Fig. 1. Fagan nomogram using the Bayesian theory showing the pretest and postprobabilities and the likelihood ratio. (A ) A straight line is applied for a low pretest probability (0.20) for a good biomarker with a positive likelihood ratio of 10, providing a posttest probability of (0.80); the important change in probability suggests a change for the physician (diagnostic or therapeutic). (B ) In contrast, when the same good biomarker is applied to a patient with a high pretest probability (0.80), the posttest probability is more than 0.95, but this may not represent an important change for the physician. (C ) The effects of several biomarkers with different likelihood ratios (2, 10, and 50) in a patient with a pretest probability of 0.50. The nomogram is reprinted with permission from Fagan.21