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.

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.

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

ERIC Educational Resources Information Center

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

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower…

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

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

ERIC Educational Resources Information Center

Eckes, Thomas

2017-01-01

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

The 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

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.

"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.

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

PubMed

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

2017-02-01

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Berbaum, Kevin S.; Dorfman, Donald D.

2001-06-01

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

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.

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.

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.

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.

Drain the lysosome: Development of the novel orally available autophagy inhibitor ROC-325.

PubMed

Carew, Jennifer S; Nawrocki, Steffan T

2017-04-03

Although macroautophagy/autophagy is a key contributor to malignant pathogenesis and therapeutic resistance, there are few FDA-approved agents that significantly affect this pathway. We used medicinal chemistry strategies to develop ROC-325, an orally available novel inhibitor of lysosomal-mediated autophagy. Detailed in vitro and in vivo studies in preclinical models of renal cell carcinoma demonstrated that ROC-325 triggered the hallmark features of lysosomal autophagy inhibition, was very well tolerated, and exhibited significant superiority with respect to autophagy inhibition and anticancer activity over hydroxychloroquine. Our findings support the clinical investigation of the safety and preliminary efficacy of ROC-325 in patients with autophagy-dependent malignancies and other disorders where aberrant autophagy contributes to disease pathogenesis.

Neuronal Effects of Sugammadex in combination with Rocuronium or Vecuronium

PubMed Central

Aldasoro, Martin; Jorda, Adrian; Aldasoro, Constanza; Marchio, Patricia; Guerra-Ojeda, Sol; Gimeno-Raga, Marc; Mauricio, Mª Dolores; Iradi, Antonio; Obrador, Elena; Vila, Jose Mª; Valles, Soraya L.

2017-01-01

Rocuronium (ROC) and Vecuronium (VEC) are the most currently used steroidal non-depolarizing neuromuscular blocking (MNB) agents. Sugammadex (SUG) rapidly reverses steroidal NMB agents after anaesthesia. The present study was conducted in order to evaluate neuronal effects of SUG alone and in combination with both ROC and VEC. Using MTT, CASP-3 activity and Western-blot we determined the toxicity of SUG, ROC or VEC in neurons in primary culture. SUG induces apoptosis/necrosis in neurons in primary culture and increases cytochrome C (CytC), apoptosis-inducing factor (AIF), Smac/Diablo and Caspase 3 (CASP-3) protein expression. Our results also demonstrated that both ROC and VEC prevent these SUG effects. The protective role of both ROC and VEC could be explained by the fact that SUG encapsulates NMB drugs. In BBB impaired conditions it would be desirable to control SUG doses to prevent the excess of free SUG in plasma that may induce neuronal damage. A balance between SUG, ROC or VEC would be necessary to prevent the risk of cell damage. PMID:28367082

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.

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

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.

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

PubMed

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

2015-08-01

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

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

PubMed

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

2017-07-26

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

ROC curves in clinical chemistry: uses, misuses, and possible solutions.

PubMed

Obuchowski, Nancy A; Lieber, Michael L; Wians, Frank H

2004-07-01

ROC curves have become the standard for describing and comparing the accuracy of diagnostic tests. Not surprisingly, ROC curves are used often by clinical chemists. Our aims were to observe how the accuracy of clinical laboratory diagnostic tests is assessed, compared, and reported in the literature; to identify common problems with the use of ROC curves; and to offer some possible solutions. We reviewed every original work using ROC curves and published in Clinical Chemistry in 2001 or 2002. For each article we recorded phase of the research, prospective or retrospective design, sample size, presence/absence of confidence intervals (CIs), nature of the statistical analysis, and major analysis problems. Of 58 articles, 31% were phase I (exploratory), 50% were phase II (challenge), and 19% were phase III (advanced) studies. The studies increased in sample size from phase I to III and showed a progression in the use of prospective designs. Most phase I studies were powered to assess diagnostic tests with ROC areas >/=0.70. Thirty-eight percent of studies failed to include CIs for diagnostic test accuracy or the CIs were constructed inappropriately. Thirty-three percent of studies provided insufficient analysis for comparing diagnostic tests. Other problems included dichotomization of the gold standard scale and inappropriate analysis of the equivalence of two diagnostic tests. We identify available software and make some suggestions for sample size determination, testing for equivalence in diagnostic accuracy, and alternatives to a dichotomous classification of a continuous-scale gold standard. More methodologic research is needed in areas specific to clinical chemistry.

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.

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.

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.

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

Reach Out Central: a serious game designed to engage young men to improve mental health and wellbeing.

PubMed

Burns, Jane M; Webb, Marianne; Durkin, Lauren A; Hickie, Ian B

2010-06-07

Reach Out Central (ROC) is a serious game drawing on the principles of cognitive behaviour theory that has been designed to improve the mental health and wellbeing of young people, particularly men. ROC was developed over a 3-year period from 2003 to 2006, in consultation with young people aged 16-25 years who use the Reach Out mental health website http://www.reachout.com). ROC was launched online in September 2007. A traditional and viral awareness campaign was designed to engage young men, particularly "gamers". In the first month after launch, ROC had 76 045 unique website visits, with 10 542 new members (52% male) joining Reach Out. An independent online evaluation involving 266 young people aged 18-25 years was conducted between August 2007 and February 2008 to examine psychological wellbeing, stigma and help seeking in ROC players. Overall results indicated that ROC was successful in attracting, engaging and educating young people. Young women reported reduced psychological distress and improved life satisfaction, problem solving and help seeking; however, no significant changes were observed for young men. Although ROC was successful in attracting young men, demonstrating that the concept resonates with them, the service failed to keep them engaged. Further research is needed to explore how (or what changes need to be made) to sustain young men's engagement in the game.

Integrated Radio and Optical Communication (iROC)

NASA Technical Reports Server (NTRS)

Raible, Daniel; Romanofsky, Robert; Pease, Gary; Kacpura, Thomas

2016-01-01

This is an overview of the Integrated Radio and Optical Communication (iROC) Project for Space Communication and Navigation Industry Days. The Goal is to develop and demonstrate new, high payoff space technologies that will promote mission utilization of optical communications, thereby expanding the capabilities of NASA's exploration, science, and discovery missions. This is an overview that combines the paramount features of select deep space RF and optical communications elements into an integrated system, scalable from deep space to near earth. It will realize Ka-band RF and 1550 nanometer optical capability. The approach is to prototype and demonstrate performance of key components to increase to TRL-5, leading to integrated hybrid communications system demonstration to increase to TRL-5, leading to integrated hybrid communications system demonstration.

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

PubMed

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

2016-01-01

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

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.

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

PubMed

He, Xin; Frey, Eric C

2006-08-01

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

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

PubMed Central

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

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

1994-04-01

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

Structural vascular disease in Africans: Performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: The SABPA study.

PubMed

Botha, J; de Ridder, J H; Potgieter, J C; Steyn, H S; Malan, L

2013-10-01

A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fasting bloods (glucose, high density lipoprotein (HDL) and triglycerides) were obtained in a well-controlled setting. The RPWC male model (LR ROC AUC: 0.71, NN ROC AUC: 0.71) was practically equal to the JSC model (LR ROC AUC: 0.71, NN ROC AUC: 0.69) to predict structural vascular -disease. Similarly, the female RPWC model (LR ROC AUC: 0.84, NN ROC AUC: 0.82) and JSC model (LR ROC AUC: 0.82, NN ROC AUC: 0.81) equally predicted CIMT as surrogate marker for structural vascular disease. Odds ratios supported validity where prediction of CIMT revealed -clinical -significance, well over 1, for both the JSC and RPWC models in African males and females (OR 3.75-13.98). In conclusion, the proposed RPWC model was substantially validated utilizing linear and non-linear analyses. We therefore propose ethnic-specific WC cut points (African males, ≥90 cm; -females, ≥98 cm) to predict a surrogate marker for structural vascular disease. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

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.

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.

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

PubMed

To Duc, Khanh

2017-11-18

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

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.

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.

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

PubMed

Chakraborty, Dev P

2011-08-21

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2015-11-23

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

Prohibitin plays a critical role in Enterovirus 71 neuropathogenesis

PubMed Central

Too, Issac Horng Khit; Bonne, Isabelle; Tan, Eng Lee; Chu, Justin Jang Hann; Alonso, Sylvie

2018-01-01

A close relative of poliovirus, enterovirus 71 (EV71) is regarded as an important neurotropic virus of serious public health concern. EV71 causes Hand, Foot and Mouth Disease and has been associated with neurological complications in young children. Our limited understanding of the mechanisms involved in its neuropathogenesis has hampered the development of effective therapeutic options. Here, using a two-dimensional proteomics approach combined with mass spectrometry, we have identified a unique panel of host proteins that were differentially and dynamically modulated during EV71 infection of motor-neuron NSC-34 cells, which are found at the neuromuscular junctions where EV71 is believed to enter the central nervous system. Meta-analysis with previously published proteomics studies in neuroblastoma or muscle cell lines revealed minimal overlapping which suggests unique host-pathogen interactions in NSC-34 cells. Among the candidate proteins, we focused our attention on prohibitin (PHB), a protein that is involved in multiple cellular functions and the target of anti-cancer drug Rocaglamide (Roc-A). We demonstrated that cell surface-expressed PHB is involved in EV71 entry into neuronal cells specifically, while membrane-bound mitochondrial PHB associates with the virus replication complex and facilitates viral replication. Furthermore, Roc-A treatment of EV71-infected neuronal cells reduced significantly virus yields. However, the inhibitory effect of Roc-A on PHB in NSC-34 cells was not through blocking the CRAF/MEK/ERK pathway as previously reported. Instead, Roc-A treated NSC-34 cells had lower mitochondria-associated PHB and lower ATP levels that correlated with impaired mitochondria integrity. In vivo, EV71-infected mice treated with Roc-A survived longer than the vehicle-treated animals and had significantly lower virus loads in their spinal cord and brain, whereas virus titers in their limb muscles were comparable to controls. Together, this study uncovers PHB as the first host factor that is specifically involved in EV71 neuropathogenesis and a potential drug target to limit neurological complications. PMID:29324904

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

PubMed Central

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

2014-01-01

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

Three new potential ovarian cancer biomarkers detected in human urine with equalizer bead technology.

PubMed

Petri, Anette Lykke; Simonsen, Anja Hviid; Yip, Tai-Tung; Hogdall, Estrid; Fung, Eric T; Lundvall, Lene; Hogdall, Claus

2009-01-01

To examine whether urine can be used to measure specific ovarian cancer proteomic profiles and whether one peak alone or in combination with other peaks or CA125 has the sensitivity and specificity to discriminate between ovarian cancer pelvic mass and benign pelvic mass. A total of 209 women were admitted for surgery for pelvic mass at the Gynaecological Department at Rigshospitalet, Copenhagen. Of the women, 156 had benign gynaecological tumors, 13 had borderline tumors and 40 had malignant epithelial ovarian cancer. The prospectively and preoperatively collected urine samples were aliquotted and frozen at -80 degrees until the time of analysis. The urine was fractionated using equalizer bead technology and then analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Biomarkers were purified and identified using combinations of chromatographic techniques and tandem mass spectrometry. Benign and malignant ovarian cancer cases were compared; 21 significantly different peaks (p<0.001) were visualized using Mann-Whitney analysis, ranging in m/z values from 1,500 to 185,000. The three most significant peaks were purified and identified as fibrinogen alpha fragment (m/z=2570.21), collagen alpha 1 (III) fragment (m/z=2707.32) and fibrinogen beta NT fragment (m/z=4425.09). The area under the receiver operator characteristic curve (ROC AUC) value for these three peaks in combination was 0.88, and their ROC AUC value in combination with CA125 was 0.96. This result supports the feasibility of using urine as a clinical diagnostic medium, and the ROC AUC value for the three most significant peaks in combination with or without CA125 demonstrates the enhanced prediction performance of combined marker analysis.

Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas.

PubMed

Xu, Boyan; Su, Lu; Wang, Zhenxiong; Fan, Yang; Gong, Gaolang; Zhu, Wenzhen; Gao, Peiyi; Gao, Jia-Hong

2018-04-17

Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas. Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (α) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis. The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (0.979) and H (0.594), indicating an improved performance for tumor differentiation. The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Three regularities of recognition memory: the role of bias.

PubMed

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

2015-12-01

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

A simple approach to estimate daily loads of total, refractory, and labile organic carbon from their seasonal loads in a watershed.

PubMed

Ouyang, Ying; Grace, Johnny M; Zipperer, Wayne C; Hatten, Jeff; Dewey, Janet

2018-05-22

Loads of naturally occurring total organic carbons (TOC), refractory organic carbon (ROC), and labile organic carbon (LOC) in streams control the availability of nutrients and the solubility and toxicity of contaminants and affect biological activities through absorption of light and complex metals with production of carcinogenic compounds. Although computer models have become increasingly popular in understanding and management of TOC, ROC, and LOC loads in streams, the usefulness of these models hinges on the availability of daily data for model calibration and validation. Unfortunately, these daily data are usually insufficient and/or unavailable for most watersheds due to a variety of reasons, such as budget and time constraints. A simple approach was developed here to calculate daily loads of TOC, ROC, and LOC in streams based on their seasonal loads. We concluded that the predictions from our approach adequately match field measurements based on statistical comparisons between model calculations and field measurements. Our approach demonstrates that an increase in stream discharge results in increased stream TOC, ROC, and LOC concentrations and loads, although high peak discharge did not necessarily result in high peaks of TOC, ROC, and LOC concentrations and loads. The approach developed herein is a useful tool to convert seasonal loads of TOC, ROC, and LOC into daily loads in the absence of measured daily load data.

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.

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

ERIC Educational Resources Information Center

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

2013-01-01

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

Wavelet and receiver operating characteristic analysis of heart rate variability

NASA Astrophysics Data System (ADS)

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

2002-02-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

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

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.

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.

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.

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.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2017-12-01

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

[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 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

First trimester prediction of maternal glycemic status.

PubMed

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

2015-05-01

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

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

PubMed

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

2016-10-01

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

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

NASA Astrophysics Data System (ADS)

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

1998-08-01

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

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.

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

Intergenic Variable-Number Tandem-Repeat Polymorphism Upstream of rocA Alters Toxin Production and Enhances Virulence in Streptococcus pyogenes.

PubMed

Zhu, Luchang; Olsen, Randall J; Horstmann, Nicola; Shelburne, Samuel A; Fan, Jia; Hu, Ye; Musser, James M

2016-07-01

Variable-number tandem-repeat (VNTR) polymorphisms are ubiquitous in bacteria. However, only a small fraction of them has been functionally studied. Here, we report an intergenic VNTR polymorphism that confers an altered level of toxin production and increased virulence in Streptococcus pyogenes The nature of the polymorphism is a one-unit deletion in a three-tandem-repeat locus upstream of the rocA gene encoding a sensor kinase. S. pyogenes strains with this type of polymorphism cause human infection and produce significantly larger amounts of the secreted cytotoxins S. pyogenes NADase (SPN) and streptolysin O (SLO). Using isogenic mutant strains, we demonstrate that deleting one or more units of the tandem repeats abolished RocA production, reduced CovR phosphorylation, derepressed multiple CovR-regulated virulence factors (such as SPN and SLO), and increased virulence in a mouse model of necrotizing fasciitis. The phenotypic effect of the VNTR polymorphism was nearly the same as that of inactivating the rocA gene. In summary, we identified and characterized an intergenic VNTR polymorphism in S. pyogenes that affects toxin production and virulence. These new findings enhance understanding of rocA biology and the function of VNTR polymorphisms in S. pyogenes. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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

PubMed

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

2009-01-01

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

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

PubMed

Pan, P C; Goldberg, D P

1990-11-01

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

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

PubMed

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

2017-08-01

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

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

PubMed

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

2016-04-01

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

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.

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

PubMed

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

2012-07-01

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

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

PubMed Central

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

2012-01-01

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

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.

Spontaneous Swallowing Frequency [Has Potential to] Identify Dysphagia in Acute Stroke

PubMed Central

Carnaby, Giselle D; Sia, Isaac; Khanna, Anna; Waters, Michael

2014-01-01

Background and Purpose Spontaneous swallowing frequency has been described as an index of dysphagia in various health conditions. This study evaluated the potential of spontaneous swallow frequency analysis as a screening protocol for dysphagia in acute stroke. Methods In a cohort of 63 acute stroke cases swallow frequency rates (swallows per minute: SPM) were compared to stroke and swallow severity indices, age, time from stroke to assessment, and consciousness level. Mean differences in SPM were compared between patients with vs. without clinically significant dysphagia. ROC analysis was used to identify the optimal threshold in SPM which was compared to a validated clinical dysphagia examination for identification of dysphagia cases. Time series analysis was employed to identify the minimally adequate time period to complete spontaneous swallow frequency analysis. Results SPM correlated significantly with stroke and swallow severity indices but not with age, time from stroke onset, or consciousness level. Patients with dysphagia demonstrated significantly lower SPM rates. SPM differed by dysphagia severity. ROC analysis yielded a threshold of SPM ≤ 0.40 which identified dysphagia (per the criterion referent) with 0.96 sensitivity, 0.68 specificity, and 0.96 negative predictive value. Time series analysis indicated that a 5 to 10 minute sampling window was sufficient to calculate spontaneous swallow frequency to identify dysphagia cases in acute stroke. Conclusions Spontaneous swallowing frequency presents high potential to screen for dysphagia in acute stroke without the need for trained, available personnel. PMID:24149008

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…

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.

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.

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

PubMed

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

2015-04-01

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

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

PubMed

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

2014-11-01

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

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

PubMed Central

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

2014-01-01

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

LIDAR Metrology for Prescription Characterization and Alignment of Large Mirrors

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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.

ROC analysis of diagnostic performance in liver scintigraphy.

PubMed

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

1981-02-01

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

Inflammatory Asthma Phenotype Discrimination Using an Electronic Nose Breath Analyzer.

PubMed

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

2015-01-01

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

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

PubMed

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

2018-01-01

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

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

PubMed

Mossman, Douglas

2013-01-01

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

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

PubMed

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

2015-06-01

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

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.

Predictors of patients who will develop prolonged occult hypoperfusion following blunt trauma.

PubMed

Schulman, Andrew M; Claridge, Jeffrey A; Carr, Gordon; Diesen, Diana L; Young, Jeffrey S

2004-10-01

Prolonged occult hypoperfusion or POH (serum lactate >2.4 mmol/L persisting >12 hours from admission) represents a reversible risk factor for adverse outcomes following traumatic injury. We hypothesized that patients at increased risk for POH could be identified at the time of admission. Prospective data from adult trauma admissions between January 1, 1998 and December 31, 2000 were analyzed. Potential risk factors for POH were determined by univariate analysis (p < or =0.10= significant). Significant factors were tested in a logistic regression model (LR) (p < or =0.05= significant). The predictive ability of the LR was tested by receiver operating curve (ROC) analysis (p < or =0.05= significant). Three hundred seventy-eight patients were analyzed, 129 with POH. Injury Severity Score (ISS), emergency department Glasgow Coma Scale score, hypotension, and the individual Abbreviated Injury Scale score (AIS) for Head (H), Abdominal/Pelvic Viscera (A) and Pelvis/Bony Extremity (P) were significantly associated with POH. LR demonstrated that ISS, A-AIS > or =3 and P-AIS > or =3 were independent predictors of POH (p <0.05). ROC analysis of the LR equation was statistically significant (Area=0.69, p <0.001). We identified factors at admission that placed patients at higher risk for developing POH. Select patients may benefit from rapid, aggressive monitoring and resuscitation, possibly preventing POH and its associated morbidity and mortality.

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.

Differentiating invasive and pre-invasive lung cancer by quantitative analysis of histopathologic images

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Sun, Hongliu; Chan, Heang-Ping; Chughtai, Aamer; Wei, Jun; Hadjiiski, Lubomir; Kazerooni, Ella

2018-02-01

We are developing automated radiopathomics method for diagnosis of lung nodule subtypes. In this study, we investigated the feasibility of using quantitative methods to analyze the tumor nuclei and cytoplasm in pathologic wholeslide images for the classification of pathologic subtypes of invasive nodules and pre-invasive nodules. We developed a multiscale blob detection method with watershed transform (MBD-WT) to segment the tumor cells. Pathomic features were extracted to characterize the size, morphology, sharpness, and gray level variation in each segmented nucleus and the heterogeneity patterns of tumor nuclei and cytoplasm. With permission of the National Lung Screening Trial (NLST) project, a data set containing 90 digital haematoxylin and eosin (HE) whole-slide images from 48 cases was used in this study. The 48 cases contain 77 regions of invasive subtypes and 43 regions of pre-invasive subtypes outlined by a pathologist on the HE images using the pathological tumor region description provided by NLST as reference. A logistic regression model (LRM) was built using leave-one-case-out resampling and receiver operating characteristic (ROC) analysis for classification of invasive and pre-invasive subtypes. With 11 selected features, the LRM achieved a test area under the ROC curve (AUC) value of 0.91+/-0.03. The results demonstrated that the pathologic invasiveness of lung adenocarcinomas could be categorized with high accuracy using pathomics analysis.

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

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

PubMed

Higham, Philip A

2007-02-01

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

Mutations in a new Arabidopsis cyclophilin disrupt its interaction with protein phosphatase 2A

NASA Technical Reports Server (NTRS)

Jackson, K.; Soll, D.; Evans, M. L. (Principal Investigator)

1999-01-01

The heterotrimeric protein phosphatase 2A (PP2A) is a component of multiple signaling pathways in eukaryotes. Disruption of PP2A activity in Arabidopsis is known to alter auxin transport and growth response pathways. We demonstrated that the regulatory subunit A of an Arabidopsis PP2A interacts with a novel cyclophilin, ROC7. The gene for this cyclophilin encodes a protein that contains a unique 30-amino acid extension at the N-terminus, which distinguishes the gene product from all previously identified Arabidopsis cyclophilins. Altered forms of ROC7 cyclophilin with mutations in the conserved DENFKL domain did not bind to PP2A. Unlike protein phosphatase 2B, PP2A activity in Arabidopsis extracts was not affected by the presence of the cyclophilin-binding molecule cyclosporin. The ROC7 transcript was expressed to high levels in all tissues tested. Expression of an ROC7 antisense transcript gave rise to increased root growth. These results indicate that cyclophilin may have a role in regulating PP2A activity, by a mechanism that differs from that employed for cyclophilin regulation of PP2B.

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.

The effect of Interaction Anxiousness Scale and Brief Social Phobia Scale for screening social anxiety disorder in college students: a study on discriminative validity.

PubMed

Cao, Jianqin; Yang, Jinwei; Zhou, Yuqiu; Chu, Fuliu; Zhao, Xiwu; Wang, Weiren; Wang, Yunlong; Peng, Tao

2016-12-01

Social anxiety disorder (SAD) is one of the most prevalent mental health problems, but there is little research concerning the effective screening instruments in practice. This study was designed to examine the discriminative validity of Interaction Anxiousness Scale (IAS) and Brief Social Phobia Scale (BSPS) for the screening of SAD through the compared and combined analysis. Firstly, 421 Chinese undergraduates were screened by the IAS and BSPS. Secondly, in the follow-up stage, 248 students were interviewed by the Structured Clinical Interview for DSM-IV. Receiver operating characteristic (ROC) analysis was used, and the related psychometric characters were checked. The results indicated that the ROC in these two scales demonstrated discrimination is in satisfactory level (range: 0.7-0.8). However, the highest agreement (92.17%) was identified when a cut-off point of 50 measured by the IAS and a cut-off point of 34 by the BSPS were combined, also with higher PPV, SENS, SPEC and OA than that reached when BSPS was used individually, as well as PPV, SPEC and OA in IAS. The findings indicate that the combination of these two scales is valid as the general screening instrument for SAD in maximizing the discriminative validity.

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.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2016-01-01

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

Filling in the blanks. An estimation of illicit cannabis growers' profits in Belgium.

PubMed

Vanhove, Wouter; Surmont, Tim; Van Damme, Patrick; De Ruyver, Brice

2014-05-01

As a result of increased pressure on cannabis cultivation in The Netherlands, the number of confiscated indoor cannabis plantations in Belgium is rising. Although increases are reported for all plantations sizes, half of the seized plantations contain less than 50 plants. In this study, factors and variables that influence costs and benefits of indoor cannabis cultivation are investigated as well as how these costs and benefits vary between different cannabis grower types. Real-situation data of four growers were used to perform financial analyses. Costs included fixed and variable material costs, as well as opportunity costs. Gross revenue per grow cycle was calculated based on most recent forensic findings for illicit Belgian cannabis plantations and was adjusted for the risk of getting caught. Finally, gross revenues and return on costs (ROC) were calculated over 1 year (4 cycles). Financial analysis shows that in all cases gross revenues as well as ROC are considerable, even after a single growth cycle. Highest profitability was found for large-scale (600 plants, ROC=6.8) and mid-scale plantations (150 plants, ROC=6.0). However, industrial plantations (23,000 plants, ROC=1.4) and micro-scale plantations (5 plants, ROC=2.8) are also highly remunerative. Shift of police focus away from micro-scale growers, least likely to be involved in criminal gangs, to large-scale and industrial scale plantations would influence costs as a result of changing risks of getting caught. However, sensitivity analysis shows that this does not significantly influence the conclusions on profitability of different types of indoor cannabis growers. Seizure and confiscation of profits are important elements in the integral and integrated policy approach required for tackling illicit indoor cannabis plantations. The large return of costs evidenced in the present study, underpin the policy relevance of confiscating those illicit profits as part of enforcement. Copyright © 2014 Elsevier B.V. All rights reserved.

Target Detection and Identification Using Canonical Correlations Analysis and Subspace Partitioning

DTIC Science & Technology

2008-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

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

PubMed

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

2017-07-01

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

Quantitative evaluation of contrast-enhanced ultrasound after intravenous administration of a microbubble contrast agent for differentiation of benign and malignant thyroid nodules: assessment of diagnostic accuracy.

PubMed

Nemec, Ursula; Nemec, Stefan F; Novotny, Clemens; Weber, Michael; Czerny, Christian; Krestan, Christian R

2012-06-01

To investigate the diagnostic accuracy, through quantitative analysis, of contrast-enhanced ultrasound (CEUS), using a microbubble contrast agent, in the differentiation of thyroid nodules. This prospective study enrolled 46 patients with solitary, scintigraphically non-functional thyroid nodules. These patients were scheduled for surgery and underwent preoperative CEUS with pulse-inversion harmonic imaging after intravenous microbubble contrast medium administration. Using histology as a standard of reference, time-intensity curves of benign and malignant nodules were compared by means of peak enhancement and wash-out enhancement relative to the baseline intensity using a mixed model ANOVA. ROC analysis was performed to assess the diagnostic accuracy in the differentiation of benign and malignant nodules on CEUS. The complete CEUS data of 42 patients (31/42 [73.8%] benign and 11/42 [26.2%] malignant nodules) revealed a significant difference (P < 0.001) in enhancement between benign and malignant nodules. Furthermore, based on ROC analysis, CEUS demonstrated sensitivity of 76.9%, specificity of 84.8% and accuracy of 82.6%. Quantitative analysis of CEUS using a microbubble contrast agent allows the differentiation of benign and malignant thyroid nodules and may potentially serve, in addition to grey-scale and Doppler ultrasound, as an adjunctive tool in the assessment of patients with thyroid nodules. • Contrast-enhanced ultrasound (CEUS) helps differentiate between benign and malignant thyroid nodules. • Quantitative CEUS analysis yields sensitivity of 76.9% and specificity of 84.8%. • CEUS may be a potentially useful adjunct in assessing thyroid nodules.

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.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2016-06-01

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

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

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.

Star Tracker Performance Estimate with IMU

NASA Technical Reports Server (NTRS)

Aretskin-Hariton, Eliot D.; Swank, Aaron J.

