominal circumference (fac). Customized and un-customized fetal weights were calculated according to Hadlock"s formula. IUGR was diagnosed by the clinical standard, i.e. estimated weight below the tenth percentile. Growth velocity was estimated by calculating the changes of fac (Dzfac/dt) at various time intervals from 3 to 10 weeks. Finally, ROC was used to compare the methods. At 3~4 weeks scan interval, the area under the ROC curve is 0.68 for customized data and 0.66 for the uncustomized data with 95% confidence interval. Comparison between simulation data and real pregnancies verified that the model is clinically acceptable.

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.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

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

PubMed

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

2018-03-01

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

Vitamin D supplementation as a potential cause of U-shaped associations between vitamin D levels and negative health outcomes: a decision tree analysis for risk of frailty.

PubMed

Kojima, Gotaro; Iliffe, Steve; Tanabe, Marianne

2017-10-16

A recent controversy in vitamin D research is a "U-shaped association", with elevated disease risks at both high and low 25-hydroxyvitamin D (25 (OH) D) levels. This is a cross-sectional study of 238 male nursing home veterans in Hawaii. Classification and regression tree (CART) analysis identified groups based on 25 (OH) D and vitamin D supplementation for frailty risk. Characteristics were examined and compared across the groups using logistic regression and receiver operating characteristic (ROC) curve analyses. CART analysis identified three distinct groups: vitamin D supplement users (n = 86), non-users with low vitamin D (n = 55), and non-users with high vitamin D (n = 97). Supplement users were the most frail, but had high mean 25 (OH) D of 26.6 ng/mL, which was compatible with 27.1 ng/mL in non-users with high vitamin D, while mean 25 (OH) D of non-users with low vitamin D was 11.7 ng/mL. Supplement users and non-users with low vitamin D were significantly more likely to be frail (odds ratio (OR) = 9.90, 95% CI = 2.18-44.86, p = 0.003; OR = 4.28, 95% CI = 1.44-12.68, p = 0.009, respectively), compared with non-users with low vitamin D. ROC curve analysis showed the three groups significantly predicted frailty (area under the curve = 0.73), with sensitivity of 64.4% and specificity of 76.7%, while 25 (OH) D did not predict frailty. In these nursing home veterans, vitamin D supplement users were the most frail but with high 25 (OH) D. This can potentially be a cause of U-shaped associations between vitamin D levels and negative health outcomes.

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

PubMed Central

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

2012-01-01

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

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

[Developing a predictive model for the caregiver strain index].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Praena-Fernández, Juan Manuel; Ortega-Calvo, Manuel

Patient homecare with multiple morbidities is an increasingly common occurrence. The caregiver strain index is tool in the form of questionnaire that is designed to measure the perceived burden of those who care for their families. The aim of this study is to construct a diagnostic nomogram of informal caregiver burden using data from a predictive model. The model was drawn up using binary logistic regression and the questionnaire items as dichotomous factors. The dependent variable was the final score obtained with the questionnaire but categorised in accordance with that in the literature. Scores between 0 and 6 were labelled as "no" (no caregiver stress) and at or greater than 7 as "yes". The version 3.1.1R statistical software was used. To construct confidence intervals for the ROC curve 2000 boot strap replicates were used. A sample of 67 caregivers was obtained. A diagnosing nomogram was made up with its calibration graph (Brier scaled = 0.686, Nagelkerke R 2 =0.791), and the corresponding ROC curve (area under the curve=0.962). The predictive model generated using binary logistic regression and the nomogram contain four items (1, 4, 5 and 9) of the questionnaire. R plotting functions allow a very good solution for validating a model like this. The area under the ROC curve (0.96; 95% CI: 0.994-0.941) achieves a high discriminative value. Calibration also shows high goodness of fit values, suggesting that it may be clinically useful in community nursing and geriatric establishments. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

[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.

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

PubMed

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

2014-06-01

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

Image Quality and Stenosis Assessment of Non-Contrast-Enhanced 3-T Magnetic Resonance Angiography in Patients with Peripheral Artery Disease Compared with Contrast-Enhanced Magnetic Resonance Angiography and Digital Subtraction Angiography

PubMed Central

Liu, Jiayi; Zhang, Nan; Fan, Zhaoyang; Luo, Nan; Zhao, Yike; Bi, Xiaoming; An, Jing; Chen, Zhong; Liu, Dongting; Wen, Zhaoying; Fan, Zhanming; Li, Debiao

2016-01-01

Purpose To evaluate the diagnostic performance of flow-sensitive dephasing (FSD)-prepared steady-state free precession (SSFP) magnetic resonance angiography (MRA) at 3 T for imaging infragenual arteries relative to contrast-enhanced MRA (CE-MRA) and digital subtraction angiography (DSA). Materials and Methods A series of 16 consecutive patients with peripheral arterial disease (PAD) underwent a combined peripheral MRA protocol consisting of FSD-MRA for the calves and large field-of-view CE-MRA. DSA was performed on all patients within 1 week of the MR angiographies. Image quality and degree of stenosis was assessed by two readers with rich experience. Inter-observer agreement was determined using kappa statistics. Receiver operating characteristic (ROC) curve analysis determined the diagnostic value of FSD-MRA, CE-MRA, and CE-MRA combined with FSD-MRA (CE+FSD MRA) in predicting vascular stenosis. Results At the calf station, no significantly difference of subjective image quality scores was found between FSD-MRA and CE-MRA. Inter-reader agreement was excellent for both FSD-MRA and CE-MRA. Both of FSD-MRA and CE-MRA carry a stenosis overestimation risk relative to DSA standard. With DSA as the reference standard, ROC curve analysis showed that the area under the curve was largest for CE+FSD MRA. The greatest sensitivity and specificity were obtained when a cut-off stenosis score of 2 was used. Conclusion In patients with severe PAD,3 T FSD-MRA provides good-quality diagnostic images without a contrast agent and is a good supplement for CE-MRA. CE+FSD MRA can improve the accuracy of vascular stenosis diagnosis. PMID:27861626

Anthropometric Indices Predict the Development of Hypertension in Normotensive and Pre-Hypertensive Middle-Aged Women in Tianjin, China: A Prospective Cohort Study

PubMed Central

Wang, Qing; Wang, Zhuoqun; Yao, Wei; Wu, Xianming; Huang, Jingjing; Huang, Lei

2018-01-01

Background The aims of this study were to investigate the relationship between optimal anthropometric indices and their cut-off values and the incidence of hypertension in a cohort of middle-aged women in China. Material/Methods A cohort of 812 women, aged between 40–70 years were recruited between May 2011 and June 2013. An ideal baseline blood pressure was defined as <120/80 mmHg; pre-hypertension was 120–139/80–89 mmHg; hypertension was ≥140/≥90 mmHg. Anthropometric measurements included waist circumference (WC), body mass index (BMI), waist-hip ratio (WHR), and waist-height ratio (WHtR). The cohort was divided into an ideal blood pressure group (Group 1) and a pre-hypertensive group (Group 2). Two-year follow-up blood pressure measurements were performed. Receiver-operating characteristic (ROC) curve analysis determined the optimal anthropometric indices and cut-off values for developing hypertension. Results At two-year follow-up, hypertension developed in 9.0% (n=31) in Group 1 and 32.3% (n=121) in Group 2. Logistic regression analysis showed that in both groups, women in the highest quartile for WC, BMI, WHR, and WHtR had a significantly increased risk of developing hypertension compared with the lowest quartile (P<0.05). ROC curve area under the curve (AUC) for these anthropometric indices were greater in Group 1, and for WC in Groups 1 and 2, with the optimal cut-off values greater in Group 1. Conclusions In a cohort of middle-aged women in China, anthropometric indices of obesity were predictive of the development of hypertension during a two-year follow-up period. PMID:29601569

Diagnostic accuracy of presepsin (soluble CD14 subtype) for prediction of bacteremia in patients with systemic inflammatory response syndrome in the Emergency Department.

PubMed

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

2014-05-01

Bacteremia is indicative of severe bacterial infection with significant mortality. Its early diagnosis is extremely important for implementation of antimicrobial therapy but a diagnostic challenge. Although blood culture is the "gold standard" for diagnosis of bacteremia this method has limited usefulness for the early detection of blood-stream infection. In this study we assessed the presepsin as predictor of bacteremia in patients with systemic inflammatory response syndrome (SIRS) on admission to the Emergency Department and compare it with current available infection biomarkers. A total of 226 patients admitted to the Emergency Department with SIRS were included. In 37 patients blood culture had a positive result (bacteremic SIRS group) and 189 had a negative blood culture result (non-bacteremic SIRS group). Simultaneously with blood culture, presepsin, procalcitonin (PCT) and C-reactive protein (CRP) were measured. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker as predictor of bacteremia. Presepsin values were significantly higher in bacteremic SIRS group when compared with non-bacteremic SIRS group. ROC curve analysis and area under curve (AUC) revealed a value of 0.750 for presepsin in differentiating SIRS patients with bacteremia from those without, similar than that for PCT (0.787) and higher than that for CRP (0.602). The best cut-off value for presepsin was 729pg/mL, which was associated with a negative predictive value of 94.4%. Presepsin may contribute to rule out the diagnosis of bacteremia in SIRS patients admitted to the Emergency Department. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Semi-quantitative analysis of salivary gland scintigraphy in Sjögren's syndrome diagnosis: a first-line tool.

PubMed

Angusti, Tiziana; Pilati, Emanuela; Parente, Antonella; Carignola, Renato; Manfredi, Matteo; Cauda, Simona; Pizzigati, Elena; Dubreuil, Julien; Giammarile, Francesco; Podio, Valerio; Skanjeti, Andrea

2017-09-01

The aim of this study was the assessment of semi-quantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to predict primary Sjögren's syndrome (pSS). Forty-six consecutive patients (41 females; age 61 ± 11 years) with sicca syndrome were studied by SGdS after injection of 200 MBq of pertechnetate. In sixteen patients, pSS was diagnosed, according to American-European Consensus Group criteria (AECGc). Semi-quantitative parameters (uptake (UP) and excretion fraction (EF)) were obtained for each gland. ROC curves were used to determine the best cut-off value. The area under the curve (AUC) was used to estimate the accuracy of each semi-quantitative analysis. To assess the correlation between scintigraphic results and disease severity, semi-quantitative parameters were plotted versus Sjögren's syndrome disease activity index (ESSDAI). A nomogram was built to perform an integrated evaluation of all the scintigraphic semi-quantitative data. Both UP and EF of salivary glands were significantly lower in pSS patients compared to those in non-pSS (p < 0.001). ROC curve showed significantly large AUC for both the parameters (p < 0.05). Parotid UP and submandibular EF, assessed by univariated and multivariate logistic regression, showed a significant and independent correlation with pSS diagnosis (p value <0.05). No correlation was found between SGdS semi-quantitative parameters and ESSDAI. The proposed nomogram accuracy was 87%. SGdS is an accurate and reproducible tool for the diagnosis of pSS. ESSDAI was not shown to be correlated with SGdS data. SGdS should be the first-line imaging technique in patients with suspected pSS.

Utility of 18F-fluorodeoxyglucose-positron emission tomography in the differential diagnosis of benign and malignant gynaecological tumours.

PubMed

Takagi, Hiroaki; Sakamoto, Jinichi; Osaka, Yasuhiro; Shibata, Takeo; Fujita, Satoko; Sasagawa, Toshiyuki

2018-02-05

Positron emission tomography/computed tomography (PET/CT) involving 18F-fluorodeoxyglucose (FDG) is widely used for systemic cancer and recurrence diagnosis. However, the differential diagnosis of benign and malignant gynaecological tumours according to FDG accumulation is unclear. This study aimed to investigate the intensity of FDG uptake/metabolic activity for the differential diagnosis of benign and malignant gynaecological tumours. This study included seven patients with physiological phenomena, 34 with benign tumours, 13 with borderline malignant tumours and 119 with malignant tumours who underwent 18F-FDG PET/CT. We assessed the maximum standardized uptake value (SUVmax) and determined its utility in the diagnosis of benign and malignant tumours using a receiver operating characteristic (ROC) curve analysis. Among the 63 patients with ovarian tumours, the mean SUVmax of 22 patients with benign ovarian tumours was 2.48 and the mean SUVmax of 41 patients with malignant ovarian tumours was 10.98 (P < 0.001). In the ROC curve analysis, the area under the curve (AUC) was 0.977, with a 95% confidence interval of 0.947-1.000. With a cut-off value of 3.97 for the optimal SUVmax, the sensitivity and specificity were 95.1% and 86.4%, respectively. In addition, the AUC was 0.911 (95% CI: 0.768-1.000) for the assessment of uterine myomas and sarcomas. With a cut-off value of 10.62 for the optimal SUVmax, the sensitivity and specificity were 91.7% and 86.7% respectively. The SUVmax value helps differentiate benign and malignant ovarian tumours, as well as uterine myomas and uterine sarcomas. © 2018 The Royal Australian and New Zealand College of Radiologists.

Role of specific IgE and skin-prick testing in predicting food challenge results to baked egg.

PubMed

Cortot, Catherine F; Sheehan, William J; Permaul, Perdita; Friedlander, James L; Baxi, Sachin N; Gaffin, Jonathan M; Dioun, Anahita F; Hoffman, Elaine B; Schneider, Lynda C; Phipatanakul, Wanda

2012-01-01

Previous studies suggest that children with egg allergy may be able to tolerate baked egg. Reliable predictors of a successful baked egg challenge are not well established. We examined egg white-specific IgE levels, skin-prick test (SPT) results, and age as predictors of baked egg oral food challenge (OFC) outcomes. We conducted a retrospective chart review of children, aged 2-18 years, receiving an egg white-specific IgE level, SPT, and OFC to baked egg from 2008 to 2010. Fifty-two oral baked egg challenges were conducted. Of the 52 challenges, 83% (n = 43) passed and 17% (n = 9) failed, including 2 having anaphylaxis. Median SPT wheal size was 12 mm (range, 0-35 mm) for passed challenges and 17 mm (range, 10-30 mm) for failed challenges (p = 0.091). The negative predictive value for passing the OFC was 100% (9 of 9) if SPT wheal size was <10 mm. Median egg white-specific IgE was 2.02 kU/L (range, <0.35-13.00 kU/L) for passed challenges and 1.52 kU/L (range, 0.51-6.10 kU/L) for failed challenges (p = 0.660). Receiver operating characteristic (ROC) curve analysis for SPT revealed an area under the curve (AUC) of 0.64. ROC curve analysis for egg white-specific IgE revealed an AUC of 0.63. There was no significant difference in age between patients who failed and those who passed (median = 8.8 years versus 7.0 years; p = 0.721). Based on our sample, SPT, egg white-specific IgE and age are not good predictors of passing a baked egg challenge. However, there was a trend for more predictability with SPT wheal size.

Sesame allergy: role of specific IgE and skin-prick testing in predicting food challenge results.

PubMed

Permaul, Perdita; Stutius, Lisa M; Sheehan, William J; Rangsithienchai, Pitud; Walter, Jolan E; Twarog, Frank J; Young, Michael C; Scott, Jordan E; Schneider, Lynda C; Phipatanakul, Wanda

2009-01-01

There are conflicting data regarding the diagnostic value of sesame-specific IgE and sesame skin test. Currently, there are no established thresholds that predict clinical reactivity. We examined the correlation of sesame ImmunoCAP and skin-prick test (SPT) results with oral challenge outcomes in children suspected of having a sesame food allergy. We conducted a retrospective chart review of children, aged 2-12 years, receiving a sesame ImmunoCAP level, SPT, and food challenge from January 2004 to August 2008 at Children's Hospital Boston and affiliated allergy clinics. Food challenges were conducted in cases of questionable clinical history or a negative ImmunoCAP and/or negative SPT despite a convincing history. Thirty-three oral sesame challenges were conducted. Of the 33 challenges performed, 21% (n = 7) failed and 79% (n = 26) passed. A sesame-specific IgE level of > or = 7 kU(A)/L showed specificity of >90%. An SPT wheal size of > or = 6 mm showed specificity of >90%. Receiver operator characteristic (ROC) curve analysis for sesame-specific IgE revealed an area under the curve (AUC) of 0.56. ROC curve analysis for SPT wheal size revealed an AUC of 0.67. To our knowledge, this study represents the largest number of sesame challenges performed to evaluate the diagnostic value of both sesame-specific IgE and SPT. Based on our sample, both tests are not good predictors of true sesame allergy as determined by an oral challenge. We were unable to establish a threshold with a 95% positive predictive value for both sesame-specific IgE and SPT.

Heart rate dynamics during cardio-pulmonary exercise testing are associated with glycemic control in individuals with type 1 diabetes.

PubMed

Moser, Othmar; Eckstein, Max L; McCarthy, Olivia; Deere, Rachel; Bain, Stephen C; Haahr, Hanne L; Zijlstra, Eric; Heise, Tim; Bracken, Richard M

2018-01-01

This study investigated the degree and direction (kHR) of the heart rate to performance curve (HRPC) during cardio-pulmonary exercise (CPX) testing and explored the relationship with diabetes markers, anthropometry and exercise physiological markers in type 1 diabetes (T1DM). Sixty-four people with T1DM (13 females; age: 34 ± 8 years; HbA1c: 7.8 ± 1% (62 ± 13 mmol.mol-1) performed a CPX test until maximum exhaustion. kHR was calculated by a second-degree polynomial representation between post-warm up and maximum power output. Adjusted stepwise linear regression analysis was performed to investigate kHR and its associations. Receiver operating characteristic (ROC) curve was performed based on kHR for groups kHR < 0.20 vs. > 0.20 in relation to HbA1c. We found significant relationships between kHR and HbA1c (β = -0.70, P < 0.0001), age (β = -0.23, P = 0.03) and duration of diabetes (β = 0.20, P = 0.04). Stepwise linear regression resulted in an overall adjusted R2 of 0.57 (R = 0.79, P < 0.0001). Our data revealed also significant associations between kHR and percentage of heart rate at heart rate turn point from maximum heart rate (β = 0.43, P < 0.0001) and maximum power output relativized to bodyweight (β = 0.44, P = 0.001) (overall adjusted R2 of 0.44 (R = 0.53, P < 0.0001)). ROC curve analysis based on kHR resulted in a HbA1c threshold of 7.9% (62 mmol.mol-1). Our data demonstrate atypical HRPC during CPX testing that were mainly related to glycemic control in people with T1DM.

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.

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.

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.

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.

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

PubMed Central

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

2010-01-01

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

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.

Diagnostic accuracy of point shear wave elastography in the detection of portal hypertension in pediatric patients.

PubMed

Burak Özkan, M; Bilgici, M C; Eren, E; Caltepe, G

2018-03-01

The purpose of this study was to determine the usefulness of point shear wave elastography (p-SWE) of the liver and spleen for the detection of portal hypertension in pediatric patients. The study consisted of 38 healthy children and 56 pediatric patients with biopsy-proven liver disease who underwent splenic and liver p-SWE. The diagnostic performance of p-SWE in detecting clinically significant portal hypertension was assessed using receiver operating characteristic (ROC) curves. Reliable measurements of splenic and liver stiffness with p-SWE were obtained in 76/94 (81%) and 80/94 patients (85%), respectively. The splenic stiffness was highest in the portal hypertension group (P<0.01). At ROC curve analysis, the area under the curve in the detection of portal hypertension was lower for splenic p-SWE than for liver p-SWE (0.906 vs. 0.746; P=0.0239). The cut-off value of splenic p-SWE for portal hypertension was 3.14m/s, with a specificity of 98.59% and a sensitivity of 68.18%. The cut-off value of liver p-SWE for portal hypertension was 2.09m/s, with a specificity of 80.28% and a sensitivity of 77.27%. In pediatric patients, p-SWE is a reliable method for detecting portal hypertension. However, splenic p-SWE is less accurate than liver p-SWE for the diagnosis of portal hypertension. Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Contrast enhanced ultrasound and magnetic resonance imaging in hepatocellular carcinoma diagnosis.

PubMed

Dumitrescu, Cristiana I; Gheonea, Ioana A; Săndulescu, Larisa; Surlin, Valeriu; Săftoiu, Adrian; Dumitrescu, Daniela

2013-12-01

The new developments in imaging technology, including contrast enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI), allow a better diagnosis of both malignant and benign liver lesions. A retrospective trial of 126 patients was conducted in the Gastroenterology and Imaging Departments of the University of Medicine and Pharmacy Craiova, Romania. CEUS and MRI were the imaging techniques used for diagnosis of focal liver lesions (FLL), especially for hepatocellular carcinoma (HCC). Histopathology was used only in 15 cases. For each method of investigation we calculated the sensitivity, specificity, positive and negative predictive values (PPV and NPV), positive and negative likelihood ratio (+LR, -LR), accuracy and we compared the ROC curves. Statistical analysis also included the Chi-square and Kappa tests. Seventy six cases were diagnosed as HCC, with average size of 5.2±3.3 cm in diameter. The sensitivity and specificity were 71.4% and 95.6% for CEUS and 91.4%, 98.9% respectively, for MRI. When comparing the ROC curves, we found a higher area under curve for MRI (0.952) then for CEUS (0.835) (p=0.005), and 95% confidence interval of 0.0343 to 0.199. No statistically significant difference in diagnosis of FLL was found between CEUS and MRI (p > 0.05) and the agreement between the two imaging techniques was good (k = 0.78). CEUS can be used as the first step in the diagnosis of liver lesions, but MRI remains the gold standard diagnostic method for liver tumors.

