Development and Validation of a Nomogram for Predicting Drug-induced thrombocytopenia in Hospitalized Patients: A Case‒Control Study Based on Propensity-Score Matching

Abstract

Abstract Objective Drug-induced thrombocytopenia (DITP) is associated with increased mortality. This study aims to establish a nomogram to predict the occurrence of DITP in hospitalized patients in a multidrug environment. Methods A single-centre retrospective study among hospitalized adult patients was conducted from January 2021 to December 2021 and was based on the Adverse Drug Events Active Surveillance and Assessment System-Ⅱ (ADE-ASAS-Ⅱ). Three controls were matched for each case according to the propensity score matching algorithm to eliminate confounding bias due to individual baseline variables. Predictors of DITP were obtained by LASSO regression and were used to build the nomogram. Results Among 88151 hospitalized patients, 478 were confirmed to have DITP, which is an incidence rate of 0.54%. After matching, 382 pairs and 1146 patients were included in the study, including 1070 cases in the development group and 427 cases in the validation group. Five variables were used to construct the nomogram: hospital stay ≥ 14days, surgery before using suspected drugs, baseline platelet count < 150×109/L, higher baseline BUN and combined with antibacterial. The areas under the curve (AUC) in the development group and validation group were 0.827 (95% CI 0.800-0.854) and 0.785 (95% CI 0.736–0.834), respectively, and the model also showed good calibration (P > 0.05) in the development group and validation group. Conclusion The established nomogram can help identify high-risk patients with DITP, assist doctors in decision-making, and effectively prevent DITP in the early stage.