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.
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.
Authors: N Smidt; A W S Rutjes; D A W M van der Windt; R W J G Ostelo; P M Bossuyt; J B Reitsma; L M Bouter; H C W de Vet Journal: Neurology Date: 2006-09-12 Impact factor: 9.910
Authors: M F Mitchell; S B Cantor; C Brookner; U Utzinger; D Schottenfeld; R Richards-Kortum Journal: Obstet Gynecol Date: 1999-11 Impact factor: 7.661
Authors: Anne W S Rutjes; Johannes B Reitsma; Marcello Di Nisio; Nynke Smidt; Jeroen C van Rijn; Patrick M M Bossuyt Journal: CMAJ Date: 2006-02-14 Impact factor: 8.262
Authors: Gea A Holtman; Yvonne Lisman-van Leeuwen; Boudewijn J Kollen; Obbe F Norbruis; Johanna C Escher; Angelika Kindermann; Yolanda B de Rijke; Patrick F van Rheenen; Marjolein Y Berger Journal: Ann Fam Med Date: 2016-09 Impact factor: 5.166
Authors: Mikashmi Kohli; Ian Schiller; Nandini Dendukuri; Keertan Dheda; Claudia M Denkinger; Samuel G Schumacher; Karen R Steingart Journal: Cochrane Database Syst Rev Date: 2018-08-27