2015-01-01

A software tool for estimating cross-boresight error of a star tracker combined with an inertial measurement unit (IMU) was developed to support trade studies for the Integrated Radio and Optical Communication project (iROC) at the National Aeronautics and Space Administration Glenn Research Center. Typical laser communication systems, such as the Lunar Laser Communication Demonstration (LLCD) and the Laser Communication Relay Demonstration (LCRD), use a beacon to locate ground stations. iROC is investigating the use of beaconless precision laser pointing to enable laser communication at Mars orbits and beyond. Precision attitude knowledge is essential to the iROC mission to enable high-speed steering of the optical link. The preliminary concept to achieve this precision attitude knowledge is to use star trackers combined with an IMU. The Star Tracker Accuracy (STAcc) software was developed to rapidly assess the capabilities of star tracker and IMU configurations. STAcc determines the overall cross-boresight error of a star tracker with an IMU given the characteristic parameters: quantum efficiency, aperture, apparent star magnitude, exposure time, field of view, photon spread, detector pixels, spacecraft slew rate, maximum stars used for quaternion estimation, and IMU angular random walk. This paper discusses the supporting theory used to construct STAcc, verification of the program and sample results.

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

PubMed

Kitahama, H

1991-05-25

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

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.

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.

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

PubMed

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

2017-10-15

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

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.

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

PubMed

Brown Connolly, Nancy E

2014-12-01

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

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

PubMed

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

2016-09-01

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

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

PubMed

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

2013-03-01

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

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.

Removing organic and nitrogen content from a highly saline municipal wastewater reverse osmosis concentrate by UV/H2O2-BAC treatment.

PubMed

Pradhan, Shovana; Fan, Linhua; Roddick, Felicity A

2015-10-01

Reverse osmosis (RO) concentrate (ROC) streams generated from RO-based municipal wastewater reclamation processes pose potential health and environmental risks on their disposal to confined water bodies such as bays. A UV/H2O2 advanced oxidation process followed by a biological activated carbon (BAC) treatment was evaluated at lab-scale for the removal of organic and nutrient content from a highly saline ROC (TDS 16 g L(-1), EC 23.5 mS cm(-1)) for its safe disposal to the receiving environment. Over the 230-day operation of the UV/H2O2-BAC process, the colour and UV absorbance (254 nm) of the ROC were reduced to well below those of the influent to the reclamation process. The concentrations of DOC and total nitrogen (TN) were reduced by approximately 60% at an empty bed contact time (EBCT) of 60 min. The reduction in ammonia nitrogen by the BAC remained high under all conditions tested (>90%). Further investigation confirmed that the presence of residual peroxide in the UV/H2O2 treated ROC was beneficial for DOC removal, but markedly inhibited the activities of the nitrifying bacteria (i.e., nitrite oxidising bacteria) in the BAC system and hence compromised total nitrogen removal. This work demonstrated that the BAC treatment could be acclimated to the very high salinity environment, and could be used as a robust method for the removal of organic matter and nitrogen from the pre-oxidised ROC under optimised conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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

PubMed

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

2002-10-01

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

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.

Development and Validation of a Novel Scoring System for Predicting Technical Success of Chronic Total Occlusion Percutaneous Coronary Interventions: The PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) Score.

PubMed

Christopoulos, Georgios; Kandzari, David E; Yeh, Robert W; Jaffer, Farouc A; Karmpaliotis, Dimitri; Wyman, Michael R; Alaswad, Khaldoon; Lombardi, William; Grantham, J Aaron; Moses, Jeffrey; Christakopoulos, Georgios; Tarar, Muhammad Nauman J; Rangan, Bavana V; Lembo, Nicholas; Garcia, Santiago; Cipher, Daisha; Thompson, Craig A; Banerjee, Subhash; Brilakis, Emmanouil S

2016-01-11

This study sought to develop a novel parsimonious score for predicting technical success of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) performed using the hybrid approach. Predicting technical success of CTO PCI can facilitate clinical decision making and procedural planning. We analyzed clinical and angiographic parameters from 781 CTO PCIs included in PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) using a derivation and validation cohort (2:1 sampling ratio). Variables with strong association with technical success in multivariable analysis were assigned 1 point, and a 4-point score was developed from summing all points. The PROGRESS CTO score was subsequently compared with the J-CTO (Multicenter Chronic Total Occlusion Registry in Japan) score in the validation cohort. Technical success was 92.9%. On multivariable analysis, factors associated with technical success included proximal cap ambiguity (beta coefficient [b] = 0.88), moderate/severe tortuosity (b = 1.18), circumflex artery CTO (b = 0.99), and absence of "interventional" collaterals (b = 0.88). The resulting score demonstrated good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow chi-square = 2.633; p = 0.268, and receiver-operator characteristic [ROC] area = 0.778) and validation (Hosmer-Lemeshow chi-square = 5.333; p = 0.070, and ROC area = 0.720) subset. In the validation cohort, the PROGRESS CTO and J-CTO scores performed similarly in predicting technical success (ROC area 0.720 vs. 0.746, area under the curve difference = 0.026, 95% confidence interval = -0.093 to 0.144). The PROGRESS CTO score is a novel useful tool for estimating technical success in CTO PCI performed using the hybrid approach. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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.

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.

Reliability and validity of urinary nerve growth factor measurement in women with lower urinary tract symptoms.

PubMed

Vijaya, Gopalan; Cartwright, Rufus; Bhide, Alka; Derpapas, Alexandros; Fernando, Ruwan; Khullar, Vik

2016-11-01

The validity and reliability of measurement of urinary NGF as a diagnostic biomarker in women with lower urinary tract dysfunction (LUTD) is uncertain. We aimed to evaluate both the diagnostic and discriminant validity, and the test-retest reliability of urinary NGF measurement in women with LUTD. Urinary NGF was measured in women with LUTD (n = 205) and asymptomatic subjects (n = 31). Urinary NGF was assayed using an ELISA method and normalized against urinary creatinine. NGF/creatinine ratios were compared between symptom subgroups using Mann-Whitney U test, and between different urodynamic diagnoses using the Kruskal-Wallis test. Receiver Operator Characteristic (ROC) analysis was employed to evaluate the diagnostic performance of urinary NGF. Test-retest reliability of NGF measurement was assessed using intra-class correlation (ICC). Urinary NGF was significantly but non-specifically increased in symptomatic patients when compared to controls (13.33 vs. 2.05 ng NGF/g Cr, P < 0.001). On multivariate logistic regression NGF was a good predictor of patients having OAB or not, however, the adjusted odds ratio only 1.006. ROC analysis demonstrated poor discriminant ability between different symptomatic groups and urodynamic groups. Using a cut off of 13.0 ng NGF/g creatinine the test provides a sensitivity of 81%, but a specificity of only 39% for overactive bladder. The assays demonstrated good test-retest reliability with ICC of 0.889. Although urinary NGF can be reliably assayed, and is increased in various LUTDs, it discriminates poorly between these disorders therefore has very limited potential as a biomarker. Neurourol. Urodynam. 35:944-948, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

Clark, Ralph O.

1991-01-01

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

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

PubMed

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

2017-01-01

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

Diagnostic depressive symptoms of the mixed bipolar episode.

PubMed

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

2000-03-01

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

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.

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.

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

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

PubMed

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

2016-01-01

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

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

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

2009-03-01

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

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.

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

PubMed Central

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

2016-01-01

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

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

PubMed

Humphries, Joyce E; Flowe, Heather D

2015-04-01

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

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

PubMed

Malmberg, Kenneth J; Xu, Jing

2006-02-01

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

SU-F-T-235: Optical Scan Based Collision Avoidance Using Multiple Stereotactic Cameras During Simulation

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

Cardan, R; Popple, R; Dobelbower, M

Purpose: To demonstrate the ability to quickly generate an accurate collision avoidance map using multiple stereotactic cameras during simulation. Methods: Three Kinect stereotactic cameras were placed in the CT simulation room and optically calibrated to the DICOM isocenter. Immediately before scanning, the patient was optically imaged to generate a 3D polygon mesh, which was used to calculate the collision avoidance area using our previously developed framework. The mesh was visually compared to the CT scan body contour to ensure accurate coordinate alignment. To test the accuracy of the collision calculation, the patient and machine were physically maneuvered in the treatmentmore » room to calculated collision boundaries. Results: The optical scan and collision calculation took 38.0 seconds and 2.5 seconds to complete respectively. The collision prediction accuracy was determined using a receiver operating curve (ROC) analysis, where the true positive, true negative, false positive and false negative values were 837, 821, 43, and 79 points respectively. The ROC accuracy was 93.1% over the sampled collision space. Conclusion: We have demonstrated a framework which is fast and accurate for predicting collision avoidance for treatment which can be determined during the normal simulation process. Because of the speed, the system could be used to add a layer of safety with a negligible impact on the normal patient simulation experience. This information could be used during treatment planning to explore the feasible geometries when optimizing plans. Research supported by Varian Medical Systems.« less

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.

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.

Identifying the Presence of Prostate Cancer in Individuals with PSA Levels <20 ng ml-1 Using Computational Data Extraction Analysis of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

PubMed

Cosma, Georgina; McArdle, Stéphanie E; Reeder, Stephen; Foulds, Gemma A; Hood, Simon; Khan, Masood; Pockley, A Graham

2017-01-01

Determining whether an asymptomatic individual with Prostate-Specific Antigen (PSA) levels below 20 ng ml -1 has prostate cancer in the absence of definitive, biopsy-based evidence continues to present a significant challenge to clinicians who must decide whether such individuals with low PSA values have prostate cancer. Herein, we present an advanced computational data extraction approach which can identify the presence of prostate cancer in men with PSA levels <20 ng ml -1 on the basis of peripheral blood immune cell profiles that have been generated using multi-parameter flow cytometry. Statistical analysis of immune phenotyping datasets relating to the presence and prevalence of key leukocyte populations in the peripheral blood, as generated from individuals undergoing routine tests for prostate cancer (including tissue biopsy) using multi-parametric flow cytometric analysis, was unable to identify significant relationships between leukocyte population profiles and the presence of benign disease (no prostate cancer) or prostate cancer. By contrast, a Genetic Algorithm computational approach identified a subset of five flow cytometry features ( CD 8 + CD 45 RA - CD 27 - CD 28 - ( CD 8 + Effector Memory cells); CD 4 + CD 45 RA - CD 27 - CD 28 - ( CD 4 + Terminally Differentiated Effector Memory Cells re-expressing CD45RA); CD 3 - CD 19 + (B cells); CD 3 + CD 56 + CD 8 + CD 4 + (NKT cells)) from a set of twenty features, which could potentially discriminate between benign disease and prostate cancer. These features were used to construct a prostate cancer prediction model using the k-Nearest-Neighbor classification algorithm. The proposed model, which takes as input the set of flow cytometry features, outperformed the predictive model which takes PSA values as input. Specifically, the flow cytometry-based model achieved Accuracy = 83.33%, AUC = 83.40%, and optimal ROC points of FPR = 16.13%, TPR = 82.93%, whereas the PSA-based model achieved Accuracy = 77.78%, AUC = 76.95%, and optimal ROC points of FPR = 29.03%, TPR = 82.93%. Combining PSA and flow cytometry predictors achieved Accuracy = 79.17%, AUC = 78.17% and optimal ROC points of FPR = 29.03%, TPR = 85.37%. The results demonstrate the value of computational intelligence-based approaches for interrogating immunophenotyping datasets and that combining peripheral blood phenotypic profiling with PSA levels improves diagnostic accuracy compared to using PSA test alone. These studies also demonstrate that the presence of cancer is reflected in changes in the peripheral blood immune phenotype profile which can be identified using computational analysis and interpretation of complex flow cytometry datasets.

Lung Reference Set A Application: LaszloTakacs - Biosystems (2010) — EDRN Public Portal

Cancer.gov

We would like to access the NCI lung cancer Combined Pre-Validation Reference Set A in order to further validate a lung cancer diagnostic test candidate. Our test is based on a panel of antibodies which have been tested on 4 different cohorts (see below, paragraph “Preliminary Data and Methods”). This Reference Set A, whose clinical setting is “Diagnosis of lung cancer”, will be used to validate the panel of monoclonal antibodies which have been demonstrated by extensive data analysis to provide the best discrimination between controls and Lung Cancer patient plasma samples, sensitivity and specificity values from ROC analyses are superior than 85 %.

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.

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

PubMed

Du, Pang; Tang, Liansheng

2009-01-30

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

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2016-01-06

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Accuracy of 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.

Development and validation of a tool for identifying women with low bone mineral density and low-impact fractures: the São Paulo Osteoporosis Risk Index (SAPORI).

PubMed

Pinheiro, M M; Reis Neto, E T; Machado, F S; Omura, F; Szejnfeld, J; Szejnfeld, V L

2012-04-01

The performance of the São Paulo Osteoporosis Risk Index (SAPORI) was tested in 1,915 women from the original cohort, São Paulo Osteoporosis Study (SAPOS) (N = 4332). This new tool was able to identify women with low bone density (spine and hip) and low-impact fracture, with an area under the receiving operator curve (ROC) of 0.831, 0.724, and 0.689, respectively. A number of studies have demonstrated the clinical relevance of risk factors for identifying individuals at risk of fracture (Fx) and osteoporosis (OP). The SAPOS is an epidemiological study for the assessment of risk factors for Fx and low bone density in women from the community of the metropolitan area of São Paulo, Brazil. The aim of the present study was to develop and validate a tool for identifying women at higher risk for OP and low-impact Fx. A total of 4,332 pre-, peri-, and postmenopausal women were analyzed through a questionnaire addressing risk factors for OP and Fx. All of them performed bone densitometry at the lumbar spine and proximal femur (DPX NT, GE-Lunar). Following the identification of the main risk factors for OP and Fx through multivariate and logistic regression, respectively, the SAPORI was designed and subsequently validated on a second cohort of 1,915 women from the metropolitan community of São Paulo. The performance of this tool was assessed through ROC analysis. The main and significant risk factors associated with low bone density and low-impact Fx were low body weight, advanced age, Caucasian ethnicity, family history of hip Fx, current smoking, and chronic use of glucocorticosteroids. Hormonal replacement therapy and regular physical activity in the previous year played a protective role (p < 0.05). After the statistical adjustments, the SAPORI was able to identify women with low bone density (T-score ≤ -2 standard deviations) in the femur, with 91.4% sensitivity, 52% specificity, and an area under the ROC of 0.831 (p < 0.001). At the lumbar spine, the performance was similar (81.5% sensitivity, 50% specificity, and area under ROC of 0.724; p < 0.001). Regarding the identification of low-impact Fx, the sensitivity was 71%, the specificity was 52%, and the area under the ROC was 0.689 (p < 0.001). The SAPORI is a simple, useful, fast, practice, and valid tool for identifying women at higher risk for low bone density and osteoporotic fractures.

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

PubMed Central

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

2015-01-01

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

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.

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.

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.

Clinical evaluation of JPEG2000 compression for digital mammography

NASA Astrophysics Data System (ADS)

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

2002-06-01

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

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

PubMed

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

2017-02-13

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

A comparison of ROC inferred from FROC and conventional ROC

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Protein induced by vitamin K absence or antagonist-II (PIVKA-II) specifically increased in Italian hepatocellular carcinoma patients.

PubMed

Viggiani, Valentina; Palombi, Sara; Gennarini, Giuseppina; D'Ettorre, Gabriella; De Vito, Corrado; Angeloni, Antonio; Frati, Luigi; Anastasi, Emanuela

2016-10-01

As a marker for Hepatocellular Carcinoma (HCC), Protein Induced by Vitamin K Absence II (PIVKA-II) seems to be superior to alpha fetoprotein (AFP). To better characterize the role of PIVKA-II, both AFP and PIVKA-II have been measured in Italian patients with diagnosis of HCC compared with patients affected by non-oncological liver pathologies. Sixty serum samples from patients with HCC, 60 samples from patients with benign liver disease and 60 samples obtained from healthy blood donors were included in the study. PIVKA-II and AFP were measured by LUMIPULSE(®) G1200 (Fujirebio-Europe, Belgium). We considered as PIVKA-II cutoff 70 mAU/ml (mean +3SD) of the values observed in healthy subjects. The evaluation of PIVKA-II showed a positivity of 70% in patients with HCC and 5% in patients with benign diseases (p < 0.0001) whereas high levels of AFP were observed in 55% of HCC patients and in 47% of patients with benign diseases. The combined Receiver Operating Characteristic (ROC) analysis of the two analytes revealed a higher sensitivity (75%) compared to those observed for the individual biomarkers. In conclusion, we demonstrate that as a marker for HCC, PIVKA-II is more specific for HCC and less prone to elevation during chronic liver diseases. The combination of the two biomarkers, evaluated by the ROC analysis, improved the specificity compared to a single marker. These data suggest that the combined analysis of the two markers could be a useful tool in clinical practice.

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.

Clinical Usefulness of Measuring Red Blood Cell Distribution Width in Patients with Hepatitis B Virus-Related Acute-On-Chronic Liver Failure.

PubMed

Jin, Lei; Gao, Yufeng; Ye, Jun; Zou, Guizhou; Li, Xu

2017-09-01

The red blood cell distribution width (RDW) is increased in chronic liver disease, but its clinical significance in hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is still unclear. The aim of the present study was to investigate the clinical significance of RDW in HBV-ACLF patients. The medical records of HBV-ACLF patients who were admitted to The Second Affiliated Hospital of Anhui Medical University between April 2012 and December 2015 were retrospectively reviewed. Correlations between RDW, neutrophil lymphocyte ratio (NLR), and the model for end-stage liver disease (MELD) scores were analyzed using the Spearman's approach. Multivariable stepwise logistic regression test was used to evaluate independent clinical parameters predicting 3-month mortality of HBV-ACLF patients. The association between RDW and hospitalization outcome was estimated by receiver operating curve (ROC) analysis. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank test. Sixty-two HBV-ACLF patients and sixty CHB patients were enrolled. RDW were increased in HBVACLF patients and positively correlated with the NLR as well as MELD scores. Multivariate analysis demonstrated that RDW value was an independent predictor for mortality. RDW had an area under the ROC of 0.799 in predicting 3-month mortality of HBV-ACLF patients. Patients with HBV-ACLF who had RDW > 17% showed significantly poorer survival than those who had RDW ≤ 17%. RDW values are significantly increased in patients with HBV-ACLF. Moreover, RDW values are an independent predicting factor for an in-hospital mortality in patients with HBV-ACLF.

Shallow Water Acoustics Studies

DTIC Science & Technology

2015-09-30

and 2) a demonstration that the predictive probability of detection ( PPD ) formalism of Dyer and Abbot works well, using QPE field data. The...applications, and 3) showing that the PPD formalism for detection could be a useful extension of the usual sonar equation ROC curves. TRANSITIONS

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

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

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.

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

PubMed

Wixted, John T; Mickes, Laura

2018-01-01

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

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

PubMed

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

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

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

PubMed

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

2011-03-01

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

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

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

2017-01-01

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

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

PubMed

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

2016-09-01

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

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

PubMed

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

2018-06-01

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

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

PubMed

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

2018-04-30

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

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

PubMed

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

2018-01-01

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

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

DTIC Science & Technology

2007-05-01

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

Optimal Hemoglobin A1c Levels for Screening of Diabetes and Prediabetes in the Japanese Population.

PubMed

Shimodaira, Masanori; Okaniwa, Shinji; Hanyu, Norinao; Nakayama, Tomohiro

2015-01-01

The aim of this study was to evaluate the utility of hemoglobin A1c (HbA1c) to identify individuals with diabetes and prediabetes in the Japanese population. A total of 1372 individuals without known diabetes were selected for this study. A 75 g oral glucose tolerance test (OGTT) was used to diagnose diabetes and prediabetes. The ability of HbA1c to detect diabetes and prediabetes was investigated using receiver operating characteristic (ROC) analysis. The kappa (κ) coefficient was used to test the agreement between HbA1c categorization and OGTT-based diagnosis. ROC analysis demonstrated that HbA1c was a good test to identify diabetes and prediabetes, with areas under the curve of 0.918 and 0.714, respectively. Optimal HbA1c cutoffs for diagnosing diabetes and prediabetes were 6.0% (sensitivity 83.7%, specificity 87.6%) and 5.7% (sensitivity 60.6%, specificity 72.1%), respectively, although the cutoff for prediabetes showed low accuracy (67.6%) and a high false-negative rate (39.4%). Agreement between HbA1c categorization and OGTT-based diagnosis was low in diabetes (κ = 0.399) and prediabetes (κ = 0.324). In Japanese subjects, the HbA1c cutoff of 6.0% had appropriate sensitivity and specificity for diabetes screening, whereas the cutoff of 5.7% had modest sensitivity and specificity in identifying prediabetes. Thus, HbA1c may be inadequate as a screening tool for prediabetes.

Post Hoc Analysis of Passive Cavitation Imaging for Classification of Histotripsy-Induced Liquefaction in Vitro.

PubMed

Bader, Kenneth B; Haworth, Kevin J; Maxwell, Adam D; Holland, Christy K

2018-01-01

Histotripsy utilizes focused ultrasound to generate bubble clouds for transcutaneous tissue liquefaction. Bubble activity maps are under development to provide image guidance and monitor treatment progress. The aim of this paper was to investigate the feasibility of using plane wave B-mode and passive cavitation images to be used as binary classifiers of histotripsy-induced liquefaction. Prostate tissue phantoms were exposed to histotripsy pulses over a range of pulse durations (5- ) and peak negative pressures (12-23 MPa). Acoustic emissions were recorded during the insonation and beamformed to form passive cavitation images. Plane wave B-mode images were acquired following the insonation to detect the hyperechoic bubble cloud. Phantom samples were sectioned and stained to delineate the liquefaction zone. Correlation between passive cavitation and plane wave B-mode images and the liquefaction zone was assessed using receiver operating characteristic (ROC) curve analysis. Liquefaction of the phantom was observed for all the insonation conditions. The area under the ROC (0.94 versus 0.82), accuracy (0.90 versus 0.83), and sensitivity (0.81 versus 0.49) was greater for passive cavitation images relative to B-mode images ( ) along the azimuth of the liquefaction zone. The specificity was greater than 0.9 for both imaging modalities. These results demonstrate a stronger correlation between histotripsy-induced liquefaction and passive cavitation imaging compared with the plane wave B-mode imaging, albeit with limited passive cavitation image range resolution.

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.

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

PubMed

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

2010-08-01

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

On the convexity of ROC curves estimated from radiological test results

PubMed Central

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

2010-01-01

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

Correlation of apparent diffusion coefficient ratio on 3.0 T MRI with prostate cancer Gleason score.

PubMed

Jyoti, Rajeev; Jain, Tarun Pankaj; Haxhimolla, Hodo; Liddell, Heath; Barrett, Sean Edward

2018-01-01

The purpose was to investigate the usefulness of ADC ratio on Diffusion MRI to discriminate between benign and malignant lesions of Prostate. Images of patients who underwent in-gantry MRI guided prostate lesion biopsy were retrospectively analyzed. Prostate Cancers with 20% or more Gleason score (GS) pattern 3 + 3 = 6 in each core or any volume of higher Gleason score pattern were included. ADC ratio was calculated by two reviewers for each lesion. The ADC ratio was calculated for each lesion by dividing the lowest ADC value in a lesion and highest ADC value in normal prostate in peripheral zone (PZ). ADC ratio values were compared with the biopsy result. Data was analysed using independent samples T-test, Spearman correlation, intra-class correlation coefficient (ICC) and Receiver operating characteristic (ROC) curve. 45 lesions in 33 patients were analyzed. 12 lesions were in transitional zone (TZ) and 33 in perpheral zone PZ. All lesions demonstrated an ADC ratio of 0.45 or lower. GS demonstrated a negative correlation with both the ADC value and ADC ratio . However, ADC ratio (p < 0.001) demonstrated a stronger correlation compared to ADC value alone (p = 0.014). There was no significant statistical difference between GS 3 + 4 and GS 4 + 3 mean ADC tumour value (p = 0.167). However when using ADC ratio , there was a significant difference (p = 0.032). ROC curve analysis demonstrated an area under the curve of 0.83 using ADC ratio and 0.76 when using ADC tumour value when discriminating Gleason 6 from Gleason ≥7 tumours. Inter-observer reliability in the calculation of ADC ratios was excellent, with ICC of 0.964. ADC ratio is a reliable and reproducible tool in quantification of diffusion restriction for clinically significant prostate cancer foci.

Fast discrimination of hydroxypropyl methyl cellulose using portable Raman spectrometer and multivariate methods

NASA Astrophysics Data System (ADS)

Song, Biao; Lu, Dan; Peng, Ming; Li, Xia; Zou, Ye; Huang, Meizhen; Lu, Feng

2017-02-01

Raman spectroscopy is developed as a fast and non-destructive method for the discrimination and classification of hydroxypropyl methyl cellulose (HPMC) samples. 44 E series and 41 K series of HPMC samples are measured by a self-developed portable Raman spectrometer (Hx-Raman) which is excited by a 785 nm diode laser and the spectrum range is 200-2700 cm-1 with a resolution (FWHM) of 6 cm-1. Multivariate analysis is applied for discrimination of E series from K series. By methods of principal components analysis (PCA) and Fisher discriminant analysis (FDA), a discrimination result with sensitivity of 90.91% and specificity of 95.12% is achieved. The corresponding receiver operating characteristic (ROC) is 0.99, indicting the accuracy of the predictive model. This result demonstrates the prospect of portable Raman spectrometer for rapid, non-destructive classification and discrimination of E series and K series samples of HPMC.

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

PubMed

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

2015-01-01

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2016-01-06

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Senator Barbara Mikulski Visits NASA Goddard

NASA Image and Video Library

2017-12-08

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

Search for Partner Proteins of A. thaliana Immunophilins Involved in the Control of Plant Immunity.

PubMed

Abdeeva, Inna A; Pogorelko, Gennady V; Maloshenok, Liliya G; Mokrykova, Maria V; Fursova, Oksana V; Bruskin, Sergey A

2018-04-19

The involvement of plant immunophilins in multiple essential processes such as development, various ways of adapting to biotic and abiotic stresses, and photosynthesis has already been established. Previously, research has demonstrated the involvement of three immunophilin genes ( AtCYP19-1/ROC3 , AtFKBP65/ROF2 , and AtCYP57 ) in the control of plant response to invasion by various pathogens. Current research attempts to identify host target proteins for each of the selected immunophilins. As a result, candidate interactors have been determined and confirmed using a yeast 2-hybrid (Y2H) system for protein⁻protein interaction assays. The generation of mutant isoforms of ROC3 and AtCYP57 harboring substituted amino acids in the in silico-predicted active sites became essential to achieving significant binding to its target partners. This data shows that ROF2 targets calcium-dependent lipid-binding domain-containing protein (At1g70790; AT1) and putative protein phosphatase (At2g30020; АТ2), whereas ROC3 interacts with GTP-binding protein (At1g30580; ENGD-1) and RmlC-like cupin (At5g39120). The immunophilin AtCYP57 binds to putative pyruvate decarboxylase-1 (Pdc1) and clathrin adaptor complex-related protein (At5g05010). Identified interactors confirm our previous findings that immunophilins ROC3 , ROF2 , and AtCYP57 are directly involved with stress response control. Further, these findings extend our understanding of the molecular functional pathways of these immunophilins.

Protein Quality Control Under Oxidative Stress Conditions

PubMed Central

Dahl, Jan-Ulrik; Gray, Michael J.; Jakob, Ursula

2015-01-01

Accumulation of reactive oxygen and chlorine species (RO/CS) is generally regarded to be a toxic and highly undesirable event, which serves as contributing factor in aging and many age-related diseases. However, it is also put to excellent use during host defense, when high levels of RO/CS are produced to kill invading microorganisms and regulate bacterial colonization. Biochemical and cell biological studies of how bacteria and other microorganisms deal with RO/CS have now provided important new insights into the physiological consequences of oxidative stress, the major targets that need protection, and the cellular strategies employed by organisms to mitigate the damage. This review examines the redox-regulated mechanisms by which cells maintain a functional proteome during oxidative stress. We will discuss the well-characterized redox-regulated chaperone Hsp33, and review recent discoveries demonstrating that oxidative stress-specific activation of chaperone function is a much more widespread phenomenon than previously anticipated. New members of this group include the cytosolic ATPase Get3 in yeast, the E. coli protein RidA, and the mammalian protein α2-macroglobin. We will conclude our review with recent evidence showing that inorganic polyphosphate (polyP), whose accumulation significantly increases bacterial oxidative stress resistance, works by a protein-like chaperone mechanism. Understanding the relationship between oxidative and proteotoxic stresses will improve our understanding of both host-microbe interactions and of how mammalian cells combat the damaging side effects of uncontrolled RO/CS production, a hallmark of inflammation. PMID:25698115

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.

