Diagnostic Test Calculator
Calculate standard evidence-based medicine (EBM) metrics including Sensitivity, Specificity, PPV, NPV, and Likelihood Ratios using a 2x2 contingency table.
2x2 Contingency Table
Enter the values for the diagnostic test results.
Key Definitions
- Sensitivity (Sn)
- Probability that the test is positive when the disease is present. (TP / (TP + FN))
- Specificity (Sp)
- Probability that the test is negative when the disease is absent. (TN / (TN + FP))
- PPV (Positive Predictive Value)
- Probability that disease is present given a positive test result.
- NPV (Negative Predictive Value)
- Probability that disease is absent given a negative test result.
Results
Computed diagnostic statistics
Enter values in the table to view results.
About Diagnostic Statistics
In clinical practice, the utility of a diagnostic test is described by its sensitivity, specificity, and predictive values. These metrics help clinicians interpret test results in the context of disease prevalence.
Formulas
Sensitivity (True Positive Rate)
TP / (TP + FN)The ability of a test to correctly identify those with the disease (SNOUT: Sensitive tests rule OUT).
Specificity (True Negative Rate)
TN / (TN + FP)The ability of a test to correctly identify those without the disease (SPIN: Specific tests rule IN).
Positive Predictive Value (PPV)
TP / (TP + FP)The probability that subjects with a positive screening test truly have the disease.
Negative Predictive Value (NPV)
TN / (TN + FN)The probability that subjects with a negative screening test truly don't have the disease.
Likelihood Ratios
Likelihood ratios (LR) are used to assess how good a diagnostic test is and to help select an appropriate diagnostic test. They have advantages over sensitivity and specificity because they are less likely to change with the prevalence of the disorder.
- LR+ > 10: Strong evidence to rule in disease.
- LR+ 5-10: Moderate evidence to rule in disease.
- LR- < 0.1: Strong evidence to rule out disease.
Note: PPV and NPV are dependent on the prevalence of the disease in the population being tested. Sensitivity and Specificity are generally intrinsic properties of the test itself.