Choosing Effective Screening Tests

Screening in the community for a priority health condition depends on the availability of a screening test that is reliable, accurate, acceptable to participants (i.e., patients and clinicians), and affordable in relation to its benefits (Wilson and Jungner 1968; Morrison 1992). Thus, screening for breast cancer is feasible because mammography, an effective screening test, is available. However, screening for lung cancer (an equally important health condition) is considered infeasible because neither early detection nor effective treatment is available (USPSTF 1996). Important epidemiologic concepts that relate to the accuracy of a screening procedure are sensitivity, specificity, predictive value of positive and negative test results, and lead time. In addition, cost-effectiveness and cost-benefit are important concepts that underlie judgments about the affordability of a screening procedure in relation to its benefits.

The ideal screening test would have high values of sensitivity, specificity, and positive predictive value and would tend to maximize the yield of true positives and minimize the yield of false positives. However, there are often trade-offs to be made between sensitivity and specificity in optimizing the yield of screening tests, especially those based on a cut-point applied to a continuously distributed variable (e.g., blood pressure). When the cut-point is decreased to increase sensitivity, the specificity will simultaneously decrease and vice versa. Strategies for balancing benefits and costs of screening include adjusting the criterion level for positivity, adjusting the frequency of screening, sequential testing (combining two or more different tests in sequence), and targeting high-risk groups with high prevalence of preclinical disease (Morrison 1992).

Sensitivity. The sensitivity of a screening test is the proportion of persons with the condition (based on a gold-standard test) who test positive. Alternatively, sensitivity is equal to number of true positives divided by the sum of true positives and false negatives (Table 7-3). Sensitivity is the property of a screening test that enables cases to be detected early (true positives). Thus, sensitivity is an important determinant of the disease-control value of a screening program. More sensitive tests tend to identify cases earlier and thus may increase the lead time that screen-detected cases gain (see section on natural history of disease). Thus, to be successful at reducing morbidity or mortality, a screening test must be highly sensitive (i.e., detect a high proportion of preclinical cases with sufficient lead time for treatment to improve outcome) (Morrison 1992).

Specificity. The specificity of a screening test is the proportion of persons without the condition who test negative. Thus, specificity is equal to the number of true negatives divided by the sum of true negatives and false positives (Table 7-3). Alternatively, specificity (1 minus % of false positives among nondiseased) is negatively related to the frequency of false positives in

Table 7-3. Measures of Accuracy of a Screening Test

Measure of Accuracy

Definition

Formula"

Sensitivity

Proportion of persons with condition who test positive

a/a + c

Specificity

Proportion of persons without condition who test negative

d/b + d

Positive predictive value

Proportion of persons with positive test who have condition

a/a + b

Negative predictive value

Proportion of persons with negative test who do not have condition

d/c + d

»Legend: a = true positive; b = false positive; c = false negative; d = true negative

»Legend: a = true positive; b = false positive; c = false negative; d = true negative

a screened population (Morrison 1992). High specificity is the property of a screening test that minimizes the number of false-positive tests and their adverse consequences that must be followed up. Conversely, a test with low specificity will lead to many false positives, requiring follow up, and may consume substantial resources. Thus, specificity has a major influence on the costs, acceptability, and feasibility of a screening program. Routine use of the prostate-specific antigen test (PSA) is a good example of a test with low specificity and a high burden of cost and side effects as a result of follow-up of false positives.

Predictive Value Positive (and Negative). The predictive value of a positive (PVP) screening test is the proportion of persons with a positive test who have the condition. PVP is equal to the number of true positives divided by the sum of true positives and false positives; or 1 minus % of false positives among screen positives (Table 7-3). The predictive value of a negative screening test is the proportion of persons with a negative test who do not have the condition (Morrison 1992; USPSTF 1996).

Reliability. The reliability of a test is its capacity to give the same result— positive or negative, whether correct or incorrect—on repeated application in a person with a given level of disease. Reliability depends on variability in the manifestations of preclinical disease being sought (e.g., daily fluctuation in blood pressure), the method of measurement, and the skill with which the observer makes the measurements. Measures of reliability include intra- or interobserver variability (Morrison 1992). A screening test of low reliability usually will not be sufficiently sensitive or specific to be useful in practice. Moreover, high reliability does not guarantee high sensitivity or specificity. However, a test that is highly sensitive is highly reliable among persons who have disease; and a test that is highly specific is highly reliable among persons who do not (Morrison 1992).

Multiple Testing Strategies. Multiphasic screening combines screening for multiple conditions on the same occasion (e.g., blood pressure, blood lipids, blood glucose, height, and weight among attendees of a county fair) (Sackett et al. 1991). The opportunity to screen for multiple conditions on a single occasion has obvious advantages in terms of convenience for the participants and potential efficiency for the organizers. However, the advantages of convenience and efficiency often are negated by the disadvantages of complex logistics, inadequate follow-up, and dilution of motivation for change when multiple problems are detected in the same person (Mittelmark et al. 1993). Integrated methods of early detection for coronary heart disease (CHD) include screening for high blood pressure and for elevated serum cholesterol and assessing behavioral risk factors (e.g., tobacco use, dietary fat intake, and physical activity level). Simultaneous screening for these risk factors as a prelude to multiple risk factor interventions is now well established in the practice of both high-risk and community-based approaches to primary prevention of CHD (Smith and Pratt 1993).

Sequential Testing Strategies. Sequential testing combines two different screening tests in sequence. The second test is done only if the first test is positive. For example, the combination of an abnormal digital rectal exam (DRE) and elevated prostate-specific antigen (PSA) test, in sequence, increased the PVP to 49% (positive on both tests), compared with 20% for PSA with negative DRE and 28%-35% for PSA alone (USPSTF 1996). More importantly, a repeatedly reactive EIA (enzyme immunoassay) test requires a sequentially administered positive Western blot test to confirm infection with the HIV (CDC 1992). Sequential testing is a technique for increasing the accuracy (PVP) of a screening procedure. However, an unknown number of persons with disease whose results are negative on the first test and are of unknown status on the second test will be missed. The alternative decision rule of admitting to diagnostic testing all persons who are positive on either test would trade off the PVP advantage of sequential testing in exchange for picking up the missed cases (Morrison 1992).

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