scholarly journals Disease Prevalence Matters: Challenge for SARS-CoV-2 Testing

Antibodies ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 50
Author(s):  
Chin-Shern Lau ◽  
Tar-Choon Aw
Keyword(s):  
Diagnostic Test ◽  
Sensitivity And Specificity ◽  
False Positive ◽  
Disease Prevalence ◽  
Test Results ◽  
Community Screening ◽  
Predictive Values ◽  
Low Prevalence

While sensitivity and specificity are important characteristics for any diagnostic test, the influence of prevalence is equally, if not more, important when such tests are used in community screening. We review the concepts of positive/negative predictive values (PPV/NPV) and how disease prevalence affects false positive/negative rates. In low-prevalence situations, the PPV decreases drastically. We demonstrate how using two tests in an orthogonal fashion can be especially beneficial in low-prevalence settings and greatly improve the PPV of the diagnostic test results.

COMPARISON OF FOURTH GENERATION ELISA AND RAPID DIAGNOSTIC TEST FOR DIAGNOSIS OF HEPATITIS C VIRUS(HCV) INFECTION IN A TERTIARY CARE HOSPITAL.

2021 ◽  
pp. 15-17
Author(s):  
Stuti Kansra Arora ◽  
Mala Chhabra ◽  
Anuradha Anuradha ◽  
Arvind Achra ◽  
Nandini Duggal
Keyword(s):  
Diagnostic Test ◽  
Rapid Diagnostic Test ◽  
Sensitivity And Specificity ◽  
Treatment Initiation ◽  
Tertiary Care ◽  
Hcv Infection ◽  
Fourth Generation ◽  
World Population ◽  
Test Results ◽  
Blood Samples

Introduction:Hepatitis C virus (HCV) infection has emerged as one of the major global health challenge affecting about 2 - 3% of the world population. Epidemiological studies have shown that HCV infection is a major risk factor for development of Acute hepatitis,chronic liver disease,cirrhosis and Hepatocellular carcinoma (HCC).Early diagnosis of HCV is important to link hepatitis testing to care and treatment initiation. Aim:To compare sensitivity and specificity of rapid diagnostic test (RDT) with fourth generation ELISA Material and Method: This study was conducted in the Department of Microbiology at Atal Bihari Vajpayee Institute of Medical Sciences (formerly Post Graduate Institute of Medical Education and Research) and Dr Ram Manohar Lohia Hospital from January 2018 to December 2018.Blood samples of patients suspected with hepatitis were tested using ELISA and rapid diagnostic test Results: In our study 26378 blood samples were tested for HCV,using fourth generation ELISA.Of these,581(2.20%) samples were found to be positive by ELISA.These HCV positive samples along with equal number of ELISA negative samples were tested by rapid diagnostic test. Sensitivity and specificity of the rapid diagnostic test was found to be 72.98 % and 100% respectively. Discussion:Rapid diagnostic test can be used during emergency hours but their results must be followed by ELISA test results in a tertiary care hospital.Reporting of false negative results should be minimized for rapid linkage to treatment initiation and to avoid silent transmission of infection.

Outbreak or illusion: consequences of ‘improved’ diagnostics for gonorrhoea

2016 ◽  
Vol 28 (7) ◽  
pp. 667-671 ◽  
Author(s):  
Amy Bennett ◽  
Katie Jeffery ◽  
Eunan O’Neill ◽  
Jackie Sherrard
Keyword(s):  
False Positive ◽  
Cross Reactivity ◽  
Practical Reasons ◽  
Predictive Values ◽  
Confirmatory Testing ◽  
Neisseria Species ◽  
Sexual Health Service ◽  
Sex With Men ◽  
A Prospective Study ◽  
Low Prevalence

The sexual health service in Oxford introduced gonorrhoea nucleic amplification acid testing using the BD Viper XTR™ System. For practical reasons, a confirmatory nucleic amplification acid testing using a different platform was not used initially. Following the introduction of nucleic amplification acid testing, the rates of gonorrhoea increased threefold. Concerns were raised that this increase represented an outbreak. A retrospective review of cases over six months suggested that there may have been a number of false-positive results. A prospective study was then undertaken over six months, where all gonorrhoea positive samples were sent for confirmatory testing. This evaluation of all gonorrhoea cases in an English county found that the overall presumptive false-positive rates for gonorrhoea nucleic amplification acid testing using BD Viper XTR™ in our population are significant at 27% of female samples, 13.2% of heterosexual male samples, 3.5% of anogenital multiple site men who have sex with men samples and 62.8% of pharyngeal only men who have sex with men samples. The data demonstrate the need for confirmatory testing using a second nucleic acid target, as per BASHH/Public Health England guidelines, especially in low-prevalence settings and extragenital sites, due to cross-reactivity with commensal Neisseria species and low positive predictive values.

