Summary
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 (c 1) and the specificity (c 2) of the test. A new variable has been introduced, the predictive factor (c), which is calculated as follows:c=c 1/(c 1+1−c 2). 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.
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Dedicated to my clinical teacher, Professor Dr. med. Dr. med. h.c. W. Creutzfeldt, on the occasion of his 60th birthday. Without knowing Bayes' formula he taught me Bayesian thinking in medicine (J.K.)
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Köbberling, J., Richter, K. & Tillil, H. The predictive factor — a method to simplify Bayes' formula and its application to diagnostic procedures. Klin Wochenschr 62, 586–592 (1984). https://doi.org/10.1007/BF01728177
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DOI: https://doi.org/10.1007/BF01728177