Discriminating talent-identified junior Australian football players using a video decision-making task.

PubMed

Woods, Carl T; Raynor, Annette J; Bruce, Lyndell; McDonald, Zane

2016-01-01

This study examined if a video decision-making task could discriminate talent-identified junior Australian football players from their non-talent-identified counterparts. Participants were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: talent-identified (State U18 Academy representatives; n = 25; 17.8 ± 0.5 years) and non-talent-identified (non-State U18 Academy selection; n = 25; 17.3 ± 0.6 years). Participants completed a video decision-making task consisting of 26 clips sourced from the Australian Football League game-day footage, recording responses on a sheet provided. A score of "1" was given for correct and "0" for incorrect responses, with the participants total score used as the criterion value. One-way analysis of variance tested the main effect of "status" on the task criterion, whilst a bootstrapped receiver operating characteristic (ROC) curve assessed the discriminant ability of the task. An area under the curve (AUC) of 1 (100%) represented perfect discrimination. Between-group differences were evident (P < 0.05) and the ROC curve was maximised with a score of 15.5/26 (60%) (AUC = 89.0%), correctly classifying 92% and 76% of the talent-identified and non-talent-identified participants, respectively. Future research should investigate the mechanisms leading to the superior decision-making observed in the talent-identified group.

Plasma fatty acid-binding protein 4 (FABP4) as a novel biomarker to predict gestational diabetes mellitus.

PubMed

Ning, Hui; Tao, Hong; Weng, Zhanping; Zhao, Xingbo

2016-12-01

Fatty acid-binding protein 4 (FABP4) is mainly expressed in adipocytes and macrophages and is demonstrated to be elevated in diabetes patients. The aim of this study was to evaluate the possible role of FABP4 in the diagnosis of GDM and to investigate the relationship between FABP4 and overweight, insulin resistance and inflammatory marker TNF-α. A total of 46 women with GDM and 55 age-matched pregnant women without GDM (non-GDM) were eligible for the study. Demographic and biochemical parameters and fasting venous blood samples of two groups were collected from all cases. Serum concentrations of FABP4 were determined using enzyme-linked immunosorbent assay (ELISA). The predictive value of Serum FABP4 level was evaluated using receiver operating characteristic curve (ROC curve) analysis. We found that the serum FABP4 levels were significantly higher in GDM compared to the non-GDM group. The area under the ROC curve assay yielded a satisfactory result of 0.94 (95 % confidence interval 0.90-0.98; p < 0.001). The best compromise between 86.96 % specificity and 89.09 % sensitivity was obtained with a cutoff value of 1.96 ng/mL for GDM diagnosis. Moreover, a significant positive correlation was observed between FABP4 and overweight, insulin resistance and TNF-α in pregnant women with GDM. These results suggest that serum FABP4 may potentially serve as a novel biomarker for the prediction of GDM.

[Evaluation of otoacoustic emissions in relation to brainstem evoked auditory potentials in children].

PubMed

Rado-Triveño, Julia; Alen-Ayca, Jaime

2016-01-01

To determine the validity of the use of acoustic otoacoustic emissions in comparison with the evoked potentials Auditory brainstem examination (PEATC), a study was carried out with 96 children between 0 and 4 years of age that went to Instituto Nacional de Rehabilitación in Lima, Peru. The results show a cut-off point corresponding to 1 in (+): 17.67 in right ear and 16.72 in left ear, and LR (-): 0.25 in ear right and 0.24 in left ear; ROC curve with area under the right ear curve of 0.830 (p<0.001) was obtained and in left ear of 0.829 (p<0.001). According to the results of LR (+) the sensitivity is 76% in the right ear and 65% In the left ear that coincides with the conformation of the ROC curve. In conclusion, acoustic emissions would not represent an alternative sufficiently discriminatory alternative as a screening test in this population.

Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and ROC curves

PubMed Central

Howard, Marc W.; Bessette-Symons, Brandy; Zhang, Yaofei; Hoyer, William J.

2006-01-01

Younger and older adults were tested on recognition memory for pictures. The Yonelinas high threshold (YHT) model, a formal implementation of two-process theory, fit the response distribution data of both younger and older adults significantly better than a normal unequal variance signal detection model. Consistent with this finding, non-linear zROC curves were obtained for both groups. Estimates of recollection from the YHT model were significantly higher for younger than older adults. This deficit was not a consequence of a general decline in memory; older adults showed comparable overall accuracy and in fact a non-significant increase in their familiarity scores. Implications of these results for theories of recognition memory and the mnemonic deficit associated with aging are discussed. PMID:16594795

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

PubMed

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

2011-06-01

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

Survey on Tuberculosis Patients in Rural Areas in China: Tracing the Role of Stigma in Psychological Distress.

PubMed

Xu, Minlan; Markström, Urban; Lyu, Juncheng; Xu, Lingzhong

2017-10-04

Depressed patients had risks of non-adherence to medication, which brought a big challenge for the control of tuberculosis (TB). The stigma associated with TB may be the reason for distress. This study aimed to assess the psychological distress among TB patients living in rural areas in China and to further explore the relation of experienced stigma to distress. This study was a cross-sectional study with multi-stage randomized sampling for recruiting TB patients. Data was collected by the use of interviewer-led questionnaires. A total of 342 eligible and accessible TB patients being treated at home were included in the survey. Psychological distress was measured using the Kessler Psychological Distress Scale (K10). Experienced stigma was measured using a developed nine-item stigma questionnaire. Univariate analysis and multiple logistic regression were used to analyze the variables related to distress, respectively. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to present the strength of the associations. Finally, the prediction of logistic model was assessed in form of the Receiver Operating Characteristic (ROC) curve and the area under the ROC curve (AUC). According to the referred cut-off point from K10, this study revealed that 65.2% (223/342) of the participants were categorized as having psychological distress. Both the stigma questionnaire and the K10 were proven to be reliable and valid in measurement. Further analysis found that experienced stigma and illness severity were significant variables to psychological distress in the model of logistic regression. The model was assessed well in predicting distress by use of experienced stigma and illness severity in form of ROC and AUC. Rural TB patients had a high prevalence of psychological distress. Experience of stigma played a significant role in psychological distress. To move the barrier of stigma from the surroundings could be a good strategy in reducing distress for the patients and TB controlling for public health management.

Metabolic tumour volume and total lesion glycolysis, measured using preoperative 18F-FDG PET/CT, predict the recurrence of endometrial cancer.

PubMed

Shim, S-H; Kim, D-Y; Lee, D-Y; Lee, S-W; Park, J-Y; Lee, J J; Kim, J-H; Kim, Y-M; Kim, Y-T; Nam, J-H

2014-08-01

To investigate the prognostic value of metabolic tumour volume (MTV) and total lesion glycolysis (TLG), measured by preoperative positron emission tomography and computerised tomography (PET/CT), in women with endometrial cancer. Retrospective cohort study. A tertiary referral centre. Women with endometrial cancer who underwent preoperative (18)F-FDG PET/CT in the period 2004-2009. Clinicopathological data for 84 women with endometrial cancer were reviewed from medical records. Cox proportional hazards modelling identified recurrence predictors. The receiver operating characteristic (ROC) curve was used to determine the cut-off value for predicting recurrence. Disease-free survival (DFS). The number of patients with International Federation of Gynecology and Obstetrics (FIGO) stages were: I (58); II (11); III (13); and IV (2). The median DFS was 48 (1-85) months. By univariate analysis, DFS was significantly associated with FIGO stage, histology, peritoneal cytology, myometrial invasion, nodal metastasis, serum CA-125, MTV, and TLG. Using multivariate analysis, the MTV (P = 0.010; hazard ratio, HR = 1.010; 95% confidence interval, 95% CI = 1.002-1.018) and TLG (P = 0.024; HR = 1.001; 95% CI = 1.000-1.002) were associated with DFS. The area under the ROC curve was 0.679 (95% CI = 0.505-0.836) after discriminating for recurrence using an MTV cut-off value of 17.15 ml. Regarding TLG, the cut-off value was 56.43 g and the area under the ROC plot was 0.661 (95% CI = 0.501-0.827). Kaplan-Meier survival graphs demonstrated a significant difference in DFS between groups categorised using the cut-off values for MTV and TLG (P < 0.022 for MTV and P < 0.047 for TLG, by log-rank test). Preoperative MTV and TLG could be independent prognostic factors predicting the recurrence of endometrial cancer. © 2014 Royal College of Obstetricians and Gynaecologists.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Limited diagnostic value of Dual-Time-Point (18)F-FDG PET/CT imaging for classifying solitary pulmonary nodules in granuloma-endemic regions both at visual and quantitative analyses.

PubMed

Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming

2016-10-01

This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Area and volume ratios for prediction of visual outcome in idiopathic macular hole.

PubMed

Geng, Xing-Yun; Wu, Hui-Qun; Jiang, Jie-Hui; Jiang, Kui; Zhu, Jun; Xu, Yi; Dong, Jian-Cheng; Yan, Zhuang-Zhi

2017-01-01

To predict the visual outcome in patients undergoing macular hole surgery by two novel three-dimensional morphological parameters on optical coherence tomography (OCT): area ratio factor (ARF) and volume ratio factor (VRF). A clinical case series was conducted, including 54 eyes of 54 patients with an idiopathic macular hole (IMH). Each patient had an OCT examination before and after surgery. Morphological parameters of the macular hole, such as minimum diameter, base diameter, and height were measured. Then, the macular hole index (MHI), tractional hole index (THI), and hole form factor (HFF) were calculated. Meanwhile, novel postoperative macular hole (MH) factors, ARF and VRF were calculated by three-dimensional morphology. Bivariate correlations were performed to acquire asymptotic significance values between the steady best corrected visual acuity (BCVA) after surgery and 2D/3D arguments of MH by the Pearson method with two-tailed test. All significant factors were analyzed by the receiver operating characteristic (ROC) curve analysis of SPSS software which were responsible for vision recovery. ROC curves analyses were performed to further discuss the different parameters on the prediction of visual outcome. The mean and standard deviation values of patients' age, symptoms duration, and follow-up time were 64.8±8.9y (range: 28-81), 18.6±11.5d (range: 2-60), and 11.4±0.4mo (range: 6-24), respectively. Steady-post-BCVA analyzed with bivariate correlations was found to be significantly correlated with base diameter ( r =0.521, P <0.001), minimum diameter ( r =0.514, P <0.001), MHI ( r =-0.531, P <0.001), THI ( r =-0.386, P =0.004), HFF ( r =-0.508, P <0.001), and ARF ( r =-0.532, P <0.001). Other characteristic parameters such as age, duration of surgery, height, diameter hole index, and VRF were not statistically significant with steady-post-BCVA. According to area under the curve (AUC) values, values of ARF, MHI, HFF, minimum diameter, THI, and base diameter are 0.806, 0.772, 0.750, 0.705, 0.690, and 0.686, respectively. However, Steady-post-BCVA analysis with bivariate correlations for VRF was no statistical significance. Results of ROC curve analysis indicated that the MHI value, HFF, and ARF was greater than 0.427, 1.027 and 1.558 respectively which could correlate with better visual acuity. Compared with MHI and HFF, ARF could effectively express three-dimensional characteristics of macular hole and achieve better sensitivity and specificity. Thus, ARF could be the most effective parameter to predict the visual outcome in macular hole surgery.

Objective Diagnosis of Cervical Cancer by Tissue Protein Profile Analysis

NASA Astrophysics Data System (ADS)

Patil, Ajeetkumar; Bhat, Sujatha; Rai, Lavanya; Kartha, V. B.; Chidangil, Santhosh

2011-07-01

Protein profiles of homogenized normal cervical tissue samples from hysterectomy subjects and cancerous cervical tissues from biopsy samples collected from patients with different stages of cervical cancer were recorded using High Performance Liquid Chromatography coupled with Laser Induced Fluorescence (HPLC-LIF). The Protein profiles were subjected to Principle Component Analysis to derive statistically significant parameters. Diagnosis of sample types were carried out by matching three parameters—scores of factors, squared residuals, and Mahalanobis Distance. ROC and Youden's Index curves for calibration standards were used for objective estimation of the optimum threshold for decision making and performance.

Evaluation of peak-picking algorithms for protein mass spectrometry.

PubMed

Bauer, Chris; Cramer, Rainer; Schuchhardt, Johannes

2011-01-01

Peak picking is an early key step in MS data analysis. We compare three commonly used approaches to peak picking and discuss their merits by means of statistical analysis. Methods investigated encompass signal-to-noise ratio, continuous wavelet transform, and a correlation-based approach using a Gaussian template. Functionality of the three methods is illustrated and discussed in a practical context using a mass spectral data set created with MALDI-TOF technology. Sensitivity and specificity are investigated using a manually defined reference set of peaks. As an additional criterion, the robustness of the three methods is assessed by a perturbation analysis and illustrated using ROC curves.

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.

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

PubMed

Song, Yang; Zhang, Yu-Dong; Yan, Xu; Liu, Hui; Zhou, Minxiong; Hu, Bingwen; Yang, Guang

2018-04-16

Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI). To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with mp-MRI. Retrospective. In all, 195 patients with localized PCa were collected from a PROSTATEx database. In total, 159/17/19 patients with 444/48/55 observations (215/23/23 PCas and 229/25/32 NCs) were randomly selected for training/validation/testing, respectively. T 2 -weighted, diffusion-weighted, and apparent diffusion coefficient images. A radiologist manually labeled the regions of interest of PCas and NCs and estimated the Prostate Imaging Reporting and Data System (PI-RADS) scores for each region. Inspired by VGG-Net, we designed a patch-based DCNN model to distinguish between PCa and NCs based on a combination of mp-MRI data. Additionally, an enhanced prediction method was used to improve the prediction accuracy. The performance of DCNN prediction was tested using a receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Moreover, the predicted result was compared with the PI-RADS score to evaluate its clinical value using decision curve analysis. Two-sided Wilcoxon signed-rank test with statistical significance set at 0.05. The DCNN produced excellent diagnostic performance in distinguishing between PCa and NC for testing datasets with an AUC of 0.944 (95% confidence interval: 0.876-0.994), sensitivity of 87.0%, specificity of 90.6%, PPV of 87.0%, and NPV of 90.6%. The decision curve analysis revealed that the joint model of PI-RADS and DCNN provided additional net benefits compared with the DCNN model and the PI-RADS scheme. The proposed DCNN-based model with enhanced prediction yielded high performance in statistical analysis, suggesting that DCNN could be used in computer-aided diagnosis (CAD) for PCa classification. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

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.

Corrected ROC analysis for misclassified binary outcomes.

PubMed

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

2017-06-15

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

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

Diagnostic evaluation of three cardiac software packages using a consecutive group of patients

PubMed Central

2011-01-01

Purpose The aim of this study was to compare the diagnostic performance of the three software packages 4DMSPECT (4DM), Emory Cardiac Toolbox (ECTb), and Cedars Quantitative Perfusion SPECT (QPS) for quantification of myocardial perfusion scintigram (MPS) using a large group of consecutive patients. Methods We studied 1,052 consecutive patients who underwent 2-day stress/rest 99mTc-sestamibi MPS studies. The reference/gold-standard classifications for the MPS studies were obtained from three physicians, with more than 25 years each of experience in nuclear cardiology, who re-evaluated all MPS images. Automatic processing was carried out using 4DM, ECTb, and QPS software packages. Total stress defect extent (TDE) and summed stress score (SSS) based on a 17-segment model were obtained from the software packages. Receiver-operating characteristic (ROC) analysis was performed. Results A total of 734 patients were classified as normal and the remaining 318 were classified as having infarction and/or ischemia. The performance of the software packages calculated as the area under the SSS ROC curve were 0.87 for 4DM, 0.80 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.03; other differences p < 0.0001). The area under the TDE ROC curve were 0.87 for 4DM, 0.82 for QPS, and 0.76 for ECTb (QPS vs. ECTb p = 0.0005; other differences p < 0.0001). Conclusion There are considerable differences in performance between the three software packages with 4DM showing the best performance and ECTb the worst. These differences in performance should be taken in consideration when software packages are used in clinical routine or in clinical studies. PMID:22214226

[An indirect ELISA using Legionella pneumophila recombinant MOMP protein and its application in serological diagnosis].

PubMed

Wang, Tao; Zhang, Caixia; Cao, Xiuqin; Yang, Zhiwei

2013-12-01

To express and purify the recombinant major outer membrane protein (MOMP) of Legionella pneumophila (Lp) as diagnostic antigen, and explore its practical value in the serological diagnosis of Lp infection. The recombinant plasmid pET-momp was transformed into the E.coli BL21 competent cells. The recombinant MOMP was induced to express, and then analyzed by SDS-PAGE electrophoresis, purified by affinity chromatography. We screened and obtained 58 positive blood serum and 32 negative blood serum using the DRG (Germany, IgG/IgM/IgA) Lp kit. The blood serum samples were detected for IgG, IgM, IgA antibody levels by indirect ELISA that we had established with the purified MOMP as the coating antigen, as well as by R&D (USA, IgG/IgM/IgA) Lp kit. Then using the receiver operating characteristic (ROC) curve, we compared these two methods in the sensitivity, specificity and consistency of the test results, for evaluating the application value of the indirect ELISA of recombinant MOMP. The approximately 45 000 recombinant MOMP was successfully expressed and purified. Compared with the indirect ELISA we established with the R&D Lp kit for detecting Lp antibody IgG, IgM and IgA in blood serum, the sensitivity of the indirect ELISA of recombinant MOMP to IgG was 90.9%, the specificity was 91.7%, the Kappa value was 0.784 (P < 0.05), and the area under the ROC curve was 0.913; the sensitivity to IgM was 91.4% and the specificity was 90.6%, the Kappa value was 0.809 (P < 0.05), and the area under the ROC curve was 0.910; the sensitivity to IgA was 92.1% and the specificity was 88.9%, the Kappa value was 0.793(P < 0.05), and the area under the ROC curve was 0.905. The recombinant MOMP was successfully induced to express and purified. The indirect ELISA we established with the recombinant MOMP protein as a diagnostic antigen showed good specificity, sensitivity and consistency, which laid a foundation for the development of serological diagnosis kit of Legionnaires' disease.

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study)123

PubMed Central

Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

2015-01-01

Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628

Anthropometric indicators of obesity in the prediction of high body fat in adolescents

PubMed Central

Pelegrini, Andreia; Silva, Diego Augusto Santos; Silva, João Marcos Ferreira de Lima; Grigollo, Leoberto; Petroski, Edio Luiz

2015-01-01

OBJECTIVE: To determine the anthropometric indicators of obesity in the prediction of high body fat in adolescents from a Brazilian State. METHODS: The study included 1,197 adolescents (15-17 years old). The following anthropometric measurements were collected: body mass (weight and height), waist circumference and skinfolds (triceps and medial calf). The anthropometric indicators analyzed were: body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and conicity index (C-Index). Body fat percentage, estimated by the Slaughter et al equation, was used as the reference method. Descriptive statistics, U Mann-Whitney test, and ROC curve were used for data analysis. RESULTS: Of the four anthropometric indicators studied, BMI, WHtR and WC had the largest areas under the ROC curve in relation to relative high body fat in both genders. The cutoffs for boys and girls, respectively, associated with high body fat were BMI 22.7 and 20.1kg/m², WHtR 0.43 and 0.41, WC 75.7 and 67.7cm and C-Index 1.12 and 1.06. CONCLUSIONS: Anthropometric indicators can be used in screening for identification of body fat in adolescents, because they are simple, have low cost and are non-invasive. PMID:25649384

Fertility biomarkers to estimate metabolic risks in women with polycystic ovary syndrome.

