Positive and negative predictive values

Positive and Negative Predictive Values

The Positive Predictive Value (PPV) and the Negative Predictive Value (NPV) are statistical measures commonly used in medical testing and diagnostic medicine. They are used to assess the performance of diagnostic and screening tests.

Definition

The Positive Predictive Value (PPV) is the probability that subjects with a positive screening test truly have the disease. It is defined as the proportion of true positive results in relation to the total number of positive results, both true positive and false positive.

The Negative Predictive Value (NPV) is the probability that subjects with a negative screening test truly do not have the disease. It is defined as the proportion of true negative results in relation to the total number of negative results, both true negative and false negative.

Calculation

The PPV and NPV are calculated using the following formulas:

PPV = True Positive / (True Positive + False Positive)

NPV = True Negative / (True Negative + False Negative)

Factors affecting PPV and NPV

The PPV and NPV of a test are not fixed, and can change depending on the prevalence of the disease in the population being tested. They are also influenced by the sensitivity and specificity of the test.

Importance in Medical Testing

The PPV and NPV are important measures in medical testing as they give an indication of the reliability of a test result. They are particularly useful in screening programs, where the aim is to detect disease in its early stages.

See also

• Sensitivity (tests)
• Specificity (tests)
• Prevalence
• Diagnostic test

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  Positive and Negative Predictive Values
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  PPV, NPV, Sensitivity and Specificity