血液病患者血小板输注无效的预测模型验证  

Validation of a predictive model for platelet transfusion refractoriness in patients with hematological diseases

作　　者：黄秀兰 岳姝含 蔡群 卢黎琦 何梦珍 雷乔 刘曹毅 张静薇[1] HUANG Xiulan;YUE Shuhan;CAI Qun;LU Liqi;HE Mengzhen;LEI Qiao;LIU Caoyi;ZHANG Jingwei(Department of Blood Transfusion,Chengdu Second People′s Hospital,Chengdu 610051,China)

机构地区：[1]成都市第二人民医院输血科,四川成都610051

出　　处：《中国输血杂志》2025年第4期537-545,共9页Chinese Journal of Blood Transfusion

基　　金：成都市科学技术局技术创新研发项目(2024-YF05-00936-SN)。

摘　　要：目的对本中心建立的血液病患者血小板输注无效(platelet transfusion refractoriness,PTR)预测模型进行验证和优化。方法采用2021年12月—2022年12月输注血小板的血液病患者数据作为训练集,2023年1—12月输注血小板的血液病患者数据作为验证集,利用验证集数据对训练集构建的预测模型进行验证。根据文献和前期研究结果收集PTR的相关危险因素,根据血小板计数纠正增加指数(corrected count increment,CCI)分为有效组和无效组。利用单因素和多因素Logistic回归分析筛选出预测因子,利用校准曲线验证模型的校准度,利用受试者工作曲线(receiver operating characteristic curve,ROC)验证模型区分度和准确度、灵敏度和特异度,利用决策曲线(decision curve analysis,DCA)分析其临床价值。结果验证集Hosmer-Lemeshow(H-L)拟合优度检验S:P=0.000,提示原模型需要优化。通过比较基线值差异和Logistic回归选择输注红细胞单位(redblood cell unit,RBC-U)和输注血小板治疗量(platelet unit,PLT-U)作为优化模型的预测因子。优化后训练集和验证集的H-L拟合优度检验S:P分别为0.930和0.056;ROC面积分别为0.7935和0.8094,特异度分别为90.95%和84.21%,灵敏度分别为59.26%和70.04%,准确度分别为78.14%和74.10%。验证集DCA结果显示其预测概率在0.2~0.8之间可获得临床净获益。结论RBC-U和PLT-U与血液病患者血小板输注无效具有负向相关性,由此构建的PTR预测模型具有中等强度的预测效能和临床获益。Objective To validate and optimize the platelet transfusion refractoriness(PTR)prediction model for patients with hematological disorders established by our center.Methods The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set,and data from January 2023 to December 2023 as the validation set.The validation set data was used to validate the predictive model constructed on the training set.Relevant risk factors for PTR were collected through literature review and preliminary studies。The patients were divided into effective and ineffective groups according to the corrected count increment(CCI)of platelet counts.Predictive factors were screened using univariate and multivariate logistic regression.The calibration of the model were assessed via calibration curves,while discrimination,accuracy,sensitivity,and specificity were evaluated using receiver operating characteristic(ROC)curves Clinical utility was further analyzed with decision curve analysis(DCA).Results The Hosmer-Lemeshow(H-L)goodness-of-fit test for the validation set yielded S:P=0.000,indicating that the original model needs optimization.Baseline comparisons and logistic regression identified the number of red blood cell units(RBC-U)and platelet units(PLT-U)transfused as key predictors for the optimized model.The H-L goodness-of-fit test S:P values for the training and validation sets were 0.930 and 0.056,respectively;the ROC areas were 0.7935 and 0.8094,specificities 90.95%and 84.21%,sensitivities 59.26%and 70.04%,and accuracies 78.14%and 74.10%,respectively.DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8.Conclusion Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients.The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

关 键 词：血液病 血小板输注无效 模型验证 

分 类 号：R457.1[医药卫生—治疗学] R331.143[医药卫生—临床医学]