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

NASA Astrophysics Data System (ADS)

Elangovan, Premkumar; Mackenzie, Alistair; Dance, David R.; Young, Kenneth C.; Cooke, Victoria; Wilkinson, Louise; Given-Wilson, Rosalind M.; Wallis, Matthew G.; Wells, Kevin

2017-04-01

A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper’s ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51  ±  0.06 and 0.54  ±  0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72  ±  0.01, 2.75  ±  0.01) and (2.77  ±  0.03, 2.82  ±  0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10  ±  0.17, 3.21  ±  0.11) and (3.01  ±  0.32, 3.19  ±  0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30 mm  ×  30 mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers.

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

Differentiation of Low- and High-Grade Pediatric Brain Tumors with High b-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model

PubMed Central

Sui, Yi; Wang, He; Liu, Guanzhong; Damen, Frederick W.; Wanamaker, Christian; Li, Yuhua

2015-01-01

Purpose To demonstrate that a new set of parameters (D, β, and μ) from a fractional order calculus (FROC) diffusion model can be used to improve the accuracy of MR imaging for differentiating among low- and high-grade pediatric brain tumors. Materials and Methods The institutional review board of the performing hospital approved this study, and written informed consent was obtained from the legal guardians of pediatric patients. Multi-b-value diffusion-weighted magnetic resonance (MR) imaging was performed in 67 pediatric patients with brain tumors. Diffusion coefficient D, fractional order parameter β (which correlates with tissue heterogeneity), and a microstructural quantity μ were calculated by fitting the multi-b-value diffusion-weighted images to an FROC model. D, β, and μ values were measured in solid tumor regions, as well as in normal-appearing gray matter as a control. These values were compared between the low- and high-grade tumor groups by using the Mann-Whitney U test. The performance of FROC parameters for differentiating among patient groups was evaluated with receiver operating characteristic (ROC) analysis. Results None of the FROC parameters exhibited significant differences in normal-appearing gray matter (P ≥ .24), but all showed a significant difference (P < .002) between low- (D, 1.53 μm2/msec ± 0.47; β, 0.87 ± 0.06; μ, 8.67 μm ± 0.95) and high-grade (D, 0.86 μm2/msec ± 0.23; β, 0.73 ± 0.06; μ, 7.8 μm ± 0.70) brain tumor groups. The combination of D and β produced the largest area under the ROC curve (0.962) in the ROC analysis compared with individual parameters (β, 0.943; D,0.910; and μ, 0.763), indicating an improved performance for tumor differentiation. Conclusion The FROC parameters can be used to differentiate between low- and high-grade pediatric brain tumor groups. The combination of FROC parameters or individual parameters may serve as in vivo, noninvasive, and quantitative imaging markers for classifying pediatric brain tumors. © RSNA, 2015 PMID:26035586

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

PubMed Central

Tang, Liansheng Larry; Zhou, Xiao-Hua

2012-01-01

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

Knowledge-Based Systems Approach to Wilderness Fire Management.

NASA Astrophysics Data System (ADS)

Saveland, James M.

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

Role of non-contrast balanced steady-state free precession megnetic resonance angiography compared to contrast-enhanced megnetic resonance angiography in diagnosing renal artery stenosis: a meta-analysis.

PubMed

Tao, Weijing; Shen, Yang; Guo, Lili; Bo, Genji

2014-01-01

Balanced steady-state free precession MR angiography (b-SSFP MRA) has shown great promise in diagnosing renal artery stenosis (RAS) as a non-contrast MR angiography (NC-MRA) method. However, results from related studies are inconsistent. The purpose of this meta-analysis was to assess the accuracy of b-SSFP MRA compared to contrast-enhanced MR angiography (CE-MRA) in diagnosing RAS. English and Chinese studies that were published prior to September 4, 2013 and that assessed b-SSFP MRA diagnostic performance in RAS patients were reviewed. Quality of the literature was assessed independently by two observers. The statistical analysis was adopted by the software of Meta-Disc version 1.4. Using the heterogeneity test, a statistical effect model was chosen to calculate different pooled weighted values. The receiver operator characteristic (ROC) space and Spearman correlation coefficient were to explore threshold effect. Sensitivity analysis and the publication bias were performed to demonstrate if the pooled estimates were stable and reliable. We produced forest plots to calculate the pooled values and corresponding 95% confidence interval (CI) of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and constructed a summary receiver operating characteristic curve (SROC) to calculate the area under the curve (AUC). A total of 10 high quality articles were used in this meta-analysis. The studies showed a high degree of heterogeneity. The "shoulder-arm" shape in the ROC plot and the Spearman correlation coefficient between the log(SEN) and log(1-SPE) suggested that there was a threshold effect. Sensitivity analysis demonstrated that the actual combined effect size was equal to the theoretical combined effect size. The publication bias was low after quality evaluation of the literature and the construction of a funnel plot. The pooled sensitivity was 0.88 (95% CI, 0.83-0.91) and pooled specificity was 0.94 (95% CI, 0.93-0.95); pooled PLR was 14.57 (95% CI, 9.78-21.71]) and pooled NLR was 0.15 (95% CI, 0.11-0.20). The AUC was 0.964 3. In contrast to CE-MRA, the b-SSFP MRA is more accurate in diagnosing RAS, and may be able to replace other diagnostic methods in patients with renal insufficiency.

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

PubMed

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

2018-05-01

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

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.

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

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

PubMed

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

2009-10-15

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

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

PubMed Central

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

2009-01-01

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

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

PubMed

Zhang, Ying; Alonzo, Todd A

2016-11-01

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

Proximal caries detection: Sirona Sidexis versus Kodak Ektaspeed Plus.

PubMed

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

2005-01-01

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

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

PubMed

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

2017-01-01

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

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.

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

ERIC Educational Resources Information Center

Broder, Arndt; Schutz, Julia

2009-01-01

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

Variations in Recollection: The Effects of Complexity on Source Recognition

ERIC Educational Resources Information Center

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

2011-01-01

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

Low uric acid level increases the risk of infectious mononucleosis and this effect is more pronounced in women

PubMed Central

Zhang, Li; Zhou, Pingping; Meng, Zhaowei; Gong, Lu; Pang, Chongjie; Li, Xue; Jia, Qiang; Tan, Jian; Liu, Na; Hu, Tianpeng; Zhang, Qing; Jia, Qiyu; Song, Kun

2017-01-01

Infectious mononucleosis (IM) due to Epstein-Barr virus infection is common. Uric acid (UA) is an important endogenous antioxidant. To the best of our knowledge, the association between UA and IM has not been comprehensively investigated to date. The aim of the present study was to investigate this association in Chinese patients. A total of 95 patients (47 men and 48 women) with IM were recruited, along with 95 healthy controls. Clinical data were classified by patient sex. Receiver operating characteristic (ROC) curve analysis was adopted to determine the cut-off values of UA for IM diagnosis and prediction. Crude and adjusted odds ratios (ORs) of UA for IM were analyzed by binary logistic regression. The UA levels were significantly lower in IM patients compared with those in controls. In addition, UA levels in men were significantly higher compared with those in women. The ROC curve demonstrated good diagnostic and predictive values of UA for IM in both sexes. The UA cut-off values were 326.00 and 243.50 µmol/l for diagnosing IM in men and women, respectively, with a diagnostic accuracy of 76.596 and 80.208%, respectively. Binary logistic regression analysis revealed a significant risk of IM in the low UA quartiles in both sexes. Following adjustments, the ORs even increased. Women with low UA levels appeared to be more susceptible to IM. For example, the crude ORs in quartile 1 were 24.000 and 52.500 for men and women, respectively, and the respective adjusted ORs were 31.437 and 301.746 (all P<0.01). To the best of our knowledge, the present study is the first to demonstrate the inverse association between UA and IM, suggesting a progressive decrease of antioxidant reserve in IM. Moreover, low UA was suggestive of IM, particularly in women. PMID:29285370

The diagnostic effect of serum miR-196b as biomarker in colorectal cancer

PubMed Central

Xu, Chunjie; Gu, Lei

2017-01-01

The microRNA, miR-196b, serves a role in normal cell differentiation, proliferation and tumorigenesis of different types of cancer. The aim of the present study was to explore the serum expression of miR-196b in colorectal cancer (CRC) and its correlation with clinicopathological features. Sera samples were obtained from 103 patients with CRC, 51 patients with colorectal adenoma (Ad) and 100 healthy individuals for the present study. The serum expression of miR-196b in sera samples of the three cohorts was detected using reverse transcription-quantitative polymerase chain reaction. The diagnostic value of miR-196b in the serum of the patients with CRC was evaluated by receiver operating characteristic (ROC) curve and survival analysis, using the Kaplan-Meier method, which was performed with the data from a 5-year follow-up. The expression of miR-196b in the serum of patients with CRC was significantly higher compared with that in Ad patients or healthy individuals (all P<0.001), and the overexpression of serum miR-196b was clearly associated with lymph node invasion, differentiation, and the tumor-lymph nodes-metastasis stage (all P<0.05). ROC curve analysis demonstrated that, comparing patients with CRC with healthy individuals, the area under the curve of serum miR-196b was 0.8135, and its specificity and sensitivity were 63 and 87.38%, respectively, at a diagnostic threshold of −4.785. Patients with CRC of miR-196b-high status had shorter overall survival and disease-free survival rates compared with those of miR-196b-low status. In conclusion, the results of the present study demonstrated that serum miR-196b is upregulated in CRC, and may have an application as a diagnostic and prognostic biomarker for patients with CRC. PMID:28123705

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.

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

PubMed

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

2018-06-01

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

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

PubMed

Koopmeiners, Joseph S; Feng, Ziding

2011-01-01

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

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

PubMed Central

Koopmeiners, Joseph S.; Feng, Ziding

2013-01-01

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

The global nonmethane reactive organic carbon budget: A modeling perspective

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Neyman-Pearson classification algorithms and NP receiver operating characteristics

PubMed Central

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

2018-01-01

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

Neyman-Pearson classification algorithms and NP receiver operating characteristics.

PubMed

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

2018-02-01

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

Bioelectrical impedance analysis-derived phase angle at admission as a predictor of 90-day mortality in intensive care patients.

PubMed

Stapel, Sandra N; Looijaard, Wilhelmus G P M; Dekker, Ingeborg M; Girbes, Armand R J; Weijs, Peter J M; Oudemans-van Straaten, Heleen M

2018-05-11

A low bioelectrical impedance analysis (BIA)-derived phase angle (PA) predicts morbidity and mortality in different patient groups. An association between PA and long-term mortality in ICU patients has not been demonstrated before. The purpose of the present study was to determine whether PA on ICU admission independently predicts 90-day mortality. This prospective observational study was performed in a mixed university ICU. BIA was performed in 196 patients within 24 h of ICU admission. To test the independent association between PA and 90-day mortality, logistic regression analysis was performed using the APACHE IV predicted mortality as confounder. The optimal cutoff value of PA for mortality prediction was determined by ROC curve analysis. Using this cutoff value, patients were categorized into low or normal PA group and the association with 90-day mortality was tested again. The PA of survivors was higher than of the non-survivors (5.0° ± 1.3° vs. 4.1° ± 1.2°, p < 0.001). The area under the ROC curve of PA for 90-day mortality was 0.70 (CI 0.59-0.80). PA was associated with 90-day mortality (OR = 0.56, CI: 0.38-0.77, p = 0.001) on univariate logistic regression analysis and also after adjusting for BMI, gender, age, and APACHE IV on multivariable logistic regression (OR = 0.65, CI: 0.44-0.96, p = 0.031). A PA < 4.8° was an independent predictor of 90-day mortality (adjusted OR = 3.65, CI: 1.34-9.93, p = 0.011). Phase angle at ICU admission is an independent predictor of 90-day mortality. This biological marker can aid in long-term mortality risk assessment of critically ill patients.

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

PubMed

Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

2017-12-01

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

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.

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

PubMed

Hantouche, E G; Demonfaucon, C

2008-12-01

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

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

PubMed

1990-09-10

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-23

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

Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

NASA Astrophysics Data System (ADS)

Izadyyazdanabadi, Mohammadhassan; Belykh, Evgenii; Martirosyan, Nikolay; Eschbacher, Jennifer; Nakaji, Peter; Yang, Yezhou; Preul, Mark C.

2017-03-01

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.

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.

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.

Non-invasive fibrosis tests are correlated with necroinflammatory actvity of liver in patients with chronic hepatitis B.

PubMed

Ozyalvacli, G; Kucukbayrak, A; Kurt, M; Gurel, K; Gunes, O; Ustun, C; Akdeniz, H

2014-01-01

The gold standarda method used for assessing necroinflammatory activity and fibrosis in the liver is a liver biopsy which has many disadvantages. Therefore, many investigators have been trying to develop non-invasive tests for predicting liver fibrosis score (LFS) of these patients. The aim of this study is to describe the relationship between certain non-invasive fibrosis markers with LFS and histological activity index (HAI) detected histopathologically by liver biopsy in chronic hepatitis B patients. A total of 54 patients who had undergone a liver biopsy with the diagnosis of chronic HBV infection were included in the study. Ishak scoring was used for the evaluation of liver fibrosis, and a modified Knodell HAI was used for demonstration of necroinflammation. In this study, non-invasive fibrosis tests were calculated as described in previous studies. Histological acitivity index was positively correlated with age, age/platelet index, cirrhosis discriminant score (CDS), AST/platelet ratio index (APRI), AST/platelet/GGT/AFP index (APGA), fibro-quotient (Fibro-Q), Goteburg University Cirrhosis Index (Guci), and Platelet/Age/Phosphatase/AFP/AST index (PAPAS). When divided into two groups according to HAI, Guci and APGA were found significantly different both in >4 and >4 HAI groups than the other group. In ROC analysis performed for LFS; PAPAS, APGA, FFI and APRI were the markers having the highest AUC levels, and in ROC analysis performed for HAI; Guci, APRI and APGA were the markers with the highest AUC levels. APRI, APGA and GUCI tests may be helpful in prediction of necroinflammatory scores in the liver.

Asperger syndrome and schizophrenia: Overlap of self-reported autistic traits using the Autism-spectrum Quotient (AQ).

PubMed

Lugnegård, Tove; Hallerbäck, Maria Unenge; Gillberg, Christopher

2015-05-01

In clinical practice, the differential diagnosis of Asperger syndrome (AS) versus schizophrenia can be a challenge. Some self-report instruments-such as the Autism-spectrum Quotient (AQ)-have been portrayed as proxies for the diagnosis of AS. However, it has not been demonstrated to what extent autistic traits-as measured by the AQ-separate AS from schizophrenia. To examine the AS-schizophrenia discriminating ability of the AQ. The AQ is a 50-item self-administered questionnaire (with score range 0-50) for measuring "autistic traits" in adults. Here, it was completed by 136 individuals: 36 with schizophrenic psychosis, 51 with AS and 49 non-clinical comparison cases. A receiver operating characteristic (ROC) analysis for the total AQ score was performed to examine the discriminating power of the instrument. Both individuals with schizophrenia and individuals with AS scored significantly higher on AQ than the non-clinical group. The mean total AQ score (± standard deviation) of the AS group (26.7 ± 8.9; range 9-44) was significantly higher than that of the schizophrenia group (22.7 ± 6.2; range 10-35) (P = 0.041). However, when using the full Likert scale for scoring, the difference did not reach significance. In the ROC analysis of total AQ scores for AS versus schizophrenia, the area under the curve (AUC) was 0.65 (P = 0.02). Although mean AQ scores separated AS and schizophrenia at a group comparison level, significant overlap of AQ scores across the two diagnostic groups clearly reduces the discriminating power of the AQ in the separation of schizophrenia from AS.

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.

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.

Bone marrow with diffuse tumor infiltration in patients with lymphoproliferative diseases: dynamic gadolinium-enhanced MR imaging.

PubMed

Rahmouni, Alain; Montazel, Jean-Luc; Divine, Marine; Lepage, Eric; Belhadj, Karim; Gaulard, Philippe; Bouanane, Mohamed; Golli, Mondher; Kobeiter, Hicham

2003-12-01

To evaluate gadolinium enhancement of bone marrow in patients with lymphoproliferative diseases and diffuse bone marrow involvement. Dynamic contrast material-enhanced magnetic resonance (MR) imaging of the thoracolumbar spine was performed in 42 patients with histologically proved diffuse bone marrow involvement and newly diagnosed myeloma (n = 31), non-Hodgkin lymphoma (n = 8), or Hodgkin disease (n = 3). The maximum percentage of enhancement (Emax), enhancement slope, and enhancement washout were determined from enhancement time curves (ETCs). A three-grade system for scoring bone marrow involvement was based on the percentage of neoplastic cells in bone marrow samples. Quantitative ETC values for the 42 patients were compared with ETC values for healthy subjects and with grades of bone marrow involvement by using mean t test comparisons. Receiver operating characteristic (ROC) analysis was conducted by comparing Emax values between patients with and those without bone marrow involvement. Baseline and follow-up MR imaging findings were compared in nine patients. Significant differences in Emax (P <.001), slope (P <.001), and washout (P =.005) were found between subjects with normal bone marrow and patients with diffuse bone marrow involvement. ROC analysis results showed Emax values to have a diagnostic accuracy of 99%. Emax, slope, and washout values increased with increasing bone marrow involvement grade. The mean Emax increased from 339% to 737%. Contrast enhancement decreased after treatment in all six patients who responded to treatment but not in two of three patients who did not respond to treatment. Dynamic contrast-enhanced MR images can demonstrate increased bone marrow enhancement in patients with lymphoproliferative diseases and marrow involvement.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

PubMed

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

2015-05-01

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

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

PubMed

Wunderlich, Adam; Abbey, Craig K

2013-11-01

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

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

PubMed

Linden, Ariel

2006-04-01

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

Receiver Operating Characteristic Curve Analysis of Beach Water Quality Indicator Variables

PubMed Central

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

2003-01-01

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

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

PubMed

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

2011-03-15

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

Epidemiology, Causes and Prevention of Car Rollover Crashes with Ejection

PubMed Central

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

2014-01-01

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

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

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.

Comparison of the results of intradermal test reactivity and serum allergen-specific IgE measurement for Malassezia pachydermatis in atopic dogs.

PubMed

Oldenhoff, Willam E; Frank, Glenn R; DeBoer, Douglas J

2014-12-01

Malassezia pachydermatis is part of the normal flora of canine skin. Malassezia hypersensitivity is recognized as a trigger for clinical signs of atopic dermatitis (AD) in some dogs. Determinations of Malassezia hypersensitivity are often made with intradermal testing (IDT), which may have limited availability in a first-opinion veterinary practice. The purpose of this study was to compare immediate IDT reactivity to M. pachydermatis with results of an enzyme-linked immunosorbent assay (ELISA) designed to detect anti-Malassezia IgE. Eighty-four dogs with a clinical diagnosis of AD. Multi-allergen IDT was performed on all dogs. Serum testing for allergen-specific IgE against a panel of common environmental allergens and M. pachydermatis was performed by ELISA using the FcεRIα receptor fragment as a detection reagent, with results reported as adjusted optical density (OD). A receiver operating characteristic (ROC) curve was used to analyse the results of the two tests. The median adjusted OD of the anti-Malassezia IgE ELISA for dogs reactive and nonreactive to M. pachydermatis on IDT was 0.137 and 0.024, respectively. Analysis of the ROC curve suggested a cut-off point for the anti-Malassezia ELISA that yielded a sensitivity of 77.0% and a specificity of 89% relative to IDT results. Substantial agreement was demonstrated between IDT reactivity and anti-Malassezia IgE as detected by the FcεRIα receptor reagent. Although correlation with a clinical diagnosis of Malassezia dermatitis was not attempted in this study, the results indicate that the ELISA may be used to demonstrate the presence of immediate-type Malassezia hypersensitivity in dogs with AD. © 2014 ESVD and ACVD.

MRI differentiation of low-grade from high-grade appendicular chondrosarcoma.

PubMed

Douis, Hassan; Singh, Leanne; Saifuddin, Asif

2014-01-01

To identify magnetic resonance imaging (MRI) features which differentiate low-grade chondral lesions (atypical cartilaginous tumours/grade 1 chondrosarcoma) from high-grade chondrosarcomas (grade 2, grade 3 and dedifferentiated chondrosarcoma) of the major long bones. We identified all patients treated for central atypical cartilaginous tumours and central chondrosarcoma of major long bones (humerus, femur, tibia) over a 13-year period. The MRI studies were assessed for the following features: bone marrow oedema, soft tissue oedema, bone expansion, cortical thickening, cortical destruction, active periostitis, soft tissue mass and tumour length. The MRI-features were compared with the histopathological tumour grading using univariate, multivariate logistic regression and receiver operating characteristic curve (ROC) analyses. One hundred and seventy-nine tumours were included in this retrospective study. There were 28 atypical cartilaginous tumours, 79 grade 1 chondrosarcomas, 36 grade 2 chondrosarcomas, 13 grade 3 chondrosarcomas and 23 dedifferentiated chondrosarcomas. Multivariate analysis demonstrated that bone expansion (P = 0.001), active periostitis (P = 0.001), soft tissue mass (P < 0.001) and tumour length (P < 0.001) were statistically significant differentiating factors between low-grade and high-grade chondral lesions with an area under the ROC curve of 0.956. On MRI, bone expansion, active periostitis, soft tissue mass and tumour length can reliably differentiate high-grade chondrosarcomas from low-grade chondral lesions of the major long bones. • Accurate differentiation of low-grade from high-grade chondrosarcomas is essential before surgery • MRI can reliably differentiate high-grade from low-grade chondrosarcomas of long bone • Differentiating features are bone expansion, periostitis, soft tissue mass and tumour length • Presence of these four MRI features demonstrated a diagnostic accuracy (AUC) of 95.6 % • The findings may result in more accurate diagnosis before definitive surgery.

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.

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

PubMed

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

2014-09-01

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

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

PubMed

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

2018-06-01

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

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

PubMed

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

2015-04-01

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

Biomarker candidates for the detection of an infectious etiology of febrile neutropenia.

PubMed

Richter, Martin E; Neugebauer, Sophie; Engelmann, Falco; Hagel, Stefan; Ludewig, Katrin; La Rosée, Paul; Sayer, Herbert G; Hochhaus, Andreas; von Lilienfeld-Toal, Marie; Bretschneider, Tom; Pausch, Christine; Engel, Christoph; Brunkhorst, Frank M; Kiehntopf, Michael

2016-04-01

Infections and subsequent septicemia are major complications in neutropenic patients with hematological malignancies. Here, we identify biomarker candidates for the early detection of an infectious origin, and monitoring of febrile neutropenia (FN). Proteome, metabolome, and conventional biomarkers from 20 patients with febrile neutropenia without proven infection (FNPI) were compared to 28 patients with proven infection, including 17 patients with bacteremia. Three peptides (mass to charge ratio 1017.4-1057.3; p-values 0.011-0.024), six proteins (mass to charge ratio 6881-17,215; p-values 0.002-0.004), and six phosphatidylcholines (p-values 0.007-0.037) were identified that differed in FNPI patients compared to patients with infection or bacteremia. Seven of these marker candidates discriminated FNPI from infection at fever onset with higher sensitivity and specificity (ROC-AUC 0.688-0.824) than conventional biomarkers i.e., procalcitonin, C-reactive protein, or interleukin-6 (ROC-AUC 0.535-0.672). In a post hoc analysis, monitoring the time course of four lysophosphatidylcholines, threonine, and tryptophan allowed for discrimination of patients with or without resolution of FN (ROC-AUC 0.648-0.919) with higher accuracy compared to conventional markers (ROC-AUC 0.514-0.871). Twenty-one promising biomarker candidates for the early detection of an infectious origin or for monitoring the course of FN were found which might overcome known shortcomings of conventional markers.

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.

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.

Comparison of rat epidermal keratinocyte organotypic culture (ROC) with intact human skin: lipid composition and thermal phase behavior of the stratum corneum.

PubMed

Pappinen, Sari; Hermansson, Martin; Kuntsche, Judith; Somerharju, Pentti; Wertz, Philip; Urtti, Arto; Suhonen, Marjukka

2008-04-01

The present report is a part of our continuing efforts to explore the utility of the rat epidermal keratinocyte organotypic culture (ROC) as an alternative model to human skin in transdermal drug delivery and skin irritation studies of new chemical entities and formulations. The aim of the present study was to compare the stratum corneum lipid content of ROC with the corresponding material from human skin. The lipid composition was determined by thin-layer chromatography (TLC) and mass-spectrometry, and the thermal phase transitions of stratum corneum were studied by differential scanning calorimetry (DSC). All major lipid classes of the stratum corneum were present in ROC in a similar ratio as found in human stratum corneum. Compared to human skin, the level of non-hydroxyacid-sphingosine ceramide (NS) was increased in ROC, while alpha-hydroxyacid-phytosphingosine ceramide (AP) and non-hydroxyacid-phytosphingosine ceramides (NP) were absent. Also some alterations in fatty acid profiles of ROC ceramides were noted, e.g., esterified omega-hydroxyacid-sphingosine contained increased levels of oleic acid instead of linoleic acid. The fraction of lipids covalently bound to corneocyte proteins was distinctly lower in ROC compared to human skin, in agreement with the results from DSC. ROC underwent a lipid lamellar order to disorder transition (T2) at a slightly lower temperature (68 degrees C) than human skin (74 degrees C). These differences in stratum corneum lipid composition and the thermal phase transitions may explain the minor differences previously observed in drug permeation between ROC and human skin.

Variations in recollection: the effects of complexity on source recognition.

PubMed

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

2011-07-01

Whether recollection is a threshold or signal detection process is highly controversial, and the controversy has centered in part on the shape of receiver operating characteristics (ROCs) and z-transformed ROCs (zROCs). U-shaped zROCs observed in tests thought to rely heavily on recollection, such as source memory tests, have provided evidence in favor of the threshold assumption, but zROCs are not always as U-shaped as threshold theory predicts. Source zROCs have been shown to become more linear when the contribution of familiarity to source discriminations is increased, and this may account for the existing results. However, another way in which source zROCs may become more linear is if the recollection threshold begins to break down and recollection becomes more graded and Gaussian. We tested the "graded recollection" account in the current study. We found that increasing stimulus complexity (i.e., changing from single words to sentences) or increasing source complexity (i.e., changing the sources from audio to videos of speakers) resulted in flatter source zROCs. In addition, conditions expected to reduce recollection (i.e., divided attention and amnesia) had comparable effects on source memory in simple and complex conditions, suggesting that differences between simple and complex conditions were due to differences in the nature of recollection, rather than differences in the utility of familiarity. The results suggest that under conditions of high complexity, recollection can appear more graded, and it can produce curved ROCs. The results have implications for measurement models and for current theories of recognition memory.

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

PubMed Central

2011-01-01

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

Required Operational Capability, USMC-ROC-LOG-216.3.5 for the Ration, Cold Weather.

DTIC Science & Technology

1987-05-06

in operations or training in an arctic environment . b. Organizational Concept. The ration , cold weather will be issued in accordance with established...all services. 2 ROC-ARCTIC 7. TECHNICAL FEASIBILITY AND ENERGY/ ENVIRONMENTAL IMPACTS a. Technical Feasibility. The risk of developing the ration ...r -A1833 963 REQUIRED OPERATIONAL CAPABILITY USMC-ROC-LOG-21635 FOR 1t/1 THE RATION COLD WEATHER(U) MARINE CORPS WASHINGTON DC 86 MAY 87 USMC-ROC-LOG

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

Class-specific Error Bounds for Ensemble Classifiers

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

Prenger, R; Lemmond, T; Varshney, K

2009-10-06

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

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

PubMed Central

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

2010-01-01

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

Rat epidermal keratinocyte organotypic culture (ROC) compared to human cadaver skin: the effect of skin permeation enhancers.

