Table 12.
Online applications for diagnostic tests: characteristics.
| Name | Input | Output |
|---|---|---|
| Diagnostic test calculatora | TP, FP, TN, FN OR Prevalence AND Se AND Sp AND sample size OR Prevalence AND PLR AND NLR AND sample size |
Prevalence AND Se AND Sp AND PLR AND NLR Fagan diagram |
|
| ||
| Diagnostic test calculator evidence-based medicine toolkitb | TP, FP, TN, FN | Se, Sp, PPV, NPV, PLR, NLR with associated 95% confidence intervals Posttest probability graph |
|
| ||
| MedCalc: Bayesian analysis modelc | Prevalence AND Se AND Sp OR TP, FP, TN, FN |
PPV, NPV, LPR, NLR, posttest probability |
|
| ||
| MedCalcd | TP, FP, TN, FN | Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals |
|
| ||
| Clinical calculator 1e | TP, FP, TN, FN | Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals |
|
| ||
| Clinical utility index calculatorf | TP, TN, total number of cases, the total number of noncases | Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals |
|
| ||
| DiagnosticTestg | Number of positive and negative gold standard results for each level of the new diagnostic test | Se, Sp, PPV, NPV, PLR, NLR, AI, DOR, Cohen's kappa, entropy reduction, and a bias Index ROC curve if > 2 levels for all possible cutoff |
|
| ||
| Simple ROC curve analysish | Absolute frequencies for false positive and the true positive for up to ten diagnostic levels | Cumulative rates (false positive and true positive) and ROC curve (equation, R2, and AUC) |
|
| ||
| ROC analysisi | Five different type of input data: an example for each type is provided | Se, Sp, AI, positive cases missed, negative cases missed, AUC, ROC curve |
|
| ||
| AUSVET: EpiToolsj | TP, FP, TN, FN | Different tools from basic accuracy to comparison of two diagnostic tests to ROC analysis |
All URLs were retrieved on April 20, 2019. TP = true positive; FP = false positive; FN = false negative; TN = true negative; Se = sensitivity; Sp = specificity; AI = accuracy index; PPV = positive predictive value; NPV = negative predictive value; PLR = positive likelihood ratio; NLR = negative likelihood ratio; DOR = diagnostic odds ratio; ROC = receiver operating characteristic; AUC = area under the ROC curve; ahttp://araw.mede.uic.edu/cgi-bin/testcalc.pl; bhttps://ebm-tools.knowledgetranslation.net/calculator/diagnostic/; chttp://www.medcalc.com/bayes.html; dhttps://www.medcalc.org/calc/diagnostic_test.php; ehttp://vassarstats.net/clin1.html; fhttp://www.psycho-oncology.info/cui.html; ghttp://www.openepi.com/DiagnosticTest/DiagnosticTest.htm; hhttp://vassarstats.net/roc1.html; ihttp://www.rad.jhmi.edu/jeng/javarad/roc/JROCFITi.html; and jhttp://epitools.ausvet.com.au/content.php?page=TestsHome.