Common things are common, but what is common? A foundation for
probabilistic diagnosis.
Scott K Aberegg, MD, MPH
Sean J Callahan, MD
Funding: There is no funding for this work.
Ethical approval: There is no requirement for ethical approval
of this work.
Summary:
The well-known clinical axiom declaring that “common things are
common” attests to the pivotal role of probability in diagnosis.
Despite the popularity of this and related axioms, there is no
operationalized definition of a common disease, and no practicable way
of incorporating actual disease frequencies into differential diagnosis.
In this expository essay, we aim to reduce the ambiguity surrounding the
definition of a common (or rare) disease and show that incidence – not
prevalence – is the proper metric of disease frequency for diagnosis.
We explore how numerical estimates of disease frequencies based on
incidence can be incorporated into differential diagnosis as well as the
inherent limitations of this method. These concepts have important
implications for diagnostic decision making and medical education, and
hold promise as a method to improve diagnostic accuracy.