Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
J Clin Epidemiol. 2021 Sep;137:113-125. doi: 10.1016/j.jclinepi.2021.03.029. Epub 2021 Apr 7.
While several prescription drug-based risk indices have been developed, their design, performance, and application has not previously been synthesized.
We searched Ovid MEDLINE, CINAHL and Embase from inception through March 3, 2020 and included studies that developed or updated a prescription drug-based risk index. Two reviewers independently performed screening and extracted information on data source, study population, cohort sizes, outcomes, study methodology and performance. Predictive performance was evaluated using C statistics for binary outcomes and R for continuous outcomes. The PROSPERO ID for this review is CRD42020165498.
Of 19,112 articles that were retrieved, 124 were full-text screened and 25 were included, each of which represented a de novo or updated drug-based index. The indices were customized to varied age groups and clinical populations and most commonly evaluated outcomes including mortality (36%), hospitalization (24%) and healthcare costs (24%). C statistics ranged from 0.62 to 0.92 for mortality and 0.59 to 0.72 for hospitalization, while adjusted R for healthcare costs ranged from 0.06 to 0.62. Seven of the 25 risk indices included used global drug classification algorithms.
More than two-dozen prescription drug-based risk indices have been developed and they differ significantly in design, performance and application.
虽然已经开发了几种基于处方药物的风险指数，但它们的设计、性能和应用尚未得到综合。
我们在 2020 年 3 月 3 日之前在 Ovid MEDLINE、CINAHL 和 Embase 中进行了搜索，并纳入了开发或更新基于处方药物的风险指数的研究。两名审查员独立进行筛选，并提取了有关数据源、研究人群、队列大小、结局、研究方法和性能的信息。使用二分类结局的 C 统计量和连续结局的 R 来评估预测性能。本综述的 PROSPERO ID 为 CRD42020165498。
在检索到的 19112 篇文章中，有 124 篇进行了全文筛选，有 25 篇被纳入，每篇都代表了一种新开发或更新的基于药物的指数。这些指数针对不同的年龄组和临床人群进行了定制，最常用于评估死亡率（36%）、住院率（24%）和医疗保健成本（24%）等结局。死亡率的 C 统计量范围为 0.62 至 0.92，住院率的 C 统计量范围为 0.59 至 0.72，而医疗保健成本的调整 R 范围为 0.06 至 0.62。25 个风险指数中有 7 个使用了全球药物分类算法。
已经开发了二十多种基于处方药物的风险指数，它们在设计、性能和应用方面存在显著差异。
