Development and validation of a nomogram to predict the risk of potentially inappropriate medication use in older depression outpatients

Background : Potentially inappropriate medication (PIM) for the elderly is a serious public health problem associated with increased adverse drug events. PIM refers to medications where the adverse risks outweigh the potential benefits. Identifying the risk factors for PIM is essential for optimizing prescription practices and improving patient safety. Objective: To establish a risk prediction model for potentially inappropriate medications (PIMs) in older patients with depression, providing guidance to optimize medication plans, reduce adverse drug reactions, and improve treatment outcomes and quality of life. Methods: The prescription of depression patients in all hospitals in the Chengdu area was taken as an example. A significant factor influencing PIM risk was identified through univariate and multivariate logistic regression analyses, and a nomogram was constructed. The discrimination and calibration of the model were evaluated via receiver operating characteristic (ROC) curves. Results: Data from the Chengdu area (n=4629) were divided into a training set (n=3548) and an internal validation set (n=1081), with Zhengzhou data (n=1620) used as the external validation set. ROC curve analysis revealed that the area under the curve (AUC) for the training set was 0.721, that for the internal validation set was 0.668, and that for the external validation set was 0.663. Conclusion: The prediction model based on these factors has good predictive value for PIM occurrence in older patients with depression.