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Review
. 2013 Aug 6;185(11):E537-44.
doi: 10.1503/cmaj.121286. Epub 2013 Jun 24.

Variation of a test's sensitivity and specificity with disease prevalence

Mariska M G Leeflang  1 , Anne W S Rutjes, Johannes B Reitsma, Lotty Hooft, Patrick M M Bossuyt
Affiliations
Review

Variation of a test's sensitivity and specificity with disease prevalence

Mariska M G Leeflang et al. CMAJ. .

Abstract

Background: Anecdotal evidence suggests that the sensitivity and specificity of a diagnostic test may vary with disease prevalence. Our objective was to investigate the associations between disease prevalence and test sensitivity and specificity using studies of diagnostic accuracy.

Methods: We used data from 23 meta-analyses, each of which included 10-39 studies (416 total). The median prevalence per review ranged from 1% to 77%. We evaluated the effects of prevalence on sensitivity and specificity using a bivariate random-effects model for each meta-analysis, with prevalence as a covariate. We estimated the overall effect of prevalence by pooling the effects using the inverse variance method.

Results: Within a given review, a change in prevalence from the lowest to highest value resulted in a corresponding change in sensitivity or specificity from 0 to 40 percentage points. This effect was statistically significant (p < 0.05) for either sensitivity or specificity in 8 meta-analyses (35%). Overall, specificity tended to be lower with higher disease prevalence; there was no such systematic effect for sensitivity.

Interpretation: The sensitivity and specificity of a test often vary with disease prevalence; this effect is likely to be the result of mechanisms, such as patient spectrum, that affect prevalence, sensitivity and specificity. Because it may be difficult to identify such mechanisms, clinicians should use prevalence as a guide when selecting studies that most closely match their situation.

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Figures

Figure 1:
Figure 1:
Prevalence estimates for each primary study in the 23 included meta-analyses. The size of the circle reflects the study size: < 100 participants; 100–500 participants; 500–1000 participants; and > 1000 participants. Prevalence is shown as a proportion.
Figure 2:
Figure 2:
The effect of prevalence on logit sensitivity and specificity. Prevalence effects on logit sensitivity and specificity are shown per 1%. Beta reflects the effect size. CI = confidence interval.
Figure 3:
Figure 3:
Change in sensitivity and specificity with increasing prevalence. The lines represent sensitivity and specificity at the minimum and maximum prevalence in each meta-analysis. Sensitivity and specificity are shown as proportions. The circles reflect sensitivity and specificity at the lowest prevalence, and the arrowheads reflect sensitivity and specificity at the highest prevalence.*p value < 0.05
See this image and copyright information in PMC

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