scholarly journals Causes of false-positive HIV rapid diagnostic test results

2013 ◽  
Vol 12 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Derryck Klarkowski ◽  
Daniel P O’Brien ◽  
Leslie Shanks ◽  
Kasha P Singh
Keyword(s):  
Diagnostic Test ◽  
Rapid Diagnostic Test ◽  
False Positive ◽  
Test Results

scholarly journals A tutorial for meta-analysis of diagnostic tests for low-prevalence diseases: Bayesian models and software

Methodology ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 258-277
Author(s):  
Johny J. Pambabay-Calero ◽  
Sergio A. Bauz-Olvera ◽  
Ana B. Nieto-Librero ◽  
Maria Purificación Galindo-Villardón ◽  
Ana B. Sánchez-García
Keyword(s):  
Diagnostic Test ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Diagnostic Test Accuracy ◽  
Mixed Effects Models ◽  
Test Accuracy ◽  
R Program ◽  
Correct Model ◽  
Analytical Integration ◽  
Low Prevalence

Although measures such as sensitivity and specificity are used in the study of diagnostic test accuracy, these are not appropriate for integrating heterogeneous studies. Therefore, it is essential to assess in detail all related aspects prior to integrating a set of studies so that the correct model can then be selected. This work describes the scheme employed for making decisions regarding the use of the R, STATA and SAS statistical programs. We used the R Program Meta-Analysis of Diagnostic Accuracy package for determining the correlation between sensitivity and specificity. This package considers fixed, random and mixed effects models and provides excellent summaries and assesses heterogeneity. For selecting various cutoff points in the meta-analysis, we used the STATA module for meta-analytical integration of diagnostic test accuracy studies, which produces bivariate outputs for heterogeneity.

Clinical Epidemiology

2016 ◽  
pp. 285-290
Author(s):  
Scott C. Litin ◽  
John B. Bundrick
Keyword(s):  
Diagnostic Test ◽  
Diagnostic Tests ◽  
Clinical Decision Making ◽  
Clinical Epidemiology ◽  
Clinical Decision ◽  
Test Results ◽  
Specific Patient ◽  
Predictive Values ◽  
Test Sensitivity ◽  
Sensitivity Specificity

Diagnostic tests are tools that either increase or decrease the likelihood of disease. The sensitivity, specificity, and predictive values of normal and abnormal test results can be calculated with even a limited amount of information. Some physicians prefer interpreting diagnostic test results by using the likelihood ratio. This ratio takes properties of a diagnostic test (sensitivity and specificity) and makes them more helpful in clinical decision making. It helps the clinician determine the probability of disease in a specific patient after a diagnostic test has been performed.

scholarly journals Bayes Lines Tool (BLT): a SQL-script for analyzing diagnostic test results with an application to SARS-CoV-2-testing

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 369
Author(s):  
Wouter Aukema ◽  
Bobby Rajesh Malhotra ◽  
Simon Goddek ◽  
Ulrike Kämmerer ◽  
Peter Borger ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Query Language ◽  
False Negative ◽  
Disease Prevalence ◽  
Test Results ◽  
True Negative ◽  
Test Sensitivity ◽  
Laboratory Test Results ◽  
Test Specificity ◽  
Analytical Reagents

The performance of diagnostic tests crucially depends on the disease prevalence, test sensitivity, and test specificity. However, these quantities are often not well known when tests are performed outside defined routine lab procedures which make the rating of the test results somewhat problematic. A current example is the mass testing taking place within the context of the world-wide SARS-CoV-2 crisis. Here, for the first time in history, laboratory test results have a dramatic impact on political decisions. Therefore, transparent, comprehensible, and reliable data is mandatory. It is in the nature of wet lab tests that their quality and outcome are influenced by multiple factors reducing their performance by handling procedures, underlying test protocols, and analytical reagents. These limitations in sensitivity and specificity have to be taken into account when calculating the real test results. As a resolution method, we have developed a Bayesian calculator, the Bayes Lines Tool (BLT), for analyzing disease prevalence, test sensitivity, test specificity, and, therefore, true positive, false positive, true negative, and false negative numbers from official test outcome reports. The calculator performs a simple SQL (Structured Query Language) query and can easily be implemented on any system supporting SQL. We provide an example of influenza test results from California, USA, as well as two examples of SARS-CoV-2 test results from official government reports from The Netherlands and Germany-Bavaria, to illustrate the possible parameter space of prevalence, sensitivity, and specificity consistent with the observed data. Finally, we discuss this tool’s multiple applications, including its putative importance for informing policy decisions.

scholarly journals A comparison of self-reported data on disability pension status with data from a nationwide administrative register

2010 ◽  
Vol 19 (2) ◽  
Author(s):  
Ingeborg Hartz ◽  
Aage Tverdal ◽  
Svetlana Skurtveit
Keyword(s):  
Positive Predictive Value ◽  
Sensitivity And Specificity ◽  
Disability Pension ◽  
Reference Standard ◽  
Total Study Population ◽  
Predictive Values ◽  
Study Population ◽  
Validity Measures ◽  
Reported Data ◽  
Low Prevalence

