基于名ogram模型构建的肺癌患者的药物不服药的预测
Jiuli Hu1, Chanchan Hu2, Yunwei Liang2
1Department of Pharmacy, The Affiliated Hospital of Chengde Medical University, Chengde, Hebei, PR China.
Medicine
|March 24, 2025
概括
在肺癌患者中,不服药是常见的,影响了生存率. 这项研究确定了关键的风险因素,如年龄和并发性疾病,开发了一个名谱来预测不坚持和指导干预措施.
科学领域:
- 在瘤学瘤学.
- 临床药房 临床药房
- 生物统计学 生物统计学
背景情况:
- 肺癌是癌症相关死亡的主要原因之一.
- 药物不服药会显著影响肺癌患者的治疗结果,存活率和症状管理.
研究的目的:
- 为了确定与肺癌患者的药物不服药相关的风险因素.
- 开发和验证这个人群中药物不服药的诺莫格拉姆预测模型.
主要方法:
- 来自161名肺癌患者的回顾性数据收集 (2020年4月至2023年3月).
- 使用Morisky药物坚持调查问卷-8.8中文版本评估药物坚持.
- 使用LASSO和多变量后勤回归来识别风险因素和构建名ogram.
- 通过一致性指数 (C指数),AUC和决策曲线分析 (DCA) 验证模型.
主要成果:
- 观察到的药物不服药率为47.20%.
- 不坚持的重要风险因素包括年龄,之前的手术,较低的教育水平,骨转移,并发病,健康状况不佳和便秘.
- 开发的名图表显示出强大的预测准确性,C指数为0.946.
结论:
- 诺米图有效预测肺癌患者的药物不服药风险.
- 早期识别高风险个体,使得有针对性的干预措施,以改善药物坚持和临床管理.
- 该工具支持个性化治疗策略,并增强瘤学环境中的患者护理.
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