PubMed

Pappinen, Sari; Tikkinen, Sanna; Pasonen-Seppänen, Sanna; Murtomäki, Lasse; Suhonen, Marjukka; Urtti, Arto

2007-03-01

The objective of this study was to evaluate the response of the rat epidermal keratinocyte organotypic culture (ROC) to permeation enhancers, and to compare these responses to those in human cadaver skin. Different concentrations of two mixtures for enhancing permeation were investigated, sodium dodecyl sulfate:phenyl piperazine and methyl pyrrolidone:dodecyl pyridinium chloride, using skin impedance spectroscopy and two experimental compounds, the lipophilic corticosterone and the hydrophilic sucrose. The chemical irritation effects of the formulations were evaluated based on leakage of lactate dehydrogenase enzyme (LDH) and cellular morphological perturbation. This study provides evidence for direct correlations of permeation/permeation, impedance/impedance and permation/impedance between the culture model and human skin. The only exception was the enhancer induced permeation of sucrose which was 1-40-fold higher in ROC compared to human skin, reflecting the more disordered lipid organization in stratum corneum and consequently the greater number of polar pathways. LDH leakage and cellular morphology indicated that it was possible to differentiate between safe permeation enhancers from irritating agents. This is not only the first study to have compared the enhancer effects on a cultured skin model with human skin, but also it has demonstrated enhancer induced irritation using an artificial skin model.

How Nonrecidivism Affects Predictive Accuracy: Evidence from a Cross-Validation of the Ontario Domestic Assault Risk Assessment (ODARA)

ERIC Educational Resources Information Center

Hilton, N. Zoe; Harris, Grant T.

2009-01-01

Prediction effect sizes such as ROC area are important for demonstrating a risk assessment's generalizability and utility. How a study defines recidivism might affect predictive accuracy. Nonrecidivism is problematic when predicting specialized violence (e.g., domestic violence). The present study cross-validates the ability of the Ontario…

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

NASA Astrophysics Data System (ADS)

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

1999-05-01

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

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.

Segmentation and feature extraction of retinal vascular morphology

NASA Astrophysics Data System (ADS)

Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

2017-02-01

Analysis of retinal fundus images is essential for physicians, optometrists and ophthalmologists in the diagnosis, care and treatment of patients. The first step of almost all forms of automated fundus analysis begins with the segmentation and subtraction of the retinal vasculature, while analysis of that same structure can aid in the diagnosis of certain retinal and cardiovascular conditions, such as diabetes or stroke. This paper investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using DRIVE, a database of fundus images. The result of the network with the application of a confidence threshold was slightly below the 2nd observer and gold standard, with an accuracy of 0.9419 and ROC of 0.9707. The output of the network with on post-processing boasted the highest sensitivity found in the literature with a score of 0.9568 and a good ROC score of 0.9689. The high sensitivity of the system makes it suitable for longitudinal morphology assessments, disease detection and other similar tasks.

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

Kallner, Anders

2017-01-01

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

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.

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

PubMed

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

2013-08-01

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

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

Ka-Band Link Study and Analysis for a Mars Hybrid RF/Optical Software Defined Radio

NASA Technical Reports Server (NTRS)

Zeleznikar, Daniel J.; Nappier, Jennifer M.; Downey, Joseph A.

2014-01-01

The integrated radio and optical communications (iROC) project at the NASA Glenn Research Center (GRC) is investigating the feasibility of a hybrid RF and optical communication subsystem for future deep space missions. The hybrid communications subsystem enables the advancement of optical communications while simultaneously mitigating the risk of infusion by combining an experimental optical transmitter and telescope with a reliable Ka-band RF transmitter and antenna. The iROC communications subsystem seeks to maximize the total data return over the course of a potential 2-year mission in Mars orbit beginning in 2021. Although optical communication by itself offers potential for greater data return over RF, the reliable Ka-band link is also being designed for high data return capability in this hybrid system. A daily analysis of the RF link budget over the 2-year span is performed to optimize and provide detailed estimates of the RF data return. In particular, the bandwidth dependence of these data return estimates is analyzed for candidate waveforms. In this effort, a data return modeling tool was created to analyze candidate RF modulation and coding schemes with respect to their spectral efficiency, amplifier output power back-off, required digital to analog conversion (DAC) sampling rates, and support by ground receivers. A set of RF waveforms is recommended for use on the iROC platform.

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

PubMed

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

2016-09-24

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

A novel multi-epitope recombined protein for diagnosis of human brucellosis.

PubMed

Yin, Dehui; Li, Li; Song, Xiuling; Li, Han; Wang, Juan; Ju, Wen; Qu, Xiaofeng; Song, Dandan; Liu, Yushen; Meng, Xiangjun; Cao, Hongqian; Song, Weiyi; Meng, Rizeng; Liu, Jinhua; Li, Juan; Xu, Kun

2016-05-21

In epidemic regions of the world, brucellosis is a reemerging zoonosis with minimal mortality but is a serious public hygiene problem. Currently, there are various methods for brucellosis diagnosis, however few of them are available to be used to diagnose, especially for serious cross-reaction with other bacteria. To overcome this disadvantage, we explored a novel multi-epitope recombinant protein as human brucellosis diagnostic antigen. We established an indirect enzyme-linked immunosorbent assay (ELISA) based on this recombinant protein. 248 sera obtained from three different groups including patients with brucellosis (146 samples), non-brucellosis patients (82 samples), and healthy individuals (20 samples) were tested by indirect ELISA. To evaluate the assay, a receiver-operating characteristic (ROC) analysis and immunoblotting were carried out using these characterized serum samples. For this test, the area under the ROC curve was 0.9409 (95 % confidence interval, 0.9108 to 0.9709), and a sensitivity of 88.89 % and a specificity of 85.54 % was given with a cutoff value of 0.3865 from this ROC analysis. The Western blot results indicate that it is feasible to differentiate human brucellosis and non-brucellosis with the newly established method based on this recombinant protein. Our results obtained high diagnostic accuracy of the ELISA assay which encourage the use of this novel recombinant protein as diagnostic antigen to implement serological diagnosis of brucellosis.

Rocking at 81 and Rolling at 34: ROC Cut-Off Scores for the Negative Acts Questionnaire–Revised in Serbia

PubMed Central

Petrović, Ivana B.; Vukelić, Milica; Čizmić, Svetlana

2017-01-01

Researchers are still searching for the ways to identify different categories of employees according to their exposure to negative acts and psychological experience of workplace bullying. We followed Notelaers and Einarsen’s application of the ROC analysis to determine the NAQ-R cut-off scores applying a “lower” and “higher” threshold. The main goal of this research was to develop and test different gold standards of personal and organizational relevance in determining the NAQ-R cut-off scores in a specific cultural and economic context of Serbia. Apart from combining self-labeling as a victim with self-perceived health, the objectives were to test the gold standards developed as a combination of self-labeling with life satisfaction, self-labeling with intention to leave and a complex gold standard based on self-labeling, self-perceived health, life satisfaction and intention to leave taken together. The ROC analysis on Serbian workforce data supports applying of different gold standards. For identifying employees in a preliminary stage of bullying, the most applicable was the gold standard based on self-labeling and intention to leave (score 34 and higher). The most accurate identification of victims could be based on the most complex gold standard (score 81 and higher). This research encourages further investigation of gold standards in different cultures. PMID:28119652

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

Validation of a Brief PTSD Scale for Clients with Severe Mental Illnesses

ERIC Educational Resources Information Center

O'Hare, Thomas; Shen, Ce; Sherrer, Margaret

2012-01-01

Trauma and Posttraumatic Stress Disorder (PTSD) are more common in severe mental illnesses (SMI) clients than in the general population, yet brief screens for detecting probable PTSD in SMI clients are nonexistent. In a two-part study, the authors used correlation analysis and receiver operating characteristics (ROC) analysis to develop and…

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.

Networked Operations of Hybrid Radio Optical Communications Satellites

NASA Technical Reports Server (NTRS)

Hylton, Alan; Raible, Daniel

2014-01-01

In order to address the increasing communications needs of modern equipment in space, and to address the increasing number of objects in space, NASA is demonstrating the potential capability of optical communications for both deep space and near-Earth applications. The Integrated Radio Optical Communications (iROC) is a hybrid communications system that capitalizes on the best of both the optical and RF domains while using each technology to compensate for the other's shortcomings. Specifically, the data rates of the optical links can be higher than their RF counterparts, whereas the RF links have greater link availability. The focus of this paper is twofold: to consider the operations of one or more iROC nodes from a networking point of view, and to suggest specific areas of research to further the field. We consider the utility of Disruption Tolerant Networking (DTN) and the Virtual Mission Operation Center (VMOC) model.

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

PubMed

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

2015-02-10

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

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A study on the relationship between muscle function, functional mobility and level of physical activity in community-dwelling elderly.

PubMed

Garcia, Patrícia A; Dias, João M D; Dias, Rosângela C; Santos, Priscilla; Zampa, Camila C

2011-01-01

to evaluate the relationship between lower extremity muscle function, calf circumference (CC), handgrip strength (HG), functional mobility and level of physical activity among age groups (65-69, 70-79, 80+) of older adults (men and women) and to identify the best parameter for screening muscle function loss in the elderly. 81 community-dwelling elderly (42 women and 39 men) participated. Walking speed (Multisprint Kit), HG (Jamar dynamometer), hip, knee and ankle muscle function (Biodex isokinetic dynamometer), level of physical activity (Human Activity Profile) and CC (tape measure) were evaluated. ANOVA, Pearson correlation and ROC curves were used for statistical analysis. Dominant CC (34.9±3 vs 37.7±3.6), habitual (1.1±0.2 vs 1.2±0.2) and fast (1.4±0.3 vs 1.7±0.3) walking speed, HG (23.8±7.5 vs 31.8±10.3), average peak torque and average hip, knee and ankle power (p<0.05) were lower for the 80+ group than for the 65-69 year-olds. There were no differences in physical activity level among age groups. Moderate significant correlations were found between muscle function parameters, walking speed and HG; a fair degree of relationship was found between muscle function parameters, CC and level of physical activity (p<0.05). The ROC curve analysis suggested a cutoff point of 14.51 Kgf for screening muscle function loss in elderly women (p=0.03). This study demonstrated an association between muscle function, HG and fast walking speed, a decrease in these parameters with age and the possibility of using HG to screen for muscle function of the lower extremities.

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

PubMed

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

2017-04-01

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

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.

Proposal of a Mediterranean Diet Serving Score

PubMed Central

Monteagudo, Celia; Mariscal-Arcas, Miguel; Rivas, Ana; Lorenzo-Tovar, María Luisa; Tur, Josep A.; Olea-Serrano, Fátima

2015-01-01

Background and Aims Numerous studies have demonstrated a relationship between Mediterranean Diet (MD) adherence and the prevention of cardiovascular diseases, cancer, and diabetes, etc. The study aim was to validate a novel instrument to measure MD adherence based on the consumption of food servings and food groups, and apply it in a female population from southern Spain and determining influential factors. Methods and Results The study included 1,155 women aged 12-83 yrs, classified as adolescents, adults, and over-60-yr-olds. All completed a validated semi-quantitative food frequency questionnaire (FFQ). The Mediterranean Dietary Serving Score (MDSS) is based on the latest update of the Mediterranean Diet Pyramid, using the recommended consumption frequency of foods and food groups; the MDSS ranges from 0 to 24. The discriminative power or correct subject classification capacity of the MDSS was analyzed with the Receiver Operating Characteristic (ROC) curve, using the MDS as reference method. Predictive factors for higher MDSS adherence were determined with a logistic regression model, adjusting for age. According to ROC curve analysis, MDSS evidenced a significant discriminative capacity between adherents and non-adherents to the MD pattern (optimal cutoff point=13.50; sensitivity=74%; specificity=48%). The mean MDSS was 12.45 (2.69) and was significantly higher with older age (p<0.001). Logistic regression analysis showed highest MD adherence by over 60-year-olds with low BMI and no habit of eating between meals. Conclusions The MDSS is an updated, easy, valid, and accurate instrument to assess MD adherence based on the consumption of foods and food groups per meal, day, and week. It may be useful in future nutritional education programs to prevent the early onset of chronic non-transmittable diseases in younger populations. PMID:26035442

The application of statistical parametric mapping to 123I-FP-CIT SPECT in dementia with Lewy bodies, Alzheimer's disease and Parkinson's disease.

PubMed

Colloby, Sean J; O'Brien, John T; Fenwick, John D; Firbank, Michael J; Burn, David J; McKeith, Ian G; Williams, E David

2004-11-01

Dopaminergic loss can be visualised using (123)I-FP-CIT single photon emission computed tomography (SPECT) in several disorders including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Most previous SPECT studies have adopted region of interest (ROI) methods for analysis, which are subjective and operator-dependent. The purpose of this study was to investigate differences in striatal binding of (123)I-FP-CIT SPECT using the automated technique of statistical parametric mapping (SPM99) in subjects with DLB, Alzheimer's disease (AD), PD and healthy age-matched controls. This involved spatial normalisation of each subject's image to a customised template, followed by smoothing and intensity normalisation of each image to its corresponding mean occipital count per voxel. Group differences were assessed using a two-sample t test. Applying a height threshold of P

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.

Pre-Radiation Therapy Fluorine 18 Fluorodeoxyglucose PET Helps Identify Patients with Esophageal Cancer at High Risk for Radiation Pneumonitis.

PubMed

Castillo, Richard; Pham, Ngoc; Castillo, Edward; Aso-Gonzalez, Samantha; Ansari, Sobiya; Hobbs, Brian; Palacio, Diana; Skinner, Heath; Guerrero, Thomas M

2015-06-01

To examine the association between pre-radiation therapy (RT) fluorine 18 fluorodeoxyglucose (FDG) uptake and post-RT symptomatic radiation pneumonitis (RP). In accordance with the retrospective study protocol approved by the institutional review board, 228 esophageal cancer patients who underwent FDG PET/CT before chemotherapy and RT were examined. RP symptoms were evaluated by using the Common Terminology Criteria for Adverse Events, version 4.0, from the consensus of five clinicians. By using the cumulative distribution of standardized uptake values (SUVs) within the lungs, those values greater than 80%-95% of the total lung voxels were determined for each patient. The effect of pre-chemotherapy and RT FDG uptake, dose, and patient or treatment characteristics on RP toxicity was studied by using logistic regression. The study subjects were treated with three-dimensional conformal RT (n = 36), intensity-modulated RT (n = 135), or proton therapy (n = 57). Logistic regression analysis demonstrated elevated FDG uptake at pre-chemotherapy and RT was related to expression of RP symptoms. Study subjects with elevated 95% percentile of the SUV (SUV95) were more likely to develop symptomatic RP (P < .000012); each 0.1 unit increase in SUV95 was associated with a 1.36-fold increase in the odds of symptomatic RP. Receiver operating characteristic (ROC) curve analysis resulted in area under the ROC curve of 0.676 (95% confidence interval: 0.58, 0.77), sensitivity of 60%, and specificity of 71% at the 1.17 SUV95 threshold. CT imaging and dosimetric parameters were found to be poor predictors of RP symptoms. The SUV95, a biomarker of pretreatment pulmonary metabolic activity, was shown to be prognostic of symptomatic RP. Elevation in this pretreatment biomarker identifies patients at high risk for posttreatment symptomatic RP. RSNA, 2015

Use of neuromuscular blockers and neostigmine for general anesthesia and its association with neuraxial blockade

PubMed Central

Santos, Filipe Nadir Caparica; Braga, Angélica de Fátima de Assunção; Junqueira, Fernando Eduardo Feres; Bezerra, Rafaela Menezes; de Almeida, Felipe Ferreira; Braga, Franklin Sarmento da Silva; Carvalho, Vanessa Henriques

2017-01-01

Abstract This research aimed to assess the use of neuromuscular blockers (NMB) and its reversal, associated or not with neuraxial blockade, after general anesthesia. This retrospective study analyzed 1295 patients that underwent surgery with general anesthesia at Prof. Dr. José Aristodemo Pinotti Hospital in 2013. The study included patients aged >1 year, with complete, readable medical charts and anesthetic records. Rocuronium (ROC) was the most used NMB (96.7%), with an initial dose of 0.60 (0.52–0.74) mg/kg and total dose of 0.38 (0.27–0.53) mg/kg/h. In 24.3% of the cases, neuraxial blockade was associated with a significantly longer anesthesia (P < .001) than in cases without neuraxial block, regardless of technique (total intravenous (TIV) vs intravenous and inhalational (IV+IN)). In 71.9% of the cases, a single dose of NMB was used. Patients under TIV general anesthesia associated with neuraxial blockade had a lower total dose of ROC (mg/kg/h) in comparison with TIV GA alone (0.30 (0.23–0.39) and 0.42 (0.30–0.56) mg/kg/h, respectively, P < .001). The same was observed for patients under IV+IN GA (0.32 (0.23–0.41) and 0.43 (0.31–0.56) mg/kg/h, respectively, P < .001). The duration of anesthesia was longer according to increasing number of additional NMB doses (P < .001). Dose of neostigmine was 2.00 (2.00–2.00) mg or 29.41 (25.31–33.89) μg/kg. The interval between neostigmine and extubation was >30 minutes in 10.9% of cases. The most widely used NMB was ROC. Neuroaxial blockade (spinal or epidural) was significantly associated with reduced total dose of ROC (mg/kg/h) during general anesthesia, even in the absence of neuromuscular monitoring and regardless of general anesthetic technique chosen. In most cases, neostigmine was used to reverse neuromuscular block. The prolonged interval between neostigmine and extubation (>30 minutes) was neither associated with total doses of ROC or neostigmine, nor with the time of NMB administration. This study corroborates the important role of quantitative neuromuscular monitors and demonstrates that neuraxial blockade is associated with reduced total ROC dose. Further studies are needed to evaluate the possible role of neuraxial blockade in reducing the incidence of postoperative residual curarization. PMID:28658142

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2012-12-01

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

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study

PubMed Central

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Background: Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. Aim: The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. Settings and Design: A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Methods: Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. Statistical Analysis Used: ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Results: Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). Conclusion: CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas. PMID:29386780

[Predicting very early rebleeding after acute variceal bleeding based in classification and regression tree analysis (CRTA).].

PubMed

Altamirano, J; Augustin, S; Muntaner, L; Zapata, L; González-Angulo, A; Martínez, B; Flores-Arroyo, A; Camargo, L; Genescá, J

2010-01-01

Variceal bleeding (VB) is the main cause of death among cirrhotic patients. About 30-50% of early rebleeding is encountered few days after the acute episode of VB. It is necessary to stratify patients with high risk of very early rebleeding (VER) for more aggressive therapies. However, there are few and incompletely understood prognostic models for this purpose. To determine the risk factors associated with VER after an acute VB. Assessment and comparison of a novel prognostic model generated by Classification and Regression Tree Analysis (CART) with classic-used models (MELD and Child-Pugh [CP]). Sixty consecutive cirrhotic patients with acute variceal bleeding. CART analysis, MELD and Child-Pugh scores were performed at admission. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of the models. Very early rebleeding rate was 13%. Variables associated with VER were: serum albumin (p = 0.027), creatinine (p = 0.021) and transfused blood units in the first 24 hrs (p = 0.05). The area under the ROC for MELD, CHILD-Pugh and CART were 0.46, 0.50 and 0.82, respectively. The value of cut analyzed by CART for the significant variables were: 1) Albumin 2.85 mg/dL, 2) Packed red cells 2 units and 3) Creatinine 1.65 mg/dL the ABC-ROC. Serum albumin, creatinine and number of transfused blood units were associated with VER. A simple CART algorithm combining these variables allows an accurate predictive assessment of VER after acute variceal bleeding. Key words: cirrhosis, variceal bleeding, esophageal varices, prognosis, portal hypertension.

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

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

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

Diagnostic Performance of (18)F-Fluorodeoxyglucose in 162 Small Pulmonary Nodules Incidentally Detected in Subjects Without a History of Malignancy.

PubMed

Calcagni, Maria Lucia; Taralli, Silvia; Cardillo, Giuseppe; Graziano, Paolo; Ialongo, Pasquale; Mattoli, Maria Vittoria; Di Franco, Davide; Caldarella, Carmelo; Carleo, Francesco; Indovina, Luca; Giordano, Alessandro

2016-04-01

Solitary pulmonary nodule (SPN) still represents a diagnostic challenge. The aim of our study was to evaluate the diagnostic performance of (18)F-fluorodeoxyglucose positron emission tomography-computed tomography in one of the largest samples of small SPNs, incidentally detected in subjects without a history of malignancy (nonscreening population) and undetermined at computed tomography. One-hundred and sixty-two small (>0.8 to 1.5 cm) and, for comparison, 206 large nodules (>1.5 to 3 cm) were retrospectively evaluated. Diagnostic performance of (18)F-fluorodeoxyglucose visual analysis, receiver-operating characteristic (ROC) analysis for maximum standardized uptake value (SUVmax), and Bayesian analysis were assessed using histology or radiological follow-up as a golden standard. In 162 small nodules, (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.3) provided 72.6% and 77.4% sensitivity and 88.0% and 82.0% specificity, respectively. The prevalence of malignancy was 38%; Bayesian analysis provided 78.8% positive and 16.0% negative posttest probabilities of malignancy. In 206 large nodules (18)F-fluorodeoxyglucose visual and ROC analyses (SUVmax = 1.9) provided 89.5% and 85.1% sensitivity and 70.8% and 79.2% specificity, respectively. The prevalence of malignancy was 65%; Bayesian analysis provided 85.0% positive and 21.6% negative posttest probabilities of malignancy. In both groups, malignant nodules had a significant higher SUVmax (p < 0.0001) than benign nodules. Only in the small group, malignant nodules were significantly larger (p = 0.0054) than benign ones. (18)F-fluorodeoxyglucose can be clinically relevant to rule in and rule out malignancy in undetermined small SPNs, incidentally detected in nonscreening population with intermediate pretest probability of malignancy, as well as in larger ones. Visual analysis can be considered an optimal diagnostic criterion, adequately detecting a wide range of malignant nodules with different metabolic activity. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Non-invasive optical detection of esophagus cancer based on urine surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Shaohua; Wang, Lan; Chen, Weiwei; Lin, Duo; Huang, Lingling; Wu, Shanshan; Feng, Shangyuan; Chen, Rong

2014-09-01

A surface-enhanced Raman spectroscopy (SERS) approach was utilized for urine biochemical analysis with the aim to develop a label-free and non-invasive optical diagnostic method for esophagus cancer detection. SERS spectrums were acquired from 31 normal urine samples and 47 malignant esophagus cancer (EC) urine samples. Tentative assignments of urine SERS bands demonstrated esophagus cancer specific changes, including an increase in the relative amounts of urea and a decrease in the percentage of uric acid in the urine of normal compared with EC. The empirical algorithm integrated with linear discriminant analysis (LDA) were employed to identify some important urine SERS bands for differentiation between healthy subjects and EC urine. The empirical diagnostic approach based on the ratio of the SERS peak intensity at 527 to 1002 cm-1 and 725 to 1002 cm-1 coupled with LDA yielded a diagnostic sensitivity of 72.3% and specificity of 96.8%, respectively. The area under the receive operating characteristic (ROC) curve was 0.954, which further evaluate the performance of the diagnostic algorithm based on the ratio of the SERS peak intensity combined with LDA analysis. This work demonstrated that the urine SERS spectra associated with empirical algorithm has potential for noninvasive diagnosis of esophagus cancer.

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.

Stool-based biomarkers of interstitial cystitis/bladder pain syndrome.

PubMed

Braundmeier-Fleming, A; Russell, Nathan T; Yang, Wenbin; Nas, Megan Y; Yaggie, Ryan E; Berry, Matthew; Bachrach, Laurie; Flury, Sarah C; Marko, Darlene S; Bushell, Colleen B; Welge, Michael E; White, Bryan A; Schaeffer, Anthony J; Klumpp, David J

2016-05-18

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Operational taxonomic units (OTUs) were identified by16S rDNA sequence analysis. Machine learning by Extended Random Forest (ERF) identified OTUs associated with symptom scores. Quantitative PCR of stool DNA with species-specific primer pairs demonstrated significantly reduced levels of E. sinensis, C. aerofaciens, F. prausnitzii, O. splanchnicus, and L. longoviformis in microbiota of IC patients. These species, deficient in IC pelvic pain (DIPP), were further evaluated by Receiver-operator characteristic (ROC) analyses, and DIPP species emerged as potential IC biomarkers. Stool metabolomic studies identified glyceraldehyde as significantly elevated in IC. Metabolomic pathway analysis identified lipid pathways, consistent with predicted metagenome functionality. Together, these findings suggest that DIPP species and metabolites may serve as candidates for novel IC biomarkers in stool. Functional changes in the IC microbiome may also serve as therapeutic targets for treating chronic pelvic pain.

Rationale, development and implementation of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest.

PubMed

Morrison, Laurie J; Nichol, Graham; Rea, Thomas D; Christenson, Jim; Callaway, Clifton W; Stephens, Shannon; Pirrallo, Ronald G; Atkins, Dianne L; Davis, Daniel P; Idris, Ahamed H; Newgard, Craig

2008-08-01

To describe the development, design and consequent scientific implications of the Resuscitation Outcomes Consortium (ROC) population-based registry; ROC Epistry-Cardiac Arrest. The ROC Epistry--Cardiac Arrest is designed as a prospective population-based registry of all Emergency Medical Services (EMSs)-attended 9-1-1 calls for patients with out-of-hospital cardiac arrest occurring in the geographical area described by the eight US and three Canadian regions. The dataset was derived by an North American interdisciplinary steering committee. Enrolled cases include individuals of all ages who experience cardiac arrest outside the hospital, with evaluation by organized EMS personnel and: (a) attempts at external defibrillation (by lay responders or emergency personnel), or chest compressions by organized EMS personnel; (b) were pulseless but did not receive attempts to defibrillate or CPR by EMS personnel. Selected data items are categorized as mandatory or optional and undergo revisions approximately every 12 months. Where possible all definitions are referenced to existing literature. Where a common definition did not exist one was developed. Optional items include standardized CPR process data elements. It is anticipated the ROC Epistry--Cardiac Arrest will enroll between approximately 9000 and 13,500 treated all rhythm arrests and 4000 and 5000 ventricular fibrillation arrests annually and approximately 8000 EMS-attended but untreated arrests. We describe the rationale, development, design and future implications of the ROC Epistry--Cardiac Arrest. This paper will serve as the reference for subsequent ROC manuscripts and for the common data elements captured in both ROC Epistry--Cardiac Arrest and the ROC trials.

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

PubMed

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

2017-08-01

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

Analysis of injury patterns and roles of care in US and Israel militaries during recent conflicts: Two are better than one.

PubMed

Antebi, Ben; Benov, Avi; Mann-Salinas, Elizabeth A; Le, Tuan D; Cancio, Leopoldo C; Wenke, Joseph C; Paran, Haim; Yitzhak, Avraham; Tarif, Bader; Gross, Kirby R; Dagan, David; Glassberg, Elon

2016-11-01

As new conflicts emerge and enemies evolve, military medical organizations worldwide must adopt the "lessons learned." In this study, we describe roles of care (ROCs) deployed and injuries sustained by both US and Israeli militaries during recent conflicts. The purpose of this collaborative work is facilitate exchange of medical data among allied forces in order to advance military medicine and facilitate strategic readiness for future military engagements that may involve less predictable situations of evacuation and care, such as prolonged field care. This retrospective study was conducted for the periods of 2003 to 2014 from data retrieved from the Department of Defense Trauma Registry and the Israel Defense Force (IDF) Trauma Registry. Comparative analyses included ROC capabilities, casualties who died of wounds, as well as mechanism of injury, anatomical wound distribution, and Injury Severity Score of US and IDF casualties during recent conflicts. Although concept of ROCs was similar among militaries, the IDF supports increased capabilities at point of injury and Role 1 including the presence of physicians, but with limited deployment of other ROCs; conversely, the US maintains fewer capabilities at Role 1 but utilized the entire spectrum of care, including extensive deployment of Roles 2/2+, during recent conflicts. Casualties from US forces (n = 19,005) and IDF (n = 2,637) exhibited significant differences in patterns of injury with higher proportions of casualties who died of wounds in the US forces (4%) compared with the IDF (0.6%). As these data suggest deployed ROCs and injury patterns of US and Israeli militaries were both conflict and system specific. We envision that identification of discordant factors and common medical strategies of the two militaries will enable strategic readiness for future conflicts as well as foster further collaboration among allied forces with the overarching universal goal of eliminating preventable death on the battlefield.

Binary ROCs in Perception and Recognition Memory Are Curved

ERIC Educational Resources Information Center

Dube, Chad; Rotello, Caren M.

