![\"Unrinalysis](\"http:\/\/bob_phillips.allmail.net\/urinalysis.gif\")
In examining a diagnostic test, we make the assumption that the characteristics of the test – its sensitivity and specificity (or likelihood ratios, the way I prefer to think) – will stay constant across different populations, although the positive and negative predictive values will change * . This is sort of true, and sort of false.<\/p>\n
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Take an imagined example: using leucocyte urine dipsticks to diagnose UTIs. If the original study is undertaken in the acute assessment department of a paediatric hospital, then the sticks will be used to differentiate between children with similar alternative diagnoses and conditions (e.g. viral infections, UTIs and avoiding school) . This is the disease spectrum<\/em>. It might be that in the referred population of the assessment unit, 10% of febrile children have UTIs (that’s the prevalence<\/em>).<\/p>\n Now the sensitivity and specificity that his study describes are likely to be true when used in a paediatric ED, or when seeing kids in primary care. Why? Because although the prevalence<\/em> of UTI may vary (maybe 1% in primary care and 5% in ED’s), the other competing diagnoses are similar. The prevalence<\/em> of the condition has changed, but the spectrum<\/em> of illnesses seen hasn’t.<\/p>\n