J Postgrad Med
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The area under the ROC curve is frequently used for assessing the predictive efficacy of a model, and the Youden index is commonly used to provide the optimal cut-off. Both are misleading tools for predictions. A ROC curve is drawn for the sensitivity of a quantitative test against its (1 - specificity) at different values of the test. ⋯ We propose predictivity-based ROC curves as tools for providing predictivities at varying prevalence in different populations. For optimal cut-off for prediction, in place of the Youden index, we propose a P-index where the sum of positive and negative predictivities is maximum after subtracting 1. To conclude, for correctly assessing adequacy of a prediction models, predictivity-based ROC curves should be used instead of the usual sensitivity-specificity-based ROC curves and the P-index should replace the Youden index.