用因果机器学习检测denozumab停药后的双酸盐的影响和治疗效果异质性
Miryoung Kim1,2,3, Nakyung Jeon1, Hae Sun Suh4,5,6
1College of Pharmacy, Pusan National University, Busan, Republic of Korea.
Scientific reports
|December 24, 2025
概括
双酸盐 (BPs) 降低了在停止服用德诺苏马布后复发性骨质疏松性骨折的风险. 因果机器学习确定了受益最多的患者子组,从而实现了个性化骨折预防策略.
科学领域:
- 骨质疏松症管理管理
- 药物监督 药物监督 药物监督
- 医学中的因果推理.
背景情况:
- 停止德诺苏马布治疗导致骨质疏松性骨折 (OF) 风险的反弹增加.
- 双酸盐 (BPs) 经常被用作连续疗法,但实际有效性和患者特异性益处尚未得到充分证实.
研究的目的:
- 评估双酸盐 (BPs) 在停止使用登苏马布后减少复发性骨质疏松性骨折 (OFs) 的实际有效性.
- 通过因果机器学习方法识别表现出BP异质治疗效应的患者子组.
主要方法:
- 全国范围的回顾性队列研究利用韩国医疗保险索赔数据.
- 应用因果生存森林模型来估计对复发性OF的异质治疗效应.
- 对治疗分配和时间到事件结果进行了双重强大的调整,对审查进行了校正.
主要成果:
- 双酸盐显著降低了复发性OF的风险,没有骨折的概率差异为0.032 (95% CI 0.022-0.042).
- 根据年龄,先前使用血压,糖尿病状况,胃潰瘍疾病,类固醇使用和治疗机构类型,治疗效应在患者子组中表现出异质性.
结论:
- 根据因果关系,现实世界的证据支持BP在停止使用登苏马布后预防骨折的有效性.
- 因果机器学习为个性化骨折预防提供了有价值的工具,通过识别患者亚组,从BP中获得最大的潜在益处.
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