## The screening test

The suitability of a screening test is determined by three standard measures (Fig. 9.13):

1. sensitivity,

2. specificity,

3. predictive value.

The value of a test used for diagnosis cannot be extrapolated to the screening situation. A diagnostic test provides information which is complementary to that of a number of other tests. A screening test has to stand-alone.

The sensitivity of a test defines the proportion of those with cancer in whom a positive test has been recorded. Both the number who are test positive and those with false negative tests need to be known so that the total number of cancers can be calculated. As it is impracticable to fully investigate those with a negative test for the presence of cancer, the number of cancers which 'surface' spontaneously during a defined period after a negative screening test, so-called 'interval cancers', are taken to represent those missed by the screening test. The number of interval cancers is expressed as the proportion of the estimated incidence of the disease, allowing the number of those whose diagnosis has been advanced by the screening test to be estimated. If interval cancers account for 20% of the expected incidence, it is assumed that screening has advanced the diagnosis of the other 80% (Table 9.2).

The specificity of a screening test is the reciprocal of the false-positive rate and is the proportion of all those without cancer who were correctly classified as negative by the screening test. As all persons with a positive test will be further investigated, the actual number of false-positive tests is known.

Sensitivity and specificity are inversely related. Although ideally they should each approach 100%, this is unrealistic. There is a 'trade-off' which depends upon the threshold for an abnormal test. If this is set so that no cancers are ever missed, the test will have a high sensitivity, but as a greater number of tests will be falsely positive, a low specificity. Conversely, if the threshold is set so that false-positive tests are minimized (high specificity), sensitivity will suffer. The relationship between sensitivity and specificity is represented by relative operating characteristic (ROC) curves, which are used to set the most suitable threshold for a test (Fig. 9.14). The more efficient a screening test, the greater will be the yield of cancers and the lower the false-positive rate.

The third criterion used to define the validity of a screening test is the positive predictive value. This represents the proportion of those with a positive test who are subsequently proven to have cancer. This measure is largely dependent on the specificity of the test but also on the underlying prevalence of the cancer in the population to be screened. When this is low the number of true positive tests decreases while, as there are more healthy persons, false-positive tests increase and the positive predictive value falls.

The acceptability of the test must clearly be evaluated before its use is extended to population screening.

Table 9.2. | |||

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