PubMed

Detti, Laura; Jeffries-Boyd, Heather E; Williams, Lucy J; Diamond, Michael P; Uhlmann, Rebecca A

2015-12-01

We sought to evaluate the relationship between the polycystic ovary syndrome (PCOS)-defining characteristics and the risk of developing metabolic complications in women presenting with complaints of infertility and/or menstrual irregularities and subsequently diagnosed with PCOS. This was a cross-sectional study. Women presenting with complaints of infertility and/or irregular menses and diagnosed with PCOS by the Rotterdam criteria, underwent endocrine, metabolic, and ultrasound assessment in the early follicular phase. Reproductive and metabolic parameters were included in regression analysis models with the PCOS-defining characteristics; ROC curves were calculated for the significant predictors. Three hundred and seventy-four women with PCOS were included in our study. Oligo-anovulation, menstrual irregularities, and hirsutism were not predictive of any of the variables. Ovarian volume, follicle count, and biochemical hyperandrogenism were predictors for hormonal, metabolic, and endometrial complications. The relationships were independent of age and body mass index. ROC curves identified lower cut-off values of the PCOS-defining characteristics to predict patients' risks of hyperinsulinemia, dyslipidemia, and glucose intolerance. Adverse metabolic effects of PCOS are already present in women at the time they present complaining of infertility and/or irregular menses. Hyperandrogenism and ultrasound can assist in predicting the patients' concomitant metabolic abnormalities and can aid physicians in tailoring counseling for effective preventive strategies.

Assessment of Diagnostic and Prognostic Role of Copeptin in the Clinical Setting of Sepsis.

PubMed

Battista, Stefania; Audisio, Umberto; Galluzzo, Claudia; Maggiorotto, Matteo; Masoero, Monica; Forno, Daniela; Pizzolato, Elisa; Ulla, Marco; Lucchiari, Manuela; Vitale, Annarita; Moiraghi, Corrado; Lupia, Enrico; Settanni, Fabio; Mengozzi, Giulio

2016-01-01

The diagnostic and prognostic usefulness of copeptin were evaluated in septic patients, as compared to procalcitonin assessment. In this single centre and observational study 105 patients were enrolled: 24 with sepsis, 25 with severe sepsis, 15 with septic shock, and 41 controls, divided in two subgroups (15 patients with gastrointestinal bleeding and 26 with suspected SIRS secondary to trauma, acute coronary syndrome, and pulmonary embolism). Biomarkers were determined at the first medical evaluation and thereafter 24, 48, and 72 hours after admission. Definitive diagnosis and in-hospital survival rates at 30 days were obtained through analysis of medical records. At entry, copeptin proved to be able to distinguish cases from controls and also sepsis group from septic shock group, while procalcitonin could distinguish also severe sepsis from septic shock group. Areas under the ROC curve for copeptin and procalcitonin were 0.845 and 0.861, respectively. Noteworthy, patients with copeptin concentrations higher than the threshold value (23.2 pmol/L), calculated from the ROC curve, at admission presented higher 30-day mortality. No significant differences were found in copeptin temporal profile among different subgroups. Copeptin showed promising diagnostic and prognostic role in the management of sepsis, together with its possible role in monitoring the response to treatment.

Assessment of Diagnostic and Prognostic Role of Copeptin in the Clinical Setting of Sepsis

PubMed Central

Battista, Stefania; Audisio, Umberto; Galluzzo, Claudia; Maggiorotto, Matteo; Masoero, Monica; Forno, Daniela; Pizzolato, Elisa; Ulla, Marco; Lucchiari, Manuela; Vitale, Annarita; Moiraghi, Corrado; Lupia, Enrico; Settanni, Fabio; Mengozzi, Giulio

2016-01-01

The diagnostic and prognostic usefulness of copeptin were evaluated in septic patients, as compared to procalcitonin assessment. In this single centre and observational study 105 patients were enrolled: 24 with sepsis, 25 with severe sepsis, 15 with septic shock, and 41 controls, divided in two subgroups (15 patients with gastrointestinal bleeding and 26 with suspected SIRS secondary to trauma, acute coronary syndrome, and pulmonary embolism). Biomarkers were determined at the first medical evaluation and thereafter 24, 48, and 72 hours after admission. Definitive diagnosis and in-hospital survival rates at 30 days were obtained through analysis of medical records. At entry, copeptin proved to be able to distinguish cases from controls and also sepsis group from septic shock group, while procalcitonin could distinguish also severe sepsis from septic shock group. Areas under the ROC curve for copeptin and procalcitonin were 0.845 and 0.861, respectively. Noteworthy, patients with copeptin concentrations higher than the threshold value (23.2 pmol/L), calculated from the ROC curve, at admission presented higher 30-day mortality. No significant differences were found in copeptin temporal profile among different subgroups. Copeptin showed promising diagnostic and prognostic role in the management of sepsis, together with its possible role in monitoring the response to treatment. PMID:27366743

The balance between the serum levels of IL-6 and IL-10 cytokines discriminates mild and severe acute pneumonia.

PubMed

de Brito, Rita de Cássia Coelho Moraes; Lucena-Silva, Norma; Torres, Leuridan Cavalcante; Luna, Carlos Feitosa; Correia, Jaílson de Barros; da Silva, Giselia Alves Pontes

2016-12-01

To identify markers for earlier diagnosis of severe pneumonia, we assess the correlation between serum cytokine profile of children with different pneumonia severity. In 25 hospitalized children, 7 with mild pneumonia and 18 with severe pneumonia, the serum concentration of 11 cytokines in three sampling times were dosed. Statistical analysis included parametric and non-parametric tests, Pearson correlation and ROC curve for cut-off definition of cytokines. At admission, IL-6 serum levels were high in mild or severe pneumonia, and was associated to vomiting (P = 0.019) in both groups; and also to dyspnea (P = 0.012) and white blood cell count (P = 0.045) in patients with severe pneumonia. IL-10 levels were also high in patients with pneumonia and were associated to lymphocytosis (P = 0.025). The ROC curve of the IL-6:IL-10 serum levels ratio discriminated severe pneumonia cases at admission, and persistence of infection in the third day of antibiotic therapy, with positive predictive values of 93% and 89%, respectively. The balance between IL-6 and IL-10 serum levels showed to be a more discriminative marker for severity definition and evaluation of recovery in patients with pneumonia.

CSF lactate for accurate diagnosis of community-acquired bacterial meningitis.

PubMed

Giulieri, S; Chapuis-Taillard, C; Jaton, K; Cometta, A; Chuard, C; Hugli, O; Du Pasquier, R; Bille, J; Meylan, P; Manuel, O; Marchetti, O

2015-10-01

CSF lactate measurement is recommended when nosocomial meningitis is suspected, but its value in community-acquired bacterial meningitis is controversial. We evaluated the diagnostic performance of lactate and other CSF parameters in a prospective cohort of adult patients with acute meningitis. Diagnostic accuracy of lactate and other CSF parameters in patients with microbiologically documented episodes was assessed by receiver operating characteristic (ROC) curves. The cut-offs with the best diagnostic performance were determined. Forty-five of 61 patients (74%) had a documented bacterial (n = 18; S. pneumoniae, 11; N. meningitidis, 5; other, 2) or viral (n = 27 enterovirus, 21; VZV, 3; other, 3) etiology. CSF parameters were significantly different in bacterial vs. viral meningitis, respectively (p < 0.001 for all comparisons): white cell count (median 1333 vs. 143/mm(3)), proteins (median 4115 vs. 829 mg/l), CSF/blood glucose ratio (median 0.1 vs. 0.52), lactate (median 13 vs. 2.3 mmol/l). ROC curve analysis showed that CSF lactate had the highest accuracy for discriminating bacterial from viral meningitis, with a cutoff set at 3.5 mmol/l providing 100% sensitivity, specificity, PPV, NPV, and efficiency. CSF lactate had the best accuracy for discriminating bacterial from viral meningitis and should be included in the initial diagnostic workup of this condition.

Problematic smartphone use, nature connectedness, and anxiety.

PubMed

Richardson, Miles; Hussain, Zaheer; Griffiths, Mark D

2018-03-01

Background Smartphone use has increased greatly at a time when concerns about society's disconnection from nature have also markedly increased. Recent research has also indicated that smartphone use can be problematic for a small minority of individuals. Methods In this study, associations between problematic smartphone use (PSU), nature connectedness, and anxiety were investigated using a cross-sectional design (n = 244). Results Associations between PSU and both nature connectedness and anxiety were confirmed. Receiver operating characteristic (ROC) curves were used to identify threshold values on the Problematic Smartphone Use Scale (PSUS) at which strong associations with anxiety and nature connectedness occur. The area under the curve was calculated and positive likelihood ratios used as a diagnostic parameter to identify optimal cut-off for PSU. These provided good diagnostic ability for nature connectedness, but poor and non-significant results for anxiety. ROC analysis showed the optimal PSUS threshold for high nature connectedness to be 15.5 (sensitivity: 58.3%; specificity: 78.6%) in response to an LR+ of 2.88. Conclusions The results demonstrate the potential utility for the PSUS as a diagnostic tool, with a level of smartphone use that users may perceive as non-problematic being a significant cut-off in terms of achieving beneficial levels of nature connectedness. Implications of these findings are discussed.

Metabolomic profile of systemic sclerosis patients.

PubMed

Murgia, Federica; Svegliati, Silvia; Poddighe, Simone; Lussu, Milena; Manzin, Aldo; Spadoni, Tatiana; Fischetti, Colomba; Gabrielli, Armando; Atzori, Luigi

2018-05-16

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726-0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7-0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

Intact protein analysis of ubiquitin in cerebrospinal fluid by multiple reaction monitoring reveals differences in Alzheimer's disease and frontotemporal lobar degeneration.

PubMed

Oeckl, Patrick; Steinacker, Petra; von Arnim, Christine A F; Straub, Sarah; Nagl, Magdalena; Feneberg, Emily; Weishaupt, Jochen H; Ludolph, Albert C; Otto, Markus

2014-11-07

The impairment of the ubiquitin-proteasome system (UPS) is thought to be an early event in neurodegeneration, and monitoring UPS alterations might serve as a disease biomarker. Our aim was to establish an alternate method to antibody-based assays for the selective measurement of free monoubiquitin in cerebrospinal fluid (CSF). Free monoubiquitin was measured with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MS/MS) in CSF of patients with Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), behavioral variant of frontotemporal dementia (bvFTD), Creutzfeldt-Jakob disease (CJD), Parkinson's disease (PD), primary progressive aphasia (PPA), and progressive supranuclear palsy (PSP). The LC-MS/MS method showed excellent intra- and interassay precision (4.4-7.4% and 4.9-10.3%) and accuracy (100-107% and 100-106%). CSF ubiquitin concentration was increased compared with that of controls (33.0 ± 9.7 ng/mL) in AD (47.5 ± 13.1 ng/mL, p < 0.05) and CJD patients (171.5 ± 103.5 ng/mL, p < 0.001) but not in other neurodegenerative diseases. Receiver operating characteristic curve (ROC) analysis of AD vs control patients revealed an area under the curve (AUC) of 0.832, and the specificity and sensitivity were 75 and 75%, respectively. ROC analysis of AD and FTLD patients yielded an AUC of 0.776, and the specificity and sensitivity were 53 and 100%, respectively. In conclusion, our LC-MS/MS method may facilitate ubiquitin determination to a broader community and might help to discriminate AD, CJD, and FTLD patients.

Tumour xenograft detection through quantitative analysis of the metabolic profile of urine in mice

NASA Astrophysics Data System (ADS)

Moroz, Jennifer; Turner, Joan; Slupsky, Carolyn; Fallone, Gino; Syme, Alasdair

2011-02-01

The metabolic content of urine from NIH III nude mice (n = 22) was analysed before and after inoculation with human glioblastoma multiforme (GBM) cancer cells. An age- and gender-matched control population (n = 14) was also studied to identify non-tumour-related changes. Urine samples were collected daily for 6 weeks, beginning 1 week before cell injection. Metabolite concentrations were obtained via targeted profiling with Chenomx Suite 5.1, based on nuclear magnetic resonance (NMR) spectra acquired on an Oxford 800 MHz cold probe NMR spectrometer. The Wilcoxon rank sum test was used to evaluate the significance of the change in metabolite concentration between the two time points. Both the metabolite concentrations and the ratios of pairs of metabolites were studied. The complicated inter-relationships between metabolites were assessed through partial least-squares discriminant analysis (PLS-DA). Receiver operating characteristic (ROC) curves were generated for all variables and the area under the curve (AUC) calculated. The data indicate that the number of statistically significant changes in metabolite concentrations was more pronounced in the tumour-bearing population than in the control animals. This was also true of the ratios of pairs of metabolites. ROC analysis suggests that the ratios were better able to differentiate between the pre- and post-injection samples compared to the metabolite concentrations. PLS-DA models produced good separation between the populations and had the best AUC results (all models exceeded 0.937). These results demonstrate that metabolomics may be used as a screening tool for GBM cells grown in xenograft models in mice.

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

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.

Should We Be Anxious When Assessing Anxiety Using the Beck Anxiety Inventory in Clinical Insomnia Patients?

PubMed Central

Carney, Colleen E.; Moss, Taryn G.; Harris, Andrea L.; Edinger, Jack D.; Krystal, Andrew D.

2011-01-01

Assessing for clinical levels of anxiety is crucial, as comorbid insomnias far outnumber primary insomnias (PI). Such assessment is complex since those with Anxiety Disorders (AD) and those with PI have overlapping symptoms. Because of this overlap, we need studies that examine the assessment of anxiety in clinical insomnia groups. Participants (N = 207) were classified as having insomnia: 1) without an anxiety disorder (I-ND), or 2) with an anxiety disorder (I-AD). Mean Beck Anxiety Inventory (BAI) item responses were compared using multivariate analysis of variance (MANOVA) and follow-up ANOVAs. As a validity check, a receiver operating characteristic (ROC) curve analysis was conducted to determine if the BAI suggested clinical cutoff was valid for identifying clinical levels of anxiety in this comorbid patient group. The I-ND had lower mean BAI scores than I-AD. There were significant group differences on 12 BAI items. The ROC curve analysis revealed the suggested BAI cutoff (≥16) had 55% sensitivity and 78% specificity. Although anxiety scores were highest in those with insomnia and an anxiety disorder, those with insomnia only had scores in the mild range for anxiety. Nine items did not distinguish between those insomnia sufferers with and without an anxiety disorder. Additionally, published cutoffs for the BAI were not optimal for identifying anxiety disorders in those with insomnia. Such limitations must be considered before using this measure in insomnia patient groups. In addition, the poor specificity and high number of overlapping symptoms between insomnia and anxiety highlight the diagnostic challenges facing clinicians. PMID:21482427

FAST for blunt abdominal trauma: Correlation between positive findings and admission acid-base measurement.

PubMed

Heidari, Kamran; Taghizadeh, Mehrdad; Mahmoudi, Sadrollah; Panahi, Hamidreza; Ghaffari Shad, Ensieh; Asadollahi, Shadi

2017-06-01

This study aimed to determine any association between positive findings in ultrasonography examination and initial BD value with regard to diagnosis of intra-abdominal bleeding following blunt abdominal trauma. A prospective, multi-center study of consecutive adult patients was performed from April to September 2015. Demographics, initial vital signs and arterial BD were evaluated with respect to presence of any association with intra-abdominal bleeding and in-hospital mortality. FAST study was performed to find intra-abdominal bleeding. Receiver operating characteristic (ROC) curves tested the ability of BD to identify patients with intra-abdominal hemorrhage and probable mortality. A total of 879 patients were included in final analysis. The mean (SD) age was 36.68 (15.7) years and 714 patients (81.2%) were male. According to multivariable analysis, statistically significant association was observed between negative admission BD and both intra-abdominal bleeding (OR 3.48, 95% CI 2.06-5.88, p<0.001) and in-hospital mortality (OR 1.55, 95% CI 1.49-1.63, p<0.001). ROC curve analysis demonstrated sensitivity of 92.7% and specificity of 22.1% for the best cut-off value of BD (-8mEq/L) to diagnose internal hemorrhage. Further, a cut-off value of -7mEq/L demonstrated significant predictive performance, 94.8% sensitivity and 53.6% specificity for in-hospital mortality. This study revealed that arterial BD is an early accessible important marker to identify intra-abdominal bleeding, as well as to predict overall in-hospital mortality in patients with blunt abdominal trauma. Copyright © 2017. Published by Elsevier Inc.

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

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.

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.

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

PubMed

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

2010-01-01

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

Comparison of nested-multiplex, Taqman & SYBR Green real-time PCR in diagnosis of amoebic liver abscess in a tertiary health care institute in India.

PubMed

Dinoop, K P; Parija, Subhash Chandra; Mandal, Jharna; Swaminathan, R P; Narayanan, P

2016-01-01

Amoebiasis is a common parasitic infection caused by Entamoeba histolytica and amoebic liver abscess (ALA) is the most common extraintestinal manifestation of amoebiasis. The aim of this study was to standardise real-time PCR assays (Taqman and SYBR Green) to detect E. histolytica from liver abscess pus and stool samples and compare its results with nested-multiplex PCR. Liver abscess pus specimens were subjected to DNA extraction. The extracted DNA samples were subjected to amplification by nested-multiplex PCR, Taqman (18S rRNA) and SYBR Green real-time PCR (16S-like rRNA assays to detect E. histolytica/E. dispar/E. moshkovskii). The amplification products were further confirmed by DNA sequence analysis. Receiver operator characteristic (ROC) curve analysis was done for nested-multiplex and SYBR Green real-time PCR and the area under the curve was calculated for evaluating the accuracy of the tests to dignose ALA. In all, 17, 19 and 25 liver abscess samples were positive for E. histolytica by nested-multiplex PCR, SYBR Green and Taqman real-time PCR assays, respectively. Significant differences in detection of E. histolytica were noted in the real-time PCR assays evaluated ( P<0.0001). The nested-multiplex PCR, SYBR Green real-time PCR and Taqman real-time PCR evaluated showed a positivity rate of 34, 38 and 50 per cent, respectively. Based on ROC curve analysis (considering Taqman real-time PCR as the gold standard), it was observed that SYBR Green real-time PCR was better than conventional nested-multiplex PCR for the diagnosis of ALA. Taqman real-time PCR targeting the 18S rRNA had the highest positivity rate evaluated in this study. Both nested multiplex and SYBR Green real-time PCR assays utilized were evaluated to give accurate results. Real-time PCR assays can be used as the gold standard in rapid and reliable diagnosis, and appropriate management of amoebiasis, replacing the conventional molecular methods.

Evaluation of Echocardiographic Epicardial Fat Thickness as a Sign of Cardiovascular Risk in Positive Exercise Test Patients.

PubMed

Katlandur, Hüseyin; Ulucan, Şeref; Özdil, Hüseyin; Keser, Ahmet; Kaya, Zeynettin; Özbek, Kerem; Ülgen, M Sıddık

2016-11-01

The association between epicardial fat thickness (EFT) and positive exercise test results for the diagnosis of coronary artery diseases (CAD) has yet to be evaluated. This study assessed the predictive value of EFT for CAD on the angiographs of patients with positive exercise tests. A total of 91 subjects were chosen consecutively from stable angina pectoris patients who were referred for coronary angiography due to a positive exercise test result. The EFT measures were obtained by echocardiographic parasternal long-axis views on the free wall of the right ventricle at end-systole of three cardiac cycles. Gensini scores were calculated by a conventional coronary angiography technique using a calculation method previously defined. Receiver operator characteristic (ROC) curve analysis revealed a 0.65 cm (95% confidence interval: 0.628, 0.832, p < 0.001) area under the curve with 74.3% sensitivity and 62.3% specificity at the cut-off value of EFT for the prediction of critical coronary artery stenosis. Following ROC curve analysis, two groups were defined according to EFT cut-off value (groups 1 and 2). The severe coronary stenosis ratio was significantly higher in group 2 compared to group 1 (31.9 % vs. 11%, p < 0.001) and Gensini scores were significantly higher in group 2 (6.3 ± 13.3 vs. 16.5 ± 17.9; p < 0.001). There was no significant correlation between Gensini scores and EFT in group 1 (r = 0.093, p = 0.549), but there was a strong significant correlation in group 2 (r = 0.730, p < 0.001). Linear multivariate regression analysis revealed that EFT (> 0.65 cm) was the only independent risk factor for critical coronary artery stenosis (β = 0.451, p < 0.001). EFT was significantly correlated with the severity and prevalence of coronary artery disease in positive exercise test patients.

Antimüllerian hormone as a predictor of live birth following assisted reproduction: an analysis of 85,062 fresh and thawed cycles from the Society for Assisted Reproductive Technology Clinic Outcome Reporting System database for 2012-2013.

