Figure 3

Calculating CID by the ROC method. This analysis defines the sensitivity and specificity of different cutoffs of a predictor (e.g., pain) for an anchor (e.g., global change). The diagonal line represents a test with no predictive value. The curve is the ROC analysis. The CID is the cutoff of the predictor with the highest sensitivity and specificity for predicting the anchor, i.e., the upper left most point on the ROC curve (marked by an x on the graph). For example, the x might represent 30% pain reduction as the best cutoff to predict “much improved” on a PGIC.