在不坚持存在的情况下,最佳动态治疗方案的估计
Dylan Spicker1, Michael P Wallace2, Grace Y Yi3,4
1Department of Mathematics and Statistics, University of New Brunswick, Saint John, New Brunswick E2L 4L5, Canada.
在估计动态治疗方案 (DTRs) 时忽视患者的不遵守会导致低于最佳的精确药物建议. 这项研究引入了一种新方法,可以准确估计最佳的DTR,即使不坚持,确保更好的治疗策略.
科学领域:
- 生物统计学 生物统计学
- 临床信息学 临床信息学
- 精准医学是一门精准的医学.
背景情况:
- 动态治疗方案 (DTR) 对个性化医疗至关重要,指导基于患者数据的治疗决策.
- 目前用于估计最佳DTR的方法经常忽视患者的不遵守,这可能导致有缺陷的治疗建议.
- 当实际治疗与处方异常时,不遵守是临床实践中常见的挑战.
研究的目的:
- 调查患者不坚持治疗对最佳动态治疗方案估计的影响.
- 开发和评估一种新的统计方法来估计最佳的DTR,以解释不遵守.
- 确保在精准医学中治疗建议的可靠性和准确性,尽管没有遵守.
主要方法:
- 探索了在DTR估计中忽略不遵守的理论后果.
- 提出了一种新的估计程序,该程序旨在对不合规性进行稳定.
- 利用模拟研究来评估拟议方法的性能和一致性.
- 演示了开发的估计器的双重稳定性特性.
主要成果:
- 在DTR估计过程中忽视不坚持通常会导致低于最佳的治疗策略.
- 拟议的方法始终估计在存在不遵守的情况下最优的DTR.
- 模拟证实了新程序的可靠性,显示了与使用非粘附数据的方法可比的性能.
结论:
- 患者的不坚持显著影响估计的动态治疗方案的有效性.
- 开发的方法提供了一种可靠的方法来估计最佳的DTR,改善精准医学结果.
- 为准确和有效的个性化治疗策略,考虑不遵守是必不可少的.
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