Can anyone advise: when calculating post-test probability of a diagnosis using the likelihood ratio for a diagnostic test, how do we make our best estimate of pre-test probability?
I understand that prevalence is often taken as a pragmatic estimate of pre-test probability. But I assume a patient who presents with symptoms of the condition has, by definition, a pre-test probability that is greater than the prevalence in the wider (or preferably age/sex specific) population.
To estimate pre-test probability, are we reliant on finding an estimate from an epidemiological study whose subjects most closely reflect the characteristics of our individual patient? This would seem a serious limitation to the utility of the Bayesian approach.