2012-01-01

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

Design and Optimization of the SPOT Primary Mirror Segment

NASA Technical Reports Server (NTRS)

Budinoff, Jason G.; Michaels, Gregory J.

2005-01-01

The 3m Spherical Primary Optical Telescope (SPOT) will utilize a single ring of 0.86111 point-to-point hexagonal mirror segments. The f2.85 spherical mirror blanks will be fabricated by the same replication process used for mass-produced commercial telescope mirrors. Diffraction-limited phasing will require segment-to-segment radius of curvature (ROC) variation of approx.1 micron. Low-cost, replicated segment ROC variations are estimated to be almost 1 mm, necessitating a method for segment ROC adjustment & matching. A mechanical architecture has been designed that allows segment ROC to be adjusted up to 400 microns while introducing a minimum figure error, allowing segment-to-segment ROC matching. A key feature of the architecture is the unique back profile of the mirror segments. The back profile of the mirror was developed with shape optimization in MSC.Nastran(TradeMark) using optical performance response equations written with SigFit. A candidate back profile was generated which minimized ROC-adjustment-induced surface error while meeting the constraints imposed by the fabrication method. Keywords: optimization, radius of curvature, Pyrex spherical mirror, Sigfit

Efficacy of a new educational tool to improve Handrubbing technique amongst healthcare workers: a controlled, before-after study.

PubMed

Stewardson, Andrew J; Iten, Anne; Camus, Véronique; Gayet-Ageron, Angèle; Caulfield, Darren; Lacey, Gerard; Pittet, Didier

2014-01-01

Hand hygiene is a key component of infection control in healthcare. WHO recommends that healthcare workers perform six specific poses during each hand hygiene action. SureWash (Glanta Ltd, Dublin, Ireland) is a novel device that uses video-measurement technology and immediate feedback to teach this technique. We assessed the impact of self-directed SureWash use on healthcare worker hand hygiene technique and evaluated the device's diagnostic capacity. A controlled before-after study: subjects in Group A were exposed to the SureWash for four weeks followed by Group B for 12 weeks. Each subject's hand hygiene technique was assessed by blinded observers at baseline (T0) and following intervention periods (T1 and T2). Primary outcome was performance of a complete hand hygiene action, requiring all six poses during an action lasting ≥20 seconds. The number of poses per hand hygiene action (maximum 6) was assessed in a post-hoc analysis. SureWash's diagnostic capacity compared to human observers was assessed using ROC curve analysis. Thirty-four and 29 healthcare workers were recruited to groups A and B, respectively. No participants performed a complete action at baseline. At T1, one Group A participant and no Group B participants performed a complete action. At baseline, the median number of poses performed per action was 2.0 and 1.0 in Groups A and B, respectively (p = 0.12). At T1, the number of poses per action was greater in Group A (post-intervention) than Group B (control): median 3.8 and 2.0, respectively (p<0.001). In Group A, the number of poses performed twelve weeks post-intervention (median 3.0) remained higher than baseline (p<0.001). The area under the ROC curves for the 6 poses ranged from 0.59 to 0.88. While no impact on complete actions was demonstrated, SureWash significantly increased the number of poses per hand hygiene action and demonstrated good diagnostic capacity.

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.

Supervised filters for EEG signal in naturally occurring epilepsy forecasting.

PubMed

Muñoz-Almaraz, Francisco Javier; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma; Pardo, Juan

2017-01-01

Nearly 1% of the global population has Epilepsy. Forecasting epileptic seizures with an acceptable confidence level, could improve the disease treatment and thus the lifestyle of the people who suffer it. To do that the electroencephalogram (EEG) signal is usually studied through spectral power band filtering, but this paper proposes an alternative novel method of preprocessing the EEG signal based on supervised filters. Such filters have been employed in a machine learning algorithm, such as the K-Nearest Neighbor (KNN), to improve the prediction of seizures. The proposed solution extends with this novel approach an algorithm that was submitted to win the third prize of an international Data Science challenge promoted by Kaggle contest platform and the American Epilepsy Society, the Epilepsy Foundation, National Institutes of Health (NIH) and Mayo Clinic. A formal description of these preprocessing methods is presented and a detailed analysis in terms of Receiver Operating Characteristics (ROC) curve and Area Under ROC curve is performed. The obtained results show statistical significant improvements when compared with the spectral power band filtering (PBF) typical baseline. A trend between performance and the dataset size is observed, suggesting that the supervised filters bring better information, compared to the conventional PBF filters, as the dataset grows in terms of monitored variables (sensors) and time length. The paper demonstrates a better accuracy in forecasting when new filters are employed and its main contribution is in the field of machine learning algorithms to develop more accurate predictive systems.

Supervised filters for EEG signal in naturally occurring epilepsy forecasting

PubMed Central

2017-01-01

Nearly 1% of the global population has Epilepsy. Forecasting epileptic seizures with an acceptable confidence level, could improve the disease treatment and thus the lifestyle of the people who suffer it. To do that the electroencephalogram (EEG) signal is usually studied through spectral power band filtering, but this paper proposes an alternative novel method of preprocessing the EEG signal based on supervised filters. Such filters have been employed in a machine learning algorithm, such as the K-Nearest Neighbor (KNN), to improve the prediction of seizures. The proposed solution extends with this novel approach an algorithm that was submitted to win the third prize of an international Data Science challenge promoted by Kaggle contest platform and the American Epilepsy Society, the Epilepsy Foundation, National Institutes of Health (NIH) and Mayo Clinic. A formal description of these preprocessing methods is presented and a detailed analysis in terms of Receiver Operating Characteristics (ROC) curve and Area Under ROC curve is performed. The obtained results show statistical significant improvements when compared with the spectral power band filtering (PBF) typical baseline. A trend between performance and the dataset size is observed, suggesting that the supervised filters bring better information, compared to the conventional PBF filters, as the dataset grows in terms of monitored variables (sensors) and time length. The paper demonstrates a better accuracy in forecasting when new filters are employed and its main contribution is in the field of machine learning algorithms to develop more accurate predictive systems. PMID:28632737

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Evaluation of community-acquired sepsis by PIRO system in the emergency department.

PubMed

Chen, Yun-Xia; Li, Chun-Sheng

2013-09-01

The predisposition, infection/insult, response, and organ dysfunction (PIRO) staging system for septic patients allows grouping of heterogeneous patients into homogeneous subgroups. The purposes of this single-center, prospective, observational cohort study were to create a PIRO system for patients with community-acquired sepsis (CAS) presenting to the emergency department (ED) and assess its prognostic and stratification capabilities. Septic patients were enrolled and allocated to derivation (n = 831) or validation (n = 860) cohorts according to their enrollment dates. The derivation cohort was used to identify independent predictors of mortality and create a PIRO system by binary logistic regression analysis, and the prognostic performance of PIRO was investigated in the validation cohort by receiver operator characteristic (ROC) curve. Ten independent predictors of 28-day mortality were identified. The PIRO system combined the components of predisposition (age, chronic obstructive pulmonary disease, hypoalbuminemia), infection (central nervous system infection), response (temperature, procalcitonin), and organ dysfunction (brain natriuretic peptide, troponin I, mean arterial pressure, Glasgow coma scale score). The area under the ROC of PIRO was 0.833 for the derivation cohort and 0.813 for the validation cohort. There was a stepwise increase in 28-day mortality with increasing PIRO score and the differences between the low- (PIRO 0-10), intermediate- (11-20), and high- (>20) risk groups were very significant in both cohorts (p < 0.01). The present study demonstrates that this PIRO system is valuable for prognosis and risk stratification in patients with CAS in the ED.

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.

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.

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

NASA Technical Reports Server (NTRS)

Simon, Donald L.

2011-01-01

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

Least squares regression methods for clustered ROC data with discrete covariates.

PubMed

Tang, Liansheng Larry; Zhang, Wei; Li, Qizhai; Ye, Xuan; Chan, Leighton

2016-07-01

The receiver operating characteristic (ROC) curve is a popular tool to evaluate and compare the accuracy of diagnostic tests to distinguish the diseased group from the nondiseased group when test results from tests are continuous or ordinal. A complicated data setting occurs when multiple tests are measured on abnormal and normal locations from the same subject and the measurements are clustered within the subject. Although least squares regression methods can be used for the estimation of ROC curve from correlated data, how to develop the least squares methods to estimate the ROC curve from the clustered data has not been studied. Also, the statistical properties of the least squares methods under the clustering setting are unknown. In this article, we develop the least squares ROC methods to allow the baseline and link functions to differ, and more importantly, to accommodate clustered data with discrete covariates. The methods can generate smooth ROC curves that satisfy the inherent continuous property of the true underlying curve. The least squares methods are shown to be more efficient than the existing nonparametric ROC methods under appropriate model assumptions in simulation studies. We apply the methods to a real example in the detection of glaucomatous deterioration. We also derive the asymptotic properties of the proposed methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of biochemical cartilage imaging techniques at 3 T MRI.

PubMed

Rehnitz, C; Kupfer, J; Streich, N A; Burkholder, I; Schmitt, B; Lauer, L; Kauczor, H-U; Weber, M-A

2014-10-01

To prospectively compare chemical-exchange saturation-transfer (CEST) with delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) and T2 mapping to assess the biochemical cartilage properties of the knee. Sixty-nine subjects were prospectively included (median age, 42 years; male/female = 32/37) in three cohorts: 10 healthy volunteers, 40 patients with clinically suspected cartilage lesions, and 19 patients about 1 year after microfracture therapy. T2 mapping, dGEMRIC, and CEST were performed at a 3 T MRI unit using a 15-channel knee coil. Parameter maps were evaluated using region-of-interest analysis of healthy cartilage, areas of chondromalacia and repair tissue. Differentiation of damaged from healthy cartilage was assessed using receiver-operating characteristic (ROC) analysis. Chondromalacia grade 2-3 had significantly higher CEST values (P = 0.001), lower dGEMRIC (T1-) values (P < 0.001) and higher T2 values (P < 0.001) when compared to the normal appearing cartilage. dGEMRIC and T2 mapping correlated moderately negative (Spearman coefficient r = -0.56, P = 0.0018) and T2 mapping and CEST moderately positive (r = 0.5, P = 0.007), while dGEMRIC and CEST did not significantly correlate (r = -0.311, P = 0.07). The repair tissue revealed lower dGEMRIC values (P < 0.001) and higher CEST values (P < 0.001) with a significant negative correlation (r = -0.589, P = 0.01), whereas T2 values were not different (P = 0.54). In healthy volunteers' cartilage, CEST and dGEMRIC showed moderate positive correlation (r = 0.56), however not reaching significance (P = 0.09). ROC-analysis demonstrated non-significant differences of T2 mapping vs CEST (P = 0.14), CEST vs dGEMRIC (P = 0.89), and T2 mapping vs dGEMRIC (P = 0.12). CEST is able to detect normal and damaged cartilage and is non-inferior in distinguishing both when compared to dGEMRIC and T2 mapping. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Standard echocardiography versus handheld echocardiography for the detection of subclinical rheumatic heart disease: protocol for a systematic review

PubMed Central

Telford, Lisa H; Abdullahi, Leila H; Ochodo, Eleanor A; Engel, Mark E

2018-01-01

Introduction Rheumatic heart disease (RHD) is a preventable and treatable chronic condition which persists in many developing countries largely affecting impoverished populations. Handheld echocardiography presents an opportunity to address the need for more cost-effective methods of diagnosing RHD in developing countries, where the disease continues to carry high rates of morbidity and mortality. Preliminary studies have demonstrated moderate sensitivity as well as high specificity and diagnostic odds for detecting RHD in asymptomatic patients. We describe a protocol for a systematic review on the diagnostic performance of handheld echocardiography compared to standard echocardiography using the 2012 World Heart Federation criteria for diagnosing subclinical RHD. Methods and analysis Electronic databases including PubMed, Scopus, Web of Science and EBSCOhost as well as reference lists and citations of relevant articles will be searched from 2012 to date using a predefined strategy incorporating a combination of Medical Subject Heading terms and keywords. The methodological validity and quality of studies deemed eligible for inclusion will be assessed against review specific Quality Assessment of Diagnostic Accuracy Studies 2 criteria and information on metrics of diagnostic accuracy and demographics extracted. Forest plots of sensitivity and specificity as well as scatter plots in receiver operating characteristic (ROC) space will be used to investigate heterogeneity. If possible, a meta-analysis will be conducted to produce summary results of sensitivity and specificity using the Hierarchical Summary ROC method. In addition, a sensitivity analysis will be conducted to investigate the effect of studies with a high risk of bias. Ethics and dissemination Ethics approval is not required for this systematic review of previously published literature. The planned review will provide a summary of the diagnostic accuracy of handheld echocardiography. Results may feed into evidence-based guidelines and should the findings of this review warrant a change in clinical practice, a summary report will be disseminated among leading clinicians and healthcare professionals in the field. PROSPERO registration number CRD42016051261. PMID:29440164

Cross-Cultural Adaptation and Validation of the Voice Handicap Index into Thai.

PubMed

Jaruchinda, Pariyanan; Suwanwarangkool, Thadchai

2015-12-01

The voice handicap index (VHI) is one of the most utilized instruments for measuring a patient's self-assessment of voice severity. The VHI has been translated into several languages, but not in Thai. To examine the psychometric properties of a Thai translation of the voice Handicap Index (VHI) and assess the applicability in the screening diagnosis. After receiving permission from the American Speech Language Hearing Association (ASHA), the original VHI had been translated and adapted to Thai by forward and backward standard translation. Eighty-five patients with voice disorders, divided in four groups according to the etiology of the diseases (neurogenic, structural, functional, and inflammatory), and 30 asymptomatic subjects were included in the present study. Internal consistency was analyzed through Cronbach's a coefficient. For the VHI test-retest reliability analysis, the Thai VHI was completed twice by 22 patients and assessed through the intraclass correlation coefficient. For clinical validity evaluation, the VHI scores from the pathological group were compared with the control group and compared among the four different pathological groups. The cutoff point for distinguishing the normal from the patient group was assessed by ROC analysis. Effects of age and gender on VHI scores were also evaluated. The Thai VHI showed a significant high internal consistency and test-retest reliability (Cronbach's α = 0.96 and r = 0.843, respectively). Mann-Whitney U test was used to compare the control group and pathological groups and revealed significant difference in total scores and its three domains scores (p < 0.001). ROC analysis demonstrated that a VHI score of 13 should be considered the threshold for revealing the impact of quality of life in voice disorder patients. Age and gender were not affect the VHI scores in both control and patient groups. The Thai VHI has high reliability and validity. The Thai version of VHI is considered to be a self-assessment tool for the severity of voice disorders in Thai patients.

Q-elastography in the presurgical diagnosis of thyroid nodules with indeterminate cytology.

PubMed

Cantisani, Vito; Ulisse, Salvatore; Guaitoli, Eleonora; De Vito, Corrado; Caruso, Riccardo; Mocini, Renzo; D'Andrea, Vito; Ascoli, Valeria; Antonaci, Alfredo; Catalano, Carlo; Nardi, Francesco; Redler, Adriano; Ricci, Paolo; De Antoni, Enrico; Sorrenti, Salvatore

2012-01-01

Quantitative ultrasound (US) elastography (Q-USE), able to evaluate tissue stiffness has been indicated as a new diagnostic tool to differentiate benign from malignant thyroid lesions. Aim of this prospective study, conducted at the Department of Surgical Sciences, of the "Sapienza" University of Rome, was to evaluate the diagnostic accuracy of Q-USE, compared with US parameters, in thyroid nodules with indeterminate cytology (Thy3).The case study included 140 nodules from 140 consecutive patients. Patient's thyroid nodules were evaluated by Q-USE, measuring the strain ratio (SR) of stiffness between nodular and surrounding normal thyroid tissue, and conventional US parameters prior fine-needle aspiration cytology. Those with Thy3 diagnosis were included in the study. Forty of the nodules analyzed harbored a malignant lesion. Q-USE demonstrated that malignant nodules have a significant higher stiffness with respect to benign one and an optimun SR cut-off value of 2.05 was individuated following ROC analysis. Univariate analysis showed that hypoechogenicity, irregular margins and SR >2.05 associated with malignancy, with an accuracy of 67.2%, 81,0% and 89.8%, respectively. Data were unaffected by nodule size or thyroiditis. These findings were confirmed in multivariate analysis demonstrating a significant association of the SR and the irregular margins with thyroid nodule's malignancy. In conclusion, we demonstrated the diagnostic utility of Q-USE in the differential diagnosis of thyroid nodules with indeterminate cytology that, if confirmed, could be of major clinical utility in patients' presurgical selection.

Q-Elastography in the Presurgical Diagnosis of Thyroid Nodules with Indeterminate Cytology

PubMed Central

Guaitoli, Eleonora; De Vito, Corrado; Caruso, Riccardo; Mocini, Renzo; D’Andrea, Vito; Ascoli, Valeria; Antonaci, Alfredo; Catalano, Carlo; Nardi, Francesco; Redler, Adriano; Ricci, Paolo; De Antoni, Enrico; Sorrenti, Salvatore

2012-01-01

Quantitative ultrasound (US) elastography (Q-USE), able to evaluate tissue stiffness has been indicated as a new diagnostic tool to differentiate benign from malignant thyroid lesions. Aim of this prospective study, conducted at the Department of Surgical Sciences, of the “Sapienza” University of Rome, was to evaluate the diagnostic accuracy of Q-USE, compared with US parameters, in thyroid nodules with indeterminate cytology (Thy3).The case study included 140 nodules from 140 consecutive patients. Patient’s thyroid nodules were evaluated by Q-USE, measuring the strain ratio (SR) of stiffness between nodular and surrounding normal thyroid tissue, and conventional US parameters prior fine-needle aspiration cytology. Those with Thy3 diagnosis were included in the study. Forty of the nodules analyzed harbored a malignant lesion. Q-USE demonstrated that malignant nodules have a significant higher stiffness with respect to benign one and an optimun SR cut-off value of 2.05 was individuated following ROC analysis. Univariate analysis showed that hypoechogenicity, irregular margins and SR >2.05 associated with malignancy, with an accuracy of 67.2%, 81,0% and 89.8%, respectively. Data were unaffected by nodule size or thyroiditis. These findings were confirmed in multivariate analysis demonstrating a significant association of the SR and the irregular margins with thyroid nodule’s malignancy. In conclusion, we demonstrated the diagnostic utility of Q-USE in the differential diagnosis of thyroid nodules with indeterminate cytology that, if confirmed, could be of major clinical utility in patients’ presurgical selection. PMID:23209819

Diagnostic and prognostic value of baseline FDG PET/CT skeletal textural features in diffuse large B cell lymphoma.

PubMed

Aide, Nicolas; Talbot, Marjolaine; Fruchart, Christophe; Damaj, Gandhi; Lasnon, Charline

2018-05-01

Our purpose was to evaluate the diagnostic and prognostic value of skeletal textural features (TFs) on baseline FDG PET in diffuse large B cell lymphoma (DLBCL) patients. Eighty-two patients with DLBCL who underwent a bone marrow biopsy (BMB) and a PET scan between December 2008 and December 2015 were included. Two readers blinded to the BMB results visually assessed PET images for bone marrow involvement (BMI) in consensus, and a third observer drew a volume of interest (VOI) encompassing the axial skeleton and the pelvis, which was used to assess skeletal TFs. ROC analysis was used to determine the best TF able to diagnose BMI among four first-order, six second-order and 11 third-order metrics, which was then compared for diagnosis and prognosis in disease-free patients (BMB-/PET-) versus patients considered to have BMI (BMB+/PET-, BMB-/PET+, and BMB+/PET+). Twenty-two out of 82 patients (26.8%) had BMI: 13 BMB-/PET+, eight BMB+/PET+ and one BMB+/PET-. Among the nine BMB+ patients, one had discordant BMI identified by both visual and TF PET assessment. ROC analysis showed that SkewnessH, a first-order metric, was the best parameter for identifying BMI with sensitivity and specificity of 81.8% and 81.7%, respectively. SkewnessH demonstrated better discriminative power over BMB and PET visual analysis for patient stratification: hazard ratios (HR), 3.78 (P = 0.02) versus 2.81 (P = 0.06) for overall survival (OS) and HR, 3.17 (P = 0.03) versus 1.26 (P = 0.70) for progression-free survival (PFS). In multivariate analysis accounting for IPI score, bulky status, haemoglobin and SkewnessH, the only independent predictor of OS was the IPI score, while the only independent predictor of PFS was SkewnessH. The better discriminative power of skeletal heterogeneity for risk stratification compared to BMB and PET visual analysis in the overall population, and more specifically in BMB-/PET- patients, suggests that it can be useful to identify diagnostically overlooked BMI.

M13. Identifying Youths at Risk for Antipsychotic-Induced Weight Gain and Metabolic Dysfunction in the Treatment of Early Onset Schizophrenia Spectrum Disorders (TEOSS)

PubMed Central

Taylor, Jerome; Jakubovski, Ewgeni; Gabriel, Daniel; Bloch, Michael

2017-01-01

Abstract Background: Antipsychotic-induced metabolic dysfunction is problematic in youths with psychosis. We used limited-access data from the NIH-funded Treatment of Early Onset Schizophrenia Spectrum Disorders (TEOSS) study to identify risk factors for neuroleptic-associated metabolic dysfunction. Methods: TEOSS randomized 119 youths with schizophrenia and schizoaffective disorder to 8 weeks of treatment with olanzapine, risperidone or molindone and monitored their response to medication as well as metabolic side effects throughout the trial. TEOSS demonstrated no differences in response rates by antipsychotic agent. In this secondary analysis we used stepwise linear regression and receiver operating characteristics (ROC) to identify baseline predictors associated with changes in weight, fasting glucose, fasting insulin and total cholesterol at week 8 in TEOSS. Results: Randomized assignment to olanzapine (parameter estimate (PE) = 2.88, SE = 1.08, P = .01) and living at home (vs institutionalization) (PE = 2.62, SE = 1.08, P = .02) associated with increased weight gain. Randomized assignment to molindone (PE = −3.45, SE = 0.97, P = .0007) associated with less weight gain. Greater increase in fasting glucose levels associated with randomization to olanzapine (PE = 18.56, SE = 7.33, P = .01) and the absence of a family history of depression (PE = −6.40, SE = 2.82, P = .03). Greater increase in fasting insulin levels associated with randomization to olanzapine (PE = 17.05, SE = 6.39, P = .01), greater number of past psychiatric hospitalizations (PE = 11.81, SE = 2.54, P < .0001), not taking an antipsychotic prior to study entry (PE = −20.35, SE = 6.50, P = .003) and the absence of a family history of depression (PE=−5.33, SE = 2.46, P = .03). Randomization to olanzapine (PE = 26.78, SE = 6.02, P < .0001), congenital heart disease (PE = 45.61, SE = 13.29, P = .0009) and legal difficulties (arrests) (PE= 17.39, SE = 7.64, P = .03) predicted greater increase in cholesterol levels. ROC analysis identified randomization to olanzapine as the most discriminative predictor of >4 kg weight gain. Conclusion: This data-driven moderator analysis confirms secondary findings of the original TEOSS study that demonstrated that metabolic outcomes, particularly weight gain is strongly determined by choice of antipsychotic agent with poor metabolic outcomes associated with olanzapine (weight, glucose, insulin and cholesterol) and better metabolic outcome associated with molindone (weight). Data-driven analysis demonstrated several other predictors of metabolic outcomes that are worthy of further replication. This research was funded by the American Academy of Child and Adolescent Psychiatry Pilot Award.

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

PubMed

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

2017-04-01

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

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

PubMed

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

2018-04-19

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

Progress Toward Adaptive Integration and Optimization of Automated and Neural Processing Systems: Establishing Neural and Behavioral Benchmarks of Optimized Performance

DTIC Science & Technology

2014-11-01

Paradigm ............................................................................19 3.4 Collaborative BCI for Improving Overall Performance...interfaces ( BCIs ) provide the biggest improvement in performance? Can we demonstrate clear advantages with BCIs ? 2 2. Simulator Development and...stimuli in real time. Fig. 18 ROC curves for each subject after the combination of 2 trials 3.4 Collaborative BCI for Improving Overall

The ROC program: accelerated restoration of competency in a jail setting.

PubMed

Rice, Kevin; Jennings, Jerry L

2014-01-01

In 29 months of operation, the restoration of competency (ROC) program provided treatment services to 192 incompetent to stand trial patients in a jail setting. The ROC restored competency for 55% of the patients in an average of 57 days compared to the state hospital average of 180 days. The average cost of treatment/restoration per admission was $15,568 compared to the state hospital average of $81,000. The ROC model accelerates needed treatment for mentally ill defendants, cuts demand for costly state hospital forensic beds, and assists jails in better managing inmates with severe psychiatric disorders--yielding major cost savings and improved care. In addition to preventing readmissions and negative behavioral episodes, the ROC improved the broader forensic system by eliminating the state hospital waiting list, accelerating access to psychiatric services, promoting local access for lawyers and family, and gaining stakeholder satisfaction.

Reliability of cone beam computed tomography as a biopsy-independent tool in differential diagnosis of periapical cysts and granulomas: An In vivo Study.

PubMed

Chanani, Ankit; Adhikari, Haridas Das

2017-01-01

Differential diagnosis of periapical cysts and granulomas is required as their treatment modalities are different. The aim of this study was to evaluate the efficacy of cone beam computed tomography (CBCT) in the differential diagnosis of periapical cysts from granulomas. A single-centered observational study was carried out in the Department of Conservative Dentistry and Endodontics, Dr. R. Ahmed Dental College and Hospital, using CBCT and dental operating microscope. Forty-five lesions were analyzed using CBCT scans. One evaluator analyzed each CBCT scan for the presence of the following six characteristic radiological features: cyst like-location, shape, periphery, internal structure, effect on the surrounding structures, and cortical plate perforation. Another independent evaluator analyzed the CBCT scans. This process was repeated after 6 months, and inter- and intrarater reliability of CBCT diagnoses was evaluated. Periapical surgeries were performed and tissue samples were obtained for histopathological analysis. To evaluate the efficacy, CBCT diagnoses were compared with histopathological diagnoses, and six receiver operating characteristic (ROC) curve analyses were conducted. ROC curve, Cronbach's alpha (α) test, and Cohen Kappa (κ) test were used for statistical analysis. Both inter- and intrarater reliability were excellent (α = 0.94, κ = 0.75 and 0.77, respectively). ROC curve with regard to ≥4 positive findings revealed the highest area under curve (0.66). CBCT is moderately accurate in the differential diagnosis of periapical cysts and granulomas.

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

Predictive inference for best linear combination of biomarkers subject to limits of detection.

PubMed

Coolen-Maturi, Tahani

2017-08-15

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed

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

2013-04-01

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

Eyewitness identification in simultaneous and sequential lineups: an investigation of position effects using receiver operating characteristics.

PubMed

Meisters, Julia; Diedenhofen, Birk; Musch, Jochen

2018-04-20

For decades, sequential lineups have been considered superior to simultaneous lineups in the context of eyewitness identification. However, most of the research leading to this conclusion was based on the analysis of diagnosticity ratios that do not control for the respondent's response criterion. Recent research based on the analysis of ROC curves has found either equal discriminability for sequential and simultaneous lineups, or higher discriminability for simultaneous lineups. Some evidence for potential position effects and for criterion shifts in sequential lineups has also been reported. Using ROC curve analysis, we investigated the effects of the suspect's position on discriminability and response criteria in both simultaneous and sequential lineups. We found that sequential lineups suffered from an unwanted position effect. Respondents employed a strict criterion for the earliest lineup positions, and shifted to a more liberal criterion for later positions. No position effects and no criterion shifts were observed in simultaneous lineups. This result suggests that sequential lineups are not superior to simultaneous lineups, and may give rise to unwanted position effects that have to be considered when conducting police lineups.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Reliable optical card-edge (ROC) connector for avionics applications

NASA Astrophysics Data System (ADS)

Darden, Bruce V.; Pimpinella, Richard J.; Seals, John D.

1994-10-01

The Reliable Optical Card-Edge (ROC) Connector is a blind-mate backplane unit designed to meet military stress requirements for avionics applications. Its modular design represents the first significant advance in connector optics since the biconic butt-coupled connector was introduced twenty years ago. This multimode connector utilizes beam optics, micro-machined silicon, and a floating, low mass subassembly design to maintain low coupling loss under high levels of shock and vibration. The ROC connector also incorporates retracting doors to protect the unmated termini from environmental contamination and abusive handling. Design features and test results for the ROC connector are presented in this paper.

