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Common things are common, but what is common? A foundation for probabilistic diagnosis.
  • Scott Aberegg,
  • Sean Callahan
Scott Aberegg
University of Utah Health
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Sean Callahan
University of Utah Health
Author Profile

Abstract

The well-known clinical axiom stating 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 a 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.

Peer review status:UNDER REVIEW

16 Jun 2021Submitted to Journal of Evaluation in Clinical Practice
28 Jun 2021Submission Checks Completed
28 Jun 2021Assigned to Editor
07 Jul 2021Reviewer(s) Assigned
25 Aug 2021Review(s) Completed, Editorial Evaluation Pending
12 Sep 2021Editorial Decision: Revise Minor
21 Sep 20211st Revision Received
23 Sep 2021Submission Checks Completed
23 Sep 2021Assigned to Editor
24 Sep 2021Reviewer(s) Assigned