Sensitivity, specificity, positive and negative predictive value

Sensitivity (positive in disease)

• Sensitivity is the ability of a test to correctly classify an individual as ′diseased′

• Sensitivity = a / a+c

• = a (true positive) / a+c (true positive + false negative)

• = Probability of being test positive when disease present.

Specificity (negative in health)

• The ability of a test to correctly classify an individual as disease- free is called the test′s specificity.

• Specificity = d / b+d

• = d (true negative) / b+d (true negative + false positive)

• = Probability of being test negative when disease absent.

Positive Predictive Value (PPV)

• It is the percentage of patients with a positive test who actually have the disease.

• PPV: = a / a+b

• = a (true positive) / a+b (true positive + false positive)

• = Probability (patient having disease when test is positive)

Negative Predictive Value (NPV)

• It is the percentage of patients with a negative test who do not have the disease.

• NPV: = d / c+d

• = d (true negative) / c+d (false negative + true negative)

• = Probability (patient not having disease when test is negative)

Disease present Disease absent

Test positive a b Total test positive(a+b)

Test negative c d Total test negative(c+d)

Total disease present (a+c)

Total normal (b+d)

Sensitivity= a/a+c

Specificity=d/b+d

Positive predictive value= a/a+b

Negative predictive value=d/c+d