PubMed

Tal, Reshef; Seifer, David B; Wantman, Ethan; Baker, Valerie; Tal, Oded

2018-02-01

To determine if serum antimüllerian hormone (AMH) is associated with and/or predictive of live birth assisted reproductive technology (ART) outcomes. Retrospective analysis of Society for Assisted Reproductive Technology Clinic Outcome Reporting System database from 2012 to 2013. Not applicable. A total of 69,336 (81.8%) fresh and 15,458 (18.2%) frozen embryo transfer (FET) cycles with AMH values. None. Live birth. A total of 85,062 out of 259,499 (32.7%) fresh and frozen-thawed autologous non-preimplantation genetic diagnosis cycles had AMH reported for cycles over this 2-year period. Of those, 70,565 cycles which had embryo transfers were included in the analysis. Serum AMH was significantly associated with live birth outcome per transfer in both fresh and FET cycles. Multiple logistic regression demonstrated that AMH is an independent predictor of live birth in fresh transfer cycles and FET cycles when controlling for age, body mass index, race, day of transfer, and number of embryos transferred. Receiver operating characteristic (ROC) curves demonstrated that the areas under the curve (AUC) for AMH as predictors of live birth in fresh cycles and thawed cycles were 0.631 and 0.540, respectively, suggesting that AMH alone is a weak independent predictor of live birth after ART. Similar ROC curves were obtained also when elective single-embryo transfer (eSET) cycles were analyzed separately in either fresh (AUC 0.655) or FET (AUC 0.533) cycles, although AMH was not found to be an independent predictor in eSET cycles. AMH is a poor independent predictor of live birth outcome in either fresh or frozen embryo transfer for both eSET and non-SET transfers. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Impulse oscillometry system as an alternative diagnostic method for chronic obstructive pulmonary disease.

PubMed

Wei, Xia; Shi, Zhihong; Cui, Yajuan; Mi, Jiuyun; Ma, Zhengquan; Ren, Jingting; Li, Jie; Xu, Shudi; Guo, Youmin

2017-11-01

We aimed to compare impulse oscillation system (IOS) and traditional pulmonary function tests (PFTs) for the assessment of the severity of chronic obstructive pulmonary disease (COPD), and to assess the use of IOS parameters to identify patients who were forced expiratory volume in 1 second (FEV1)%pred < 50%.Patients with COPD (n = 215) were enrolled at the Ninth Hospital of Xi'an Affiliated Hospital of Xi'an Jiaotong University between October 2014 and September 2016. All patients were assessed by traditional PFT and IOS. Diagnostic performance of IOS parameters to determine indication for patients of FEV1%pred < 50% was assessed on receiver-operating characteristics (ROC) curve analysis.Out of 215 patients, 18, 83, 78, and 36 patients were classified as grade 1, 2, 3, and 4, respectively, according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity grading. On Spearman correlation analysis, FEV1%pred, MMEF 75%-25%, and residual volume/total lung capacity (RV/TLC) correlated with total respiratory impedance (Z5)%pred, resistance at 5 Hz (R5)-resistance at 20 Hz (R20), R5-R20% R5, R5, R5%pred, frequency response (Fres), reactance area (Ax), and reactance at 5 Hz (X5). On ROC curve analysis, the area under the curve (AUC) of X5 absolute value, Fres, Ax, Z5%pred, R5-R20, and R5-R20% R5 were 0.748, 0.755, 0.760, 0.705, 0.715, and 0.735, respectively, for COPD patients who required inhalational glucocorticoid therapy.IOS parameters showed a good correlation with traditional pulmonary function parameters; reactance parameters showed a stronger correlation than that of the resistance parameters. IOS can be used as an alternative method for pulmonary function assessment in patients with COPD with FEV1%pred < 50% who need inhalational glucocorticoid therapy. ChiCTR-OCH-14004904.

Impulse oscillometry system as an alternative diagnostic method for chronic obstructive pulmonary disease

PubMed Central

Wei, Xia; Shi, Zhihong; Cui, Yajuan; Mi, Jiuyun; Ma, Zhengquan; Ren, Jingting; Li, Jie; Xu, Shudi; Guo, Youmin

2017-01-01

Abstract We aimed to compare impulse oscillation system (IOS) and traditional pulmonary function tests (PFTs) for the assessment of the severity of chronic obstructive pulmonary disease (COPD), and to assess the use of IOS parameters to identify patients who were forced expiratory volume in 1 second (FEV1)%pred < 50%. Patients with COPD (n = 215) were enrolled at the Ninth Hospital of Xi’an Affiliated Hospital of Xi’an Jiaotong University between October 2014 and September 2016. All patients were assessed by traditional PFT and IOS. Diagnostic performance of IOS parameters to determine indication for patients of FEV1%pred < 50% was assessed on receiver-operating characteristics (ROC) curve analysis. Out of 215 patients, 18, 83, 78, and 36 patients were classified as grade 1, 2, 3, and 4, respectively, according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity grading. On Spearman correlation analysis, FEV1%pred, MMEF 75%–25%, and residual volume/total lung capacity (RV/TLC) correlated with total respiratory impedance (Z5)%pred, resistance at 5 Hz (R5)-resistance at 20 Hz (R20), R5-R20% R5, R5, R5%pred, frequency response (Fres), reactance area (Ax), and reactance at 5 Hz (X5). On ROC curve analysis, the area under the curve (AUC) of X5 absolute value, Fres, Ax, Z5%pred, R5-R20, and R5-R20% R5 were 0.748, 0.755, 0.760, 0.705, 0.715, and 0.735, respectively, for COPD patients who required inhalational glucocorticoid therapy. IOS parameters showed a good correlation with traditional pulmonary function parameters; reactance parameters showed a stronger correlation than that of the resistance parameters. IOS can be used as an alternative method for pulmonary function assessment in patients with COPD with FEV1%pred < 50% who need inhalational glucocorticoid therapy. Clinical trial registration number: ChiCTR-OCH-14004904. PMID:29145259

Appropriate body mass index and waist circumference cutoffs for middle and older age group in Thailand: data of 19,621 participants from Thai epidemiologic stroke (TES) study.

PubMed

Samsen, Maiyadhaj; Hanchaiphiboolkul, Suchat; Puthkhao, Pimchanok; Tantirittisak, Tasanee; Towanabut, Somchai

2012-09-01

To determine the appropriate body mass index (BMI) and waist circumference (WC) cutoff point for identification of at least one cardiovascular risk factor (hypertension, dyslipidemia, and type 2 diabetes) in Thailand, and to compare the discrimination ability of BMI with that of WC for discrimination of at least one cardiovascular risk factor. Baseline health survey data of participants of Thai Epidemiologic Stroke (TES) Study, who were free from stroke, enrolled from five geographic regions around the country, were studied as cross-sectional analysis. Receiver operating characteristics curve (ROC) analysis was performed to determine the appropriate cutoff points of BMI and WC in identifying those with presence of at least one cardiovascular risk factors. The BMI or WC value with the shortest distance on the ROC curve was considered to be appropriate cutoffs. Comparing the ability of BMI in discrimination of at least one cardiovascular risk factor with that of WC was performed by comparing ROC area under curve (AUC). Among 19,621 (6,608 men and 13,013 women) participants with age range of 45 to 80 years, the average age was 59.8 years for men and 58.5 years for women. The appropriate cutoff point of BMI was 23 kg/m2 in men and 24 kg/m2 in women. The cutoffs of WC were 80 cm and 78 cm in men and women, respectively. In both gender, waist circumference (WC) (AUC in men = 0.684; 95% CI, 0.672-0.695, AUC in women = 0.673; 95% CI, 0.665-0.681) was significantly (p < 0.001) better than BMI (AUC in men = 0.667; 95% CI, 0.656-0.679, AUC in women = 0.636; 95% CI, 0.628-0.644) in discrimination of at least one cardiovascular risk factor. In Thai adults aged 45 to 80 years, the cutoff points of BMI should be 23 kg/m2 in men and 24 kg/m2 in women. For WC, 80 cm and 78 cm should be considered to be appropriate cutoffs for men and women, respectively. Waist circumference (WC) as a simple obesity index should be advocated for public health screening.

Association between promoter methylation of MLH1 and MSH2 and reactive oxygen species in oligozoospermic men-A pilot study.

PubMed

Gunes, S; Agarwal, A; Henkel, R; Mahmutoglu, A M; Sharma, R; Esteves, S C; Aljowair, A; Emirzeoglu, D; Alkhani, A; Pelegrini, L; Joumah, A; Sabanegh, E

2018-04-01

MLH1 and MSH2 are important genes for DNA mismatch repair and crossing over during meiosis and are implicated in male infertility. Therefore, the methylation patterns of the DNA mismatch repair genes MLH1 and MSH2 in oligozoospermic males were investigated. Ten oligozoospermic patients and 29 normozoospermic donors were analysed. Methylation profiles of the MLH1 and MSH2 promotors were analysed. In addition, sperm motility and seminal reactive oxygen species (ROS) were recorded. Receiver operating characteristic (ROC) analysis was conducted to determine the accuracy of the DNA methylation status of MLH1 and MSH2 to distinguish between oligozoospermic and normozoospermic men. In oligozoospermic men, MLH1 was significantly (p = .0013) more methylated compared to normozoospermic men. Additionally, there was a significant positive association (r = .384; p = .0159) between seminal ROS levels and MLH1 methylation. Contrary, no association between MSH2 methylation and oligozoospermia was found. ROC curve analysis for methylation status of MLH1 was significant (p = .0275) with an area under the curve of 61.1%, a sensitivity of 22.2% and a specificity of 100.0%. This pilot study indicates oligozoospermic patients have more methylation of MLH1 than normozoospermic patients. Whether hypermethylation of the MLH1 promoter plays a role in repairing relevant mismatches of sperm DNA strands in idiopathic oligozoospermia warrants further investigation. © 2017 Blackwell Verlag GmbH.

Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

NASA Astrophysics Data System (ADS)

Zhang, Nannan; Zhou, Kefa; Du, Xishihui

2017-04-01

Mineral prospectivity mapping (MPM) is a multi-step process that ranks promising target areas for further exploration. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are knowledge-driven MPM approaches. In this study, both approaches were used for data processing, based on which MPM was performed for porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang. The results of the two methods were then compared. The two methods combined expert experience and the Studentized contrast (S(C)) values of the weights-of-evidence approach to calculate the weights of 15 layers, and these layers were then integrated by the gamma operator (γ). Through prediction-area (P-A) plot analysis, the optimal γ for fuzzy logic and fuzzy AHP was determined as 0.95 and 0.93, respectively. The thresholds corresponding to different levels of metallogenic probability were defined via concentration-area (C-A) fractal analysis. The prediction performances of the two methods were compared on this basis. The results showed that in MPM based on fuzzy logic, the area under the receiver operating characteristic (ROC) curve was 0.806 and 81.48% of the known deposits were predicted, whereas in MPM based on fuzzy AHP, the area under the ROC curve was 0.862 and 92.59% of the known deposits were predicted. Therefore, prediction based on fuzzy AHP is more accurate and can provide directions for future prospecting.

Prenatal diagnosis of fetal respiratory function: evaluation of fetal lung maturity using lung-to-liver signal intensity ratio at magnetic resonance imaging.

PubMed

Oka, Yasuko; Rahman, Mosfequr; Sasakura, Chihaya; Waseda, Tomoo; Watanabe, Yukio; Fujii, Ryota; Makinoda, Satoru

2014-12-01

The purpose of this retrospective study is to determine the fetal lung-to-liver signal intensity ratio (LLSIR) on T2-weighted images for the prediction of neonatal respiratory outcome. One hundred ten fetuses who underwent magnetic resonance imaging (MRI) examination for various indications after 22 weeks of gestation participated in this study. LLSIR was measured as the ratio of signal intensities of the fetal lung and liver on T2-weighted images at MRI. We examined the changes of the ratio with advancing gestation and the relations between LLSIR and the presence of the severe respiratory disorder (SRD) after birth. The best cut-off value of the LLSIR to predict respiratory outcome after birth was calculated using receiver operating characteristic (ROC) curve analysis. Lung-to-liver signal intensity ratio correlated significantly with advancing gestational age (R = 0.35, p < 0.001). The non-SRD group had higher LLSIR compared with the SRD group (2.15 ± 0.30 vs. 1.53 ± 0.40, p < 0.001). ROC curve analysis showed that fetuses with an LLSIR < 2.00 were more likely to develop SRD [sensitivity: 100%, 95% confidence interval (CI): 52-100%; specificity: 73%, 95% CI 54-88%]. The fetal LLSIR on T2-weighted images is an accurate marker to diagnose the fetal lung maturity. © 2014 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.

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

PubMed Central

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

2016-01-01

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

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

Pancreatic thickness as a predictive factor for postoperative pancreatic fistula after distal pancreatectomy using an endopath stapler.

PubMed

Okano, Keiichi; Oshima, Minoru; Kakinoki, Keitaro; Yamamoto, Naoki; Akamoto, Shintaro; Yachida, Shinichi; Hagiike, Masanobu; Kamada, Hideki; Masaki, Tsutomu; Suzuki, Yasuyuki

2013-02-01

No consistent risk factor has yet been established for the development of pancreatic fistula (PF) after distal pancreatectomy (DP) with a stapler. A total of 31 consecutive patients underwent DP with an endopath stapler between June 2006 and December 2010 using a slow parenchymal flattening technique. The risk factors for PF after DP with an endopath stapler were identified based on univariate and multivariate analyses. Clinical PF developed in 7 of 31 (22 %) patients who underwent DP with a stapler. The pancreata were significantly thicker at the transection line in patients with PF (19.4 ± 1.47 mm) in comparison to patients without PF (12.6 ± 0.79 mm; p = 0.0003). A 16-mm cut-off for pancreatic thickness was established based on the receiver operating characteristic (ROC) curve; the area under the ROC curve was 0.875 (p = 0.0215). Pancreatic thickness (p = 0.0006) and blood transfusion (p = 0.028) were associated with postoperative PF in a univariate analysis. Pancreatic thickness was the only significant independent factor (odds ratio 9.99; p = 0.036) according to a multivariate analysis with a specificity of 72 %, and a sensitivity of 85 %. Pancreatic thickness is a significant independent risk factor for PF development after DP with an endopath stapler. The stapler technique is thus considered to be an appropriate modality in patients with a pancreatic thicknesses of <16 mm.

Screening instruments for a population of older adults: The 10-item Kessler Psychological Distress Scale (K10) and the 7-item Generalized Anxiety Disorder Scale (GAD-7).

PubMed

Vasiliadis, Helen-Maria; Chudzinski, Veronica; Gontijo-Guerra, Samantha; Préville, Michel

2015-07-30

Screening tools that appropriately detect older adults' mental disorders are of great public health importance. The present study aimed to establish cutoff scores for the 10-item Kessler Psychological Distress (K10) and the 7-item Generalized Anxiety Disorder (GAD-7) scales when screening for depression and anxiety. We used data from participants (n = 1811) in the Enquête sur la Santé des Aînés-Service study. Depression and anxiety were measured using DSM-V and DSM-IV criteria. Receiver operating characteristic (ROC) curve analysis provided an area under the curve (AUC) of 0.767 and 0.833 for minor and for major depression when using K10. A cutoff of 19 was found to balance sensitivity (0.794) and specificity (0.664) for minor depression, whereas a cutoff of 23 was found to balance sensitivity (0.692) and specificity (0.811) for major depression. When screening for an anxiety with GAD-7, ROC analysis yielded an AUC of 0.695; a cutoff of 5 was found to balance sensitivity (0.709) and specificity (0.568). No significant differences were found between subgroups of age and gender. Both K10 and GAD-7 were able to discriminate between cases and non-cases when screening for depression and anxiety in an older adult population of primary care service users. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

Kim, Dong Wook

2015-08-01

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

New scoring system combining the FIB-4 index and cytokeratin-18 fragments for predicting steatohepatitis and liver fibrosis in patients with nonalcoholic fatty liver disease.

PubMed

Tada, Toshifumi; Kumada, Takashi; Toyoda, Hidenori; Saibara, Toshiji; Ono, Masafumi; Kage, Masayoshi

To establish a new scoring system as a noninvasive tool for predicting steatohepatitis and liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). A total of 170 patients histologically diagnosed with nonalcoholic steatohepatitis (NASH) (n = 130) or nonalcoholic fatty liver (NAFL) (n = 40) were enrolled. We analyzed receiver operating characteristic (ROC) curves and performed multivariate analysis to predict steatohepatitis and liver fibrosis. Multivariate analysis showed that cytokeratin-18 fragment (CK18-F) levels (≥278 U/L) (odds ratio [OR], 4.46; 95% confidence interval [CI], 1.42-14.00; p = 0.010) and the FIB-4 index (≥1.46) (OR, 4.54; 95% CI, 1.93-29.50; p = 0.004) were independently associated with prediction of NASH. We then established a new scoring system (named the FIC-22 score) for predicting NASH using CK18-F levels and FIB-4 index. The areas under the ROC curve (AUROCs) of the FIC-22 score and NAFIC score were 0.82 (95% CI, 0.75-0.89) and 0.71 (95% CI, 0.62-0.78) (p = 0.044). Additionally, the AUROC of the FIC-22 score for predicting the presence of fibrosis (F ≥ 1) was 0.78 (95% CI, 0.70-0.85). In patients with NAFLD, the FIC-22 score had high predictive accuracy not only for steatohepatitis but also for the presence of liver fibrosis.

Lymphopenia predicts poor prognosis in patients with esophageal squamous cell carcinoma.

PubMed

Feng, Ji-Feng; Liu, Jin-Shi; Huang, Ying

2014-12-01

Lymphopenia is a useful predictive factor in several cancers. The aim of this study was to determine the prognostic value of lymphopenia in patients with esophageal squamous cell carcinoma (ESCC).A retrospective analysis of 307 consecutive patients who had undergone esophagectomy for ESCC was conducted. In our study, a lymphocyte count (LC) of fewer than 1.0 Giga/L was defined as lymphopenia. Kaplan-Meier method was used to calculate the cancer-specific survival (CSS). Cox regression analyses were performed to evaluate the prognostic factors. Receiver operating characteristic (ROC) curve was also plotted to verify the accuracy of LC for CSS prediction.The mean LC was 1.55 ± 0.64 Giga/L (range 0.4-3.7 Giga/L). The incidence of lymphopenia (LC < 1.0 Giga/L) was 16.6% (51/307). Patients with lymphopenia (LC < 1.0 Giga/L) had a significantly shorter 5-year CSS (21.6% vs 43.8%, P = 0.004). On multivariate analysis, lymphopenia (LC < 1.0 Giga/L) was an independent prognostic factor in patients with ESCC (P = 0.013). Lymphopenia had a hazard ratio (HR) of 1.579 [95% confidence interval (CI): 1.100-2.265] for CSS. ROC curve demonstrated that lymphopenia (LC < 1.0 Giga/L) predicts survival with a sensitivity of 86.2% and a specificity of 27.2%. Lymphopenia (LC < 1.0 Giga/L) is still an independent predictive factor for long-term survival in patients with ESCC.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study.

PubMed

Wu, Li; Lin, Huandong; Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen; Gao, Xin

2017-01-01

Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45-54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count.

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study

PubMed Central

Gao, Jian; Li, Xiaoming; Xia, Mingfeng; Wang, Dan; Aleteng, Qiqige; Ma, Hui; Pan, Baishen

2017-01-01

Background and aims Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population. Methods In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age. Results The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45–54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856. Conclusions The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count. PMID:28886160

[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.

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

PubMed

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

2018-06-01

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

Quantitative DNA methylation analysis of paired box gene 1 and LIM homeobox transcription factor 1 α genes in cervical cancer

PubMed Central

Xu, Ling; Xu, Jun; Hu, Zheng; Yang, Baohua; Wang, Lifeng; Lin, Xiao; Xia, Ziyin; Zhang, Zhiling; Zhu, Yunheng

2018-01-01

DNA methylation is associated with tumorigenesis and may act as a potential biomarker for detecting cervical cancer. The aim of the present study was to explore the methylation status of the paired box gene 1 (PAX1) and the LIM homeobox transcription factor 1 α (LMX1A) gene in a spectrum of cervical lesions in an Eastern Chinese population. This single-center study involved 121 patients who were divided into normal cervix (NC; n=28), low-grade squamous intraepithelial lesion (LSIL; n=32), high-grade squamous intraepithelial lesion (HSIL; n=34) and cervical squamous cell carcinoma (CSCC; n=27) groups, according to biopsy results. Following extraction and modification of the DNA, quantitative assessment of the PAX1 and LMX1A genes in exfoliated cells was performed using pyrosequencing analysis. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity and specificity of each parameter and cut-off values of the percentage of methylation reference (PMR) for differentiation diagnosis. Analysis of variance was used to identify differences among groups. The PMR of the two genes was significantly higher in the HSIL and CSCC groups compared with that in the NC and LSIL groups (P<0.001). ROC curve analysis demonstrated that the sensitivity, specificity and accuracy for detection of CSCC were 0.790, 0.837 and 0.809, respectively, using PAX1; and 0.633, 0.357 and 0.893, respectively, using LMX1A. These results indicated that quantitative PAX1 methylation demonstrates potential for cervical cancer screening, while further investigation is required to determine the potential of LMX1A methylation. PMID:29541217

Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

PubMed

Prabitha, Vasumathi Gopala; Suchetha, Sambasivan; Jayanthi, Jayaraj Lalitha; Baiju, Kamalasanan Vijayakumary; Rema, Prabhakaran; Anuraj, Koyippurath; Mathews, Anita; Sebastian, Paul; Subhash, Narayanan

2016-01-01

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

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

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.

