What happens when you increase specificity?

What happens when you increase specificity?

The more specific the test, the less likely an individual with a positive test will be free from disease and the greater the positive predictive value. When the prevalence of preclinical disease is low, the positive predictive value will also be low, even using a test with high sensitivity and specificity.

What happens if you increase the sensitivity of a test?

In general, as: Sensitivity increases (lower threshold), false-positive test results will increase, Specificity increases (higher threshold), false-negative test results increase.

Is there a trade off between sensitivity and specificity?

Results: Sensitivity and specificity are measures of the accuracy of a diagnostic test. There is a trade-off between sensitivity and specificity that is dependent on the cut-off level chosen for a positive diagnosis. Predictive values are measures of the usefulness of a test once the test results are known.

Is there a difference between sensitivity and specificity?

Unfortunately, it does not differentiate the sensitivity and specificity of tests. Tests with very poor sensitivity and very good specificity would end up with the same index as tests which have excellent sensitivity and virtually no specificity.

When does the specificity of a screening test decrease?

A specific test is usually negative in disease free patients (few false positives ). When many disease free patients have a positive test (false positives), the specificity decreases. Utility as a screening test may diminish because it results in too many needless work-ups.

How does a cutoff point affect the sensitivity of a test?

In general, raising the cutoff point to make a test more specific will reduce the sensitivity (increase the false negatives). Lowering the cutoff point to make the test more sensitive will reduce specificity (increase the false positives).

What are the sensivity and specificity of a blood test?

The sensivity and specificity are characteristics of this test. For a clinician, however, the important fact is among the people who test positive, only 20% actually have the disease. For those that test negative, 90% do not have the disease. Now, let’s change the prevalence..