scholarly journals Low cut-off value of serum (1,3)-beta-d-glucan for the diagnosis of Pneumocystis pneumonia in non-HIV patients: a retrospective cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jumpei Taniguchi ◽  
Kei Nakashima ◽  
Hiroki Matsui ◽  
Tomohisa Watari ◽  
Ayumu Otsuki ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Medical Center ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Pneumocystis Pneumonia ◽  
Polymerase Chain Reaction Test ◽  
Negative Results ◽  
Chain Reaction Test ◽  
Receiver Operating

Abstract Background Non-human immunodeficiency virus (HIV) Pneumocystis pneumonia (PCP) is a fulminant disease with an increasing incidence. The serum beta-d-glucan (BDG) assay is used as an adjunct to the diagnosis of PCP; however, the cut-off value for this assay is not well-defined, especially in the non-HIV PCP population. Therefore, we aimed to identify the assay cut-off value for this population. Methods In this retrospective observational study, we reviewed the medical records of all patients (≥ 18 years old) with clinical suspicion of PCP who underwent evaluation of respiratory tract specimens between December 2008 and June 2014 at Kameda Medical Center. We created a receiver operating characteristic curve and calculated the area under the curve to determine the cut-off value for evaluating the inspection accuracy of the BDG assay. Results A total of 173 patients were included in the study. Fifty patients showed positive results in specimen staining, loop-mediated isothermal amplification assay, and polymerase chain reaction test, while 123 patients showed negative results. The receiver operating characteristic analyses suggested that the BDG cut-off level was 8.5 pg/mL, with a sensitivity and specificity of 76% and 76%, respectively. Conclusions The Wako-BDG cut-off value for the diagnosis of non-HIV PCP is 8.5 pg/mL, which is lower than the classical cut-off value from previous studies. Clinicians should potentially consider this lower BDG cut-off value in the diagnosis and management of patients with non-HIV PCP. Trial registration: The participants were retrospectively registered.

scholarly journals miR-142-3p as a novel biomarker for predicting poor prognosis in renal cell carcinoma patients after surgery

2019 ◽  
Vol 34 (3) ◽  
pp. 302-308 ◽  
Author(s):  
Xiqi Peng ◽  
Xiang Pan ◽  
Kaihao Liu ◽  
Chunduo Zhang ◽  
Liwen Zhao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Receiver Operating Characteristic ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Poor Prognosis ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Receiver Operating

Background: miR-142-3p has proved to be involved in tumorigenesis and the development of renal cell carcinoma. The present study aimed to explore the prognostic value of miR-142-3p. Methods: Total RNA was extracted from renal cell carcinoma specimens and the expression level of miR-142-3p was measured. Pearson Chi-square test, Kaplan–Meier analysis, as well as univariate and multivariate regression analysis were performed to determine the correlation between miR-142-3p and the prognosis of renal cell carcinoma patients. Receiver operating characteristic curves were constructed to evaluate the predictive efficiency of miR-142-3p for the prognosis of renal cell carcinoma patients. Data from The Cancer Genome Atlas (TCGA) were utilized to validate our findings. Results: Our results demonstrated that upregulation of miR-142-3p was correlated with shorter overall survival (P=0.002) and was, in the meantime, an independent prognostic factor for renal cell carcinoma patients (P=0.002). The receiver operating characteristic curve combining miR-142-3p expression with tumor stage showed an area under the curve of 0.633 (95% confidence interval 0.563, 0.702). The result of TCGA data was consistent with our findings. Conclusions: Our results suggest miR-142-3p expression is correlated with poor prognosis of renal cell carcinoma patients and may serve as a prognostic biomarker in the future.

A simple method to estimate the time-dependent receiver operating characteristic curve and the area under the curve with right censored data

2016 ◽  
Vol 27 (8) ◽  
pp. 2264-2278 ◽  
Author(s):  
Liang Li ◽  
Tom Greene ◽  
Bo Hu
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Disease Onset ◽  
Area Under The Curve ◽  
Time Dependent ◽  
Operating Characteristic Curve ◽  
Receiver Operating

The time-dependent receiver operating characteristic curve is often used to study the diagnostic accuracy of a single continuous biomarker, measured at baseline, on the onset of a disease condition when the disease onset may occur at different times during the follow-up and hence may be right censored. Due to right censoring, the true disease onset status prior to the pre-specified time horizon may be unknown for some patients, which causes difficulty in calculating the time-dependent sensitivity and specificity. We propose to estimate the time-dependent sensitivity and specificity by weighting the censored data by the conditional probability of disease onset prior to the time horizon given the biomarker, the observed time to event, and the censoring indicator, with the weights calculated nonparametrically through a kernel regression on time to event. With this nonparametric weighting adjustment, we derive a novel, closed-form formula to calculate the area under the time-dependent receiver operating characteristic curve. We demonstrate through numerical study and theoretical arguments that the proposed method is insensitive to misspecification of the kernel bandwidth, produces unbiased and efficient estimators of time-dependent sensitivity and specificity, the area under the curve, and other estimands from the receiver operating characteristic curve, and outperforms several other published methods currently implemented in R packages.

scholarly journals Risk assessment and receiver operating characteristic curves

2011 ◽  
Vol 42 (5) ◽  
pp. 895-898 ◽  
Author(s):  
G. Szmukler ◽  
B. Everitt ◽  
M. Leese
Keyword(s):  
Risk Assessment ◽  
Clinical Practice ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Assessment Instruments ◽  
Receiver Operating Characteristic Curves ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Risk assessment is now regarded as a necessary competence in psychiatry. The area under the curve (AUC) statistic of the receiver operating characteristic curve is increasingly offered as the main evidence for accuracy of risk assessment instruments. But, even a highly statistically significant AUC is of limited value in clinical practice.

scholarly journals COMPARISION OF BINARY DIAGNOSTIC PREDICTORS USING ENTROPY

2018 ◽  
Vol 6 (1) ◽  
pp. 440-447
Author(s):  
Kathare Alfred ◽  
Otieno Argwings ◽  
Kimeli Victor
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Gold Standard ◽  
Large Scale ◽  
Operating Characteristic ◽  
Standard Procedure ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Operating Characteristic Curve ◽  
Receiver Operating

The use of gold standard procedures in screening may be costly, risky or even unethical. It is, therefore, not admissible for large scale application. In this case, a more acceptable diagnostic predictor is applied to a sample of subjects alongside a gold standard procedure. The performance of the predictor is then evaluated using Receiver Operating Characteristic curve. The area under the curve, then, provides a summative measure of the performance of the predictor. The Receiver Operating Characteristic curve is a trade-off between sensitivity and specificity which in most cases are of different clinical significance. Also, the area under the curve is criticized for lack of coherent interpretation. In this study, we proposed the use of entropy as a summary index measure of uncertainty to compare diagnostic predictors. Noting that a diseased subject who is truly identified with the disease at a lower cut-off will also be identified at a higher cut-off, we substituted time variable in survival analysis for cut-offs in a binary predictor. We then derived the entropy of the functions of diagnostic predictors. Application of the procedure to real data showed that entropy was a strong measure for quantifying the amount of uncertainty engulfed in a set of cut-offs of binary diagnostic predictor.

The area under the generalized receiver-operating characteristic curve

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Pablo Martínez-Camblor ◽  
Sonia Pérez-Fernández ◽  
Susana Díaz-Coto
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Asymptotic Variance ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Finite Samples ◽  
Real World Problem ◽  
Graphical Tool ◽  
Receiver Operating

Abstract The receiver operating-characteristic (ROC) curve is a well-known graphical tool routinely used for evaluating the discriminatory ability of continuous markers, referring to a binary characteristic. The area under the curve (AUC) has been proposed as a summarized accuracy index. Higher values of the marker are usually associated with higher probabilities of having the characteristic under study. However, there are other situations where both, higher and lower marker scores, are associated with a positive result. The generalized ROC (gROC) curve has been proposed as a proper extension of the ROC curve to fit these situations. Of course, the corresponding area under the gROC curve, gAUC, has also been introduced as a global measure of the classification capacity. In this paper, we study in deep the gAUC properties. The weak convergence of its empirical estimator is provided while deriving an explicit and useful expression for the asymptotic variance. We also obtain the expression for the asymptotic covariance of related gAUCs and propose a non-parametric procedure to compare them. The finite-samples behavior is studied through Monte Carlo simulations under different scenarios, presenting a real-world problem in order to illustrate its practical application. The R code functions implementing the procedures are provided as Supplementary Material.

scholarly journals Prediction of Advisability of Returning Home Using the Home Care Score

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Akiyoshi Matsugi ◽  
Keisuke Tani ◽  
Yoshiki Tamaru ◽  
Nami Yoshioka ◽  
Akira Yamashita ◽  
...  
Keyword(s):  
Home Care ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Functional Independence Measure ◽  
Functional Independence ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Purpose. The aim of this study was to assess whether the home care score (HCS), which was developed by the Ministry of Health and Welfare in Japan in 1992, is useful for the prediction of advisability of home care.Methods. Subjects living at home and in assisted-living facilities were analyzed. Binominal logistic regression analyses, using age, sex, the functional independence measure score, and the HCS, along with receiver operating characteristic curve analyses, were conducted.Findings/Conclusions. Only HCS was selected for the regression equation. Receiver operating characteristic curve analysis revealed that the area under the curve (0.9), sensitivity (0.82), specificity (0.83), and positive predictive value (0.84) for HCS were higher than those for the functional independence measure, indicating that the HCS is a powerful predictor for advisability of home care.Clinical Relevance. Comprehensive measurements of the condition of provided care and the activities of daily living of the subjects, which are included in the HCS, are required for the prediction of advisability of home care.

scholarly journals Value of Fractional Uric Acid Excretion in Differential Diagnosis of Hyponatremic Patients on Diuretics