FibroScan, aspartate aminotransferase and alanine aminotransferase ratio (AAR), aspartate aminotransferase to platelet ratio index (APRI), fibrosis index based on the 4 factor (FIB-4), and their combinations in the assessment of liver fibrosis in patients with hepatitis B.

PubMed

Ding, Deping; Li, Hongbing; Liu, Ping; Chen, Lingli; Kang, Jian; Zhang, Yinhua; Ma, Deqiang; Chen, Yue; Luo, Jie; Meng, Zhongji

2015-01-01

The aim of this study was to assess the effects of FibroScan, aspartate aminotransferase and alanine aminotransferase ratio (AAR), aspartate aminotransferase to platelet ratio index (APRI), fibrosis index based on the 4 factor (FIB-4) and their combinations on liver fibrosis in patients with hepatitis B. 406 hospitalized patients with chronic hepatitis B (CHB) and cirrhosis in our hospital were analyzed retrospectively and collected patients clinical indicators, including liver stiffness (LS), AAR, APRI and FIB-4, and then compared the differences of these indicators between CHB group and hepatitis B with cirrhosis group. Receiver operating curve (ROC) was used to evaluate the differentiating capacity of these indicators on CHB and liver cirrhosis. Four indicators related to liver cirrhosis had a statistical significance between two groups (P < 0.01); the under ROC curve areas of LS, AAR, APRI and FIB-4 for differential diagnosis of CHB and liver cirrhosis were 0.866, 0.772, 0.632 and 0.885, respectively. The under ROC curve areas of LS, AAR, APRI and FIB-4 for differential diagnosis of liver cirrhosis at compensatory stage and de-compensatory stage were 0.627, 0.666, 0.795 and 0.820, respectively. LS, AAR, APRI and FIB-4 were good indicators as clinical diagnosis and differential diagnosis on hepatitis B related cirrhosis.

Fractal and Gray Level Cooccurrence Matrix Computational Analysis of Primary Osteosarcoma Magnetic Resonance Images Predicts the Chemotherapy Response.

PubMed

Djuričić, Goran J; Radulovic, Marko; Sopta, Jelena P; Nikitović, Marina; Milošević, Nebojša T

2017-01-01

The prediction of induction chemotherapy response at the time of diagnosis may improve outcomes in osteosarcoma by allowing for personalized tailoring of therapy. The aim of this study was thus to investigate the predictive potential of the so far unexploited computational analysis of osteosarcoma magnetic resonance (MR) images. Fractal and gray level cooccurrence matrix (GLCM) algorithms were employed in retrospective analysis of MR images of primary osteosarcoma localized in distal femur prior to the OsteoSa induction chemotherapy. The predicted and actual chemotherapy response outcomes were then compared by means of receiver operating characteristic (ROC) analysis and accuracy calculation. Dbin, Λ, and SCN were the standard fractal and GLCM features which significantly associated with the chemotherapy outcome, but only in one of the analyzed planes. Our newly developed normalized fractal dimension, called the space-filling ratio (SFR) exerted an independent and much better predictive value with the prediction significance accomplished in two of the three imaging planes, with accuracy of 82% and area under the ROC curve of 0.20 (95% confidence interval 0-0.41). In conclusion, SFR as the newly designed fractal coefficient provided superior predictive performance in comparison to standard image analysis features, presumably by compensating for the tumor size variation in MR images.

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

PubMed

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Potential Role of Circulating MiR-21 in the Diagnosis and Prognosis of Digestive System Cancer: A Systematic Review and Meta-Analysis.

PubMed

Yin, Chengqiang; Zhou, Xiaoying; Dang, Yini; Yan, Jin; Zhang, Guoxin

2015-12-01

Recent evidences indicate that circulating microRNAs (miRNAs) exhibit aberrant expression in the plasma of patients suffering from cancer compared to normal individuals, suggesting that it may be a useful noninvasion diagnostic method. MiR-21 plays crucial roles in carcinogenesis and can be served as a biomarker for the detection of various cancers. Therefore, the aim of this meta-analysis is to assess the potential role of miR-21 for digestive system cancer. By searching the PubMed, Embase, and Web of Science for publications concerning the diagnostic value of miR-21 for digestive system cancer, total of 23 publications were included in this meta-analysis. Receiver operating characteristic curves (ROC) were used to check the overall test performance. For prognostic meta-analysis, pooled hazard ratios (HRs) of circulating miR-21 for survival were calculated. Totally 23 eligible publications were included in this meta-analysis (15 articles for diagnosis and 8 articles for prognosis). For diagnostic meta-analysis, the summary estimates revealed that the pooled sensitivity and specificity were 0.76 (95% CI = 0.70-0.82) and 0.84 (95% CI = 0.78-0.89). Besides, the area under the summary ROC curve (AUC) is 0.87. For prognostic meta-analysis, the pooled HR of higher miR-21 expression in circulation was 1.94 (95% CI = 0.99-3.82, P = 0.055), which indicated higher miR-21 expression could be likely to predict poorer survival in digestive system cancer. The subgroup analysis implied the higher expression of miR-21 was correlated with worse overall survival in the Asian population in digestive system cancer (HR = 2.41, 95% CI = 1.21-4.77, P = 0.012). The current evidence suggests circulating miR-21 may be suitable to be a diagnostic and prognostic biomarker for digestive system cancer in the Asians.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

PubMed

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.

PubMed

Fernández, Leónides; Mediano, Pilar; García, Ricardo; Rodríguez, Juan M; Marín, María

2016-09-01

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.

Responsiveness of Self-Report Measures in Individuals with Vertigo, Dizziness and Unsteadiness

PubMed Central

Friscia, Lauren A.; Morgan, Michael T.; Sparto, Patrick J.; Furman, Joseph M.; Whitney, Susan L.

2018-01-01

Objective The responsiveness (sensitivity to change) of many self-report measures commonly used with individuals who have balance and vestibular dysfunction has not been assessed. The purpose of this study was to determine the responsiveness of four self-report measures including the Activities-specific Balance Confidence (ABC) scale, the Dizziness Handicap Inventory (DHI), the Falls Efficacy Scale-International (FES-I), and the Vestibular Activities and Participation (VAP) scale in people seeking treatment for vertigo, dizziness, and unsteadiness. Study design A prospective descriptive study. Patients Forty-five patients (mean age 56 y, range 18–79 y) with vertigo, dizziness, and unsteadiness were included. Main outcome measures Participants completed the measures at their initial physician examination and four to six weeks later. The follow-up visit included a Global Rating of Change Scale (GROC). The change in total scores for each self-report measure from initial visit to follow-up visit were recorded and compared against the GROC. A Spearman correlation was performed to determine the relationship between all four self-report measures and the GROC. A Receiver Operating Characteristic (ROC) curve was also used to evaluate responsiveness. Results Significant correlations were found between the GROC and ABC (ρ = 0.50), DHI (ρ = 0.61), and FES-I (ρ = 0.36), but not the VAP (ρ = 0.27). The ROC curve analysis showed that the area under the curve was significantly greater than 0.5 for the ABC, DHI and FES-I. Conclusion The DHI demonstrated the greatest responsiveness, with an optimal cutoff of a change in 3 points related to significant change. PMID:24829039

Stratification of complexity in congenital heart surgery: comparative study of the Risk Adjustment for Congenital Heart Surgery (RACHS-1) method, Aristotle basic score and Society of Thoracic Surgeons-European Association for Cardio- Thoracic Surgery (STS-EACTS) mortality score.

PubMed

Cavalcanti, Paulo Ernando Ferraz; Sá, Michel Pompeu Barros de Oliveira; Santos, Cecília Andrade dos; Esmeraldo, Isaac Melo; Chaves, Mariana Leal; Lins, Ricardo Felipe de Albuquerque; Lima, Ricardo de Carvalho

2015-01-01

To determine whether stratification of complexity models in congenital heart surgery (RACHS-1, Aristotle basic score and STS-EACTS mortality score) fit to our center and determine the best method of discriminating hospital mortality. Surgical procedures in congenital heart diseases in patients under 18 years of age were allocated to the categories proposed by the stratification of complexity methods currently available. The outcome hospital mortality was calculated for each category from the three models. Statistical analysis was performed to verify whether the categories presented different mortalities. The discriminatory ability of the models was determined by calculating the area under the ROC curve and a comparison between the curves of the three models was performed. 360 patients were allocated according to the three methods. There was a statistically significant difference between the mortality categories: RACHS-1 (1) - 1.3%, (2) - 11.4%, (3)-27.3%, (4) - 50 %, (P<0.001); Aristotle basic score (1) - 1.1%, (2) - 12.2%, (3) - 34%, (4) - 64.7%, (P<0.001); and STS-EACTS mortality score (1) - 5.5 %, (2) - 13.6%, (3) - 18.7%, (4) - 35.8%, (P<0.001). The three models had similar accuracy by calculating the area under the ROC curve: RACHS-1- 0.738; STS-EACTS-0.739; Aristotle- 0.766. The three models of stratification of complexity currently available in the literature are useful with different mortalities between the proposed categories with similar discriminatory capacity for hospital mortality.

Multivariate modelling of prostate cancer combining magnetic resonance derived T2, diffusion, dynamic contrast-enhanced and spectroscopic parameters.

PubMed

Riches, S F; Payne, G S; Morgan, V A; Dearnaley, D; Morgan, S; Partridge, M; Livni, N; Ogden, C; deSouza, N M

2015-05-01

The objectives are determine the optimal combination of MR parameters for discriminating tumour within the prostate using linear discriminant analysis (LDA) and to compare model accuracy with that of an experienced radiologist. Multiparameter MRIs in 24 patients before prostatectomy were acquired. Tumour outlines from whole-mount histology, T2-defined peripheral zone (PZ), and central gland (CG) were superimposed onto slice-matched parametric maps. T2, Apparent Diffusion Coefficient, initial area under the gadolinium curve, vascular parameters (K(trans),Kep,Ve), and (choline+polyamines+creatine)/citrate were compared between tumour and non-tumour tissues. Receiver operating characteristic (ROC) curves determined sensitivity and specificity at spectroscopic voxel resolution and per lesion, and LDA determined the optimal multiparametric model for identifying tumours. Accuracy was compared with an expert observer. Tumours were significantly different from PZ and CG for all parameters (all p < 0.001). Area under the ROC curve for discriminating tumour from non-tumour was significantly greater (p < 0.001) for the multiparametric model than for individual parameters; at 90 % specificity, sensitivity was 41 % (MRSI voxel resolution) and 59 % per lesion. At this specificity, an expert observer achieved 28 % and 49 % sensitivity, respectively. The model was more accurate when parameters from all techniques were included and performed better than an expert observer evaluating these data. • The combined model increases diagnostic accuracy in prostate cancer compared with individual parameters • The optimal combined model includes parameters from diffusion, spectroscopy, perfusion, and anatominal MRI • The computed model improves tumour detection compared to an expert viewing parametric maps.

Cervical varicosities may predict placenta accreta in posterior placenta previa: a magnetic resonance imaging study.

PubMed

Ishibashi, Hiroki; Miyamoto, Morikazu; Shinnmoto, Hiroshi; Murakami, Wakana; Soyama, Hiroaki; Nakatsuka, Masaya; Natsuyama, Takahiro; Yoshida, Masashi; Takano, Masashi; Furuya, Kenichi

2017-10-01

The aim of this study was to prenatally predict placenta accreta in posterior placenta previa using magnetic resonance imaging (MRI). This retrospective study was approved by the Institutional Review Board of our hospital. We identified 81 patients with singleton pregnancy who had undergone cesarean section due to posterior placenta previa at our hospital between January 2012 and December 2016. We calculated the sensitivity and specificity of several well-known findings, and of cervical varicosities quantified using magnetic resonance imaging, in predicting placenta accreta in posterior placenta previa. To quantify cervical varicosities, we calculated the A/B ratio, where "A" was the minimum distance from the most dorsal cervical varicosity to the deciduous placenta, and "B" was the minimum distance from the most dorsal cervical varicosity to the amniotic placenta. The appropriate cut-off value of the A/B ratio was determined using a receiver operating characteristic (ROC) curve. Three patients (3.7%) were diagnosed as having placenta accreta. The sensitivity and specificity of the well-known findings were 0 and 97.4%, respectively. Furthermore, the A/B ratio ranged from 0.02 to 0.79. ROC curve analysis revealed that the area under the combined placenta accreta and A/B ratio curve was 0.96. When the cutoff value of the A/B ratio was set 0.18, the sensitivity and specificity were 100 and 91%, respectively. It was difficult to diagnose placenta accreta in the posterior placenta previa using the well-known findings. The quantification of cervical varicosities could effectively predict placenta accreta.

Knowledge-Based Systems Approach to Wilderness Fire Management.

NASA Astrophysics Data System (ADS)

Saveland, James M.

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

[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.

[Value of non-invasive models of liver fibrosis in judgment of treatment timing in chronic hepatitis B patients with ALT < 2×upper limit of normal].

PubMed

Zhou, Q Q; Hu, Y B; Zhou, K; Zhang, W W; Li, M H; Dong, P; Di, J G; Hong, L; Du, Q W; Xie, Y; Sun, Q F

2016-09-20

Objective: To investigate the value of non-invasive liver fibrosis models, FIB-4, S index, aspartate aminotransferase to platelet ratio index(APRI), globulin-platelet(GP)model, aspartate aminotransferase/platelet/gamma-glutamyl transpeptidase/alpha-fetoprotein(APGA), and platelet/age/phosphatase/alpha-fetoprotein/aspartate aminotransferase(PAPAS), in the diagnosis of marked liver fibrosis in chronic hepatitis B(CHB)patients with ALT < 2×upper limit of normal(ULN), as well as treatment timing for this population. Methods: A total of 389 CHB patients with ALT < 2×ULN who were admitted to Beijing Ditan Hospital and whose treatment timing was difficult to judge were enrolled. Transdermal liver biopsy was performed to obtain pathological results, and routine serological tests were performed, including routine blood test, serum biochemical parameters, hepatitis B virus(HBV)markers, and HBV DNA. According to liver pathology, the patients were divided into non-marked liver fibrosis group(S < 2)with 324 patients and marked liver fibrosis group(S≥2)with 65 patients. The non-invasive models for predicting liver fibrosis was established with reference to original articles. SPSS 19.0 software was used for statistical analysis, and the receiver operating characteristic(ROC)curve was used to compare the value of different non-invasive models in predicting marked liver fibrosis in this population. Results: All the non-invasive models had a certain diagnostic value for liver fibrosis degree in these patients, and the areas under the ROC curve for APRI, FIB-4, APGA, S index, PAPAS, and GP model were 0.718, 0.691, 0.758, 0.729, 0.673, and 0.691, respectively. APGA had the largest area under the ROC curve(0.758, 95% CI 0.673-0.844), and gamma-glutamyl transpeptidase was significantly positively correlated with liver fibrosis degree. Conclusion: The non-invasive models of liver fibrosis can identify marked liver fibrosis in CHB patients with ALT < 2×ULN in whom it is difficult to judge treatment timing and help to determine treatment timing for them. APGA model has the highest value and can reduce the need for liver biopsy to the certain degree.

Variable corneal compensation improves discrimination between normal and glaucomatous eyes with the scanning laser polarimeter.

PubMed

Tannenbaum, Dana P; Hoffman, Douglas; Lemij, Hans G; Garway-Heath, David F; Greenfield, David S; Caprioli, Joseph

2004-02-01

The presently available scanning laser polarimeter (SLP) has a fixed corneal compensator (FCC) that neutralizes corneal birefringence only in eyes with birefringence that matches the population mode. A prototype variable corneal compensator (VCC) provides neutralization of individual corneal birefringence based on individual macular retardation patterns. The aim of this study was to evaluate the relative ability of the SLP with the FCC and with the VCC to discriminate between normal and glaucomatous eyes. Prospective, nonrandomized, comparative case series. Algorithm-generating set consisting of 56 normal eyes and 55 glaucomatous eyes and an independent data set consisting of 83 normal eyes and 56 glaucomatous eyes. Sixteen retardation measurements were obtained with the SLP with the FCC and the VCC from all subjects. Dependency of parameters on age, gender, ethnic origin, and eye side was sought. Logistic regression was used to evaluate how well the various parameters could detect glaucoma. Discriminant functions were generated, and the area under the receiver operating characteristic (ROC) curve was determined. Discrimination between normal and glaucomatous eyes on the basis of single parameters was significantly better with the VCC than with the FCC for 6 retardation parameters: nasal average (P = 0.0003), superior maximum (P = 0.0003), ellipse average (P = 0.002), average thickness (P = 0.003), superior average (P = 0.010), and inferior average (P = 0.010). Discriminant analysis identified the optimal combination of parameters for the FCC and for the VCC. When the discriminant functions were applied to the independent data set, areas under the ROC curve were 0.84 for the FCC and 0.90 for the VCC (P<0.021). When the discriminant functions were applied to a subset of patients with early visual field loss, areas under the ROC curve were 0.82 for the FCC and 0.90 for the VCC (P<0.016). Individual correction for corneal birefringence with the VCC significantly improved the ability of the SLP to distinguish between normal and glaucomatous eyes and enabled detection of patients with early glaucoma.

A Model to Predict Duration of Ventilation and 30-Day Mortality in Patients with Traumatic Injuries

DTIC Science & Technology

2014-12-02

count and serum albumin had significantly high centralities and were identified the “hubs” in the network. The area under the ROC curve ( AUC -ROC) of...Pre-flight systolic blood pressure was 121 [109-143] mmHg, pulse 100 [84-116] bpm, and base deficit 0 [-2-2]. The median number of blood products...OR 9.2 [1.88-166.11]), and whole blood (OR 3.18 [1.38-7.04]) were associated with death. The combination of variables produced an AUC of 0.84 with

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.

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.

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

PubMed

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

2013-02-01

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

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

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

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

2012-12-01

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

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

PubMed

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

2013-05-01

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

Significance of peak height velocity as a predictive factor for curve progression in patients with idiopathic scoliosis

PubMed Central

2015-01-01

Background Much attention has been paid to peak height velocity (PHV) as a possible predictor of curve progression in patients with idiopathic scoliosis (IS). The aim of this study was to analyze the relationship between the magnitude of the Cobb angle at PHV and scoliosis progression, defined as having surgery prior to skeletal maturity in female patients with IS. Methods A retrospective review identified 56 skeletally immature female IS patients who were followed until maturity. The mean age and the mean pubertal status at the initial visit were 10 years and 24 months before menarche respectively, with a follow-up period of 5 years. They were divided into two groups: non-surgery group (NS) and surgery group (S), depending on their treatment method in use at the final follow-up visit. Surgery group was defined as an ultimately having surgery due to Cobb angle greater than 45 degrees prior to skeletal maturity regardless of conservative management. Height measurements were recorded at each visit; height velocity was calculated as the height change, in cm, divided by the time interval, in years. The PHV, chronological age at PHV (APHV), height at PHV (HPHV), and final height (FH) were determined for each group. In patients with Cobb angle greater than 30 degrees, the corrected height was calculated by Kono formula and corrected height velocity values were provided. The sensitivity, specificity, and area under the curve (AUC) of the receiver-operating -characteristic (ROC) analysis were calculated to predict spinal curve progression for various Cobb-angle cutoff values at PHV. Results The corrected PHV had a mean value of 8.5 and 8.9 cm/year in the NS-group and S-group, respectively. The APHV was 11.9 and 11 years, the corrected HPHV was 152.9, and 149.3 cm, and the corrected FH was 159.9 and 159.3 cm, respectively. When a Cobb angle of 31.5 degrees was at PHV, ROC analysis revealed 78% sensitivity, 82% specificity, and an AUC of 0.93, acceptable values for curve progression in patients with IS. Conclusions These findings indicate that 31.5 degrees of spinal curvature when patients are at PHV is a significant predictive indicator for progression of the curve to a magnitude requiring surgery. We suggest that the curve-progression risk assessment in patients with IS should include PHV, along with measures of skeletal and non-skeletal maturities. PMID:25815057

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

Vertical or horizontal orientation of foot radiographs does not affect image interpretation

PubMed Central

Ferran, Nicholas Antonio; Ball, Luke; Maffulli, Nicola

2012-01-01

Summary This study determined whether the orientation of dorsoplantar and oblique foot radiographs has an effect on radiograph interpretation. A test set of 50 consecutive foot radiographs were selected (25 with fractures, and 25 normal), and duplicated in the horizontal orientation. The images were randomly arranged, numbered 1 through 100, and analysed by six image interpreters. Vertical and horizontal area under the ROC curve, accuracy, sensitivity and specificity were calculated for each image interpreter. There was no significant difference in the area under the ROC curve, accuracy, sensitivity or specificity of image interpretation between images viewed in the vertical or horizontal orientation. While conventions for display of radiographs may help to improve the development of an efficient visual search strategy in trainees, and allow for standardisation of publication of radiographic images, variation from the convention in clinical practice does not appear to affect the sensitivity or specificity of image interpretation. PMID:23738310

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.

