Evaluating a Tests Performance Characteristics

Given that tests are not totally accurate or precise, one must have a way to quantify these shortcomings. A test's ability to discriminate diseased from nondiseased persons is defined by its sensitivity, specificity, and positive and negative predictive values. Table 15-3 shows how each is calculated. Sensitivity and specificity are inherent technical aspects of a test and are independent of the prevalence of disease in the population tested. However, given that diseases have a spectrum of manifestations, sensitivity and specificity are improved if the population is heavily weighted with patients who have advanced (vs. early) illness.

Sensitivity is defined as the percentage of persons with the disease who are correctly identified by the test. Specificity is the percentage of persons who are disease-free and correctly excluded by the test. The positive predictive value is defined as the percentage of persons with a positive test who actually have the disease, whereas the negative predictive value is the percentage of persons with a negative test who do not have the disease. Predictive value is influenced by the sensitivity and specificity of the test and the prevalence (the percentage of people in a population who at a given time have the disease).

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Acne is a name that is famous in its own right, but for all of the wrong reasons. Most teenagers know, and dread, the very word, as it so prevalently wrecks havoc on their faces throughout their adolescent years.

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