Links To And Excerpts From “Key concepts in clinical epidemiology: Estimating pre-test probability”

Today, I review, link to, and excerpt from Key concepts in clinical epidemiology: Estimating pre-test probability [PubMed Abstract] [Full-Text HTML] [Full-Text PDF]. Elenore Judy B Uy 1. J Clin Epidemiol. 2022 Apr:144:198-202. doi: 10.1016/j.jclinepi.2021.10.022. Epub 2021 Nov 2.

All that follows is from the above resource.


Appropriate medical management largely hinges on correctly diagnosing the underlying disease. Often, clinicians are faced with a dizzying array of accurate, albeit expensive and/or invasive diagnostic tests. What tends to be overlooked is that the probability of a disease once the test results are in (post-test probability) is a function of both the probability of the disease before the test was done (pre-test probability) and the diagnostic accuracy of the test. Clinicians need to be cognizant of inherent limitations in estimating pre-test probability and be more adept at finding ways to overcome these limitations. An accurate estimate of pre-test probability is pivotal. It guides the decision whether or not to conduct further testing, the choice of diagnostic test to perform, the interpretation of the test result, and the subsequent management of the patient’s disease.

Keywords: Clinical Decision-Making; Diagnosis; Diagnostic tests; Pre-test probability.


It is largely acknowledged that the process of arriving at a given patient’s diagnosis is a complex, multi-step process that begins with gathering initial clinical data, and forming one or more diagnostic hypotheses.
In the context of arriving at a single definitive diagnosis amidst many differential diagnoses, clinicians use diagnostic tests to estimate the probability of disease in a given patient. The probability of disease changes from before the test is done (pre-test probability) to after the test results are in (post-test probability). The final probability of disease depends on 3 things – the characteristics of the test itself, the test result (positive, negative or in-between), and the probability of disease before the test was done, that is, the pre-test probability of disease.

The estimation of pre-test probabilities is important and necessary:

  • 1
    to decide whether or not further testing should be done,
  • 2
    to identify which test to use, and
  • 3
    to revise the probability of disease after the test results are in.

Estimating initial pre-test probability

The pre-test probability of a disease can be derived either from clinician experience or research evidence (e.g. disease prevalence and clinical prediction rules); for a single patient, or for groups of patients. The advantages and pitfalls of these approaches are summarized in Table 1.
Fig1 when server ready
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