Hounsfield unit of screw trajectory as a predictor of pedicle screw loosening after single level lumber interbody fusion.

PubMed

Sakai, Yusuke; Takenaka, Shota; Matsuo, Yohei; Fujiwara, Hiroyasu; Honda, Hirotsugu; Makino, Takahiro; Kaito, Takashi

2018-06-01

This study aims to clarify the clinical potential of Hounsfield unit (HU), measured on computed tomography (CT) images, as a predictor of pedicle screw (PS) loosening, compared to bone mineral density (BMD). A total of 206 screws in 52 patients (21 men and 31 women; mean age 68.2 years) were analyzed retrospectively. The screws were classified into two groups depending on their screw loosening status on 3-month follow-up CT (loosening screw group vs. non-loosening screw group). Preoperative HU of the trajectory was evaluated by superimposing preoperative and postoperative CT images using three-dimensional image analysis software. Age, sex, body mass index, screw size, BMD of lumbar, and HU of screw trajectory were analyzed in association with screw loosening. Multivariate logistic regression analysis was performed, and the thresholds for PS loosening risk factors were evaluated using a continuous numerical variable and receiver operating characteristic (ROC) curve analyses. The area under the curve (AUC) was used to determine the diagnostic performance, and values > 0.75 were considered to represent good performance. The loosening screw group contained 24 screws (12%). Multivariate analysis revealed that the significant independent risk factors were not BMD but male sex [P = 0.028; odds ratio (OR) 2.852, 95% confidence interval (CI) 1.120-7.258] and HU of screw trajectory (P = 0.006; OR 0.989, 95% CI 0.980-0.997). ROC curve analysis demonstrated that the AUC for HU of screw trajectory for women was 0.880 (95% CI 0.798-0.961). The cutoff value was 153.5. AUC for men was 0.635 (95% CI 0.449-0.821), which was not considered to be a good performance. Low HU of screw trajectories was identified as a risk factor of PS loosening for women. For female patients with low HU, additional augmentation is recommended to prevent PS loosening. Copyright © 2018 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

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.

The Basilar Artery on Computed Tomography Angiography Score for Acute Basilar Artery Occlusion Treated with Mechanical Thrombectomy.

PubMed

Yang, Haihua; Ma, Ning; Liu, Lian; Gao, Feng; Mo, Dapeng; Miao, Zhongrong

2018-06-01

Recently, the Basilar Artery on Computed Tomography Angiography (BATMAN) score predicts clinical outcome of acute basilar artery occlusion (BAO), yet there is no extensive external validation. The purpose of this study was to validate the prognostic value of BATMAN scoring system for the prediction of clinical outcome in patients with acute BAO treated with endovascular mechanical thrombectomy by using cerebral digital subtraction angiography (DSA). We analyzed the clinical and angiographic data of consecutive patients with acute BAO from March 2012 to November 2016. The BATMAN scoring system was used to assess the collateral status and thrombus burden. Thrombolysis in Cerebral Infarction (TICI) score 2b-3 was defined as successful recanalization. Receiver operating characteristic (ROC) curve was used to determine the area under the curve (AUC) and the optimum cutoff value. Multivariate regression analysis was used to identify the predictor of clinical outcome. This study included 63 patients with acute BAO who underwent mechanical thrombectomy. Of these patients, 90.5% (57/63) achieved successful recanalization (TICI, 2b-3) and 34.9% (22/63) had a favorable outcome (modified Rankin Scale score 0-2). ROC analysis indicated that the AUC of the BATMAN score was .722 (95% confidence interval [CI], .594-.827), and the optimal cutoff value was 3 (sensitivity = 72.73, specificity = 63.41). In multivariate logistic regression analysis, the BATMAN score higher than 3 was associated with favorable outcome (odds ratio, 5.214; 95% CI, 1.47-18.483; P = .011). The BATMAN score on DSA seems to predict the functional outcome in patients of acute BAO treated with mechanical thrombectomy. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI).

PubMed

Lussu, Milena; Camboni, Tania; Piras, Cristina; Serra, Corrado; Del Carratore, Francesco; Griffin, Julian; Atzori, Luigi; Manzin, Aldo

2017-09-21

Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1 H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R 2 Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.

Evaluating the influence of geo-environmental factors on gully erosion in a semi-arid region of Iran: An integrated framework.

PubMed

Rahmati, Omid; Tahmasebipour, Naser; Haghizadeh, Ali; Pourghasemi, Hamid Reza; Feizizadeh, Bakhtiar

2017-02-01

Despite the importance of soil erosion in sustainable development goals in arid and semi-arid areas, the study of the geo-environmental conditions and factors influencing gully erosion occurrence is rarely undertaken. As effort to this challenge, the main objective of this study is to apply an integrated approach of Geographic Object-Based Image Analysis (GEOBIA) together with high-spatial resolution imagery (SPOT-5) for detecting gully erosion features at the Kashkan-Poldokhtar watershed, Iran. We also aimed to apply a Conditional Probability (CP) model for establishing the spatial relationship between gullies and the Geo-Environmental Factors (GEFs). The gully erosion inventory map prepared using GEOBIA and field surveying was randomly partitioned into two subsets: (1) part 1 that contains 70% was used in the training phase of the CP model; (2) part 2 is a validation dataset (30%) for validation of the model and to confirm its accuracy. Prediction performances of the GEOBIA and CP model were checked by overall accuracy and Receiver Operating Characteristics (ROC) curve methods, respectively. In addition, the influence of all GEFs on gully erosion was evaluated by performing a sensitivity analysis model. The validation findings illustrated that overall accuracy for GEOBIA approach and the area under the ROC curve for the CP model were 92.4% and 89.9%, respectively. Also, based on sensitivity analysis, soil texture, drainage density, and lithology represent significantly effects on the gully erosion occurrence. This study has shown that the integrated framework can be successfully used for modeling gully erosion occurrence in a data-poor environment. Copyright © 2016 Elsevier B.V. All rights reserved.

Pelvic floor morphometry: a predictor of success of pelvic floor muscle training for women with stress and mixed urinary incontinence.

PubMed

Dumoulin, Chantale; Tang, An; Pontbriand-Drolet, Stéphanie; Madill, Stephanie J; Morin, Mélanie

2017-08-01

The aim of this study was to determine if pelvic floor muscle (PFM) morphometry at baseline, as measured by MRI, can predict response to PFM training in women with stress or mixed urinary incontinence (UI). This study was a prospective quasi-experimental pre-test, post-test cohort study of women with UI, aged 60 years and older. All participants completed a baseline assessment of UI severity and impact, using the 72-h bladder diary and the Incontinence Impact Questionnaire. They underwent a pelvic MRI examination to assess the PFM anatomy. Women then participated in a 12-week PFM training program. Finally, they attended a post intervention assessment of UI severity and impact. The association between morphometry and PFM training response was assessed by univariate analysis, multivariate analysis, and receiver operating characteristic (ROC) curve analysis. The urethro-vesical junction height at rest, as measured by MRI before treatment, was associated with response to PFM training both on univariate (p ≤ 0.005) and multivariate analyses (p = 0.007). The area under the ROC curve was 0.82 (95% confidence interval [CI]: 0.67-0.96). Using a cut-off point of 11.4 mm, participants' response to PFM training was predicted with a sensitivity of 77% and a specificity of 83%. Incontinent women with a urethro-vesical junction height above this threshold were 35% more likely to respond to PFM training (OR 1.35; 95% CI: 1.08-1.67). In older women with UI, a urethro-vesical junction height at rest of at least 11.4 mm appears to be predictive of PFM training response.

Doppler Audio Signal Analysis as an Additional Tool in Evaluation of Umbilical Artery Circulation.

PubMed

Thuring, Ann; Källén, Karin; Brännström, K Jonas; Jansson, Tomas; Maršál, Karel

2017-10-01

Purpose  To investigate the predictive capacity of a new method for sound spectrum analysis of Doppler signals recorded from the umbilical artery in high-risk pregnancies. Material and Methods  The retrospective study comprised 127 pregnant women with various pregnancy complications between 23 and 39 gestational weeks. Umbilical artery blood flow velocity waveforms were recorded with Doppler ultrasound and characterized by pulsatility index (PI) and blood flow class (BFC). Doppler audio signals were stored on a digital video recorder and the sound frequency at the energy level 15 dB below its peak (MAX peak-15 dB ) was estimated off-line. The prediction of probability for composite adverse pregnancy outcome (operative delivery for fetal distress, admission to neonatal intensive care unit, perinatal death) was evaluated using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. Results  With increasing umbilical artery BFC, the MAX peak-15 dB frequencies decreased (p < 0.0001) and the PI increased (p < 0.0001). The ROC AUCs for adverse outcome for MAX peak-15 dB and for PI were 0.842 and 0.836 (p = 0.88), respectively. For the combination of MAX peak-15 dB and PI, the corresponding AUC was 0.894, significantly higher than that of PI (p < 0.03) and of MAX peak-15 dB (p < 0.05). Conclusion  Umbilical artery Doppler sound spectrum analysis might be a useful supplement to PI in the clinical evaluation of fetoplacental circulation. © Georg Thieme Verlag KG Stuttgart · New York.

Relative to open surgery, minimally-invasive renal and ureteral pediatric surgery offers no improvement in 30-day complications, yet requires longer operative time: Data from the National Surgical Quality Improvement Program Pediatrics.

PubMed

Colaco, Marc; Hester, Austin; Visser, William; Rasper, Alison; Terlecki, Ryan

2018-05-01

Performance of minimally-invasive surgery (MIS) is increasing relative to open surgery. We sought to compare the contemporary rates of short-term complications of open versus laparoscopic renal and ureteral surgery in pediatric patients. A retrospective cross-sectional analysis of the National Surgical Quality Improvement Program Pediatrics database was performed of all cases in 2014 identified using CPT procedure codes for nephrectomy, partial nephrectomy (PN), ureteroneocystostomy (UNC), and pyeloplasty, and reviewed for postoperative complications. Univariate analysis was performed to determine 30-day complications, with comparison between open and MIS approaches. Receiver operator curve (ROC) analysis was performed to determine differences in body surface area (BSA) and age for open versus MIS. Review identified 207 nephrectomies, 72 PN, 920 UNC, and 625 pyeloplasties. MIS was associated with older age and larger BSA except for cases of UNC. Apart from PN, operative durations were longer with MIS. However, only PN was associated with significantly longer length of hospital stay (LOS). There was no difference in incidence of all other 30-day complications. When evaluating BSA via ROC, the area under the curve (AUC) was found to be 0.730 and was significant. Children with a BSA greater than 0.408 m 2 were more likely to have MIS (sensitivity, 66.9%; specificity, 69.3%). Regarding age, the AUC was 0.732. Children older than 637.5 days were more likely to have MIS (sensitivity, 72.8%; specificity, 63.3%). Pediatric MIS is associated with longer operative time for nephrectomy, but shorter LOS following PN. Surgical approach was not associated with difference in short-term complications.

Minimal clinically important difference of voice handicap index-10 in vocal fold paralysis.

PubMed

Young, VyVy N; Jeong, Kwonho; Rothenberger, Scott D; Gillespie, Amanda I; Smith, Libby J; Gartner-Schmidt, Jackie L; Rosen, Clark A

2018-06-01

The Voice Handicap Index-10 (VHI-10) is commonly used to measure patients' perception of vocal handicap. Clinical consensus has previously defined clinically meaningful improvement as a decrease ≥5. This study determines the minimal clinically important difference (MCID) for VHI-10 in patients with unilateral vocal fold paralysis (UVFP) using anchor-based methodology. Prospective cohort questionnaire analysis. Two hundred eighty-one UVFP patients completed the VHI-10 on two consecutive visits (within 3 months). At the follow-up visit, patients answered an 11-point Global Rating of Change Questionnaire (GRCQ) scored from -5 to +5. Relationship between the GRCQ and change in VHI-10 was quantified using analysis of variance, and MCID for the VHI-10 was determined using receiver operating characteristic (ROC) curve analysis. Overall mean VHI-10 change was -3.71 (standard deviation [SD] = 8.89) and mean GRCQ was 1.37 (SD = 2.51). Average interval between measurements was 1.73 months (SD = 0.83). Mean changes in VHI-10 scores were -7.45, -0.53, and +4.40 for patients whose GRCQ scores indicated improvement, no change, and worsening, respectively. Differences between mean scores were statistically significant (P < .001). Area under the ROC curve was 0.80, demonstrating the classification accuracy of VHI-10 change scores. A VHI-10 change of -4 was determined to be the optimal threshold that discriminated between improvement and no improvement (sensitivity and specificity 0.62 and 0.88, respectively). The MCID for improvement in VHI-10 in UVFP patients is a decrease of 4. This information improves understanding of patients' response to treatment and allows comparison between different treatments. Future research should determine MCID for VHI-10 across all voice disorders. 4. Laryngoscope, 128:1419-1424, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Risk factors for radiation pneumonitis after stereotactic radiation therapy for lung tumours: clinical usefulness of the planning target volume to total lung volume ratio.

PubMed

Ueyama, Tomoko; Arimura, Takeshi; Takumi, Koji; Nakamura, Fumihiko; Higashi, Ryutaro; Ito, Soichiro; Fukukura, Yoshihiko; Umanodan, Tomokazu; Nakajo, Masanori; Koriyama, Chihaya; Yoshiura, Takashi

2018-06-01

To identify risk factors for symptomatic radiation pneumonitis (RP) after stereotactic radiation therapy (SRT) for lung tumours. We retrospectively evaluated 68 lung tumours in 63 patients treated with SRT between 2011 and 2015. RP was graded according to the National Cancer Institute-Common Terminology Criteria for Adverse Events version 4.0. SRT was delivered at 7.0-12.0 Gy per each fraction, once daily, to a total of 48-64 Gy (median, 50 Gy). Univariate analysis was performed to assess patient- and treatment-related factors, including age, sex, smoking index (SI), pulmonary function, tumour location, serum Krebs von den Lungen-6 value (KL-6), dose-volume metrics (V5, V10, V20, V30, V40 and VS5), homogeneity index of the planning target volume (PTV), PTV dose, mean lung dose (MLD), contralateral MLD and V2, PTV volume, lung volume and the PTV/lung volume ratio (PTV/Lung). Performance of PTV/Lung in predicting symptomatic RP was also analysed using receiver operating characteristic (ROC) analysis. The median follow-up period was 21 months. 10 of 63 patients (15.9%) developed symptomatic RP after SRT. On univariate analysis, V10, V20, PTV volume and PTV/Lung were significantly associated with occurrence of RP  ≥Grade 2. ROC curves indicated that symptomatic RP could be predicted using PTV/Lung [area under curve (AUC): 0.88, confidence interval (CI: 0.78-0.95), cut-off value: 1.09, sensitivity: 90.0% and specificity: 72.4%]. PTV/Lung is a good predictor of symptomatic RP after SRT. Advances in knowledge: The cases with high PTV/Lung should be carefully monitored with caution for the occurrence of RP after SRT.

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

PubMed

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

2018-01-01

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

Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students.

PubMed

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; Sanders-Tordecilla, Alejandra; Ojeda-Pardo, Mónica Liliana; Cobo-Mejía, Elisa Andrea; Castellanos-Vega, Rocío Del Pilar; García-Hermoso, Antonio; González-Jiménez, Emilio; Schmidt-RioValle, Jacqueline; González-Ruíz, Katherine

2017-09-13

High body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components ( p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m² in men, and 38.95% and 11.86 kg/m² in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes' thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.

Cutoff values for bacteria and leukocytes for urine sediment analyzer FUS200 in culture-positive urinary-tract infections.

PubMed

Kocer, Derya; Sarıguzel, Fatma M; Karakukcu, Cıgdem

2014-08-01

The microscopic analysis of urine is essential for the diagnosis of patients with urinary tract infections. Quantitative urine culture is the 'gold standard' method for definitive diagnosis of urinary-tract infections, but it is labor-intensive, time consuming, and does not provide the same-day results. The aim of this study was to evaluate the analytical and diagnostic performance of the FUS200 (Changchun Dirui Industry, China), a new urine sedimentation analyzer in comparison to urine culture as the reference method. We evaluated 1000 urine samples, submitted for culture and urine analysis with a preliminary diagnosis of urinary-tract infection. Cut-off values for the FUS200 were determined by comparing the results with urine cultures. The cut-off values by the receiver operating characteristic (ROC) curve technique, sensitivity, and specificity were calculated for bacteria and white blood cells (WBCs). Among the 1000 urine specimens submitted for culture, 637 cultures (63.7%) were negative, and 363 were (36.3%) positive. The best cut-off values obtained from ROC analysis were 16/μL for bacteriuria (sensitivity: 82.3%, specificity: 58%), and 34/μL for WBCs (sensitivity: 72.3%, specificity: 65.2%). The area under the curve (AUC) for the bacteria and WBCs count were 0.71 (95% CI: 0.67-0.74) and, 0.72 (95% CI: 0.69-0.76) respectively. The most important requirement of a rapid diagnostic screening test is sensitivity, and, in this perspective, an unsatisfactory sensitivity by using bacteria recognition and quantification performed by the FUS200 analyzer has been observed. After further technical improvements in particle recognition and laboratory personnel training, the FUS200 might show better results.

Quantitative evaluation of diffusion-kurtosis imaging for grading endometrial carcinoma: a comparative study with diffusion-weighted imaging.

PubMed

Chen, T; Li, Y; Lu, S-S; Zhang, Y-D; Wang, X-N; Luo, C-Y; Shi, H-B

2017-11-01

To evaluate the diagnostic performance of histogram analysis of diffusion kurtosis magnetic resonance imaging (DKI) and standard diffusion-weighted imaging (DWI) in discriminating tumour grades of endometrial carcinoma (EC). Seventy-three patients with EC were included in this study. The apparent diffusion coefficient (ADC) value from standard DWI, apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ) from DKI were acquired using a 3 T magnetic resonance imaging (MRI) system. The measurement was based on an entire-tumour analysis. Histogram parameters (D app , K app , and ADC) were compared between high-grade (grade 3) and low-grade (grade 1 and 2) tumours. The diagnostic performance of imaging parameters for discriminating high- from low-grade tumours was analysed using a receiver operating characteristic curve (ROC). The area under the ROC curve (AUC) of the 10th percentile of D app , 90th percentile of K app and 10th percentile of ADC were higher than other parameters in distinguishing high-grade tumours from low-grade tumours (AUC=0.821, 0.891 and 0.801, respectively). The combination of 10th percentile of D app and 90th percentile of K app improved the AUC to 0.901, which was significantly higher than that of the 10th percentile of ADC (0.810, p=0.0314) in differentiating high- from low-grade EC. Entire-tumour volume histogram analysis of DKI and standard DWI were feasible for discriminating histological tumour grades of EC. DKI was relatively better than DWI in distinguishing high-grade from low-grade tumour in EC. Copyright © 2017. Published by Elsevier Ltd.

A new method using multiphoton imaging and morphometric analysis for differentiating chromophobe renal cell carcinoma and oncocytoma kidney tumors

NASA Astrophysics Data System (ADS)

Wu, Binlin; Mukherjee, Sushmita; Jain, Manu

2016-03-01

Distinguishing chromophobe renal cell carcinoma (chRCC) from oncocytoma on hematoxylin and eosin images may be difficult and require time-consuming ancillary procedures. Multiphoton microscopy (MPM), an optical imaging modality, was used to rapidly generate sub-cellular histological resolution images from formalin-fixed unstained tissue sections from chRCC and oncocytoma.Tissues were excited using 780nm wavelength and emission signals (including second harmonic generation and autofluorescence) were collected in different channels between 390 nm and 650 nm. Granular structure in the cell cytoplasm was observed in both chRCC and oncocytoma. Quantitative morphometric analysis was conducted to distinguish chRCC and oncocytoma. To perform the analysis, cytoplasm and granules in tumor cells were segmented from the images. Their area and fluorescence intensity were found in different channels. Multiple features were measured to quantify the morphological and fluorescence properties. Linear support vector machine (SVM) was used for classification. Re-substitution validation, cross validation and receiver operating characteristic (ROC) curve were implemented to evaluate the efficacy of the SVM classifier. A wrapper feature algorithm was used to select the optimal features which provided the best predictive performance in separating the two tissue types (classes). Statistical measures such as sensitivity, specificity, accuracy and area under curve (AUC) of ROC were calculated to evaluate the efficacy of the classification. Over 80% accuracy was achieved as the predictive performance. This method, if validated on a larger and more diverse sample set, may serve as an automated rapid diagnostic tool to differentiate between chRCC and oncocytoma. An advantage of such automated methods are that they are free from investigator bias and variability.

Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals.

PubMed

Er, Leay-Kiaw; Wu, Semon; Chou, Hsin-Hua; Hsu, Lung-An; Teng, Ming-Sheng; Sun, Yu-Chen; Ko, Yu-Lin

2016-01-01

Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters--such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios--was analyzed to identify IR. For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR.

Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals

PubMed Central

Er, Leay-Kiaw; Wu, Semon; Chou, Hsin-Hua; Hsu, Lung-An; Teng, Ming-Sheng; Sun, Yu-Chen; Ko, Yu-Lin

2016-01-01

Background Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. Methods We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters—such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios—was analyzed to identify IR. Results For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). Conclusion TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR. PMID:26930652

Serum galectin-9 as a noninvasive biomarker for the detection of endometriosis and pelvic pain or infertility-related gynecologic disorders.

PubMed

Brubel, Reka; Bokor, Attila; Pohl, Akos; Schilli, Gabriella Krisztina; Szereday, Laszlo; Bacher-Szamuel, Reka; Rigo, Janos; Polgar, Beata

2017-12-01

To investigate the usefulness of soluble galectin-9 (Gal-9) in the noninvasive laboratory diagnosis of endometriosis and various gynecologic disorders. Prospective case-control study. University medical centers. A total of 135 women of reproductive age were involved in the study, 77 endometriosis patients, 28 gynecologic controls, and 30 healthy women. Diagnostic laparoscopy and collection of tissue biopsies, peritoneal cells, and native peripheral blood from different case groups of gynecology patients and healthy women. The expression of mRNA and serum concentration of Gal-9. Semiquantitative reverse transcription-polymerase chain reaction analysis and serum soluble Gal-9 ELISA were performed on three different cohorts of patients: those with endometriosis, those with benign gynecologic disorders, and healthy controls. Differences in the Gal-9 concentrations between the investigated groups and the stability of Gal-9 in the serum and diagnostic characteristics of Gal-9 ELISA were determined by statistical evaluation and receiver operating characteristic (ROC) curve analysis. Significantly elevated Gal-9 levels were found in both minimal-mild (I-II) and moderate-severe (III-IV) stages of endometriosis in comparison with healthy controls. At a cutoff of 132 pg/mL, ROC analysis revealed an excellent diagnostic value of Gal-9 ELISA in endometriosis (area under the curve = 0.973) with a sensitivity of 94% and specificity of 93.75%, indicating better diagnostic potential than that of other endometriosis biomarkers. Furthermore, various pelvic pain or infertility-associated benign gynecologic conditions were also associated with increased serum Gal-9 levels. Our results suggest that Gal-9 could be a promising noninvasive biomarker of endometriosis and a predictor of various infertility or pelvic pain-related gynecologic disorders. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Gene expression profile of blood cells for the prediction of delayed cerebral ischemia after intracranial aneurysm rupture: a pilot study in humans.

PubMed

Baumann, Antoine; Devaux, Yvan; Audibert, Gérard; Zhang, Lu; Bracard, Serge; Colnat-Coulbois, Sophie; Klein, Olivier; Zannad, Faiez; Charpentier, Claire; Longrois, Dan; Mertes, Paul-Michel

2013-01-01

Delayed cerebral ischemia (DCI) is a potentially devastating complication after intracranial aneurysm rupture and its mechanisms remain poorly elucidated. Early identification of the patients prone to developing DCI after rupture may represent a major breakthrough in its prevention and treatment. The single gene approach of DCI has demonstrated interest in humans. We hypothesized that whole genome expression profile of blood cells may be useful for better comprehension and prediction of aneurysmal DCI. Over a 35-month period, 218 patients with aneurysm rupture were included in this study. DCI was defined as the occurrence of a new delayed neurological deficit occurring within 2 weeks after aneurysm rupture with evidence of ischemia either on perfusion-diffusion MRI, CT angiography or CT perfusion imaging, or with cerebral angiography. DCI patients were matched against controls based on 4 out of 5 criteria (age, sex, Fisher grade, aneurysm location and smoking status). Genome-wide expression analysis of blood cells obtained at admission was performed by microarrays. Transcriptomic analysis was performed using long oligonucleotide microarrays representing 25,000 genes. Quantitative PCR: 1 µg of total RNA extracted was reverse-transcribed, and the resulting cDNA was diluted 10-fold before performing quantitative PCR. Microarray data were first analyzed by 'Significance Analysis of Microarrays' software which includes the Benjamini correction for multiple testing. In a second step, microarray data fold change was compared using a two-tailed, paired t test. Analysis of receiver-operating characteristic (ROC) curves and the area under the ROC curves were used for prediction analysis. Logistic regression models were used to investigate the additive value of multiple biomarkers. A total of 16 patients demonstrated DCI. Significance Analysis of Microarrays software failed to retrieve significant genes, most probably because of the heterogeneity of the patients included in the microarray experiments and the small size of the DCI population sample. Standard two-tailed paired t test and C-statistic revealed significant associations between gene expression and the occurrence of DCI: in particular, the expression of neuroregulin 1 was 1.6-fold upregulated in patients with DCI (p = 0.01) and predicted DCI with an area under the ROC curve of 0.96. Logistic regression analyses revealed a significant association between neuroregulin 1 and DCI (odds ratio 1.46, 95% confidence interval 1.02-2.09, p = 0.02). This pilot study suggests that blood cells may be a reservoir of prognostic biomarkers of DCI in patients with intracranial aneurysm rupture. Despite an evident lack of power, this study elicited neuroregulin 1, a vasoreactivity-, inflammation- and angiogenesis-related gene, as a possible candidate predictor of DCI. Larger cohort studies are needed but genome-wide microarray-based studies are promising research tools for the understanding of DCI after intracranial aneurysm rupture. © 2013 S. Karger AG, Basel.

Compressive Sensing for Background Subtraction

DTIC Science & Technology

2009-12-20

i) reconstructing an image using only a single optical pho- todiode (infrared, hyperspectral, etc.) along with a digital micromirror device (DMD... curves , we use the full images, run the background subtraction algorithm proposed in [19], and obtain baseline background subtracted images. We then...the images to generate the ROC curve . 5.5 Silhouettes vs. Difference Images We have used a multi camera set up for a 3D voxel reconstruction using the

A mathematical model approach toward combining information from multiple image projections of the same patient

NASA Astrophysics Data System (ADS)

Chawla, Amarpreet S.; Samei, Ehsan; Abbey, Craig

2007-03-01

In this study, we used a mathematical observer model to combine information obtained from multiple angular projections of the same breast to determine the overall detection performance of a multi-projection breast imaging system in detectability of a simulated mass. 82 subjects participated in the study and 25 angular projections of each breast were acquired. Projections from a simulated 3 mm 3-D lesion were added to the projection images. The lesion was assumed to be embedded in the compressed breast at a distance of 3 cm from the detector. Hotelling observer with Laguerre-Gauss channels (LG CHO) was applied to each image. Detectability was analyzed in terms of ROC curves and the area under ROC curves (AUC). The critical question studied is how to best integrate the individual decision variables across multiple (correlated) views. Towards that end, three different methods were investigated. Specifically, 1) ROCs from different projections were simply averaged; 2) the test statistics from different projections were averaged; and 3) a Bayesian decision fusion rule was used. Finally, AUC of the combined ROC was used as a parameter to optimize the acquisition parameters to maximize the performance of the system. It was found that the Bayesian decision fusion technique performs better than the other two techniques and likely offers the best approximation of the diagnostic process. Furthermore, if the total dose level is held constant at 1/25th of dual-view mammographic screening dose, the highest detectability performance is observed when considering only two projections spread along an angular span of 11.4°.

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

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.

A simplified clinical risk score predicts the need for early endoscopy in non-variceal upper gastrointestinal bleeding.

PubMed

Tammaro, Leonardo; Buda, Andrea; Di Paolo, Maria Carla; Zullo, Angelo; Hassan, Cesare; Riccio, Elisabetta; Vassallo, Roberto; Caserta, Luigi; Anderloni, Andrea; Natali, Alessandro

2014-09-01

Pre-endoscopic triage of patients who require an early upper endoscopy can improve management of patients with non-variceal upper gastrointestinal bleeding. To validate a new simplified clinical score (T-score) to assess the need of an early upper endoscopy in non variceal bleeding patients. Secondary outcomes were re-bleeding rate, 30-day bleeding-related mortality. In this prospective, multicentre study patients with bleeding who underwent upper endoscopy were enrolled. The accuracy for high risk endoscopic stigmata of the T-score was compared with that of the Glasgow Blatchford risk score. Overall, 602 patients underwent early upper endoscopy, and 472 presented with non-variceal bleeding. High risk endoscopic stigmata were detected in 145 (30.7%) cases. T-score sensitivity and specificity for high risk endoscopic stigmata and bleeding-related mortality was 96% and 30%, and 80% and 71%, respectively. No statistically difference in predicting high risk endoscopic stigmata between T-score and Glasgow Blatchford risk score was observed (ROC curve: 0.72 vs. 0.69, p=0.11). The two scores were also similar in predicting re-bleeding (ROC curve: 0.64 vs. 0.63, p=0.4) and 30-day bleeding-related mortality (ROC curve: 0.78 vs. 0.76, p=0.3). The T-score appeared to predict high risk endoscopic stigmata, re-bleeding and mortality with similar accuracy to Glasgow Blatchford risk score. Such a score may be helpful for the prediction of high-risk patients who need a very early therapeutic endoscopy. Copyright © 2014 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

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.

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.

OP007. PLGF in combination with other commonly utilised tests and other biomarkers for predicting need for delivery for pre-eclampsia within 14days in women presenting prior to 35weeks' gestation.

PubMed

Lucy, Chappell; Suzy, Duckworth; Melanie, Griffin; Paul, Seed; Christopher, Redman; Andrew, Shennan

2013-04-01

Current means of assessing women presenting with suspected pre-eclampsia using BP and proteinuria are of limited use in predicting need for imminent delivery. We undertook a prospective multicentre study to determine diagnostic accuracy of PlGF <5th centile (Triage assay) and other candidate biomarkers in women presenting with suspected pre-eclampsia at 20-35weeks' gestation, in determining need for delivery for pre-eclampsia within 14days. We calculated ROC curves for predictive potential and undertook principal factor analysis to determine additional predictive ability for biomarker combinations. In 287 women enrolled prior to 35weeks, ROC area (0.88, SE 0.03) for PlGF <5th centile for pre-eclampsia requiring delivery within 14days was greater than all other commonly utilised tests (systolic and diastolic BP, urate, ALT), either singly (range 0.58-0.68), or in combination (0.69) (p<0.001 for all comparisons), and was greater than that of all other biomarkers; addition of 2 other biomarker panels (either procalcitonin, nephrin and BNP; or cystatin and PAPP-A) increased ROC area to 0.90 but these biomarkers had limited predictive ability on their own. In women presenting prior to 35weeks' gestation with suspected pre-eclampsia, low PlGF has a greater ROC area than other commonly utilised tests. Additional biomarkers add only a small increment to the predictive value of a single PlGF measurement. Copyright © 2013. Published by Elsevier B.V.

Enhanced Analysis Techniques for an Imaging Neutron and Gamma Ray Spectrometer

NASA Astrophysics Data System (ADS)

Madden, Amanda C.

The presence of gamma rays and neutrons is a strong indicator of the presence of Special Nuclear Material (SNM). The imaging Neutron and gamma ray SPECTrometer (NSPECT) developed by the University of New Hampshire and Michigan Aerospace corporation detects the fast neutrons and prompt gamma rays from fissile material, and the gamma rays from radioactive material. The instrument operates as a double scatter device, requiring a neutron or a gamma ray to interact twice in the instrument. While this detection requirement decreases the efficiency of the instrument, it offers superior background rejection and the ability to measure the energy and momentum of the incident particle. These measurements create energy spectra and images of the emitting source for source identification and localization. The dual species instrument provides superior detection than a single species alone. In realistic detection scenarios, few particles are detected from a potential threat due to source shielding, detection at a distance, high background, and weak sources. This contributes to a small signal to noise ratio, and threat detection becomes difficult. To address these difficulties, several enhanced data analysis tools were developed. A Receiver Operating Characteristic Curve (ROC) helps set instrumental alarm thresholds as well as to identify the presence of a source. Analysis of a dual-species ROC curve provides superior detection capabilities. Bayesian analysis helps to detect and identify the presence of a source through model comparisons, and helps create a background corrected count spectra for enhanced spectroscopy. Development of an instrument response using simulations and numerical analyses will help perform spectra and image deconvolution. This thesis will outline the principles of operation of the NSPECT instrument using the double scatter technology, traditional analysis techniques, and enhanced analysis techniques as applied to data from the NSPECT instrument, and an outline of how these techniques can be used to superior detection of radioactive and fissile materials.

Comparison of gadolinium-EOB-DTPA-enhanced and diffusion-weighted liver MRI for detection of small hepatic metastases.

PubMed

Shimada, Kotaro; Isoda, Hiroyoshi; Hirokawa, Yuusuke; Arizono, Shigeki; Shibata, Toshiya; Togashi, Kaori

2010-11-01

To compare the accuracy of gadolinium ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI with that of diffusion-weighted MRI (DWI) in the detection of small hepatic metastases (2 cm or smaller). Forty-five patients underwent abdominal MRI at 3 T, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), heavily T2WI (HASTE), DWI with a b-value of 500 s/mm(2) and contrast-enhanced MRI with Gd-EOB-DTPA. Two groups were assigned and compared: group A (T1WI, T2WI, HASTE and contrast-enhanced study with Gd-EOB-DTPA), and group B (T1WI, T2WI, HASTE and DWI). Two observers independently interpreted the images obtained in a random order. For all hepatic metastases, the diagnostic performance using each imaging set was evaluated by receiver-operating characteristic (ROC) curve analysis. A total of 51 hepatic metastases were confirmed. The area under the ROC curve (Az) of group A was larger than that of group B, and the difference in the mean Az values between the two image sets was statistically significant, whereas, there were three metastases that lay near thin vessels or among multiple cysts and were better visualised in group B than in group A. Gd-EOB-DTPA-enhanced MRI showed higher accuracy in the detection of small metastases than DWI.

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.

Tower of London test: a comparison between conventional statistic approach and modelling based on artificial neural network in differentiating fronto-temporal dementia from Alzheimer's disease.

PubMed

Franceschi, Massimo; Caffarra, Paolo; Savarè, Rita; Cerutti, Renata; Grossi, Enzo

2011-01-01

The early differentiation of Alzheimer's disease (AD) from frontotemporal dementia (FTD) may be difficult. The Tower of London (ToL), thought to assess executive functions such as planning and visuo-spatial working memory, could help in this purpose. Twentytwo Dementia Centers consecutively recruited patients with early FTD or AD. ToL performances of these groups were analyzed using both the conventional statistical approaches and the Artificial Neural Networks (ANNs) modelling. Ninety-four non aphasic FTD and 160 AD patients were recruited. ToL Accuracy Score (AS) significantly (p < 0.05) differentiated FTD from AD patients. However, the discriminant validity of AS checked by ROC curve analysis, yielded no significant results in terms of sensitivity and specificity (AUC 0.63). The performances of the 12 Success Subscores (SS) together with age, gender and schooling years were entered into advanced ANNs developed by Semeion Institute. The best ANNs were selected and submitted to ROC curves. The non-linear model was able to discriminate FTD from AD with an average AUC for 7 independent trials of 0.82. The use of hidden information contained in the different items of ToL and the non linear processing of the data through ANNs allows a high discrimination between FTD and AD in individual patients.

[Development of competency to stand trial rating scale in offenders with mental disorders].

PubMed

Chen, Xiao-Bing; Cai, Wei-Xiong

2013-04-01

According with Chinese legal system, to develop a competency to stand trial rating scale in offenders with mental disorders. Proceeding from the juristical elements, 15 items were extracted and formulated a preliminary instrument named the competency to stand trial rating scale in offenders with mental disorders. The item analysis included six aspects, which were critical ratio, item-total correlation, corrected item-total correlation, alpha value if item deleted, communalities of items, and factor loading. The Logistic regression equation and cut-off score of ROC curve were used to explore the diagnostic efficiency. The data of critical ratio of extreme group were 18.390-46.763; item-total correlation, 0.639-0.952; corrected item-total correlation, 0.582-0.944; communalities of items, 0.377-0.916; and factor loadings, 0.614-0.957. Seven items were included in the regression equation and the accuracy of back substitution test was 96.0%. The score of 33 was ascertained as the cut-off score by ROC fitting curve, the overlapping ratio compared with the expertise was 95.8%. The sensibility and the specificity were 0.938 and 0.966, respectively, while the positive and negative likelihood ratios were 27.67 and 0.06, respectively. With all items satisfied the requirement of homogeneity test, the rating scale has a reasonable construct and excellent diagnostic efficiency.

'Critical view of safety' as an alternative to routine intraoperative cholangiography during laparoscopic cholecystectomy for acute biliary pathology.

PubMed

Sanjay, Pandanaboyana; Fulke, Jennifer L; Exon, David J

2010-08-01

The study aims to evaluate the use of "critical view of safety" (CVS) for the prevention of bile duct injuries during laparoscopic cholecystectomy for acute biliary pathology as an alternative to routine intraoperative cholangiography (IOC). A policy of routine CVS to identify biliary anatomy and selective IOC for patients suspected to have common bile duct (CBD) stone was adopted. Receiver operator curves (ROCs) were used to identify cutoff values predicting CBD stones. Four hundred forty-seven consecutive, same admission laparoscopic cholecystectomies performed between August 2004 and July 2007 were reviewed. CVS was achieved in 388 (87%) patients. Where CVS was not possible, the operation was completed open. CBD stones were identified in 22/57 patients who underwent selective IOC. Preoperative liver function and CBD diameter were significantly higher in those with CBD stones (P < .001). ROC curve analysis identified preoperative cutoff values of bilirubin (35 mumol/L), alkaline phosphatase (250 IU/L), alanine aminotransferase (240 IU/L), and a CBD diameter of 10 mm, as predictive of CBD stones. No bile duct injuries occurred in this series. In acute biliary pathology, the use of CVS helps clarify the anatomy of Calot's triangle and is a suitable alternative to routine IOC. Selective cholangiography should be employed when preoperative liver function and CBD diameter are above defined thresholds.

Using Changes in Binding Globulins to Assess Oral Contraceptive Compliance

PubMed Central

Westhoff, Carolyn; Petrie, K.A.; Cremers, S.

2012-01-01

Background Validity of oral contraceptive pill (OCP) clinical trial results depends on participant compliance. Ethinyl estradiol (EE2) induces increases in hepatic binding globulin (BG) levels. Measuring these BG increases may provide an effective and convenient approach to distinguishing non-compliant from compliant OCP users in research settings. This analysis evaluated the usefulness of measuring increases in corticosteroid, sex hormone and thyroxine binding globulins (CBG, SHBG, TBG) as measures of OCP compliance. Methods We used frozen serum from a trial that compared ovarian suppression between normal weight and obese women randomized to one of two OCPs containing EE2 and levonorgestrel (LNG). Based on serial LNG measurements during the trial, 17% of participants were non-compliant. We matched non-compliant participants with compliant participants by age, BMI, ethnicity and OCP formulation. We measured CBG, SHBG and TBG levels, and compared change from baseline to 3-month follow-up between the non-compliant and compliant participants. Construction of receiver operator characteristic (ROC) curves allowed comparison of various BG measures. Results Changes in CBG and TBG distinguished OCP non-compliant users from compliant users (area under the ROC curve (AUROC), 0.86 and 0.89, p < 0.01). Changes in SHBG were less discriminating (AUROC 0.69) Conclusions EE2 induced increases in CBG and TBG provide a sensitive integrated marker of compliance with an LNG-containing OCP. PMID:22795088

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

First trimester PAPP-A in the detection of non-Down syndrome aneuploidy.

