Computational and Mathematical Methods in Medicine

Review Article

Medical Diagnostic Tests: A Review of Test Anatomy, Phases, and Statistical Treatment of Data

Table 12

Online applications for diagnostic tests: characteristics.


Name	Input	Output

Diagnostic test calculator^a	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 toolkit^b	TP, FP, TN, FN	Se, Sp, PPV, NPV, PLR, NLR with associated 95% confidence intervals Posttest probability graph

MedCalc: Bayesian analysis model^c	Prevalence AND Se AND Sp OR TP, FP, TN, FN	PPV, NPV, LPR, NLR, posttest probability

MedCalc^d	TP, FP, TN, FN	Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals

Clinical calculator 1^e	TP, FP, TN, FN	Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals

Clinical utility index calculator^f	TP, TN, total number of cases, the total number of noncases	Se, Sp, PPV, NPV, PLR, NLR, prevalence, AI with associated 95% confidence intervals

DiagnosticTest^g	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 analysis^h	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: EpiTools^j	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.