Table 1:

Theoretical framework of how disease prevalence and test accuracy may be related (10)

Factor	Effect on prevalence	Effect on accuracy
Clinical variability
Patient spectrum	Distribution of symptoms and severity may change with varying prevalence	Differences in symptoms and severity influences sensitivity and specificity
Referral filter	How and through what care pathway patients are referred may influence the spectrum of disease in the population	A change in setting and patient spectrum may also alter a test’s sensitivity and specificity
Reader expectations	Prevalence influences reader expectations: if one knows that the prevalence should be high, then one’s intrinsic threshold may be lowered	Changing one’s intrinsic threshold will influence accuracy
Artifactual variability
Distorted inclusion of participants	Excluding patients with difficult to diagnose conditions may influence the prevalence	Excluding patients with difficult to diagnose conditions will overestimate the accuracy of a test
Verification bias	If not all patients receive the (same) reference standard, this influences prevalence	Verification bias has an effect on test accuracy
Imperfect reference standard	Prevalence will be over- or underestimated	Test accuracy may be underestimated; the extent of which varies with prevalence