scholarly journals CAST-HSROC: A Web Application for Calculating the Summary Points of Diagnostic Test Accuracy From the Hierarchical Summary Receiver Operating Characteristic Model

Cureus ◽  
2021 ◽  
Author(s):  
Masahiro Banno ◽  
Yasushi Tsujimoto ◽  
Yan Luo ◽  
Chisato Miyakoshi ◽  
Yuki Kataoka
Keyword(s):  
Receiver Operating Characteristic ◽  
Diagnostic Test ◽  
Web Application ◽  
Operating Characteristic ◽  
Diagnostic Test Accuracy ◽  
Test Accuracy ◽  
Summary Receiver Operating Characteristic ◽  
Characteristic Model ◽  
Receiver Operating

Optimal combination of biomarkers for time-dependent receiver operating characteristic estimation and related problems

2014 ◽  
Vol 26 (2) ◽  
pp. 898-913
Author(s):  
Zhong Guan ◽  
Jing Qin
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Diagnostic Test ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Time Dependent ◽  
Likelihood Method ◽  
Test Accuracy ◽  
Operating Characteristic Curve ◽  
Receiver Operating

The receiver operating characteristic curve is commonly used for assessing diagnostic test accuracy and for discriminatory ability of a medical diagnostic test in distinguishing between diseases and non-diseased individuals. With the advance of technology, many genetic variables and biomarker variables are easily collected. The most challenging problem is how to combine clinical, genetic, and biomarker variables together to predict disease status. If one is interested in predicting t-year survival, however, the status of “case” (death) and “control” (survival) at the given t-year is unknown for those individuals who were censored before t-year. To conduct a receiver operating characteristic analysis, one has to impute those ambiguous statuses. In this paper, we study a maximum pseudo likelihood method to estimate the underlying parameters and baseline distribution functions. The proposed approach produces more efficient and smoother estimate of the optimal time-dependent receiver operating characteristic curve and more stable estimation of the prediction rule for the t-year survivors. More importantly, the proposal is equipped with a goodness-of-fit test for the model assumption based on the bootstrap method. Two real medical data sets are used for illustration.

scholarly journals Diagnostic Accuracy of FDA Authorized Serology Tests to Detect SARS-CoV-2 Antibodies: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Rajesh Pandey ◽  
Anand Gourishankar
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Receiver Operating Characteristic ◽  
Test Performance ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Time Interval ◽  
Test Accuracy ◽  
Summary Receiver Operating Characteristic ◽  
Receiver Operating

AbstractImportanceSerology tests are diagnostic and complementary to molecular tests during the COVID-19 pandemic.ObjectiveTo evaluate the diagnostic accuracy of FDA authorized serology tests for the detection of SARS-CoV-2 infection.Data sourcesA search of MEDLINE, SCOPUS, CINAHL Plus, and EMBASE up to April 4, 2020, was performed to identify studies using the “COVID 19 testing” and “meta-analysis.” FDA website was accessed for the list of tests for emergency use authorization (EUA).Study SelectionManufacturer reported serology tests published in the FDA website were selected. Two reviewers independently assessed the eligibility of the selected reports.Data extraction and synthesisThe meta-analysis was performed in accordance with the PRISMA guidelines. A bivariate analysis using the “random-effects model” was applied for pooled summary estimates of sensitivity, specificity, and the summary receiver operating characteristic curves.Main outcomes and measuresThe primary outcome was the diagnostic accuracy of the serology test for detecting SARS-CoV-2 infection. Subgroup analysis of the diagnostic accuracy with lag time between symptom onset and testing were studied.ResultsSeven manufacturer listed reports were included. The pooled sensitivity was 87% (95% CI, 78% - 93%), the pooled specificity was 100% (95% CI, 97% - 100%), and the area under the hierarchical summary receiver operating characteristic curve was 0.97. At ≤ 7 days, sensitivity was 44% (95% CI, 21% - 70%), and for 8-14 days, sensitivity was 84% (95% CI, 67 % - 94%).For blood draws ≥ 15 days after the onset of symptoms, sensitivity was 96% (95% CI, 93% - 98%). Heterogeneity was substantial, and the risk of bias was low in this analysis.Conclusions and relevanceFDA authorized serology tests demonstrate high diagnostic accuracy for SARS-CoV-2 infection (certainty of evidence: moderate). There is a wide variation in the test accuracy based on the duration between the onset of symptoms and the tests (certainty of evidence: low).Key– pointsQuestionsWhat is the pooled diagnostic accuracy of FDA authorized serology tests to detect SARS-CoV-2 antibodies?FindingsIn this systematic review and meta-analysis of seven reports from FDA authorized serology tests to detect antibodies against SARS-CoV2 antibodies (3336 patients/ samples) pooled sensitivity was 87%, and pooled specificity was almost 100%. There was a wide variation in test performance based on the duration between the onset of symptoms and the tests.MeaningFDA authorized tests are highly accurate to detect antibodies against SARS-CoV-2 antibodies if tests are performed under a similar condition, as presented in the original report. There is a wide variation in the test performance based on the time interval between the onset of symptoms to the tests.

