基于真实世界数据研究阿帕替尼致高血压预测模型的建立与评价

doi:10.19803/j.1672-8629.20240579

摘要/Abstract

摘要： 目的分析阿帕替尼致高血压的危险因素并建立预测模型,同时验证该模型的准确率。方法回顾性收集 2020年1月1日至2023年12月31日安庆市立医院使用阿帕替尼治疗的168例住院患者信息,其中2020年1月1日至2022年12月31日病例121例作为训练集,2023年1月1日至2023年12月31日47例病例作为验证集。利用训练集患者临床信息筛选出阿帕替尼致高血压的独立危险因素,建立预测模型并利用ROC曲线对模型进行评价,再利用验证集患者信息验证该模型的准确率。结果 121例训练集患者中共有51例（42.15%）发生了高血压。与未发生高血压组相比,高血压组在性别、年龄、是否合并高血压、单药是否高剂量、是否联合免疫及化疗共5个指标异常,其差异具有统计学意义（P<0.05）,二元Logistic 回归分析显示年龄、性别、是否合并高血压、和是否联合免疫及化疗是阿帕替尼致高血压的独立危险因素,4个危险因素联合建立预测模型的ROC曲线下面积为0.850,敏感度为72.50%,特异度为84.30%;47例患者进行交叉验证,预测模型的准确率为87.23％。结论年龄、性别、是否合并高血压及是否联合免疫及化疗是阿帕替尼致高血压的独立危险因素,对预测阿帕替尼致高血压发生率有一定价值。

关键词: 阿帕替尼, 高血压, 血管内皮生长因子, 危险因素, 真实世界数据, Logistic回归, 预测模型

Abstract: Objective To analyze the risk factors for hypertension induced by apatinib, establish a prediction model and verify its accuracy. Methods The data of 168 inpatients treated with apatinib in Anqing Municipal Hospital between 2020 and 2023 was retrospectively analyzed. In addition, 121 of these cases treated between 2020 and 2022 were used as the training set while another 47 cases treated in 2023 were selected as the validation set. The independent risk factors for apatinib-induced hypertension were screened using the clinical information of patients in the training set. A prediction model was established and evaluated by the ROC curve. The accuracy of the model was verified using the information of patients in the validation set. Results A total of 51 patients (42.15%) in the training set developed hypertension. Compared with the non-hypertensive group, there was statistically significant difference in gender, age, rates of complications with hypertension, dose and the adoption of immunization and chemotherapy in the hypertension group (P <0.05). Binary logistic regression analysis showed that age, gender, complications with hypertension, and the combination of immunization and chemotherapy were independent risk factors for apatinib-induced hypertension. The area under the ROC curve of the prediction model was 0.850, the sensitivity was 72.50%, and the specificity was 84.30%. The 47 patients in the validation set were selected for cross-validation, and the accuracy of the prediction model was 87.23%. Conclusion Age, gender, complications with hypertension, and the combination of immunization and chemotherapy are independent risk factors for apatinib-induced hypertension. The fitting model can help predict the incidence of apatinib-induced hypertension.

Key words: Apatinib, Hypertension, Vascular Endothelial Growth Factor (Vegf), Risk Factors, Real-World Data, Logistic Regression, Prediction Model

中图分类号:

R975
R994.11

王栓, 黄灿, 齐腊梅. 基于真实世界数据研究阿帕替尼致高血压预测模型的建立与评价[J]. 中国药物警戒, 2025, 22(4): 429-435.

WANG Shuan, HUANG Can, QI Lamei. Establishment and Evaluation of Apatinib-Induced Hypertension Prediction Model Based on Real-World Data[J]. Chinese Journal of Pharmacovigilance, 2025, 22(4): 429-435.

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https://zgywjj.magtechjournal.com/CN/Y2025/V22/I4/429

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