title: The predictive factor--a method to simplify Bayes' formula and its application to diagnostic procedures.
abstract: According to Bayes' rule the predictive value (PV) of a diagnostic test (= probability of disease if the test is positive) depends on the prevalence of the disease (= a priori probability), the sensitivity (c1) and the specificity (c2) of the test. A new variable has been introduced, the predictive factor (c), which is calculated as follows: c = c1/(c1 +1 -c2). Since the PV only depends on this factor and on the prevalence, the calculation is much easier and a general graphical solution is possible. This simplification renders several additional advantages and facilitates the understanding of the dependence of PV on prevalence.
mesh_terms: D001499:Bayes Theorem; D019411:Clinical Laboratory Techniques; D006680:HLA Antigens / Q000032:analysis; D015796:HLA-B27 Antigen; D006801:Humans; D008954:Models, Biological; D011336:Probability; D011379:Prognosis; D013167:Spondylitis, Ankylosing / Q000175:diagnosis; D013223:Statistics as Topic
chemical_list: D006680:HLA Antigens; D015796:HLA-B27 Antigen