2008 ◽  
Vol 93 (8) ◽  
pp. 2991-2997 ◽  
Author(s):  
Wiebke Fenske ◽  
Stefan Störk ◽  
Ann-Cathrin Koschker ◽  
Anne Blechschmidt ◽  
Daniela Lorenz ◽  
...  
Keyword(s):  
Uric Acid ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Diuretic Therapy ◽  
Isotonic Saline ◽  
Area Under The Curve ◽  
Characteristic Analysis ◽  
Diagnostic Potential ◽  
Receiver Operating

Abstract Background: The syndrome of inappropriate antidiuresis (SIAD) is the most frequent cause of hyponatremia. Its diagnosis requires decreased serum osmolality, inappropriately diluted urine (e.g. >100 mOsm/kg), clinical euvolemia, and a urinary sodium (Na) excretion (U-Na) more than 30 mmol/liter. However, in hyponatremic patients taking diuretics, this definition is unreliable due to the natriuretic effect of diuretics. Here, we examined the diagnostic potential of alternative laboratory measurements to diagnose SIAD, regardless of the use of diuretics. Methods: A total of 86 consecutive hyponatremic patients (serum Na <130 mmol/liter) was classified based on their history, clinical evaluation, osmolality, and saline response to isotonic saline into a SIAD and a non-SIAD group. U-Na, serum urate concentration, and fractional excretion (FE) of Na, urea, and uric acid (UA) were measured in all subjects. The accuracy to diagnose SIAD was assessed using receiver operating characteristic analysis. Results: A total of 31 patients (36%) had a diagnosis of SIAD, and 55 (64%) were classified as non-SIAD. There were 57 patients (68%) who were on diuretics (15 in the SIAD group, 42 in the non-SIAD group). In the absence of diuretic therapy, SIAD was accurately diagnosed using U-Na (area under the receiver operating characteristic curve 0.96; 0.92–1.02). However, in patients on diuretics, the diagnosis was unreliable (area under the curve 0.85; 0.73–0.97). There, FE-UA performed best compared with all other markers tested (area under the curve 0.96; 0.92–1.12), resulting in a positive predictive value of 100% if a cutoff value of 12% was used. Conclusion: FE-UA allows the diagnosis of SIAD with excellent specificity. Combining the information on U-Na and FE-UA leads to a very high diagnostic accuracy in hyponatremic patients with and without diuretic treatment.

scholarly journals Comparative Analysis of Anterior Segment Parameters in Normal and Keratoconus Eyes Generated by Scheimpflug Tomography

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Faik Orucoglu ◽  
Ebru Toker
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Anterior Segment ◽  
Area Under The Curve ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Purpose. To assess and compare the anterior and posterior corneal surface parameters, keratoconus indices, thickness profile data, and data from enhanced elevation maps of keratoconic and normal corneas with the Pentacam Scheimpflug corneal tomography and to determine the sensitivity and specificity of these parameters in discriminating keratoconus from normal eyes.Methods. The study included 656 keratoconus eyes and 515 healthy eyes with a mean age of30.95±9.25and32.90±14.78years, respectively. Forty parameters obtained from the Pentacam tomography were assessed by the receiver operating characteristic curve analysis for their efficiency.Results. Receiver operating characteristic curve analyses showed excellent predictive accuracy (area under the curve, ranging from 0.914 to 0.972) for 21 of the 40 parameters evaluated. Among all parameters indices of vertical asymmetry, keratoconus index, front elevation at thinnest location, back elevation at thinnest location, Ambrósio Relational Thickness (ARTmax), deviation of average pachymetric progression, deviation of ARTmax, and total deviation showed excellent (>90%) sensitivity and specificity in addition to excellent area under the receiver operating characteristic curve (AUROC).Conclusions. Parameters derived from the topometric and Belin-Ambrósio enhanced ectasia display maps very effectively discriminate keratoconus from normal corneas with excellent sensitivity and specificity.

Two-stage receiver operating-characteristic curve estimator for cohort studies

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Susana Díaz-Coto ◽  
Norberto Octavio Corral-Blanco ◽  
Pablo Martínez-Camblor
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Practical Implementation ◽  
Two Stage ◽  
Statistical Tool ◽  
Finite Samples ◽  
Receiver Operating

AbstractThe receiver operating-characteristic (ROC) curve is a graphical statistical tool routinely used for studying the classification accuracy in both, diagnostic and prognosis problems. Given the different nature of these situations, ROC curve estimation has been separately considered for binary (diagnostic) and time-to-event (prognosis) outcomes, even for data coming from the same study design. In this work, the authors propose a two-stage ROC curve estimator which allows to link both contexts through a general prediction model (first-stage) and the empirical cumulative estimator of the distribution function (second-stage) of the considered test (marker) on the total population. The so-called two-stage Mixed-Subject (sMS) approach proves its behavior on both, large-samples (theoretically) and finite-samples (via Monte Carlo simulations). Besides, a useful asymptotic distribution for the concomitant area under the curve is also computed. Results show the ability of the proposed estimator to fit non-standard situations by considering flexible predictive models. Two real-world examples, one with binary and one with time-dependent outcomes, help us to a better understanding of the proposed methodology on usual practical circumstances. The R code used for the practical implementation of the proposed methodology and its documentation is provided as supplementary material.

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