PubMed

Ochshorn, Y; Kupferminc, M J; Wolman, I; Orr-Urtreger, A; Jaffa, A J; Yaron, Y

2001-07-01

Combined first trimester screening using pregnancy associated plasma protein-A (PAPP-A), free beta-human chorionic gonadotrophin, and nuchal translucency (NT), is currently accepted as probably the best combination for the detection of Down syndrome (DS). Current first trimester algorithms provide computed risks only for DS. However, low PAPP-A is also associated with other chromosome anomalies such as trisomy 13, 18, and sex chromosome aneuploidy. Thus, using currently available algorithms, some chromosome anomalies may not be detected. The purpose of the present study was to establish a low-end cut-off value for PAPP-A that would increase the detection rates for non-DS chromosome anomalies. The study included 1408 patients who underwent combined first trimester screening. To determine a low-end cut-off value for PAPP-A, a Receiver-Operator Characteristic (ROC) curve analysis was performed. In the entire study group there were 18 cases of chromosome anomalies (trisomy 21, 13, 18, sex chromosome anomalies), 14 of which were among screen-positive patients, a detection rate of 77.7% for all chromosome anomalies (95% CI: 55.7-99.7%). ROC curve analysis detected a statistically significant cut-off for PAPP-A at 0.25 MoM. If the definition of screen-positive were to also include patients with PAPP-A<0.25 MoM, the detection rate would increase to 88.8% for all chromosome anomalies (95% CI: 71.6-106%). This low cut-off value may be used until specific algorithms are implemented for non-Down syndrome aneuploidy. Copyright 2001 John Wiley & Sons, Ltd.

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

PubMed

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

2016-04-30

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

Alzheimer's disease detection using 11C-PiB with improved partial volume effect correction

NASA Astrophysics Data System (ADS)

Raniga, Parnesh; Bourgeat, Pierrick; Fripp, Jurgen; Acosta, Oscar; Ourselin, Sebastien; Rowe, Christopher; Villemagne, Victor L.; Salvado, Olivier

2009-02-01

Despite the increasing use of 11C-PiB in research into Alzheimer's disease (AD), there are few standardized analysis procedures that have been reported or published. This is especially true with regards to partial volume effects (PVE) and partial volume correction. Due to the nature of PET physics and acquisition, PET images exhibit relatively low spatial resolution compared to other modalities, resulting in bias of quantitative results. Although previous studies have applied PVE correction techniques on 11C-PiB data, the results have not been quantitatively evaluated and compared against uncorrected data. The aim of this study is threefold. Firstly, a realistic synthetic phantom was created to quantify PVE. Secondly, MRI partial volume estimate segmentations were used to improve voxel-based PVE correction instead of using hard segmentations. Thirdly, quantification of PVE correction was evaluated on 34 subjects (AD=10, Normal Controls (NC)=24), including 12 PiB positive NC. Regional analysis was performed using the Anatomical Automatic Labeling (AAL) template, which was registered to each patient. Regions of interest were restricted to the gray matter (GM) defined by the MR segmentation. Average normalized intensity of the neocortex and selected regions were used to evaluate the discrimination power between AD and NC both with and without PVE correction. Receiver Operating Characteristic (ROC) curves were computed for the binary discrimination task. The phantom study revealed signal losses due to PVE between 10 to 40 % which were mostly recovered to within 5% after correction. Better classification was achieved after PVE correction, resulting in higher areas under ROC curves.

Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively.

PubMed

Lahner, D; Kabon, B; Marschalek, C; Chiari, A; Pestel, G; Kaider, A; Fleischmann, E; Hetz, H

2009-09-01

Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac/Vigileo system, to predict fluid responsiveness as measured by the oesophageal Doppler. Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to <350 ms. Patients were connected to a monitoring device, obtaining SVV by APCO. Haemodynamic variables were recorded before and after fluid bolus application. Fluid responsiveness was defined as an increase in stroke volume index >10%. The ability of SVV to predict fluid responsiveness was assessed by calculation of the area under the receiver operating characteristic (ROC) curve. Twenty patients received 67 fluid boluses. Fifty-two of the 67 fluid boluses administered resulted in fluid responsiveness. SVV achieved an area under the ROC curve of 0.512 [confidence interval (CI) 0.32-0.70]. A cut-off point for fluid responsiveness was found for SVV > or =8.5% (sensitivity: 77%; specificity: 43%; positive predictive value: 84%; and negative predictive value: 33%). This prospective, interventional observer-blinded study demonstrates that SVV obtained by APCO, using the FloTrac/Vigileo system, is not a reliable predictor of fluid responsiveness in the setting of major abdominal surgery.

Ultrasonographic Evaluation of Cervical Lymph Nodes in Thyroid Cancer.

PubMed

Machado, Maria Regina Marrocos; Tavares, Marcos Roberto; Buchpiguel, Carlos Alberto; Chammas, Maria Cristina

2017-02-01

Objective To determine what ultrasonographic features can identify metastatic cervical lymph nodes, both preoperatively and in recurrences after complete thyroidectomy. Study Design Prospective. Setting Outpatient clinic, Department of Head and Neck Surgery, School of Medicine, University of São Paulo, Brazil. Subjects and Methods A total of 1976 lymph nodes were evaluated in 118 patients submitted to total thyroidectomy with or without cervical lymph node dissection. All the patients were examined by cervical ultrasonography, preoperatively and/or postoperatively. The following factors were assessed: number, size, shape, margins, presence of fatty hilum, cortex, echotexture, echogenicity, presence of microcalcification, presence of necrosis, and type of vascularity. The specificity, sensitivity, positive predictive value, and negative predictive value of each variable were calculated. Univariate and multivariate logistic regression analyses were conducted. A receiver operator characteristic (ROC) curve was plotted to determine the best cutoff value for the number of variables to discriminate malignant lymph nodes. Results Significant differences were found between metastatic and benign lymph nodes with regard to all of the variables evaluated ( P < .05). Logistic regression analysis revealed that size and echogenicity were the best combination of altered variables (odds ratio, 40.080 and 7.288, respectively) in discriminating malignancy. The ROC curve analysis showed that 4 was the best cutoff value for the number of altered variables to discriminate malignant lymph nodes, with a combined specificity of 85.7%, sensitivity of 96.4%, and efficiency of 91.0%. Conclusion Greater diagnostic accuracy was achieved by associating the ultrasonographic variables assessed rather than by considering them individually.

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

NASA Astrophysics Data System (ADS)

Naghibi, Seyed Amir; Moradi Dashtpagerdi, Mostafa

2017-01-01

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.

Evaluation of suspension array analysis for detection of egg yolk antibodies against Salmonella Enteritidis.

PubMed

Thomas, M E; Klinkenberg, D; Bergwerff, A A; van Eerden, E; Stegeman, J A; Bouma, A

2010-06-01

Salmonella enterica serovar Enteritidis (SE) is an important source of food-related diarrhoea in humans, and table eggs are considered the primordial source of contamination of the human food chain. Using eggs collected at egg-packing stations as samples could be a convenient strategy to detect colonization of layer flocks. The aim of this study was to evaluate egg yolk anti-Salmonella antibody detection using suspension array analysis. An egg yolk panel from contact-infected and non-colonized laying hens was used for the evaluation. Receiver Operating Characteristic (ROC) curves were generated to define a cut-off value and to assess the overall accuracy of the assay. The diagnostic sensitivity and specificity were estimated by maximum likelihood. Sensitivity was quantified on hen level and on sample level, and also quantified as a function of time since colonization. The area under the ROC curve was estimated at 0.984 (se 0.006, P<0.001). Of all colonized contact-infected hens, 67.6% [95% CI: 46.8, 100] developed an antibody response, which was detectable 17.4 days [14.3, 26.9] after colonization. In total, 98% [95.4, 99.4] of the 'immunopositive' hens had test positive eggs. The overall sensitivity of the immunological test was 66.7% [45.9, 98.7] and the specificity was 98.5% [97.8, 99.1]. This study provided essential parameters for optimizing surveillance programs based on detection of antibodies, and indicates that immunology based on examination of egg yolk gives important information about the Salmonella status of the flock. (c) 2010 Elsevier B.V. All rights reserved.

Large meniscus extrusion ratio is a poor prognostic factor of conservative treatment for medial meniscus posterior root tear.

PubMed

Kwak, Yoon-Ho; Lee, Sahnghoon; Lee, Myung Chul; Han, Hyuk-Soo

2018-03-01

The purpose of this study was to find a prognostic factor of medial meniscus posterior root tear (MMPRT) for surgical decision making. Eighty-eight patients who were diagnosed as acute or subacute MMPRT without severe degeneration of the meniscus were treated conservatively for 3 months. Fifty-seven patients with MMPRT showed good response to conservative treatment (group 1), while the remaining 31 patients who failed to conservative treatment (group 2) received arthroscopic meniscus repair. Their demographic characteristics and radiographic features including hip-knee-ankle angle, joint line convergence angle, Kellgren-Lawrence grade in plain radiographs, meniscus extrusion (ME) ratio (ME-medial femoral condyle ratio, ME-medial tibial plateau ratio, ME-meniscus width ratio), the location of bony edema, and cartilage lesions in MRI were compared. Receiver operating characteristic (ROC) curve analysis was also performed to determine the cut-off values of risk factors. The degree of ME-medial femoral condyle and medial tibia plateau ratio of group 2 was significantly higher than group 1 (0.08 and 0.07 vs. 0.1 and 0.09, respectively, both p < 0.001). No significant (n.s.) difference in other variables was found between the two groups. On ROC curve analysis, ME-medial femoral condyle ratio was confirmed as the most reliable prognostic factor of conservative treatment for MMPRT (area under ROC = 0.8). The large meniscus extrusion ratio was the most reliable poor prognostic factor of conservative treatment for MMPRT. Therefore, for MMPRT patients with large meniscus extrusion, early surgical repair could be considered as the primary treatment option. III.

The predictive value of C-reactive protein (CRP) in acute pancreatitis - is interval change in CRP an additional indicator of severity?

PubMed

Stirling, Aaron D; Moran, Neil R; Kelly, Michael E; Ridgway, Paul F; Conlon, Kevin C

2017-10-01

Using revised Atlanta classification defined outcomes, we compare absolute values in C-reactive protein (CRP), with interval changes in CRP, for severity stratification in acute pancreatitis (AP). A retrospective study of all first incidence AP was conducted over a 5-year period. Interval change in CRP values from admission to day 1, 2 and 3 was compared against the absolute values. Receiver-operator characteristic (ROC) curve and likelihood ratios (LRs) were used to compare ability to predict severe and mild disease. 337 cases of first incidence AP were included in our analysis. ROC curve analysis demonstrated the second day as the most useful time for repeat CRP measurement. A CRP interval change >90 mg/dL at 48 h (+LR 2.15, -LR 0.26) was equivalent to an absolute value of >150 mg/dL within 48 h (+LR 2.32, -LR 0.25). The optimal cut-off for absolute CRP based on new, more stringent definition of severity was >190 mg/dL (+LR 2.72, -LR 0.24). Interval change in CRP is a comparable measure to absolute CRP in the prognostication of AP severity. This study suggests a rise of >90 mg/dL from admission or an absolute value of >190 mg/dL at 48 h predicts severe disease with the greatest accuracy. Copyright © 2017 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

Evaluation of the predictive capacity of vertical segmental tetrapolar bioimpedance for excess weight detection in adolescents.

PubMed

Neves, Felipe Silva; Leandro, Danielle Aparecida Barbosa; Silva, Fabiana Almeida da; Netto, Michele Pereira; Oliveira, Renata Maria Souza; Cândido, Ana Paula Carlos

2015-01-01

To analyze the predictive capacity of the vertical segmental tetrapolar bioimpedance apparatus in the detection of excess weight in adolescents, using tetrapolar bioelectrical impedance as a reference. This was a cross-sectional study conducted with 411 students aged between 10 and 14 years, of both genders, enrolled in public and private schools, selected by a simple and stratified random sampling process according to the gender, age, and proportion in each institution. The sample was evaluated by the anthropometric method and underwent a body composition analysis using vertical bipolar, horizontal tetrapolar, and vertical segmental tetrapolar assessment. The ROC curve was constructed based on calculations of sensitivity and specificity for each point of the different possible measurements of body fat. The statistical analysis used Student's t-test, Pearson's correlation coefficient, and McNemar's chi-squared test. Subsequently, the variables were interpreted using SPSS software, version 17.0. Of the total sample, 53.7% were girls and 46.3%, boys. Of the total, 20% and 12.5% had overweight and obesity, respectively. The body segment measurement charts showed high values of sensitivity and specificity and high areas under the ROC curve, ranging from 0.83 to 0.95 for girls and 0.92 to 0.98 for boys, suggesting a slightly higher performance for the male gender. Body fat percentage was the most efficient criterion to detect overweight, while the trunk segmental fat was the least accurate indicator. The apparatus demonstrated good performance to predict excess weight. Copyright © 2015 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Resonance Raman Spectroscopy of human brain metastasis of lung cancer analyzed by blind source separation

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-Hui; Pu, Yang; Cheng, Gangge; Yu, Xinguang; Zhou, Lixin; Lin, Dongmei; Zhu, Ke; Alfano, Robert R.

2017-02-01

Resonance Raman (RR) spectroscopy offers a novel Optical Biopsy method in cancer discrimination by a means of enhancement in Raman scattering. It is widely acknowledged that the RR spectrum of tissue is a superposition of spectra of various key building block molecules. In this study, the Resonance Raman (RR) spectra of human metastasis of lung cancerous and normal brain tissues excited by a visible selected wavelength at 532 nm are used to explore spectral changes caused by the tumor evolution. The potential application of RR spectra human brain metastasis of lung cancer was investigated by Blind Source Separation such as Principal Component Analysis (PCA). PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components (PCs). The results show significant RR spectra difference between human metastasis of lung cancerous and normal brain tissues analyzed by PCA. To evaluate the efficacy of for cancer detection, a linear discriminant analysis (LDA) classifier is utilized to calculate the sensitivity, and specificity and the receiver operating characteristic (ROC) curves are used to evaluate the performance of this criterion. Excellent sensitivity of 0.97, specificity (close to 1.00) and the Area Under ROC Curve (AUC) of 0.99 values are achieved under best optimal circumstance. This research demonstrates that RR spectroscopy is effective for detecting changes of tissues due to the development of brain metastasis of lung cancer. RR spectroscopy analyzed by blind source separation may have potential to be a new armamentarium.

HOMA-IR and QUICKI: decide on a general standard instead of making further comparisons.

PubMed

Rössner, Sophia M; Neovius, Martin; Mattsson, Anna; Marcus, Claude; Norgren, Svante

2010-11-01

To limit further comparisons between the two fasting indices Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and Quantitative Insulin Sensitivity Check Index (QUICKI), and to examine their robustness in assessing insulin sensitivity. A total of 191 obese children and adolescents (age 13.9 ± 2.9 years, BMI SDS 6.1 ± 1.6), who had undergone a Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT), were included. Receiver operating characteristic curve (ROC) analysis was used to compare indices in detecting insulin resistance and Bland-Altman plots to investigate agreement between three consecutive fasting samples when compared to using single samples. ROC analysis showed that the diagnostic accuracy was identical for QUICKI and HOMA-IR [area under the curve (AUC) boys 0.80, 95%CI 0.70-0.89; girls 0.80, 0.71-0.88], while insulin had a nonsignificantly lower AUC (boys 0.76, 0.66-0.87; girls 0.75, 0.66-0.84). Glucose did not perform better than chance as a diagnostic test (boys 0.47, 0.34-0.60; girls 0.57, 0.46-0.68). Indices varied with consecutive sampling, mainly attributable to fasting insulin variations (mean maximum difference in HOMA-IR -0.8; -0.9 to -0.7). Using both HOMA-IR and QUICKI in further studies is superfluous as these indices function equally well as predictors of the FSIVGTT sensitivity index. Focus should be on establishing a general standard for research and clinical purposes. © 2010 The Author(s)/Journal Compilation © 2010 Foundation Acta Paediatrica.

Hemodynamic correlates of nutritional indexes in heart failure.

PubMed

Horiuchi, Yu; Tanimoto, Shuzou; Okuno, Taishi; Aoki, Jiro; Yahagi, Kazuyuki; Sato, Yu; Tanaka, Tetsu; Koseki, Keita; Komiyama, Kota; Nakajima, Hiroyoshi; Hara, Kazuhiro; Tanabe, Kengo

2018-06-01

Malnutrition in heart failure (HF) is related to altered intestinal function, which could be due to hemodynamic changes. We investigated the usefulness of novel nutritional indexes in relation to hemodynamic parameters. We retrospectively analyzed 139 HF patients with reduced ejection fraction who underwent right heart catheterization. We investigated correlations between right side pressures and nutritional indexes, which include controlling nutritional (CONUT) score and geriatric nutritional risk index (GNRI). Receiver operating characteristic (ROC) curves were generated to investigate the prognostic accuracy of CONUT score and GNRI for a composite of death or HF hospitalization in 12 months. Logistic regression analysis was performed to investigate whether hemodynamic correlates were associated with malnutrition, which was defined based on CONUT sore or GNRI. Higher right side pressures were positively correlated with worse nutritional status according to CONUT score, but were negatively correlated with worse nutritional status according to GNRI. Area under ROC curve for the composite endpoint was 0.746 in CONUT score and 0.576 in GNRI. The composite endpoint occurred in 40% of CONUT score≥3 and in 11% of CONUT score<3 (p<0.001). These relationships were also investigated with GNRI (40% of GNRI<95 vs. 17% of GNRI≥95, p=0.002). In multivariate analysis, higher right atrial pressure was significantly associated with higher CONUT score, while no hemodynamic parameter was related to GNRI. CONUT score was associated with right side congestion, while no association between GNRI and right side congestion was noted. CONUT score had better predictive value than GNRI. Copyright © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Analysis of deep inferior epigastric perforator (DIEP) arteries by using MDCTA: Comparison between 2 post-processing techniques.

PubMed

Saba, Luca; Atzeni, Matteo; Ribuffo, Diego; Mallarini, Giorgio; Suri, Jasjit S

2012-08-01

Our purpose was to compare two post-processing techniques, Maximum-Intensity-Projection (MIP) and Volume Rendering (VR) for the study of perforator arteries. Thirty patients who underwent Multi-Detector-Row CT Angiography (MDCTA) between February 2010 and May 2010 were retrospectively analyzed. For each patient and for each reconstruction method, the image quality was evaluated and the inter- and intra-observer agreement was calculated according to the Cohen statistics. The Hounsfield Unit (HU) value in the common femoral artery was quantified and the correlation (Pearson Statistic) between image quality and HU value was explored. The Pearson r between the right and left common femoral artery was excellent (r=0.955). The highest image quality score was obtained using MIP for both observers (total value 75, with a mean value 2.67 for observer 1 and total value of 79 and a mean value of 2.82 for observer 2). The highest agreement between the two observers was detected using the MIP protocol with a Cohen kappa value of 0.856. The ROC area under the curve (Az) for the VR is 0.786 (0.086 SD; p value=0.0009) whereas the ROC area under the curve (Az) for the MIP is 0.0928 (0.051 SD; p value=0.0001). MIP showed the optimal inter- and intra-observer agreement and the highest quality scores and therefore should be used as post-processing techniques in the analysis of perforating arteries. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Assessment of tenascin-C levels in ventricular noncompaction/hypertrabeculation patients: a cross-sectional study.

PubMed

Erer, Hatice Betul; Guvenc, Tolga Sinan; Kemik, Ahu Sarbay; Yilmaz, Hale; Kul, Seref; Altay, Servet; Oz, Dilaver; Zeren, Gonul; Ekmekci, Ahmet; Zencirci, Aycan Esen; Sayar, Nurten; Eren, Mehmet

2014-02-01

Ventricular noncompaction/hypertrabeculation (NC/HT) is a rare form of congenital cardiomyopathy. We aimed to investigate the presence of serum tenascin-C (TN-C) in adult patients with NC/HT and evaluate its value. Serum TN-C levels were measured by ELISA in 50 NC/HT patients both with/without systolic dysfunction and in 23 normal controls. Systolic dysfunction was defined as ejection fraction (EF) ≤ 40. Mann-Whitney U-test and ROC curve analysis were done. Of 49 NC/HT patients, 24 (49%) patients had systolic dysfunction (mean age 36 ± 15) and 25 patients (51%) had normal systolic function (mean age 36 ± 17). The ages between groups were not different. The mean levels of serum TN-C in patients with or without systolic dysfunction were 26 ± 10 ng/mL and 26 ± 8 ng/mL respectively, compared to normal controls, 7 ± 2 ng/mL (P < 0.001). No significance was observed between 2 groups of NC/HT patients regarding TN-C levels (P = 0.8). The ROC curve analysis revealed that a TN-C value of 11.7 ng/mL identified patients with NC/HT with 100% sensitivity and specifity. High serum TN-C levels are present in adult NC/HT cardiomyopathy even when left ventricular systolic function remains normal. Also, serum TN-C levels could be regarded as a candidate biomarker in the diagnosis of NC/HT which needs to be tested in larger prospective studies. © 2013, Wiley Periodicals, Inc.