Foundations of medical diagnosis: what actually are the parameters involved in Bayes' theorem?

Stat Med. 1994 Feb 15;13(3):201-9; discussion 211-5. doi: 10.1002/sim.4780130302.

Abstract

Three decades ago, the thesis was adduced that setting diagnostic probabilities requires, by the inherent nature of diagnosis-pertinent medical knowledge, the use of Bayes' theorem. That paper was both vague and inconsistent in its delineation of the nature of the parameters involved in this formulation, and subsequent authors have only added to the confusion. Nevertheless, that thesis has been, and continues to be, enthusiastically embraced by clinical scholars. We here posit what those parameters must be taken to represent in principle; and this explication reveals that their quantification poses generally unsurmountable epistemologic challenges. The implication of this is not that informed setting of diagnostic probabilities is generally infeasible. Our conclusion is, instead, that the seminal thesis was founded on an untenable pair of premises about the nature of scientifically attainable knowledge pertinent to diagnosis.

MeSH terms

  • Bayes Theorem*
  • Diagnosis*
  • Humans
  • Likelihood Functions*
  • Logistic Models
  • Predictive Value of Tests*
  • Prevalence