scholarly journals Perbandingan Kriteria ACR-1997 dan SLICC-2012 dalam Diagnosis Lupus Eritematosus Sistemik pada Anak

Sari Pediatri ◽  
2021 ◽  
Vol 22 (6) ◽  
pp. 386
Author(s):  
Dwi Lestari Pramesti ◽  
Dina Muktiarti
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Systemic Lupus ◽  
Summary Receiver Operating Characteristic ◽  
American College Of Rheumatology ◽  
Review Manager ◽  
Receiver Operating

Latar belakang. Lupus eritematosus sistemik merupakan penyakit autoimun sistemik pada jaringan ikat yang bersifat kronik dan progresif, terutama pada anak. Hingga saat ini belum ada diagnosis baku emas, sehingga untuk menegakkan diagnosis dapat menggunakan kriteria The American College of Rheumatology (ACR) tahun 1997 atau The Systemic Lupus International Collaborating Clinics (SLICC) tahun 2012.Tujuan. Mengumpulkan bukti ilmiah perbandingan penggunaan kriteria ACR-1997 dan SLICC-2012 dalam diagnosis lupus eritematosus sistemik pada anak.Metode. Penelusuran literatur secara sistematis secara daring melalui database Pubmed dan Cochrane. Analisis dilakukan menggunakan Review Manager dan model hierarchical summary receiver operating characteristic (HSROC) pada studi meta-analsiis. Kualitas studi dinilai dengan QUADAS-2.Hasil. Satu artikel telaah sistematis dan meta-analisis dan satu artikel studi longitudinal dilakukan telaah kritis. Kualitas kedua studi dinilai baik. Studi oleh Hartman dkk menunjukkan kriteria ACR-1997 lebih dianjurkan sebagai kriteria klasifikasi LES pada anak karena lebih spesifik (94,1% vs 82%) dan menghindari terjadinya positif palsu. Studi kedua oleh Lythgoe dkk menunjukkan SLICC-2012 lebih sensitif (92,9% vs 84,1%) dan secara lebih dini mengklasifikasi pasien anak dengan LES.Kesimpulan. Kriteria SLICC-2012 memiliki sensitivitas yang lebih tinggi dalam klasifikasi LES pada anak tetapi memiliki spesifisitas yang lebih rendah dibandingkan ACR-1997. Namun, SLICC-2012 dapat mengklasifikasi LES lebih dini secara signifikan dibandingkan ACR-1997.

scholarly journals Diagnostic Test Accuracy of the 4AT for Delirium Detection: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 17 (20) ◽  
pp. 7515 ◽  
Author(s):  
Eunhye Jeong ◽  
Jinkyung Park ◽  
Juneyoung Lee
Keyword(s):  
Systematic Review ◽  
Diagnostic Test ◽  
Healthcare Professionals ◽  
Meta Analysis ◽  
Diagnostic Test Accuracy ◽  
Test Accuracy ◽  
Summary Receiver Operating Characteristic ◽  
Bivariate Model ◽  
Data Synthesis

Under-recognition of delirium is an international problem. For the early detection of delirium, a feasible and valid screening tool for healthcare professionals is needed. This study aimed to present a scientific reason for using the 4 ‘A’s Test (4AT) through a systematic review and meta-analysis of studies on the diagnostic test accuracy. We systematically searched articles in the EMBASE, MEDLINE, CINAHL, and PsycINFO databases and selected relevant articles on the basis of the predefined inclusion criteria. The quality of the included articles was evaluated using the Quality Assessment of the Diagnostic Accuracy Studies-2 tool. We estimated the pooled values of diagnostic test accuracy by employing the bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model in data synthesis. A total of 3729 patients of 13 studies were included in the analysis. The pooled estimates of sensitivity and specificity of the 4AT were 81.5% (95% confidence interval: 70.7%, 89.0%) and 87.5% (79.5%, 92.7%), respectively. Given the 4AT’s evidence of accuracy and practicality, we suggest healthcare professionals to utilize this tool for routine screening of delirium. However, for detecting delirium in the dementia population, further work is required to evaluate the 4AT with other cut-off points or scoring methods in order for it to be more sensitive and specific.