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

PubMed

Bantis, Leonidas E; Feng, Ziding

2016-10-30

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC -1 (t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare them with other known approaches, and present a real-data application involving prostate cancer screening. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

TU-G-BRD-08: In-Vivo EPID Dosimetry: Quantifying the Detectability of Four Classes of Errors

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

Ford, E; Phillips, M; Bojechko, C

Purpose: EPID dosimetry is an emerging method for treatment verification and QA. Given that the in-vivo EPID technique is in clinical use at some centers, we investigate the sensitivity and specificity for detecting different classes of errors. We assess the impact of these errors using dose volume histogram endpoints. Though data exist for EPID dosimetry performed pre-treatment, this is the first study quantifying its effectiveness when used during patient treatment (in-vivo). Methods: We analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. This dose was compared to the TPSmore » dose using a 3%/3mm gamma criteria. To simulate errors, modifications were made to treatment plans using four possible classes of error: 1) patient misalignment, 2) changes in patient body habitus, 3) machine output changes and 4) MLC misalignments. Each error was applied with varying magnitudes. To assess the detectability of the error, the area under a ROC curve (AUC) was analyzed. The AUC was compared to changes in D99 of the PTV introduced by the simulated error. Results: For systematic changes in the MLC leaves, changes in the machine output and patient habitus, the AUC varied from 0.78–0.97 scaling with the magnitude of the error. The optimal gamma threshold as determined by the ROC curve varied between 84–92%. There was little diagnostic power in detecting random MLC leaf errors and patient shifts (AUC 0.52–0.74). Some errors with weak detectability had large changes in D99. Conclusion: These data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic MLC misalignments and machine output changes. There was no correlation found between the detectability of the error using the gamma pass rate, ROC analysis and the impact on the dose volume histogram. Funded by grant R18HS022244 from AHRQ.« less

Diagnostic performance of traditional hepatobiliary biomarkers of drug-induced liver injury in the rat.

PubMed

Ennulat, Daniela; Magid-Slav, Michal; Rehm, Sabine; Tatsuoka, Kay S

2010-08-01

Nonclinical studies provide the opportunity to anchor biochemical with morphologic findings; however, liver injury is often complex and heterogeneous, confounding the ability to relate biochemical changes with specific patterns of injury. The aim of the current study was to compare diagnostic performance of hepatobiliary markers for specific manifestations of drug-induced liver injury in rat using data collected in a recent hepatic toxicogenomics initiative in which rats (n = 3205) were given 182 different treatments for 4 or 14 days. Diagnostic accuracy of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (Tbili), serum bile acids (SBA), alkaline phosphatase (ALP), gamma glutamyl transferase (GGT), total cholesterol (Chol), and triglycerides (Trig) was evaluated for specific types of liver histopathology by Receiver Operating Characteristic (ROC) analysis. To assess the relationship between biochemical and morphologic changes in the absence of hepatocellular necrosis, a second ROC analysis was performed on a subset of rats (n = 2504) given treatments (n = 152) that did not cause hepatocellular necrosis. In the initial analysis, ALT, AST, Tbili, and SBA had the greatest diagnostic utility for manifestations of hepatocellular necrosis and biliary injury, with comparable magnitude of area under the ROC curve and serum hepatobiliary marker changes for both. In the absence of hepatocellular necrosis, ALT increases were observed with biochemical or morphologic evidence of cholestasis. In both analyses, diagnostic utility of ALP and GGT for biliary injury was limited; however, ALP had modest diagnostic value for peroxisome proliferation, and ALT, AST, and total Chol had moderate diagnostic utility for phospholipidosis. None of the eight markers evaluated had diagnostic value for manifestations of hypertrophy, cytoplasmic rarefaction, inflammation, or lipidosis.

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

PubMed

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

2015-04-01

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

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

PubMed

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

2014-07-01

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

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

PubMed

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

2017-11-10

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

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

PubMed

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

2017-02-01

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

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.

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

PubMed

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

2016-07-01

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

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

PubMed

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

2010-08-01

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

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.

Diagnosis and molecular characterization of Trichomonas vaginalis in sex workers in the Philippines

PubMed Central

Queza, Macario Ireneo P; Rivera, Windell L

2013-01-01

Trichomonas vaginalis is a pathogenic protozoon which causes the sexually transmitted infection, trichomoniasis. The absence or non-specificity of symptoms often leads to misdiagnosis of the infection. In this study, 969 samples consisting of vaginal swabs and urine were collected and screened from social hygiene clinics across the Philippines. Of the 969 samples, 216 were used for the comparative analysis of diagnostic tools such as wet mount microscopy, culture, and PCR utilizing universal trichomonad primers, TFR1/2 and species-specific primers, TVK3/7 and TV1/2. PCR demonstrated higher sensitivity of 100% compared to 77% of the wet mount. PCR primer set TVK3/7 and culture had the same and the best expected average performance [receiver-operating characteristic (ROC): 0.98]. Prevalence of infection in the sample population was 6.8%. PMID:23683368

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

PubMed

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

2017-11-09

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

Dynamics of receptor-operated Ca(2+) currents through TRPC channels controlled via the PI(4,5)P2-PLC signaling pathway.

PubMed

Mori, Masayuki X; Itsuki, Kyohei; Hase, Hideharu; Sawamura, Seishiro; Kurokawa, Tatsuki; Mori, Yasuo; Inoue, Ryuji

2015-01-01

Transient receptor potential canonical (TRPC) channels are Ca(2+)-permeable, nonselective cation channels that carry receptor-operated Ca(2+) currents (ROCs) triggered by receptor-induced, phospholipase C (PLC)-catalyzed hydrolysis of phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]. Within the vasculature, TRPC channel ROCs contribute to smooth muscle cell depolarization, vasoconstriction, and vascular remodeling. However, TRPC channel ROCs exhibit a variable response to receptor-stimulation, and the regulatory mechanisms governing TRPC channel activity remain obscure. The variability of ROCs may be explained by their complex regulation by PI(4,5)P2 and its metabolites, which differentially affect TRPC channel activity. To resolve the complex regulation of ROCs, the use of voltage-sensing phosphoinositide phosphatases and model simulation have helped to reveal the time-dependent contribution of PI(4,5)P2 and the possible role of PI(4,5)P2 in the regulation of ROCs. These approaches may provide unprecedented insight into the dynamics of PI(4,5)P2 regulation of TRPC channels and the fundamental mechanisms underlying transmembrane ion flow. Within that context, we summarize the regulation of TRPC channels and their coupling to receptor-mediated signaling, as well as the application of voltage-sensing phosphoinositide phosphatases to this research. We also discuss the controversial bidirectional effects of PI(4,5)P2 using a model simulation that could explain the complicated effects of PI(4,5)P2 on different ROCs.

Effect of coagulation on treatment of municipal wastewater reverse osmosis concentrate by UVC/H2O2.

PubMed

Umar, Muhammad; Roddick, Felicity; Fan, Linhua

2014-02-15

Disposal of reverse osmosis concentrate (ROC) is a growing concern due to potential health and ecological risks. Alum coagulation was investigated as pre-treatment for the UVC/H2O2 treatment of two high salinity ROC samples (ROC A and B) of comparable organic and inorganic content. Coagulation removed a greater fraction of the organic content for ROC B (29%) than ROC A (16%) which correlated well with the reductions of colour and A254. Although the total reductions after 60 min UVC/H2O2 treatment with and without coagulation were comparable, large differences in the trends of reduction were observed which were attributed to the different nature of the organic content (humic-like) of the samples as indicated by the LC-OCD analyses and different initial (5% and 16%) biodegradability. Coagulation and UVC/H2O2 treatment preferentially removed humic-like compounds which resulted in low reaction rates after UVC/H2O2 treatment of the coagulated samples. The improvement in biodegradability was greater (2-3-fold) during UVC/H2O2 treatment of the pre-treated samples than without pre-treatment. The target DOC residual (≤ 15 mg/L) was obtained after 30 and 20 min irradiation of pre-treated ROC A and ROC B with downstream biological treatment, corresponding to reductions of 55% and 62%, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Syntheses, structural determinations of [Ru(ROCS2)2(PPh3)2](+/0) pairs, and kinetic analyses of thermal reactions involving transient trans-[Ru(iPrOCS2)2(PPh3)2] species (ROCS2(-) = ethyl- or isopropyldithiocarbonate and PPh3 = triphenylphosphine).

PubMed

Noda, Kyoko; Ohuchi, Yuko; Hashimoto, Akira; Fujiki, Masayuki; Itoh, Sumitaka; Iwatsuki, Satoshi; Noda, Toshiaki; Suzuki, Takayoshi; Kashiwabara, Kazuo; Takagi, Hideo D

2006-02-06

Controlled-potential electrochemical oxidation of cis-[Ru(ROCS2)2(PPh3)2] (R = Et, iPr) yielded corresponding Ru(III) complexes, and the crystal structures of cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2](PF6) were determined. Both pairs of complexes exhibited almost identical coordination structures. The Ru-P distances in trans-[Ru(III)(ROCS2)2(PPh3)2](PF6) [2.436(3)-2.443(3) A] were significantly longer than those in cis-[Ru(II)(ROCS2)2(PPh3)2] [2.306(1)-2.315(2) A]: the smaller ionic radius of Ru(III) than that of Ru(II) stabilizes the trans conformation for the Ru(III) complex due to the steric requirement of bulky phosphine ligands while mutual trans influence by the phosphine ligands induces significant elongation of the Ru(III)-P bonds. Cyclic voltammograms of the cis-[Ru(ROCS2)2(PPh3)2] and trans-[Ru(ROCS2)2(PPh3)2]+ complexes in dichloromethane solution exhibited typical dual redox signals corresponding to the cis-[Ru(ROCS2)2(PPh3)2](+/0) (ca. +0.15 and +0.10 V vs ferrocenium/ferrocene couple for R = Et and iPr, respectively) and to trans-[Ru(ROCS2)2(PPh3)2](+/0) (-0.05 and -0.15 V vs ferrocenium/ferrocene for R = Et and iPr, respectively) couples. Analyses on the basis of the Nicholson and Shain's method revealed that the thermal disappearance rate of transient trans-[Ru(ROCS2)2(PPh3)2] was dependent on the concentration of PPh3 in the bulk: the rate constant for the intramolecular isomerization reaction of trans-[Ru(iPrOCS2)2(PPh3)2] was determined as 0.338 +/- 0.004 s(-1) at 298.3 K (deltaH* = 41.8 +/- 1.5 kJ mol(-1) and deltaS* = -114 +/- 7 J mol(-1) K(-1)), while the dissociation rate constant of coordinated PPh3 from the trans-[Ru(iPrOCS2)2(PPh3)2] species was estimated as 0.113 +/- 0.008 s(-1) at 298.3 K (deltaH* = 97.6 +/- 0.8 kJ mol(-1) and deltaS* = 64 +/- 3 J mol(-1) K(-1)), by monitoring the EC reaction (electrode reaction followed by chemical processes) at different concentrations of PPh3 in the bulk. It was found that the trans to cis isomerization reaction takes place via the partial dissociation of iPrOCS2(-) from Ru(II), contrary to the previous claim that it takes place by the twist mechanism.

Assessing the Classification Accuracy of Early Numeracy Curriculum-Based Measures Using Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Laracy, Seth D.; Hojnoski, Robin L.; Dever, Bridget V.

2016-01-01

Receiver operating characteristic curve (ROC) analysis was used to investigate the ability of early numeracy curriculum-based measures (EN-CBM) administered in preschool to predict performance below the 25th and 40th percentiles on a quantity discrimination measure in kindergarten. Areas under the curve derived from a sample of 279 students ranged…

Receiver Operating Characteristic Analysis for Classification Based on Various Prior Probabilities of Groups with an Application to Breath Analysis

NASA Astrophysics Data System (ADS)

Cimermanová, K.

2009-01-01

In this paper we illustrate the influence of prior probabilities of diseases on diagnostic reasoning. For various prior probabilities of classified groups characterized by volatile organic compounds of breath profile, smokers and non-smokers, we constructed the ROC curve and the Youden index with related asymptotic pointwise confidence intervals.

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.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding.

PubMed

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-05-28

To distinguish upper from lower gastrointestinal (GI) bleeding. Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL.

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding

PubMed Central

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-01-01

AIM: To distinguish upper from lower gastrointestinal (GI) bleeding. METHODS: Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. RESULTS: Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. CONCLUSION: The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL. PMID:26034359

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…

Processes and process development in Taiwan

NASA Technical Reports Server (NTRS)

Hwang, H. L.

1986-01-01

Silicon material research in the Republic of China (ROC) parallels its development in the electronic industry. A brief outline of the historical development in ROC silicon material research is given. Emphasis is placed on the recent Silane Project managed by the National Science Council, ROC, including project objectives, task forces, and recent accomplishments. An introduction is also given to industrialization of the key technologies developed in this project.

Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients.

PubMed

Liu, Wen-Yue; Lin, Shi-Gang; Zhu, Gui-Qi; Poucke, Sven Van; Braddock, Martin; Zhang, Zhongheng; Mao, Zhi; Shen, Fei-Xia; Zheng, Ming-Hua

2016-01-01

Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality. Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve. 4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813-0.834, P< 0.001) and 0.738 (95% CI: 0.725-0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001). We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group.

UXO Live Site Classification Demonstrations: A Retrospective Summary

DTIC Science & Technology

2017-10-01

performance ROC Curve Number of True Clutter Incorrectly Classified TO I R em ed ia tio n: Pe rc en t o f T ru e TO I Co rr ec tly C la ss ifi ed...rocket, 382 practice bomb , M103 bomb nose fuze, 100lb bomb , M1 practice bomb MPV, TEMTADS 2x2 2014 Waikoloa Waikoloa, HI 9 small ISO, 37mm, medium

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.

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.

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

PubMed

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

2017-11-01

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

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.

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

NASA Astrophysics Data System (ADS)

Zhou, Weimin; Anastasio, Mark A.

2018-03-01

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

Visual-search model observer for assessing mass detection in CT

NASA Astrophysics Data System (ADS)

Karbaschi, Zohreh; Gifford, Howard C.

2017-03-01

Our aim is to devise model observers (MOs) to evaluate acquisition protocols in medical imaging. To optimize protocols for human observers, an MO must reliably interpret images containing quantum and anatomical noise under aliasing conditions. In this study of sampling parameters for simulated lung CT, the lesion-detection performance of human observers was compared with that of visual-search (VS) observers, a channelized nonprewhitening (CNPW) observer, and a channelized Hoteling (CH) observer. Scans of a mathematical torso phantom modeled single-slice parallel-hole CT with varying numbers of detector pixels and angular projections. Circular lung lesions had a fixed radius. Twodimensional FBP reconstructions were performed. A localization ROC study was conducted with the VS, CNPW and human observers, while the CH observer was applied in a location-known ROC study. Changing the sampling parameters had negligible effect on the CNPW and CH observers, whereas several VS observers demonstrated a sensitivity to sampling artifacts that was in agreement with how the humans performed.

An enhancement of ROC curves made them clinically relevant for diagnostic-test comparison and optimal-threshold determination.

PubMed

Subtil, Fabien; Rabilloud, Muriel

2015-07-01

The receiver operating characteristic curves (ROC curves) are often used to compare continuous diagnostic tests or determine the optimal threshold of a test; however, they do not consider the costs of misclassifications or the disease prevalence. The ROC graph was extended to allow for these aspects. Two new lines are added to the ROC graph: a sensitivity line and a specificity line. Their slopes depend on the disease prevalence and on the ratio of the net benefit of treating a diseased subject to the net cost of treating a nondiseased one. First, these lines help researchers determine the range of specificities within which test comparisons of partial areas under the curves is clinically relevant. Second, the ROC curve point the farthest from the specificity line is shown to be the optimal threshold in terms of expected utility. This method was applied: (1) to determine the optimal threshold of ratio specific immunoglobulin G (IgG)/total IgG for the diagnosis of congenital toxoplasmosis and (2) to select, among two markers, the most accurate for the diagnosis of left ventricular hypertrophy in hypertensive subjects. The two additional lines transform the statistically valid ROC graph into a clinically relevant tool for test selection and threshold determination. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

Saito, Takaya; Rehmsmeier, Marc

2015-01-01

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

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.

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.

Towards more efficient burn care: Identifying factors associated with good quality of life post-burn.

PubMed

Finlay, V; Phillips, M; Allison, G T; Wood, F M; Ching, D; Wicaksono, D; Plowman, S; Hendrie, D; Edgar, D W

2015-11-01

As minor burn patients constitute the vast majority of a developed nation case-mix, streamlining care for this group can promote efficiency from a service-wide perspective. This study tested the hypothesis that a predictive nomogram model that estimates likelihood of good long-term quality of life (QoL) post-burn is a valid way to optimise patient selection and risk management when applying a streamlined model of care. A sample of 224 burn patients managed by the Burn Service of Western Australia who provided both short and long-term outcomes was used to estimate the probability of achieving a good QoL defined as 150 out of a possible 160 points on the Burn Specific Health Scale-Brief (BSHS-B) at least six months from injury. A multivariate logistic regression analysis produced a predictive model provisioned as a nomogram for clinical application. A second, independent cohort of consecutive patients (n=106) was used to validate the predictive merit of the nomogram. Male gender (p=0.02), conservative management (p=0.03), upper limb burn (p=0.04) and high BSHS-B score within one month of burn (p<0.001) were significant predictors of good outcome at six months and beyond. A Receiver Operating Curve (ROC) analysis demonstrated excellent (90%) accuracy overall. At 80% probability of good outcome, the false positive risk was 14%. The nomogram was validated by running a second ROC analysis of the model in an independent cohort. The analysis confirmed high (86%) overall accuracy of the model, the risk of false positive was reduced to 10% at a lower (70%) probability. This affirms the stability of the nomogram model in different patient groups over time. An investigation of the effect of missing data on sample selection determined that a greater proportion of younger patients with smaller TBSA burns were excluded due to loss to follow up. For clinicians managing comparable burn populations, the BSWA burns nomogram is an effective tool to assist the selection of patients to a streamlined care pathway with the aim of improving efficiency of service delivery. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Persistent free radicals in carbon-based materials on transformation of refractory organic contaminants (ROCs) in water: A critical review.

PubMed

Qin, Yaxin; Li, Guiying; Gao, Yanpeng; Zhang, Lizhi; Ok, Yong Sik; An, Taicheng

2018-06-15

With the increased concentrations and kinds of refractory organic contaminants (ROCs) in aquatic environments, many previous reviews systematically summarized the applications of carbon-based materials in the adsorption and catalytic degradation of ROCs for their economically viable and environmentally friendly behavior. Interestingly, recent studies indicated that carbon-based materials in natural environment can also mediate the transformation of ROCs directly or indirectly due to their abundant persistent free radicals (PFRs). Understanding the formation mechanisms of PFRs in carbo-based materials and their interactions with ROCs is essential to develop their further applications in environment remediation. However, there is no comprehensive review so far about the direct and indirect removal of ROCs mediated by PFRs in amorphous, porous and crystalline carbon-based materials. The review aims to evaluate the formation mechanisms of PFRs in carbon-based materials synthesized through pyrolysis and hydrothermal carbonization processes. The influence of synthesis conditions (temperature and time) and carbon sources on the types as well as the concentrations of PFRs in carbon-based materials are also discussed. In particular, the effects of metals on the concentrations and types of PFRs in carbon-based materials are highlighted because they are considered as the catalysts for the formation of PFRs. The formation mechanisms of reactive species and the further transformation mechanisms of ROCs are briefly summarized, and the surface properties of carbon-based materials including surface area, types and number of functional groups, etc. are found to be the key parameters controlling their activities. However, due to diversity and complexity of carbon-based materials, the exact relationships between the activities of carbon-based materials and PFRs are still uncertain. Finally, the existing problems and current challenges for the ROCs transformation with carbon-based materials are also pointed out. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hsp-27 levels and thrombus burden relate to clinical outcomes in patients with ST-segment elevation myocardial infarction

PubMed Central

Tian, Maozhou; Zhu, Lingmin; Lin, Hongyang; Lin, Qiaoyan; Huang, Peng; Yu, Xiao; Jing, Yanyan

2017-01-01

High thrombus burden, subsequent distal embolization, and myocardial no-reflow remain a large obstacle that may negate the benefits of urgent coronary revascularization in patients with ST-segment elevation myocardial infarction (STEMI). However, the biological function and clinical association of Hsp-27 with thrombus burden and clinical outcomes in patients with STEMI is not clear. Consecutive patients (n = 146) having STEMI undergoing primary percutaneous coronary intervention (pPCI) within 12 hours from the onset of symptoms were enrolled in this prospective study in the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shangdong, P.R. China. Patients were divided into low thrombus burden and high thrombus burden groups. The present study demonstrated that patients with high-thrombus burden had higher plasma Hsp-27 levels ([32.0 ± 8.6 vs. 58.0 ± 12.3] ng/mL, P < 0.001). The median value of Hsp-27 levels in all patients with STEMI was 45 ng/mL. Using the receiver operating characteristic (ROC) curve analysis, plasma Hsp-27 levels were of significant diagnostic value for high thrombus burden (AUC, 0.847; 95% CI, 0.775–0.918; P < 0.01). The multivariate cox regression analysis demonstrated that Hsp-27 > 45 ng/mL (HR 2.801, 95% CI 1.296–4.789, P = 0.001), were positively correlated with the incidence of major adverse cardiovascular events (MACE). Kaplan-Meier survival analysis demonstrated that MACE-free survival at 180-day follow-up was significantly lower in patients with Hsp-27 > 45 ng/mL (log rank = 10.28, P < 0.001). Our data demonstrate that plasma Hsp-27 was positively correlated with high thrombus burden and the incidence of MACE in patients with STEMI who underwent pPCI. PMID:29088740

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.

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.

Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis.

PubMed

Zhang, Yang; Xiao, Xiong; Zhang, Junting; Gao, Zhixian; Ji, Nan; Zhang, Liwei

2017-06-01

To evaluate the diagnostic accuracy of routine blood examinations and Cerebrospinal Fluid (CSF) lactate level for Post-neurosurgical Bacterial Meningitis (PBM) at a large sample-size of post-neurosurgical patients. The diagnostic accuracies of routine blood examinations and CSF lactate level to distinguish between PAM and PBM were evaluated with the values of the Area Under the Curve of the Receiver Operating Characteristic (AUC -ROC ) by retrospectively analyzing the datasets of post-neurosurgical patients in the clinical information databases. The diagnostic accuracy of routine blood examinations was relatively low (AUC -ROC <0.7). The CSF lactate level achieved rather high diagnostic accuracy (AUC -ROC =0.891; CI 95%, 0.852-0.922). The variables of patient age, operation duration, surgical diagnosis and postoperative days (the interval days between the neurosurgery and examinations) were shown to affect the diagnostic accuracy of these examinations. The variables were integrated with routine blood examinations and CSF lactate level by Fisher discriminant analysis to improve their diagnostic accuracy. As a result, the diagnostic accuracy of blood examinations and CSF lactate level was significantly improved with an AUC -ROC value=0.760 (CI 95%, 0.737-0.782) and 0.921 (CI 95%, 0.887-0.948) respectively. The PBM diagnostic accuracy of routine blood examinations was relatively low, whereas the accuracy of CSF lactate level was high. Some variables that are involved in the incidence of PBM can also affect the diagnostic accuracy for PBM. Taking into account the effects of these variables significantly improves the diagnostic accuracies of routine blood examinations and CSF lactate level. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tumor necrosis factor receptor 1 (TNFRI) for ventilator-associated pneumonia diagnosis by cytokine multiplex analysis.

PubMed

Martin-Loeches, Ignacio; Bos, Lieuwe D; Povoa, Pedro; Ramirez, Paula; Schultz, Marcus J; Torres, Antoni; Artigas, Antonio

2015-12-01

The diagnosis of ventilator-associated pneumonia (VAP) is challenging. An important aspect to improve outcome is early recognition of VAP and the initiation of the appropriate empirical treatment. We hypothesized that biological markers in plasma can rule out VAP at the moment of clinical suspicion and could rule in VAP before the diagnosis can be made clinically. In this prospective study, patients with VAP (n = 24, microbiology confirmed) were compared to controls (n = 19) with a similar duration of mechanical ventilation. Blood samples from the day of VAP diagnosis and 1 and 3 days before were analyzed with a multiplex array for markers of inflammation, coagulation, and apoptosis. The best biomarker combination was selected and the diagnostic accuracy was given by the area under the receiver operating characteristic curve (ROC-AUC). TNF-receptor 1 (TNFRI) and granulocyte colony-stimulating factor (GCSF) were selected as optimal biomarkers at the day of VAP diagnosis, which resulted in a ROC-AUC of 0.96, with excellent sensitivity. Three days before the diagnosis TNFRI and plasminogen activator inhibitor-1 (PAI-1) levels in plasma predicted VAP with a ROC-AUC of 0.79. The slope of IL-10 and PAI-1 resulted in a ROC-AUC of 0.77. These biomarkers improved the classification of the clinical pulmonary infection score when combined. Concentration of TNFRI and PAI-1 and the slope of PAI-1 and IL-10 may be used to predict the development of VAP as early as 3 days before the diagnosis made clinically. TNFRI and GCSF may be used to exclude VAP at the moment of clinical suspicion. Especially TNFRI seems to be a promising marker for the prediction and diagnosis of VAP.

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

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

PubMed

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

2016-09-01

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

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.

Expression and prognostic significance of CCL11/CCR3 in glioblastoma.

PubMed

Tian, Min; Chen, Lina; Ma, Li; Wang, Dandan; Shao, Bin; Wu, Jianyu; Wu, Hangyu; Jin, Yimin

2016-05-31

Glioblastoma (GBM) is the most lethal primary nervous system cancer, but due to its rarity and complexity, its pathogenesis is poorly understood. To identify potential tumorigenic factors in GBM, we screened antibody-based cytokine arrays and found that CCL11 was upregulated. We then demonstrated in vitro that both CCL11 and its receptor, CCR3, were overexpressed and promoted the proliferation, migration and invasion of cancer cells. To examine the clinical significance of CCL11/CCR3, 458 GBM samples were divided into a training cohort with 225 cases and a test cohort containing 233 cases. In the training set, immunohistochemical analysis showed overexpression of CCL11 and CCR3 were correlated with unfavorable overall survival (OS). We further developed a prognostic classifier combining CCL11 and CCR3 expression and Karnofsky performance status (KPS) for predicting one-year survival in GBM patients. Receiver operating characteristic (ROC) analysis demonstrated that this predictor achieved 90.7% sensitivity and 73.4% specificity. These results were validated with the test sample set. Our findings suggest that CCL11-CCR3 binding is involved in the progression of GBM and may prompt a novel therapeutic approach. In addition, CCL11 and CCR3 expression, combined with KPS, may be used as an accurate predictor of one-year survival in GBM patients.

Expression and prognostic significance of CCL11/CCR3 in glioblastoma

PubMed Central

Tian, Min; Chen, Lina; Ma, Li; Wang, Dandan; Shao, Bin; Wu, Jianyu; Wu, Hangyu; Jin, Yimin

2016-01-01

Glioblastoma (GBM) is the most lethal primary nervous system cancer, but due to its rarity and complexity, its pathogenesis is poorly understood. To identify potential tumorigenic factors in GBM, we screened antibody-based cytokine arrays and found that CCL11 was upregulated. We then demonstrated in vitro that both CCL11 and its receptor, CCR3, were overexpressed and promoted the proliferation, migration and invasion of cancer cells. To examine the clinical significance of CCL11/CCR3, 458 GBM samples were divided into a training cohort with 225 cases and a test cohort containing 233 cases. In the training set, immunohistochemical analysis showed overexpression of CCL11 and CCR3 were correlated with unfavorable overall survival (OS). We further developed a prognostic classifier combining CCL11 and CCR3 expression and Karnofsky performance status (KPS) for predicting one-year survival in GBM patients. Receiver operating characteristic (ROC) analysis demonstrated that this predictor achieved 90.7% sensitivity and 73.4% specificity. These results were validated with the test sample set. Our findings suggest that CCL11-CCR3 binding is involved in the progression of GBM and may prompt a novel therapeutic approach. In addition, CCL11 and CCR3 expression, combined with KPS, may be used as an accurate predictor of one-year survival in GBM patients. PMID:27119233

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.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

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

2014-01-01

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

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

PubMed

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

2015-01-01

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

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.

