Diagnostic testing, pre- and post-test probabilities, and their use in clinical practice.
In the process of establishing a diagnosis, the clinician calculates the disease probabilities, which keep changing as data is gathered from clinical history, physical examination and laboratory and imaging data. This paper sets out to explain, in a simple and practical way, how the characteristics of a test can be applied in order to determine post-test probability, that is, the probability of a specific disease being present. Before applying the test, we start with a pretest probability that corresponds to the prevalence of the disease. With each additional test this probability changes, until a threshold is reached that includes or excludes the clinical diagnosis. To calculate the post-test probabilities, the sensitivity and specificity of the test are used to calculate the positive and negative predictive values for a determined pretest probability, as well as likelihood ratios (through graphics or nomograms, approximations or equations). Among the test characteristics, the most useful for calculating post-test probabilities are likelihood ratios, which have several advantages over sensitivity and specificity.
Paulo
Sérgio
S
Centro de Estudos de Medicina Baseada na Evidência, Faculdade de Medicina de Lisboa, Lisboa, Portugal.
Mendes
Susana
S
Vizinho
Ricardo
R
Carneiro
António Vaz
AV
D015510:Clinical Medicine / Q000592:standards; D003955:Diagnostic Tests, Routine / Q000706:statistics & numerical data*; D006801:Humans; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity