Abstract
This study aims to explore the factors that affect the efficacy of apheresis platelet transfusion in patients with hematologic diseases and construct a nomogram prediction model to predict the possibility of obtaining satisfactory platelet transfusion efficacy and guide scientific and rational platelet transfusion. The basic information of 2,007 hematologic patients who received apheresis platelet transfusions from June 2022 to April 2023 and the corresponding donor information and apheresis platelet data are collected. The risk factors that cause ineffective platelet transfusions are screened through a logistic regression analysis. Then, the risk factors are introduced into R software, and a nomogram prediction model is established and validated. The regression analysis shows that the independent risk factors for ineffective platelet transfusion are platelet count before transfusion, white blood cell count, hemoglobin content and mean corpuscular hemoglobin, cumulative platelet transfusion times, platelet antibody positivity, fever, splenomegaly, graft-versus-host disease, bleeding, and platelet storage days. These factors are included in the nomogram, and the calibration curve for predicting transfusion efficiency reveals good consistency between the nomogram-predicted results and the actual observations. The area under the curve obtained through internal repeated sampling is 0.756. This study comprehensively assessed the risks associated with factors leading to ineffective platelet transfusion and successfully constructed and validated a nomogram prediction model. This model provides an important predictive tool for assessing the efficacy of platelet transfusion in patients with hematologic diseases, with the potential to guide scientific and rational platelet transfusion practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12288-024-01857-0.