药物暴露作为糖尿病视网膜病变风险预测模型中的预测因素-系统性审查和元分析
Maria Anna Bantounou1, Tulika A K Nahar2, Josip Plascevic1
1From the School of Medicine, University of Aberdeen (M.A.B., J.P., S.P.), Aberdeen, UK.
American journal of ophthalmology
|July 21, 2024
概括
这次审查发现胰岛素使用与糖尿病视网膜病变 (DR) 风险增加以及改善的DR预测模型有关. 在模型中更好的药物处理可以提高DR的预测准确性.
科学领域:
- 糖尿病中的药物监测和预测建模.
- 眼科和代谢疾病研究.
背景情况:
- 糖尿病视网膜病变 (DR) 是糖尿病的一个主要并发症,需要准确的风险预测.
- 药物暴露是影响DR发展和进展的潜在因素,但其在预测模型中的处理不一致.
研究的目的:
- 系统地审查如何在糖尿病视网膜病变 (DR) 风险预测模型中处理药物暴露.
- 通过网络元分析识别与DR风险相关的药物.
- 通过元分析确定哪些药物可以提高DR预测模型的性能.
主要方法:
- 在2023年12月之前发表的研究 (EMBASE,MEDLINE,SCOPUS) 的系统审查和元分析.
- 网络元分析以估计药物-DR关联的几率比率 (OR).
- 进行元分析,以计算用于模型性能评估的C统计数据.
- 使用已知工具进行偏差风险和确定性评估 (PROSPERO:CRD42022349764).
主要成果:
- 包括28项研究 (678,837名参与者);19项具有高偏差风险.
- 胰岛素是最常见的模拟药物 (n=24) 并与DR风险增加有关 (OR=2.50).
- 包括胰岛素的模型表现更高 (C-统计=0.84) 与没有 (C-统计=0.70) 的模型相比.
- 药物暴露主要被视为一个分类变量,仅限于使用时间变化的方法.
结论:
- 这是第一个评估DR预测模型中药物暴露处理的审查.
- 胰岛素使用与更高的DR风险和改善模型性能有关,但低于最佳的建模方法可能会掩盖其他药物效应.
- 未来的DR预测模型应该将药物暴露作为一个变量,利用时间变化的方法,并考虑药物治疗方案的细节,以提高预测准确度.
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