scholarly journals Graphical enhancements to summary receiver operating characteristic plots to facilitate the analysis and reporting of meta‐analysis of diagnostic test accuracy data

2020 ◽  
Author(s):  
Amit Patel ◽  
Nicola Cooper ◽  
Suzanne Freeman ◽  
Alex Sutton
2020 ◽  
Author(s):  
Rajesh Pandey ◽  
Anand Gourishankar

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.


Author(s):  
Eunhye Jeong ◽  
Jinkyung Park ◽  
Juneyoung Lee

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.


2019 ◽  
Vol 39 (4) ◽  
Author(s):  
Jung-Soo Pyo ◽  
Won Jin Cho

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.


2014 ◽  
Vol 26 (2) ◽  
pp. 898-913
Author(s):  
Zhong Guan ◽  
Jing Qin

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.


2015 ◽  
Vol 25 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Zhaolian Lu ◽  
Yingjian Chen ◽  
Zhide Hu ◽  
Chengjin Hu

ObjectiveThis study aimed to assess the diagnostic value of lysophosphatidic acid (LPA) in ovarian cancer.MethodsA systematic review of related studies was performed; sensitivity, specificity, and other measures about the accuracy of serum LPA in the diagnosis of ovarian cancer were pooled using random-effects models. Summary receiver operating characteristic curve analysis was used to summarize the overall test performance.ResultsSix studies involving 363 patients with ovarian cancer and 273 healthy control women met the inclusion criteria. The summary estimates for LPA in diagnosing ovarian cancer in the included studies were as follows: sensitivity, 0.94 [95% confidence interval (CI), 0.91–0.96]; specificity, 0.88 (95% CI, 0.83–0.91); and diagnostic odds ratio, 141.59 (95% CI, 52.1–384.63). The area under the curve and Q value for summary receiver operating characteristic curves were 0.97 and 0.92, respectively.ConclusionsThe LPA assay showed high accuracy and sensitivity for the diagnosis of ovarian cancer. The present study was limited by the small number of available studies and sample size; therefore, additional studies with a better design and larger samples are needed to further assess the diagnostic accuracy of LPA.


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