<p><strong><em>Objectives: </em></strong>Validation studies of self-reported disability pension status have been scarce. The objective of this study was to estimate the sensitivity and specificity, as well as positive and negative predictive values of self-reported disability pension status using an official administrative register as reference standard.</p><p><strong><em>Methods: </em></strong>Data from Cohort of Norway (CONOR) surveys conducted in 2001 in the three Norwegian counties Oslo (HUBRO), Hedmark and Oppland (OPPHED) are included in this study, altogether 17,244 individuals. At the time of investigation, the subjects included in our study-population were aged 30-31, 40-41, 45-47 and 59-61 years. Self-reported data on disability pension status was compared with data from the nationwide population and housing census in Norway (Statistics Norway), performed November 3rd 2001. Data were linked using the unique 11-digit identification number, assigned to all individuals living in Norway.</p><p><strong><em>Results: </em></strong>Sensitivity and specificity for self-reported questions on disability pension were 97.6% (95% CI 91.1-94.1) and 96.8% (96.5-97.1). Positive and negative predictive values were 70.1% (67.9-72.3) and 99.8% (99.7-99.9). Validity measures in a subpopulation, those surveyed in October-November 2001, were almost identical as for the total study-population surveyed in 2001.</p><p><strong>Conclusion: </strong>The sensitivity of self-reported disability pension status was high. The positive predictive value was lower which may reflect a low prevalence.</p>

Implications of covariate induced test dependence on the diagnostic accuracy of latent class analysis in pulmonary tuberculosis

2021 ◽  
Author(s):  
Alfred Kipyegon Keter ◽  
Lutgarde Lynen ◽  
Alastair van Heerden ◽  
Els Goetghebeur ◽  
Bart K.M. Jacobs
Keyword(s):  
Pulmonary Tuberculosis ◽  
Diagnostic Accuracy ◽  
Diagnostic Test ◽  
Sensitivity And Specificity ◽  
Diagnostic Tests ◽  
Latent Class ◽  
Test Accuracy ◽  
Test Results ◽  
Test Sensitivity ◽  
Correct Estimation

Abstract Background Lack of a perfect reference standard for pulmonary tuberculosis (PTB) diagnosis complicates assessment of accuracy of new diagnostic tests. Alternative strategies such as discrepant resolution and use of composite reference standards may lead to incorrect inferences on disease prevalence and diagnostic test sensitivity and specificity. Latent class analysis (LCA), a statistical method for analyzing diagnostic test results in the absence of a gold standard, allows correct estimation under strict assumptions. The model assumes that the diagnostic tests are independent conditional on the true disease status and that the diagnostic test sensitivity and specificity remain constant across subpopulations. These assumptions are violated when a factor such as severe comorbidity affects the prevalence and/or alters the diagnostic test performance. We aim to provide guidance on correct estimation of the prevalence and diagnostic test accuracy based on LCA when a known factor induces dependence among the diagnostic tests. If unaccounted for, this dependence may lead to misleading inferences. Methods Through likelihood evaluation and simulation we examined implications of likely model violations on estimation of prevalence, sensitivity and specificity among passive case-finding presumptive PTB patients with or without HIV. We generated independent results for five diagnostic tests conditional on PTB and HIV. We performed Bayesian LCA, separately for five and three diagnostic tests using four working models with or without constant PTB prevalence and diagnostic test accuracy across HIV subpopulations. Results In evaluating three diagnostic tests, the models accounting for heterogeneity in diagnostic accuracy produced consistent estimates while the models ignoring it produced biased estimates. The model ignoring heterogeneity in PTB prevalence is less problematic. When evaluating five diagnostic tests, the models were robust to violation of the assumptions. Conclusions Well-chosen covariate-specific adaptations of the model can avoid bias implied by recognized heterogeneity in PTB patient populations generating otherwise dependent test results in LCA.

scholarly journals Identification of False-Positive Syphilis Antibody Results Using a Semiquantitative Algorithm

2011 ◽  
Vol 18 (6) ◽  
pp. 1038-1040 ◽  
Author(s):  
Belinda Yen-Lieberman ◽  
Juliet Daniel ◽  
Cathy Means ◽  
Joan Waletzky ◽  
Thomas M. Daly
Keyword(s):  
False Positive ◽  
Antibody Test ◽  
Test Results ◽  
Repeat Testing ◽  
Screening Algorithm ◽  
Low Prevalence ◽  
Syphilis Serology ◽  
Positive Results ◽  
Potential False Positive

ABSTRACTScreening patients for syphilis serology using a “treponemal assay-first” approach presents unique challenges, particularly when applied to low-prevalence populations. The use of a screening algorithm that incorporates semiquantitative values from treponemal antibody test results can help to identify potential false-positive results while requiring a minimum of repeat testing.

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