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Screening tests: a review with examples.

Maxim LD, Niebo R, Utell MJ - Inhal Toxicol (2014)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Everest Consulting Associates , Cranbury, NJ , USA and.

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.

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Positive predictive value (PPV), negative predictive value (NPV) and accuracy as a function of assumed prevalence for first numerical example.
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Figure 2: Positive predictive value (PPV), negative predictive value (NPV) and accuracy as a function of assumed prevalence for first numerical example.

Mentions: The a posteriori probability of having the disease given a positive test result, or PPV, is one obvious measure of the evidence provided by the test. Other things being equal, tests with high specificity (few false positives) tend to have a high PPV. However, unlike sensitivity or specificity (which might be termed “pure characteristics” of the test), the PPV is also a function of the characteristics of the population under study; PPV is a function of the prevalence. In the numerical example given in Table 4, the prevalence was assumed to be 0.5 (i.e. 50% of the population or subpopulation had the disease). Figure 2 shows how the PPV, NPV and accuracy depend upon the assumed prevalence Π in the population being screened. As can be seen, both PPV and accuracy decrease (sharply in the case of PPV) as Π decreases from the base case assumption of 0.50. Conversely, the NPV increases as the prevalence decreases.


Screening tests: a review with examples.

Maxim LD, Niebo R, Utell MJ - Inhal Toxicol (2014)

Positive predictive value (PPV), negative predictive value (NPV) and accuracy as a function of assumed prevalence for first numerical example.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389712&req=5

Figure 2: Positive predictive value (PPV), negative predictive value (NPV) and accuracy as a function of assumed prevalence for first numerical example.
Mentions: The a posteriori probability of having the disease given a positive test result, or PPV, is one obvious measure of the evidence provided by the test. Other things being equal, tests with high specificity (few false positives) tend to have a high PPV. However, unlike sensitivity or specificity (which might be termed “pure characteristics” of the test), the PPV is also a function of the characteristics of the population under study; PPV is a function of the prevalence. In the numerical example given in Table 4, the prevalence was assumed to be 0.5 (i.e. 50% of the population or subpopulation had the disease). Figure 2 shows how the PPV, NPV and accuracy depend upon the assumed prevalence Π in the population being screened. As can be seen, both PPV and accuracy decrease (sharply in the case of PPV) as Π decreases from the base case assumption of 0.50. Conversely, the NPV increases as the prevalence decreases.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Everest Consulting Associates , Cranbury, NJ , USA and.

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.

Show MeSH