Estimation of the volume under the receiver-operating characteristic surface adjusting for non-ignorable verification bias

2018 ◽  
Vol 27 (3) ◽  
pp. 715-739 ◽  
Author(s):  
Ying Zhang ◽  
Todd A Alonzo ◽  
Keyword(s):  
Receiver Operating Characteristic ◽  
Diagnostic Test ◽  
Operating Characteristic ◽  
Disease Status ◽  
Characteristic Surface ◽  
Finite Sample ◽  
Classification Problems ◽  
Verification Bias ◽  
Inverse Probability Weighted ◽  
Receiver Operating

The receiver-operating characteristic surface is frequently used for presenting the accuracy of a diagnostic test for three-category classification problems. One common problem that can complicate the estimation of the volume under receiver-operating characteristic surface is that not all subjects receive the verification of the true disease status. Estimation based only on data from subjects with verified disease status may be biased, which is referred to as verification bias. In this article, we propose new verification bias correction methods to estimate the volume under receiver-operating characteristic surface for a continuous diagnostic test. We assume the verification process is missing not at random, which means the missingness might be related to unobserved clinical characteristics. Three classes of estimators are proposed, namely, inverse probability weighted, imputation-based, and doubly robust estimators. A jackknife estimator of variance is derived for all the proposed volume under receiver-operating characteristic surface estimators. The finite sample properties of the new estimators are examined via simulation studies. We illustrate our methods with data collected from Alzheimer’s disease research.

scholarly journals Comparative Assessment of Three Common Algorithms for Estimating the Variance of the Area under the Nonparametric Receiver Operating Characteristic Curve

2002 ◽  
Vol 2 (3) ◽  
pp. 280-289 ◽  
Author(s):  
Mario A. Cleves
Keyword(s):  
Receiver Operating Characteristic ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Simulated Data ◽  
Small Samples ◽  
Binary Outcomes ◽  
Discriminatory Accuracy ◽  
Receiver Operating

The area under the receiver operating characteristic (ROC) curve is often used to summarize and compare the discriminatory accuracy of a diagnostic test or modality, and to evaluate the predictive power of statistical models for binary outcomes. Parametric maximum likelihood methods for fitting of the ROC curve provide direct estimates of the area under the ROC curve and its variance. Nonparametric methods, on the other hand, provide estimates of the area under the ROC curve, but do not directly estimate its variance. Three algorithms for computing the variance for the area under the nonparametric ROC curve are commonly used, although ambiguity exists about their behavior under diverse study conditions. Using simulated data, we found similar asymptotic performance between these algorithms when the diagnostic test produces results on a continuous scale, but found notable differences in small samples, and when the diagnostic test yields results on a discrete diagnostic scale.

scholarly journals Diagnostic and prognostic implications of parafibromin immunohistochemistry in parathyroid carcinomaT

2019 ◽  
Vol 39 (4) ◽  
Author(s):  
Jung-Soo Pyo ◽  
Won Jin Cho
Keyword(s):  
Parathyroid Adenoma ◽  
Diagnostic Test ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Disease Free Survival ◽  
Diagnostic Test Accuracy ◽  
Parathyroid Hyperplasia ◽  
Test Accuracy ◽  
Summary Receiver Operating Characteristic ◽  
Prognostic Implications

Abstract The aim of the present study was to elucidate the diagnostic and prognostic implications of parafibromin immunohistochemistry (IHC) in parathyroid carcinoma (PC). We performed a meta-analysis to examine the rate of loss of parafibromin expression from 18 eligible studies. In addition, a diagnostic test accuracy review was conducted to investigate the diagnostic role of parafibromin in PC. The rates of loss of parafibromin expression were 0.522 (95% CI: 0.444–0.599), 0.291 (95% CI: 0.207–0.391), 0.027 (95% CI: 0.011–0.064), and 0.032 (95% CI: 0.008–0.119) in PC, atypical parathyroid adenoma (APA), parathyroid adenoma (PA), and parathyroid hyperplasia, respectively. In the diagnostic test accuracy review for diagnosis of PC, the pooled sensitivity and specificity of parafibromin IHC was 0.53 (95% CI: 0.46–0.59) and 0.96 (95% CI: 0.95–0.97), respectively. The diagnostic odds ratio and the area under curve on summary receiver operating characteristic curve was 25.31 (95% CI: 8.91–71.87) and 0.7954, respectively. In addition, the meta-analysis demonstrated that loss of parafibromin expression was significantly correlated with worse disease-free survival (hazard ratio: 2.832; 95% CI: 1.081–7.421). Loss of parafibromin IHC expression was significantly higher in PC than in APA, PA, and parathyroid hyperplasia. Parafibromin IHC could be useful for diagnosis and prediction of prognosis of PC in daily practice.

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