对腹腔大动脉动脉瘤的基于血液的生物标志物的鉴定和评估
Ben Li1,2,3,4, Hamzah Khan2, Farah Shaikh2
1Department of Surgery, University of Toronto, Toronto M5T 1P5, Canada.
Journal of proteome research
|April 22, 2024
概括
结合临床数据和两种特定蛋白质 (angiopoietin-2和aggrecan) 的新模型显著改善了腹腔大动脉动脉瘤患者主要大动脉不良事件的预测. 这提供了更好的预后准确性.
科学领域:
- 心血管研究研究心血管研究
- 生物标志物发现发现
- 医学预测 医学预测
背景情况:
- 腹腔大动脉动脉瘤 (AAA) 的个人蛋白质生物标志物在预测预后方面存在局限性.
- 需要采用全面的小组方法来提高AAA结果的预测准确性.
研究的目的:
- 在患有腹腔大动脉动脉瘤 (AAA) 的患者中开发和验证主要大动脉不良事件 (MAAE) 的预测模型.
- 评估蛋白质生物标记面板的增量价值与AAA预后的临床特征相结合.
主要方法:
- 一组452名有/没有AAA患者的前性队列被跟踪了2年.
- 一个随机森林模型被训练使用临床特征和9个生物标志物的血清度.
- 该模型预测了2年的MAAE,包括AAA快速扩张,干预或破裂在内的复合结果.
主要成果:
- 两种蛋白质,血管蛋白-2和aggrecan,在AAA患者中显著升高.
- 仅使用临床特征的预测模型就实现了0.74.7的AUROC.
- 整合2蛋白面板提高了模型的预测性能,达到0.86.8的AUROC.
结论:
- 临床和生物标志物数据的组合模型准确地预测腹腔大动脉动脉瘤 (AAA) 患者的2年MAAE.
- 鉴定的蛋白质面板显著提高了AAA结果的预后能力.
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