Determinants of the magnitude of response to vitamin D supplementation in adolescent girls identified using a decision tree algorithm.

Vitamin D (VitD) supplementation is an inexpensive and effective approach for improving VitD insufficiency/deficiency. However, the response to supplementation, with respect to the increase in serum 25(OH)D level varies between individuals. In this study, we have assessed the factors associated with the response to VitD supplementation using a decision-tree algorithm. Serum VitD levels, pre- and post-VitD supplementation was used as the determinant of responsiveness. The model was validated by constructing a receiver operating characteristic curve. Serum VitD at baseline levels was at the apex of the tree in our model, followed by serum low-density lipoprotein cholesterol and triglyceride, age, waist-hip ratio, and high-density lipoprotein cholesterol. Our model suggests that these determinants of responsiveness to VitD supplementation had sensitivity, specificity, and accuracy, 59.4, 75.8 and 69.3%, respectively. The decision tree model appears to be a relatively accurate, specific, and sensitive approach for identifying the factors associated with response to VitD supplementation.