在阿片类药物使用障碍治疗期间恢复使用的个人水平风险预测
Sean X Luo1, Daniel J Feaster2, Ying Liu1
1Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
JAMA psychiatry
|October 4, 2023
概括
一个新的预测工具有助于识别返回阿片类药物使用障碍治疗的早期风险. 临床医生可以利用这一点,在关键的前三周的护理期间集中干预.
科学领域:
- 成 药物 药物 药物 药物
- 临床预测模型临床预测模型
- 公共卫生 公共卫生
背景情况:
- 预测在早期治疗中恢复阿片类药物使用对于有效干预至关重要.
- 目前的模型缺乏在治疗阿片类药物使用障碍 (OUD) 的初始阶段识别高风险患者的能力.
研究的目的:
- 开发一个个体级预测工具来评估回归阿片类药物使用的风险.
- 在OUD治疗的早期阶段确定复发的关键预测因素.
主要方法:
- 通过使用国家药物滥用临床试验网络 (CTN) 内的三项实用随机临床试验的协调个人级数据创建了一个决策分析模型.
- 该模型纳入了2199名接受甲,布普伦诺芬或延长释放纳尔克松的成年参与者的数据.
- 开发了回归使用的预测模型,定义为连续四周在12周之前缺失或呈阳性尿液药物查 (UDS) 的非处方阿片类药物.
主要成果:
- 一个初始模型与四个预测因素 (海洛因使用日,吗啡和可卡因阳性UDS,海洛因注射) 显示中等的预测性能 (AUROC,0.67).
- 结合前三个治疗周的UDS结果,显著改善了预测 (AUROC,0.82).
- 一个简化的风险评分 (CTN-0094 OUD回归使用风险评分) 有效地对患者进行了分层,根据早期UDS结果,风险从13%到85%不等.
结论:
- 开发的预测模型是治疗第3周恢复阿片类药物使用的通用风险指标.
- 旨在预防复发的干预措施应优先考虑关键的早期治疗期.
- CTN-0094 OUD回归使用风险评分为临床风险分层和有针对性的干预提供了一个实用的工具.
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