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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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Regret (1 – PPV) as a function of prevalence ∏ and specificity for example in Table 4 assuming sensitivity held constant at 0.90.
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Figure 3: Regret (1 – PPV) as a function of prevalence ∏ and specificity for example in Table 4 assuming sensitivity held constant at 0.90.

Mentions: Figure 3 shows how the regret (so defined) varies with both the prevalence and specificity, when the sensitivity is held constant at 0.90. Looking at Figure 3, you can see how the likelihood that a subject who tests positive actually is disease free changes as the prevalence changes. If the actual prevalence in the population were say 0.3, the regret would be approximately 0.7 and if the prevalence were as low as 0.08, the regret would be 0.9. This example illustrates the point that both technical parameters of the screening test and prevalence need to be considered.


Screening tests: a review with examples.

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

Regret (1 – PPV) as a function of prevalence ∏ and specificity for example in Table 4 assuming sensitivity held constant at 0.90.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: Regret (1 – PPV) as a function of prevalence ∏ and specificity for example in Table 4 assuming sensitivity held constant at 0.90.
Mentions: Figure 3 shows how the regret (so defined) varies with both the prevalence and specificity, when the sensitivity is held constant at 0.90. Looking at Figure 3, you can see how the likelihood that a subject who tests positive actually is disease free changes as the prevalence changes. If the actual prevalence in the population were say 0.3, the regret would be approximately 0.7 and if the prevalence were as low as 0.08, the regret would be 0.9. This example illustrates the point that both technical parameters of the screening test and prevalence need to be considered.

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