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Diagnostic Testing

Establish evidence for tests that diagnose disease and healthy people

The Diagnostic Testing decision tree will help researchers navigate the applied decision making processes associated with the establishing the utility and interpretability of diagnostic tests.

In order to conduct a study on a diagnostic test, researchers first have to choose the current "gold standard" to compare the diagnostic test of interest to when establishing evidence.

Each participant is given the diagnostic test and then the findings, either positive or negative, are compared to the findings of the "gold standard" method of diagnosis.

The prevalence of the disease state being detected by the diagnostic test and the "gold standard" also has to be taken into consideration. With higher rates of prevalence, researchers will get more "positive" results simply due to the fact that more cases exist in the population.

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Diagnostic testing calculations

Sensitivity is the ability of a diagnostic test to detect disease.
Sensitivity
Specificity is the ability of a diagnostic test to identify the healthy.
Specificity
Researchers want to set the optimum cut-point for maximizing both sensitivity and specificity with a diagnostic test that uses a continuous scale of measurement. Researchers may also want to compare the diagnostic abilities of several diagnostic tests concurrently using Area Under the Curve (AUC or c-statistic). 
Receiver Operator Characteristic
Positive predictive value is how believable a "positive" test result is in a given population.
Positive Predictive Value (PPV)
Negative predictive value is how believable a "negative" test result is in a given population.
Negative Predictive Value (NPV)
Diagnostic accuracy is the overall ability of a test to correctly diagnose disease states. 
Diagnostic Accuracy
Predict for future outcomes or events using pretest probabilities, clinical factors, and likelihood ratios.
Bayes' Theorem
The Youden index gives an overall measure of the ability of a given diagnostic test based sensitivity and specificity.
Youden index

Downloads for diagnostic testing

Click on the Download Database for a free Excel database formatted for diagnostic testing data.
Download Database
Download a free Excel calculator for diagnostic testing calculations.
Download Calculator

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There are eight important calculations in diagnostic testing: Sensitivity, specificity, receiver operator characteristic (ROC), positive predictive value (PPV), negative predictive value (NPV), total diagnostic accuracy, Bayes Theorem, and the Youden index.

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