Screening tests: a review with examples

Abstract

Screening tests are widely used in medicine to assess the likelihood that members of a defined population have a particular disease. This article presents an overview of such tests including the definitions of key technical (sensitivity and specificity) and population characteristics necessary to assess the benefits and limitations of such tests. Several examples are used to illustrate calculations, including the characteristics of low dose computed tomography as a lung cancer screen, choice of an optimal PSA cutoff and selection of the population to undergo mammography. The importance of careful consideration of the consequences of both false positives and negatives is highlighted. Receiver operating characteristic curves are explained as is the need to carefully select the population group to be tested.

Keywords: Benefits and limitations; positive and negative predicted value; prevalence; screening tests; sensitivity; specificity.

Figure 1.

Reported sensitivity and specificity of a sample of screening tests reported in the literature. Circles are studies summarized here (Table A1) while triangles represent studies reported in Alberg et al. (2004).

Figure 2.

Positive predictive value (PPV), negative predictive value (NPV) and accuracy as a function of assumed prevalence for first numerical example.

Figure 3.

Regret (1 – PPV) as a function of prevalence ∏ and specificity for example in Table 4 assuming sensitivity held constant at 0.90.

Figure 4.

Combination of values of prevalence, specificity and sensitivity associated with a regret probability of 0.80.

Figure 5.

Positive predictive value from mammography for women in various age groups with and without a family history of cancer according to data provided in Kerlikowske et al. (1993).

Figure 6.

Receiver operating characteristic curve of prostate specific antigen (PSA) test, based on data from Thompson et al. (2005) among men aged 70 or more. Numbers shown are the specific cutoff on the PSA test result. The area under the curve (AUC) in this case is 0.678.

Figure 7.

Receiver operating characteristic curves of prostate specific antigen (PSA) test, based on data from Thompson et al. (2005) among men aged 70 or more (AUC = 0.678). The top curve uses a combined PSA and Gleason Grade > 8 score (AUC = 0.827). The bottom curve is what would be expected by chance alone (AUC = 0.50).