Department of Laboratory Medicine, West China Hospital of Sichuan University, Sichuan, China.
J Cancer Res Clin Oncol. 2024 Sep 6;150(9):412. doi: 10.1007/s00432-024-05914-z.
Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder characterized by isolated thrombocytopenia that is often misdiagnosed due to the lack of a gold standard for diagnosis and currently relies on exclusionary approaches. This project combines several laboratory parameters to construct a clinical prediction model for adult ITP patients.
A total of 428 patients with thrombocytopenia who visited the West China Hospital of Sichuan University between January 2021 and March 2023 were enrolled. Based on the diagnostic criteria, we divided those patients into an ITP group and a non-ITP group. A total of 34 laboratory parameters were analyzed via univariate analysis and correlation analysis, and the least absolute shrinkage and selection operator regression analysis was used to establish the model. The training and validation sets were divided at a ratio of 7:3, and we used a fivefold cross-validation method to construct the model.
The model included the following variables: red blood cell, mean corpuscular hemoglobin concentration, red blood cell distribution width-standard deviation, platelet variability index score, immature platelet fraction, lymphocyte absolute value. The prediction model exhibited good performance, with a sensitivity of 0.89 and a specificity of 0.83 in the training set and a sensitivity of 0.90 and a specificity of 0.87 in the validation set.
The clinical prediction model can assess the probability of ITP in thrombocytopenic patients and has good predictive accuracy for the diagnosis of ITP.
原发性免疫性血小板减少症（ITP）是一种以孤立性血小板减少为特征的自身免疫性出血性疾病，由于缺乏诊断的金标准，常被误诊，目前依赖于排除性方法。本项目结合了多个实验室参数，构建了一个用于成人 ITP 患者的临床预测模型。
共纳入 2021 年 1 月至 2023 年 3 月期间在四川大学华西医院就诊的 428 例血小板减少症患者。根据诊断标准，我们将这些患者分为 ITP 组和非 ITP 组。通过单因素分析和相关性分析对 34 个实验室参数进行分析，并用最小绝对收缩和选择算子回归分析建立模型。训练集和验证集的划分比例为 7:3，我们采用五重交叉验证方法构建模型。
模型包含以下变量：红细胞、平均红细胞血红蛋白浓度、红细胞分布宽度标准差、血小板变异指数评分、未成熟血小板分数、淋巴细胞绝对值。该预测模型具有良好的性能，在训练集中的敏感性为 0.89，特异性为 0.83，在验证集中的敏感性为 0.90，特异性为 0.87。
临床预测模型可以评估血小板减少症患者发生 ITP 的概率，对 ITP 的诊断具有良好的预测准确性。