Differences in Clinical Features of Methamphetamine Users with Persistent Psychosis and Patients with Schizophrenia.

PubMed

Wang, Liang-Jen; Lin, Shih-Ku; Chen, Yi-Chih; Huang, Ming-Chyi; Chen, Tzu-Ting; Ree, Shao-Chun; Chen, Chih-Ken

Methamphetamine exerts neurotoxic effects and elicits psychotic symptoms. This study attempted to compare clinical differences between methamphetamine users with persistent psychosis (MAP) and patients with schizophrenia. In addition, we examined the discrimination validity by using symptom clusters to differentiate between MAP and schizophrenia. We enrolled 53 MAP patients and 53 patients with schizophrenia. The psychopathology of participants was assessed using the Chinese version of the Diagnostic Interview for Genetic Studies and the 18-item Brief Psychiatric Rating Scale. Logistic regression was used to examine the predicted probability scores of different symptom combinations on discriminating between MAP and schizophrenia. The receiver operating characteristic (ROC) analyses and area under the curve (AUC) were further applied to examine the discrimination validity of the predicted probability scores on differentiating between MAP and schizophrenia. We found that MAP and schizophrenia demonstrated similar patterns of delusions. Compared to patients with schizophrenia, MAP experienced significantly higher proportions of visual hallucinations and of somatic or tactile hallucinations. However, MAP exhibited significantly lower severity in conceptual disorganization, mannerism/posturing, blunted affect, emotional withdrawal, and motor retardation compared to patients with schizophrenia. The ROC analysis showed that a predicted probability score combining the aforementioned 7 items of symptoms could significantly differentiate between MAP and schizophrenia (AUC = 0.77). Findings in the current study suggest that nuanced differences might exist in the clinical presentation of secondary psychosis (MAP) and primary psychosis (schizophrenia). Combining the symptoms as a whole may help with differential diagnosis for MAP and schizophrenia. © 2016 S. Karger AG, Basel.

Comparison of the current AJCC-TNM numeric-based with a new anatomical location-based lymph node staging system for gastric cancer: A western experience.

PubMed

Galizia, Gennaro; Lieto, Eva; Auricchio, Annamaria; Cardella, Francesca; Mabilia, Andrea; Diana, Anna; Castellano, Paolo; De Vita, Ferdinando; Orditura, Michele

2017-01-01

In gastric cancer, the current AJCC numeric-based lymph node staging does not provide information on the anatomical extent of the disease and lymphadenectomy. A new anatomical location-based node staging, proposed by Choi, has shown better prognostic performance, thus soliciting Western world validation. Data from 284 gastric cancers undergoing radical surgery at the Second University of Naples from 2000 to 2014 were reviewed. The lymph nodes were reclassified into three groups (lesser and greater curvature, and extraperigastric nodes); presence of any metastatic lymph node in a given group was considered positive, prompting a new N and TNM stage classification. Receiver-operating-characteristic (ROC) curves for censored survival data and bootstrap methods were used to compare the capability of the two models to predict tumor recurrence. More than one third of node positive patients were reclassified into different N and TNM stages by the new system. Compared to the current staging system, the new classification significantly correlated with tumor recurrence rates and displayed improved indices of prognostic performance, such as the Bayesian information criterion and the Harrell C-index. Higher values at survival ROC analysis demonstrated a significantly better stratification of patients by the new system, mostly in the early phase of the follow-up, with a worse prognosis in more advanced new N stages, despite the same current N stage. This study suggests that the anatomical location-based classification of lymph node metastasis may be an important tool for gastric cancer prognosis and should be considered for future revision of the TNM staging system.

A strategy to optimize CT pediatric dose with a visual discrimination model

NASA Astrophysics Data System (ADS)

Gutierrez, Daniel; Gudinchet, François; Alamo-Maestre, Leonor T.; Bochud, François O.; Verdun, Francis R.

2008-03-01

Technological developments of computed tomography (CT) have led to a drastic increase of its clinical utilization, creating concerns about patient exposure. To better control dose to patients, we propose a methodology to find an objective compromise between dose and image quality by means of a visual discrimination model. A GE LightSpeed-Ultra scanner was used to perform the acquisitions. A QRM 3D low contrast resolution phantom (QRM - Germany) was scanned using CTDI vol values in the range of 1.7 to 103 mGy. Raw data obtained with the highest CTDI vol were afterwards processed to simulate dose reductions by white noise addition. Noise realism of the simulations was verified by comparing normalized noise power spectra aspect and amplitudes (NNPS) and standard deviation measurements. Patient images were acquired using the Diagnostic Reference Levels (DRL) proposed in Switzerland. Noise reduction was then simulated, as for the QRM phantom, to obtain five different CTDI vol levels, down to 3.0 mGy. Image quality of phantom images was assessed with the Sarnoff JNDmetrix visual discrimination model and compared to an assessment made by means of the ROC methodology, taken as a reference. For patient images a similar approach was taken but using as reference the Visual Grading Analysis (VGA) method. A relationship between Sarnoff JNDmetrix and ROC results was established for low contrast detection in phantom images, demonstrating that the Sarnoff JNDmetrix can be used for qualification of images with highly correlated noise. Patient image qualification showed a threshold of conspicuity loss only for children over 35 kg.

RNA-DNA hybrid (R-loop) immunoprecipitation mapping: an analytical workflow to evaluate inherent biases

PubMed Central

Halász, László; Karányi, Zsolt; Boros-Oláh, Beáta; Kuik-Rózsa, Tímea; Sipos, Éva; Nagy, Éva; Mosolygó-L, Ágnes; Mázló, Anett; Rajnavölgyi, Éva; Halmos, Gábor; Székvölgyi, Lóránt

2017-01-01

The impact of R-loops on the physiology and pathology of chromosomes has been demonstrated extensively by chromatin biology research. The progress in this field has been driven by technological advancement of R-loop mapping methods that largely relied on a single approach, DNA-RNA immunoprecipitation (DRIP). Most of the DRIP protocols use the experimental design that was developed by a few laboratories, without paying attention to the potential caveats that might affect the outcome of RNA-DNA hybrid mapping. To assess the accuracy and utility of this technology, we pursued an analytical approach to estimate inherent biases and errors in the DRIP protocol. By performing DRIP-sequencing, qPCR, and receiver operator characteristic (ROC) analysis, we tested the effect of formaldehyde fixation, cell lysis temperature, mode of genome fragmentation, and removal of free RNA on the efficacy of RNA-DNA hybrid detection and implemented workflows that were able to distinguish complex and weak DRIP signals in a noisy background with high confidence. We also show that some of the workflows perform poorly and generate random answers. Furthermore, we found that the most commonly used genome fragmentation method (restriction enzyme digestion) led to the overrepresentation of lengthy DRIP fragments over coding ORFs, and this bias was enhanced at the first exons. Biased genome sampling severely compromised mapping resolution and prevented the assignment of precise biological function to a significant fraction of R-loops. The revised workflow presented herein is established and optimized using objective ROC analyses and provides reproducible and highly specific RNA-DNA hybrid detection. PMID:28341774

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

Using the NANA toolkit at home to predict older adults' future depression.

PubMed

Andrews, J A; Harrison, R F; Brown, L J E; MacLean, L M; Hwang, F; Smith, T; Williams, E A; Timon, C; Adlam, T; Khadra, H; Astell, A J

2017-04-15

Depression is currently underdiagnosed among older adults. As part of the Novel Assessment of Nutrition and Aging (NANA) validation study, 40 older adults self-reported their mood using a touchscreen computer over three, one-week periods. Here, we demonstrate the potential of these data to predict future depression status. We analysed data from the NANA validation study using a machine learning approach. We applied the least absolute shrinkage and selection operator with a logistic model to averages of six measures of mood, with depression status according to the Geriatric Depression Scale 10 weeks later as the outcome variable. We tested multiple values of the selection parameter in order to produce a model with low deviance. We used a cross-validation framework to avoid overspecialisation, and receiver operating characteristic (ROC) curve analysis to determine the quality of the fitted model. The model we report contained coefficients for two variables: sadness and tiredness, as well as a constant. The cross-validated area under the ROC curve for this model was 0.88 (CI: 0.69-0.97). While results are based on a small sample, the methodology for the selection of variables appears suitable for the problem at hand, suggesting promise for a wider study and ultimate deployment with older adults at increased risk of depression. We have identified self-reported scales of sadness and tiredness as sensitive measures which have the potential to predict future depression status in older adults, partially addressing the problem of underdiagnosis. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease.

PubMed

Søreide, K; Thorsen, K; Søreide, J A

2015-02-01

Mortality prediction models for patients with perforated peptic ulcer (PPU) have not yielded consistent or highly accurate results. Given the complex nature of this disease, which has many non-linear associations with outcomes, we explored artificial neural networks (ANNs) to predict the complex interactions between the risk factors of PPU and death among patients with this condition. ANN modelling using a standard feed-forward, back-propagation neural network with three layers (i.e., an input layer, a hidden layer and an output layer) was used to predict the 30-day mortality of consecutive patients from a population-based cohort undergoing surgery for PPU. A receiver-operating characteristic (ROC) analysis was used to assess model accuracy. Of the 172 patients, 168 had their data included in the model; the data of 117 (70%) were used for the training set, and the data of 51 (39%) were used for the test set. The accuracy, as evaluated by area under the ROC curve (AUC), was best for an inclusive, multifactorial ANN model (AUC 0.90, 95% CIs 0.85-0.95; p < 0.001). This model outperformed standard predictive scores, including Boey and PULP. The importance of each variable decreased as the number of factors included in the ANN model increased. The prediction of death was most accurate when using an ANN model with several univariate influences on the outcome. This finding demonstrates that PPU is a highly complex disease for which clinical prognoses are likely difficult. The incorporation of computerised learning systems might enhance clinical judgments to improve decision making and outcome prediction.

Paired split-plot designs of multireader multicase studies.

PubMed

Chen, Weijie; Gong, Qi; Gallas, Brandon D

2018-07-01

The widely used multireader multicase ROC study design for comparing imaging modalities is the fully crossed (FC) design: every reader reads every case of both modalities. We investigate paired split-plot (PSP) designs that may allow for reduced cost and increased flexibility compared with the FC design. In the PSP design, case images from two modalities are read by the same readers, thereby the readings are paired across modalities. However, within each modality, not every reader reads every case. Instead, both the readers and the cases are partitioned into a fixed number of groups and each group of readers reads its own group of cases-a split-plot design. Using a [Formula: see text]-statistic based variance analysis for AUC (i.e., area under the ROC curve), we show analytically that precision can be gained by the PSP design as compared with the FC design with the same number of readers and readings. Equivalently, we show that the PSP design can achieve the same statistical power as the FC design with a reduced number of readings. The trade-off for the increased precision in the PSP design is the cost of collecting a larger number of truth-verified patient cases than the FC design. This means that one can trade-off between different sources of cost and choose a least burdensome design. We provide a validation study to show the iMRMC software can be reliably used for analyzing data from both FC and PSP designs. Finally, we demonstrate the advantages of the PSP design with a reader study comparing full-field digital mammography with screen-film mammography.

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.

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

PubMed Central

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

2015-01-01

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

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.

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.

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.

Standardized UXO Technology Demonstration Site, Blind Grid Scoring Record Number 842

DTIC Science & Technology

2007-06-01

collection sessions. Daily: A location identified as having no subsurface metal will be designated as a calibration point. Readings will be... metallic item will be placed below the center of the sensors, and the instrument’s response will be observed. The item will then be removed, and static... nonferrous anomalies. Due to limitations of the magnetometer, the nonferrous items cannot be detected. Therefore, the ROC curves presented in Figures

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.

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.

Revisiting the Roco G-protein cycle.

PubMed

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

2015-01-01

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

Attempted validation of the NUn score and inflammatory markers as predictors of esophageal anastomotic leak and major complications.

PubMed

Findlay, J M; Tilson, R C; Harikrishnan, A; Sgromo, B; Marshall, R E K; Maynard, N D; Gillies, R S; Middleton, M R

2015-10-01

The ability to predict complications following esophagectomy/extended total gastrectomy would be of great clinical value. A recent study demonstrated significant correlations between anastomotic leak (AL) and numerical values of C-reactive protein (CRP), white cell count (WCC) and albumin measured on postoperative day (POD) 4. A predictive model comprising all three (NUn score >10) was found to be highly sensitive and discriminant in predicting AL and complications. We attempted a retrospective validation in our center. Data were collected on all resections performed during a 5-year period (April 2008-2013) using prospectively maintained databases. Our biochemistry laboratory uses a maximum CRP value (156 mg/L), unlike that of the original study; otherwise all variables and outcome measures were comparable. Analysis was performed for all patients with complete blood results on POD4. Three hundred twenty-six patients underwent resection, of which 248 had POD4 bloods. There were 21 AL overall (6.44%); 16 among those with complete POD4 blood results (6.45%). There were 8 (2.45%) in-hospital deaths; 7 (2.82%) in those with POD4 results. No parameters were associated with AL or complication severity on univariate analysis. WCC was associated with AL in multivariate binary logistic regression with albumin and CRP (OR 1.23 [95% CI 1.03-1.47]; P = 0.021). When a binary variable of CRP ≥ 156 mg/L was used rather than an absolute value, no factors were significant. Mean NUn was 8.30 for AL, compared with 8.40 for non-AL (P = 0.710 independent t-test). NUn > 10 predicted 0 of 16 leaks (sensitivity 0.00%, specificity 94.4%, receiver operator curve [ROC] area under the curve [AUC] 0.485; P = 0.843). NUn > 7.65 was 93% sensitive and 21.6% specific. ROC for WCC alone was comparable with NUn (AUC 0.641 [0.504-0.779]; P = 0.059; WCC > 6.89 93.8% sensitive, 20.7% specific; WCC > 15 6.3% sensitive and 97% specific). There were no associations between any parameters and other complications. In a comparable cohort with the original study, we demonstrated a similar multivariate association between WCC alone on POD4 and subsequent demonstration of AL, but not albumin or CRP (measured up to 156 mg/L). The NUn score overall (calculated with this caveat) and a threshold of 10 was not found to have clinical utility in predicting AL or complications. © 2014 International Society for Diseases of the Esophagus.

Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Dwyer, Andrew J.; Summers, Ronald M.; Mollura, Daniel J.

2011-03-01

The 2009 pandemic is a global outbreak of novel H1N1 influenza. Radiologic images can be used to assess the presence and severity of pulmonary infection. We develop a computer-aided assessment system to analyze the CT images from Swine-Origin Influenza A virus (S-OIV) novel H1N1 cases. The technique is based on the analysis of lung texture patterns and classification using a support vector machine (SVM). Pixel-wise tissue classification is computed from the SVM value. The method was validated on four H1N1 cases and ten normal cases. We demonstrated that the technique can detect regions of pulmonary abnormality in novel H1N1 patients and differentiate these regions from visually normal lung (area under the ROC curve is 0.993). This technique can also be applied to differentiate regions infected by different pulmonary diseases.

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

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

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

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.

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

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2001-07-01

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

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

PubMed Central

Surujballi, Om; Mallory, Maria

2001-01-01

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

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.

Quantitative assessment of myocardial blood flow in coronary artery disease by cardiovascular magnetic resonance: comparison of Fermi and distributed parameter modeling against invasive methods.

PubMed

Papanastasiou, Giorgos; Williams, Michelle C; Dweck, Marc R; Alam, Shirjel; Cooper, Annette; Mirsadraee, Saeed; Newby, David E; Semple, Scott I

2016-09-13

Mathematical modeling of perfusion cardiovascular magnetic resonance (CMR) data allows absolute quantification of myocardial blood flow and can potentially improve the diagnosis and prognostication of obstructive coronary artery disease (CAD), against the current clinical standard of visual assessments. This study compares the diagnostic performance of distributed parameter modeling (DP) against the standard Fermi model, for the detection of obstructive CAD, in per vessel against per patient analysis. A pilot cohort of 28 subjects (24 included in the final analysis) with known or suspected CAD underwent adenosine stress-rest perfusion CMR at 3T. Data were analysed using Fermi and DP modeling against invasive coronary angiography and fractional flow reserve, acquired in all subjects. Obstructive CAD was defined as luminal stenosis of ≥70 % alone, or luminal stenosis ≥50 % and fractional flow reserve ≤0.80. On ROC analysis, DP modeling outperformed the standard Fermi model, in per vessel and per patient analysis. In per patient analysis, DP modeling-derived myocardial blood flow at stress demonstrated the highest sensitivity and specificity (0.96, 0.92) in detecting obstructive CAD, against Fermi modeling (0.78, 0.88) and visual assessments (0.79, 0.88), respectively. DP modeling demonstrated consistently increased diagnostic performance against Fermi modeling and showed that it may have merit for stratifying patients with at least one vessel with obstructive CAD. Clinicaltrials.gov NCT01368237 Registered 6 of June 2011. URL: https://clinicaltrials.gov/ct2/show/NCT01368237.

Screening for Generalized Anxiety Disorder in inpatient psychosomatic rehabilitation: pathological worry and the impact of depressive symptoms

PubMed Central

Salzer, Simone; Stiller, Christian; Tacke-Pook, Achim; Jacobi, Claus; Leibing, Eric

2009-01-01

Objective: Pathological worry is considered to be a defining feature for Generalized Anxiety Disorder (GAD). The Penn State Worry Questionnaire (PSWQ) is an instrument for assessing pathological worry. Two earlier studies demonstrated the suitability of the PSWQ as screening instrument for GAD in outpatient and non-clinical samples. This study examined the suitability of the PSWQ as a screening instrument for GAD in a German inpatient sample (N=237). Furthermore, a comparison of patients with GAD and patients with depression and other anxiety disorders regarding pathological worry and depression was carried out in a sub-sample of N=118 patients. Method: Cut-off scores optimizing sensitivity, optimizing specificity and simultaneously optimizing both sensitivity and specificity were calculated for the PSWQ score by receiver operating characteristic analysis (ROC). Differences regarding pathological worry and depression measured by the PSWQ and the Beck Depression Inventory (BDI) across five diagnostic subgroups were examined by conducting one-way ANOVAs. The influence of depression on pathological worry was controlled by conducting an ANCOVA with BDI score as a covariate. Results: The ROC analysis showed an area under the curve of AUC=.67 (p=0.02) with only 54.4% of the patients correctly classified. Comparison of diagnostic subgroups showed that after controlling the influence of depression, differences referring to pathological worry between diagnostic subgroups no longer existed. Conclusions: Contrary to the earlier results we found that the use of the PSWQ as a screening instrument for GAD at least in a sample of psychotherapy inpatients is not meaningful. Instead of that, the PSWQ can be used to discriminate high from low worriers in clinical samples. Thus, the instrument can be useful in establishing e.g. symptom-oriented group interventions as they are established in behavioural-medicine inpatient settings. Furthermore, our findings stress the influence of (comorbid) depressive symptoms on the process of worrying. PMID:19742048

Screening for Generalized Anxiety Disorder in inpatient psychosomatic rehabilitation: pathological worry and the impact of depressive symptoms.

PubMed

Salzer, Simone; Stiller, Christian; Tacke-Pook, Achim; Jacobi, Claus; Leibing, Eric

2009-07-09

Pathological worry is considered to be a defining feature for Generalized Anxiety Disorder (GAD). The Penn State Worry Questionnaire (PSWQ) is an instrument for assessing pathological worry. Two earlier studies demonstrated the suitability of the PSWQ as screening instrument for GAD in outpatient and non-clinical samples. This study examined the suitability of the PSWQ as a screening instrument for GAD in a German inpatient sample (N=237). Furthermore, a comparison of patients with GAD and patients with depression and other anxiety disorders regarding pathological worry and depression was carried out in a sub-sample of N=118 patients. Cut-off scores optimizing sensitivity, optimizing specificity and simultaneously optimizing both sensitivity and specificity were calculated for the PSWQ score by receiver operating characteristic analysis (ROC). Differences regarding pathological worry and depression measured by the PSWQ and the Beck Depression Inventory (BDI) across five diagnostic subgroups were examined by conducting one-way ANOVAs. The influence of depression on pathological worry was controlled by conducting an ANCOVA with BDI score as a covariate. The ROC analysis showed an area under the curve of AUC=.67 (p=0.02) with only 54.4% of the patients correctly classified. Comparison of diagnostic subgroups showed that after controlling the influence of depression, differences referring to pathological worry between diagnostic subgroups no longer existed. Contrary to the earlier results we found that the use of the PSWQ as a screening instrument for GAD at least in a sample of psychotherapy inpatients is not meaningful. Instead of that, the PSWQ can be used to discriminate high from low worriers in clinical samples. Thus, the instrument can be useful in establishing e.g. symptom-oriented group interventions as they are established in behavioural-medicine inpatient settings. Furthermore, our findings stress the influence of (comorbid) depressive symptoms on the process of worrying.

Molecular Profiling of Post-Reperfusion Milieu Determines Acute Kidney Injury after Liver Transplantation: a Prospective Study.

PubMed

Pulitano, Carlo; Ho, Phong; Verran, Deborah; Sandroussi, Charbel; Joseph, David; Bowen, David G; McCaughan, Geoffrey W; Crawford, Michael; Shackel, Nicholas

2018-04-23

Acute kidney injury (AKI) after liver transplantation (LT) is a common event, but its pathogenesis remains unclear. The aim of this prospective study is to investigate the potential relationship between post-reperfusion gene expression, serum mediators, and the onset of AKI after LT. Sixty-five consecutive patients undergoing LT were included in the study. Reverse transcription polymerase chain reaction (RT- PCR), was performed on liver biopsies. Gene expression of 23 genes involved in ischemia reperfusion injury (IRI) was evaluated. The serum concentrations of endothelin-1 (ET-1), and inflammatory cytokines were analyzed. AKI after LT developed in 21 (32%) recipients (AKI group). RT-PCR of reperfusion biopsy in AKI group showed higher expression of several genes involved in IRI compared to non-AKI group. Fold changes in the gene expression of ET-1, IL-18, and TNF-α were associated with creatinine peak value. AKI patients had also significantly higher ET-1, IL-18, and TNF-α postoperative serum levels. Multivariate analysis showed that ET-1 (OR 16.7, 95% CI 3.34-83.42, P = 0.001) and IL-18 (OR 5.27, 95% CI 0.99-27.82, P = 0.048) serum levels on POD1 were independently predictor of AKI. Receiver operator characteristic (ROC) analysis demonstrated that the combination of biomarkers ET-1+IL-18 was highly predictive of AKI (ROC-AUC 0.91, 95% CI: 0.83-0.99). Early allograft dysfunction and chronic kidney disease stage ≥ 2 occurred more frequently in AKI patients. These results suggest that the graft itself, rather than intraoperative hemodynamic instability plays a main role in AKI after LT. This data may have mechanistic and diagnostic implications for AKI after LT. This article is protected by copyright. All rights reserved. © 2018 by the American Association for the Study of Liver Diseases.

Usefulness of coronary calcium scoring to myocardial perfusion SPECT in the diagnosis of coronary artery disease in a predominantly high risk population.

PubMed

Schaap, Jeroen; Kauling, Robert M; Boekholdt, S Matthijs; Post, Martijn C; Van der Heyden, Jan A; de Kroon, Thom L; van Es, H Wouter; Rensing, Benno J W M; Verzijlbergen, J Fred

2013-03-01

Coronary calcium scoring (CCS) adds to the diagnostic performance of myocardial perfusion single-photon emission computed tomography (SPECT) to assess the presence of significant coronary artery disease (CAD). Patients with a high pre-test likelihood are expected to have a high CCS which potentially could enhance the diagnostic performance of myocardial perfusion SPECT in this specific patient group. We evaluated the added value of CCS to SPECT in the diagnosis of significant CAD in patients with an intermediate to high pre-test likelihood. In total, 129 patients (mean age 62.7 ± 9.7 years, 65 % male) with stable anginal complaints and intermediate to high pre-test likelihood of CAD (median 87 %, range 22-95) were prospectively included in this study. All patients received SPECT and CCS imaging preceding invasive coronary angiography (CA). Fractional flow reserve (FFR) measurements were acquired from patients with angiographically estimated 50-95 % obstructive CAD. For SPECT a SSS > 3 was defined significant CAD. For CCS the optimal cut-off value for significant CAD was determined by ROC curve analysis. The reference standard for significant CAD was a FFR of <0.80 acquired by CA. Significant CAD was demonstrated in 64 patients (49.6 %). Optimal CCS cut-off value for significant CAD was >182.5. ROC curve analysis for prediction of the presence of significant CAD for SPECT, CCS and the combination of CCS and SPECT resulted in an area under the curve (AUC) of 0.88 (95 % CI 81-94), 0.75 (95 % CI 66-83 %) and 0.92 (95 % CI 87-97 %) respectively. The difference of the AUC between SPECT and the combination of CCS and SPECT was 0.05 (P = 0.12). The addition of CCS did not significantly improve the diagnostic performance of SPECT in the evaluation of patients with a predominantly high pre-test likelihood of CAD.

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

PubMed

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

2015-03-01

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

A fractional motion diffusion model for grading pediatric brain tumors.

PubMed

Karaman, M Muge; Wang, He; Sui, Yi; Engelhard, Herbert H; Li, Yuhua; Zhou, Xiaohong Joe

2016-01-01

To demonstrate the feasibility of a novel fractional motion (FM) diffusion model for distinguishing low- versus high-grade pediatric brain tumors; and to investigate its possible advantage over apparent diffusion coefficient (ADC) and/or a previously reported continuous-time random-walk (CTRW) diffusion model. With approval from the institutional review board and written informed consents from the legal guardians of all participating patients, this study involved 70 children with histopathologically-proven brain tumors (30 low-grade and 40 high-grade). Multi- b -value diffusion images were acquired and analyzed using the FM, CTRW, and mono-exponential diffusion models. The FM parameters, D fm , φ , ψ (non-Gaussian diffusion statistical measures), and the CTRW parameters, D m , α , β (non-Gaussian temporal and spatial diffusion heterogeneity measures) were compared between the low- and high-grade tumor groups by using a Mann-Whitney-Wilcoxon U test. The performance of the FM model for differentiating between low- and high-grade tumors was evaluated and compared with that of the CTRW and the mono-exponential models using a receiver operating characteristic (ROC) analysis. The FM parameters were significantly lower ( p  < 0.0001) in the high-grade ( D fm : 0.81 ± 0.26, φ : 1.40 ± 0.10, ψ : 0.42 ± 0.11) than in the low-grade ( D fm : 1.52 ± 0.52, φ : 1.64 ± 0.13, ψ : 0.67 ± 0.13) tumor groups. The ROC analysis showed that the FM parameters offered better specificity (88% versus 73%), sensitivity (90% versus 82%), accuracy (88% versus 78%), and area under the curve (AUC, 93% versus 80%) in discriminating tumor malignancy compared to the conventional ADC. The performance of the FM model was similar to that of the CTRW model. Similar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.

Pre–Radiation Therapy Fluorine 18 Fluorodeoxyglucose PET Helps Identify Patients with Esophageal Cancer at High Risk for Radiation Pneumonitis

PubMed Central

Castillo, Richard; Pham, Ngoc; Castillo, Edward; Aso-Gonzalez, Samantha; Ansari, Sobiya; Hobbs, Brian; Palacio, Diana; Skinner, Heath

2015-01-01

Purpose To examine the association between pre–radiation therapy (RT) fluorine 18 fluorodeoxyglucose (FDG) uptake and post-RT symptomatic radiation pneumonitis (RP). Materials and Methods In accordance with the retrospective study protocol approved by the institutional review board, 228 esophageal cancer patients who underwent FDG PET/CT before chemotherapy and RT were examined. RP symptoms were evaluated by using the Common Terminology Criteria for Adverse Events, version 4.0, from the consensus of five clinicians. By using the cumulative distribution of standardized uptake values (SUVs) within the lungs, those values greater than 80%–95% of the total lung voxels were determined for each patient. The effect of pre-chemotherapy and RT FDG uptake, dose, and patient or treatment characteristics on RP toxicity was studied by using logistic regression. Results The study subjects were treated with three-dimensional conformal RT (n = 36), intensity-modulated RT (n = 135), or proton therapy (n = 57). Logistic regression analysis demonstrated elevated FDG uptake at pre-chemotherapy and RT was related to expression of RP symptoms. Study subjects with elevated 95% percentile of the SUV (SUV95) were more likely to develop symptomatic RP (P < .000012); each 0.1 unit increase in SUV95 was associated with a 1.36-fold increase in the odds of symptomatic RP. Receiver operating characteristic (ROC) curve analysis resulted in area under the ROC curve of 0.676 (95% confidence interval: 0.58, 0.77), sensitivity of 60%, and specificity of 71% at the 1.17 SUV95 threshold. CT imaging and dosimetric parameters were found to be poor predictors of RP symptoms. Conclusion The SUV95, a biomarker of pretreatment pulmonary metabolic activity, was shown to be prognostic of symptomatic RP. Elevation in this pretreatment biomarker identifies patients at high risk for posttreatment symptomatic RP. © RSNA, 2015 PMID:25584706

The Contribution of Whole Blood Viscosity to the Process of Aortic Valve Sclerosis.

PubMed

Sercelik, Alper; Besnili, Abbas Fikret

2018-01-01

We aimed to investigate whether increased whole blood viscosity (WBV) could be an important factor for the occurrence of aortic valve sclerosis (AVS). A total of 209 patients were enrolled in the study. WBV was calculated using the hematocrit and total plasma protein at a low shear rate (LSR) and a high shear rate (HSR). AVS was defined as irregular valve thickening and calcification (without evidence of outflow obstruction) documented by a peak transvalvular velocity < 2.5 m/s on echocardiographic examination. The patient group consisted of 109 patients with AVS (77 females, 32 males), and 100 subjects without AVS (65 females, 35 males) were assigned to the control group. In the AVS group, WBV values were significantly higher for HSR (17.4 ± 0.5 vs. 17.1 ± 0.7 208 s-1, p < 0.001) and LSR (65.9 ± 12.5 vs. 59.7 ± 16.7 0.5 s-1, p = 0.002). In multivariate logistic regression analysis, WBV at HSR and LSR were independent predictors of AVS (odds ratio, OR: 2.24, 95% confidence interval, CI: 1.38-3.64, p = 0.001; OR: 1.026, 95% CI: 1.006-1.046, p = 0.01, respectively). Receiver-operating characteristic (ROC) curve analysis indicated that a WBV cutoff value of 65.4 at LSR had a sensitivity of 46.8% and a specificity of 60.0% (area under the ROC curve, AUC: 0.615, 95% CI: 0.535-0.696, p = 0.004), and a WBV cutoff value of 17.1 at HSR had a sensitivity of 61.5% and specificity of 53% (AUC: 0.648, 95% CI: 0.571-0.725, p < 0.001) for the prediction of AVS. This study demonstrated that WBV was independently associated with AVS. WBV could be an indicator of inflammation and vessel remodeling without evidence of outflow obstruction. © 2018 The Author(s) Published by S. Karger AG, Basel.

Electron Transport in a Dioxygenase-Ferredoxin Complex: Long Range Charge Coupling between the Rieske and Non-Heme Iron Center

PubMed Central

Jono, Ryota; Shimizu, Kentaro

2016-01-01

Dioxygenase (dOx) utilizes stereospecific oxidation on aromatic molecules; consequently, dOx has potential applications in bioremediation and stereospecific oxidation synthesis. The reactive components of dOx comprise a Rieske structure Cys2[2Fe-2S]His2 and a non-heme reactive oxygen center (ROC). Between the Rieske structure and the ROC, a universally conserved Asp residue appears to bridge the two structures forming a Rieske-Asp-ROC triad, where the Asp is known to be essential for electron transfer processes. The Rieske and ROC share hydrogen bonds with Asp through their His ligands; suggesting an ideal network for electron transfer via the carboxyl side chain of Asp. Associated with the dOx is an itinerant charge carrying protein Ferredoxin (Fdx). Depending on the specific cognate, Fdx may also possess either the Rieske structure or a related structure known as 4-Cys-[2Fe-2S] (4-Cys). In this study, we extensively explore, at different levels of theory, the behavior of the individual components (Rieske and ROC) and their interaction together via the Asp using a variety of density function methods, basis sets, and a method known as Generalized Ionic Fragment Approach (GIFA) that permits setting up spin configurations manually. We also report results on the 4-Cys structure for comparison. The individual optimized structures are compared with observed spectroscopic data from the Rieske, 4-Cys and ROC structures (where information is available). The separate pieces are then combined together into a large Rieske-Asp-ROC (donor/bridge/acceptor) complex to estimate the overall coupling between individual components, based on changes to the partial charges. The results suggest that the partial charges are significantly altered when Asp bridges the Rieske and the ROC; hence, long range coupling through hydrogen bonding effects via the intercalated Asp bridge can drastically affect the partial charge distributions compared to the individual isolated structures. The results are consistent with a proton coupled electron transfer mechanism. PMID:27656882

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

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

USDA-ARS?s Scientific Manuscript database

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

Examining Classification Criteria: A Comparison of Three Cut Score Methods

ERIC Educational Resources Information Center

DiStefano, Christine; Morgan, Grant

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2005-01-01

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

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

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.

3D T2-weighted imaging to shorten multiparametric prostate MRI protocols.

PubMed

Polanec, Stephan H; Lazar, Mathias; Wengert, Georg J; Bickel, Hubert; Spick, Claudio; Susani, Martin; Shariat, Shahrokh; Clauser, Paola; Baltzer, Pascal A T

2018-04-01

To determine whether 3D acquisitions provide equivalent image quality, lesion delineation quality and PI-RADS v2 performance compared to 2D acquisitions in T2-weighted imaging of the prostate at 3 T. This IRB-approved, prospective study included 150 consecutive patients (mean age 63.7 years, 35-84 years; mean PSA 7.2 ng/ml, 0.4-31.1 ng/ml). Two uroradiologists (R1, R2) independently rated image quality and lesion delineation quality using a five-point ordinal scale and assigned a PI-RADS score for 2D and 3D T2-weighted image data sets. Data were compared using visual grading characteristics (VGC) and receiver operating characteristics (ROC)/area under the curve (AUC) analysis. Image quality was similarly good to excellent for 2D T2w (mean score R1, 4.3 ± 0.81; R2, 4.7 ± 0.83) and 3D T2w (mean score R1, 4.3 ± 0.82; R2, 4.7 ± 0.69), p = 0.269. Lesion delineation was rated good to excellent for 2D (mean score R1, 4.16 ± 0.81; R2, 4.19 ± 0.92) and 3D T2w (R1, 4.19 ± 0.94; R2, 4.27 ± 0.94) without significant differences (p = 0.785). ROC analysis showed an equivalent performance for 2D (AUC 0.580-0.623) and 3D (AUC 0.576-0.629) T2w (p > 0.05, respectively). Three-dimensional acquisitions demonstrated equivalent image and lesion delineation quality, and PI-RADS v2 performance, compared to 2D in T2-weighted imaging of the prostate. Three-dimensional T2-weighted imaging could be used to considerably shorten prostate MRI protocols in clinical practice. • 3D shows equivalent image quality and lesion delineation compared to 2D T2w. • 3D T2w and 2D T2w image acquisition demonstrated comparable diagnostic performance. • Using a single 3D T2w acquisition may shorten the protocol by 40%. • Combined with short DCE, multiparametric protocols of 10 min are feasible.

Secretome protein signature of human pancreatic cancer stem-like cells.

PubMed

Brandi, Jessica; Dalla Pozza, Elisa; Dando, Ilaria; Biondani, Giulia; Robotti, Elisa; Jenkins, Rosalind; Elliott, Victoria; Park, Kevin; Marengo, Emilio; Costello, Eithne; Scarpa, Aldo; Palmieri, Marta; Cecconi, Daniela

2016-03-16

Emerging research has demonstrated that pancreatic ductal adenocarcinoma (PDAC) contains a sub-population of cancer stem cells (CSCs) characterized by self-renewal, anchorage-independent-growth, long-term proliferation and chemoresistance. The secretome analysis of pancreatic CSCs has not yet been performed, although it may provide insight into tumour/microenvironment interactions and intracellular processes, as well as to identify potential biomarkers. To characterize the secreted proteins of pancreatic CSCs, we performed an iTRAQ-based proteomic analysis to compare the secretomes of Panc1 cancer stem-like cells (Panc1 CSCs) and parental cell line. A total of 72 proteins were found up-/down-regulated in the conditioned medium of Panc1 CSCs. The pathway analysis revealed modulation of vital physiological pathways including glycolysis, gluconeogenesis and pentose phosphate. Through ELISA immunoassays we analysed the presence of the three proteins most highly secreted by Panc1 CSCs (ceruloplasmin, galectin-3, and MARCKS) in sera of PDAC patient. ROC curve analysis suggests ceruloplasmin as promising marker for patients negative for CA19-9. Overall, our study provides a systemic secretome analysis of pancreatic CSCs revealing a number of secreted proteins which participate in pathological conditions including cancer differentiation, invasion and metastasis. They may serve as a valuable pool of proteins from which biomarkers and therapeutic targets can be identified. The secretome of CSCs is a rich reservoir of biomarkers of cancer progression and molecular therapeutic targets, and thus is a topic of great interest for cancer research. The secretome analysis of pancreatic CSCs has not yet been performed. Recently, our group has demonstrated that Panc-1 CSCs isolated from parental cell line by using the CSC selective medium, represent a model of great importance to deepen the understanding of the biology of pancreatic adenocarcinoma. To our knowledge, this is the first proteomic study of pancreatic CSC secretome. We performed an iTRAQ-based analysis to compare the secretomes of Panc1 CSCs and Panc1 parental cell line and identified a total of 43 proteins secreted at higher level by pancreatic cancer stem cells. We found modulation of different vital physiological pathways (such as glycolysis and gluconeogenesis, pentose phosphate pathway) and the involvement of CSC secreted proteins (for example 72kDa type IV collagenase, galectin-3, alpha-actinin-4, and MARCKS) in pathological conditions including cancer differentiation, invasion and metastasis. By ELISA verification we found that MARCKS and ceruloplasmin discriminate between controls and PDAC patients; in addition ROC curve analyses indicate that MARCKS does not have diagnostic accuracy, while ceruloplasmin could be a promising marker only for patients negative for CA19-9. We think that the findings reported in our manuscript advance the understanding of the pathways implicated in tumourigenesis, metastasis and chemoresistance of pancreatic cancer, and also identify a pool of proteins from which novel candidate diagnostic and therapeutic biomarkers could be discovered. Copyright © 2016 Elsevier B.V. All rights reserved.

Can a toxin gene NAAT be used to predict toxin EIA and the severity of Clostridium difficile infection?

PubMed

Garvey, Mark I; Bradley, Craig W; Wilkinson, Martyn A C; Holden, Elisabeth

2017-01-01

Diagnosis of C. difficile infection (CDI) is controversial because of the many laboratory methods available and their lack of ability to distinguish between carriage, mild or severe disease. Here we describe whether a low C. difficile toxin B nucleic acid amplification test (NAAT) cycle threshold (CT) can predict toxin EIA, CDI severity and mortality. A three-stage algorithm was employed for CDI testing, comprising a screening test for glutamate dehydrogenase (GDH), followed by a NAAT, then a toxin enzyme immunoassay (EIA). All diarrhoeal samples positive for GDH and NAAT between 2012 and 2016 were analysed. The performance of the NAAT CT value as a classifier of toxin EIA outcome was analysed using a ROC curve; patient mortality was compared to CTs and toxin EIA via linear regression models. A CT value ≤26 was associated with ≥72% toxin EIA positivity; applying a logistic regression model we demonstrated an association between low CT values and toxin EIA positivity. A CT value of ≤26 was significantly associated ( p  = 0.0262) with increased one month mortality, severe cases of CDI or failure of first line treatment. The ROC curve probabilities demonstrated a CT cut off value of 26.6. Here we demonstrate that a CT ≤26 indicates more severe CDI and is associated with higher mortality. Samples with a low CT value are often toxin EIA positive, questioning the need for this additional EIA test. A CT ≤26 could be used to assess the potential for severity of CDI and guide patient treatment.

Standardized UXO Technology Demonstration Site Blind Grid Scoring Record Number 909 (Sky Research, Inc.)

DTIC Science & Technology

2008-09-01

heading north from the southern end point, and then returning south from the northern end point. 2) A metallic pin-flag is placed over the midpoint...test involves traverses across a known point located away from buried UXO or other metallic debris. A 5-meter- length of line is walked in eight...ferrous and nonferrous anomalies. Due to limitations of the magnetometer, the nonferrous items cannot be detected. Therefore, the ROC curves

Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets

DTIC Science & Technology

2012-12-01

curves of the proposed method and that of Fails et al.. For the kNN ROC curve, k = 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81...et al. [6] and Ramachandran et al. [7] both demonstrated success in detecting mines using the k-nearest-neighbor ( kNN ) algorithm based on the EMI...error is also included in the feature vector. The kNN labels an unknown target based on the closest targets in a training set. Collins et al. [2] and

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.

Use of an objective structured clinical exam (OSCE) for early identification of communication skills deficits in interns.

PubMed

Goldhamer, Mary Ellen J; Cohen, Amy; Brooks, Michelle; Macklin, Eric A; Co, John Patrick T; Weinstein, Debra

2018-01-01

There is limited information about whether OSCE during GME orientation can identify trainee communication deficits before these become evident via clinical performance evaluations. Ninety-seven interns matriculating to eight residency programs in six specialties at four hospitals participated in a nine-station communication skills OSCE. Ratings were based on the "Kalamazoo, adapted" communication skills checklist. Possible association with intern performance evaluations was assessed by repeated-measures logistic regression and ROC curves were generated. The mean OSCE score was 4.08 ± 0.27 with a range of 3.3-4.6. Baseline OSCE scores were associated with subsequent communication concerns recorded by faculty, based on 1591 evaluations. A 0.1-unit decrease in the OSCE communication score was associated with an 18% higher odds of being identified with a communication concern by faculty evaluation (odds ratio 1.18, 95% CI 1.01-1.36, p = 0.034). ROC curves did not demonstrate a "cut-off" score (AUC= 0.558). Non-faculty evaluators were 3-5 times more likely than faculty evaluators to identify communication deficits, based on 1900 evaluations. Lower OSCE performance was associated with faculty communication concerns on performance evaluations; however, a "cut-off" score was not demonstrated that could identify trainees for potential early intervention. Multi-source evaluation also identified trainees with communication skills deficits.

Lung Injury Prediction Score Is Useful in Predicting Acute Respiratory Distress Syndrome and Mortality in Surgical Critical Care Patients

PubMed Central

Bauman, Zachary M.; Gassner, Marika Y.; Coughlin, Megan A.; Mahan, Meredith; Watras, Jill

2015-01-01

Background. Lung injury prediction score (LIPS) is valuable for early recognition of ventilated patients at high risk for developing acute respiratory distress syndrome (ARDS). This study analyzes the value of LIPS in predicting ARDS and mortality among ventilated surgical patients. Methods. IRB approved, prospective observational study including all ventilated patients admitted to the surgical intensive care unit at a single tertiary center over 6 months. ARDS was defined using the Berlin criteria. LIPS were calculated for all patients and analyzed. Logistic regression models evaluated the ability of LIPS to predict development of ARDS and mortality. A receiver operator characteristic (ROC) curve demonstrated the optimal LIPS value to statistically predict development of ARDS. Results. 268 ventilated patients were observed; 141 developed ARDS and 127 did not. The average LIPS for patients who developed ARDS was 8.8 ± 2.8 versus 5.4 ± 2.8 for those who did not (p < 0.001). An ROC area under the curve of 0.79 demonstrates LIPS is statistically powerful for predicting ARDS development. Furthermore, for every 1-unit increase in LIPS, the odds of developing ARDS increase by 1.50 (p < 0.001) and odds of ICU mortality increase by 1.22 (p < 0.001). Conclusion. LIPS is reliable for predicting development of ARDS and predicting mortality in critically ill surgical patients. PMID:26301105

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

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

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.

Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles

PubMed Central

2016-01-01

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

Hypoxia-induced HIF1α targets in melanocytes reveal a molecular profile associated with poor melanoma prognosis

PubMed Central

Loftus, Stacie K.; Baxter, Laura L.; Cronin, Julia C.; Fufa, Temesgen D.; Pavan, William J.

2017-01-01

Summary Hypoxia and HIF1α signaling direct tissue-specific gene responses regulating tumor progression, invasion and metastasis. By integrating HIF1α knockdown and hypoxia-induced gene expression changes, this study identifies a melanocyte-specific, HIF1α-dependent/hypoxia-responsive gene expression signature. Integration of these gene expression changes with HIF1α ChIP-Seq analysis identifies 81 HIF1α direct target genes in melanocytes. The expression levels for ten of the HIF1α direct targets – GAPDH, PKM, PPAT, DARS, DTWD1, SEH1L, ZNF292, RLF, AGTRAP, and GPC6 – are significantly correlated with reduced time of Disease Free Status (DFS) in melanoma by logistic regression (P-value =0.0013) and ROC curve analysis (AUC= 0.826, P-value<0.0001). This HIF1α-regulated profile defines a melanocyte-specific response under hypoxia, and demonstrates the role of HIF1α as an invasive cell state gatekeeper in regulating cellular metabolism, chromatin and transcriptional regulation, vascularization and invasion. PMID:28168807

Clinical, radiological, and physiological differences between obliterative bronchiolitis and problematic severe asthma in adolescents and young adults: the early origins of the overlap syndrome?

PubMed

Bandeira, Teresa; Negreiro, Filipa; Ferreira, Rosário; Salgueiro, Marisa; Lobo, Luísa; Aguiar, Pedro; Trindade, J C

2011-06-01

Few reports have compared chronic obstructive lung diseases (OLDs) starting in childhood. To describe functional, radiological, and biological features of obliterative bronchiolitis (OB) and further discriminate to problematic severe asthma (PSA) or to diagnose a group with overlapping features. Patients with OB showed a greater degree of obstructive lung defect and higher hyperinflation (P < 0.001). The most frequent high-resolution computed tomography (HRCT) features (increased lung volume, inspiratory decreased attenuation, mosaic pattern, and expiratory air trapping) showed significantly greater scores in OB patients. Patients with PSA have shown a higher frequency of atopy (P < 0.05). ROC curve analysis demonstrated discriminative power for the LF variables, HRCT findings and for atopy between diagnoses. Further analysis released five final variables more accurate for the identification of a third diagnostic group (FVC%t, post-bronchodilator ΔFEV(1) in ml, HRCT mosaic pattern, SPT, and D. pteronyssinus-specific IgE). We found that OB and PSA possess identifiable characteristic features but overlapping values may turn them undistinguishable. Copyright © 2011 Wiley-Liss, Inc.

A Simple and Effective Physical Characteristic Profiling Method for Methamphetamine Tablet Seized in China.

PubMed

Li, Tao; Hua, Zhendong; Meng, Xin; Liu, Cuimei

2018-03-01

Methamphetamine (MA) tablet production confers chemical and physical properties. This study developed a simple and effective physical characteristic profiling method for MA tablets with capital letter "WY" logos, which realized the discrimination between linked and unlinked seizures. Seventeen signature distances extracted from the "WY" logo were explored as factors for multivariate analysis and demonstrated to be effective to represent the features of tablets in the drug intelligence perspective. Receiver operating characteristic (ROC) curve was used to evaluate efficiency of different pretreatments and distance/correlation metrics, while "Standardization + Euclidean" and "Logarithm + Euclidean" algorithms outperformed the rest. Finally, hierarchical cluster analysis (HCA) was applied to the data set of 200 MA tablet seizures randomly selected from cases all around China in 2015, and 76% of them were classified into a group named after "WY-001." Moreover, the "WY-001" tablets occupied 51-80% tablet seizures from 2011 to 2015 in China, indicating the existence of a huge clandestine factory incessantly manufacturing MA tablets. © 2017 American Academy of Forensic Sciences.

Liver fibrosis: in vivo evaluation using intravoxel incoherent motion-derived histogram metrics with histopathologic findings at 3.0 T.

PubMed

Hu, Fubi; Yang, Ru; Huang, Zixing; Wang, Min; Zhang, Hanmei; Yan, Xu; Song, Bin

2017-12-01

To retrospectively determine the feasibility of intravoxel incoherent motion (IVIM) imaging based on histogram analysis for the staging of liver fibrosis (LF) using histopathologic findings as the reference standard. 56 consecutive patients (14 men, 42 women; age range, 15-76, years) with chronic liver diseases (CLDs) were studied using IVIM-DWI with 9 b-values (0, 25, 50, 75, 100, 150, 200, 500, 800 s/mm 2 ) at 3.0 T. Fibrosis stage was evaluated using the METAVIR scoring system. Histogram metrics including mean, standard deviation (Std), skewness, kurtosis, minimum (Min), maximum (Max), range, interquartile (Iq) range, and percentiles (10, 25, 50, 75, 90th) were extracted from apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps. All histogram metrics among different fibrosis groups were compared using one-way analysis of variance or nonparametric Kruskal-Wallis test. For significant parameters, receivers operating characteristic curve (ROC) analyses were further performed for the staging of LF. Based on their METAVIR stage, the 56 patients were reclassified into three groups as follows: F0-1 group (n = 25), F2-3 group (n = 21), and F4 group (n = 10). The mean, Iq range, percentiles (50, 75, and 90th) of D* maps between the groups were significant differences (all P < 0.05). Area under the ROC curve (AUC) of the mean, Iq range, 50, 75, and 90th percentile of D* maps for identifying significant LF (≥F2 stage) was 0.901, 0.859, 0.876, 0.943, and 0.886 (all P < 0.0001), respectively; for diagnosing severe fibrosis or cirrhosis (F4), AUC was 0.917, 0.922, 0.943, 0.985, and 0.939 (all P < 0.0001), respectively. The histogram metrics of ADC, D, and f maps demonstrated no significant difference among the groups (all P > 0.05). Histogram analysis of D* map derived from IVIM can be used to stage liver fibrosis in patients with CLDs and provide more quantitative information beyond the mean value.

Markov model plus k-word distributions: a synergy that produces novel statistical measures for sequence comparison.

PubMed

Dai, Qi; Yang, Yanchun; Wang, Tianming

2008-10-15

Many proposed statistical measures can efficiently compare biological sequences to further infer their structures, functions and evolutionary information. They are related in spirit because all the ideas for sequence comparison try to use the information on the k-word distributions, Markov model or both. Motivated by adding k-word distributions to Markov model directly, we investigated two novel statistical measures for sequence comparison, called wre.k.r and S2.k.r. The proposed measures were tested by similarity search, evaluation on functionally related regulatory sequences and phylogenetic analysis. This offers the systematic and quantitative experimental assessment of our measures. Moreover, we compared our achievements with these based on alignment or alignment-free. We grouped our experiments into two sets. The first one, performed via ROC (receiver operating curve) analysis, aims at assessing the intrinsic ability of our statistical measures to search for similar sequences from a database and discriminate functionally related regulatory sequences from unrelated sequences. The second one aims at assessing how well our statistical measure is used for phylogenetic analysis. The experimental assessment demonstrates that our similarity measures intending to incorporate k-word distributions into Markov model are more efficient.

Diagnostic accuracy of atypical p-ANCA in autoimmune hepatitis using ROC- and multivariate regression analysis.

PubMed

Terjung, B; Bogsch, F; Klein, R; Söhne, J; Reichel, C; Wasmuth, J-C; Beuers, U; Sauerbruch, T; Spengler, U

2004-09-29

Antineutrophil cytoplasmic antibodies (atypical p-ANCA) are detected at high prevalence in sera from patients with autoimmune hepatitis (AIH), but their diagnostic relevance for AIH has not been systematically evaluated so far. Here, we studied sera from 357 patients with autoimmune (autoimmune hepatitis n=175, primary sclerosing cholangitis (PSC) n=35, primary biliary cirrhosis n=45), non-autoimmune chronic liver disease (alcoholic liver cirrhosis n=62; chronic hepatitis C virus infection (HCV) n=21) or healthy controls (n=19) for the presence of various non-organ specific autoantibodies. Atypical p-ANCA, antinuclear antibodies (ANA), antibodies against smooth muscles (SMA), antibodies against liver/kidney microsomes (anti-Lkm1) and antimitochondrial antibodies (AMA) were detected by indirect immunofluorescence microscopy, antibodies against the M2 antigen (anti-M2), antibodies against soluble liver antigen (anti-SLA/LP) and anti-Lkm1 by using enzyme linked immunosorbent assays. To define the diagnostic precision of the autoantibodies, results of autoantibody testing were analyzed by receiver operating characteristics (ROC) and forward conditional logistic regression analysis. Atypical p-ANCA were detected at high prevalence in sera from patients with AIH (81%) and PSC (94%). ROC- and logistic regression analysis revealed atypical p-ANCA and SMA, but not ANA as significant diagnostic seromarkers for AIH (atypical p-ANCA: AUC 0.754+/-0.026, odds ratio [OR] 3.4; SMA: 0.652+/-0.028, OR 4.1). Atypical p-ANCA also emerged as the only diagnostically relevant seromarker for PSC (AUC 0.690+/-0.04, OR 3.4). None of the tested antibodies yielded a significant diagnostic accuracy for patients with alcoholic liver cirrhosis, HCV or healthy controls. Atypical p-ANCA along with SMA represent a seromarker with high diagnostic accuracy for AIH and should be explicitly considered in a revised version of the diagnostic score for AIH.

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.

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

PubMed

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

2018-05-01

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

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

PubMed

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

2017-03-01

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

The Weiss Functional Impairment Rating Scale-Parent Form for assessing ADHD: evaluating diagnostic accuracy and determining optimal thresholds using ROC analysis.

PubMed

Thompson, Trevor; Lloyd, Andrew; Joseph, Alain; Weiss, Margaret

2017-07-01

The Weiss Functional Impairment Rating Scale-Parent Form (WFIRS-P) is a 50-item scale that assesses functional impairment on six clinically relevant domains typically affected in attention-deficit/hyperactivity disorder (ADHD). As functional impairment is central to ADHD, the WFIRS-P offers potential as a tool for assessing functional impairment in ADHD. These analyses were designed to examine the overall performance of WFIRS-P in differentiating ADHD and non-ADHD cases using receiver operating characteristics (ROC) analysis. This is the first attempt to empirically determine the level of functional impairment that differentiates ADHD children from normal controls. This observational study comprised 5-19-year-olds with physician-diagnosed ADHD (n = 476) and non-ADHD controls (n = 202). ROC analysis evaluated the ability of WFIRS-P to discriminate between ADHD and non-ADHD, and identified a WFIRS-P cut-off score that optimises correct classification. Data were analysed for the complete sample, for males versus females and for participants in two age groups (5-12 versus 13-19 years). Area under the curve (AUC) was 0.91 (95% confidence interval 0.88-0.93) for the overall WFIRS-P score, suggesting highly accurate classification of ADHD distinct from non-ADHD. Sensitivity (0.83) and specificity (0.85) were maximal for a mean overall WFIRS-P score of 0.65, suggesting that this is an appropriate threshold for differentiation. DeLong's test found no significant differences in AUCs for males versus females or 5-12 versus 13-19 years, suggesting that WFIRS-P is an accurate classifier of ADHD across gender and age. When assessing function, WFIRS-P appears to provide a simple and effective basis for differentiating between individuals with/without ADHD in terms of functional impairment. Disease-specific applications of QOL research.

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

PubMed

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

2011-12-28

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

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

PubMed

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

2011-08-01

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

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

PubMed Central

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

2017-01-01

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

Cut-Offs and Response Criteria for the Hospital Universitario La Princesa Index (HUPI) and Their Comparison to Widely-Used Indices of Disease Activity in Rheumatoid Arthritis.

PubMed

González-Álvaro, Isidoro; Castrejón, Isabel; Ortiz, Ana M; Toledano, Esther; Castañeda, Santos; García-Vadillo, Alberto; Carmona, Loreto

2016-01-01

To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal [PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide [EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if ≤2, low disease activity if >2 and ≤5), moderate if >5 and <9 and high if ≥9. HUPI's AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28's AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis.

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

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

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

1994-05-01

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