Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Health Science Center Libraries, University of Florida, Gainesville, FL, USA.
Res Social Adm Pharm. 2022 Jul;18(7):3079-3093. doi: 10.1016/j.sapharm.2021.08.003. Epub 2021 Aug 5.
The (prescription) sequence symmetry analysis (PSSA) design has been used to identify potential prescribing cascade signals by assessing the prescribing sequence of an index drug relative to a marker drug presumed to treat an adverse drug event provoked by the index drug.
This review aimed to explore the use of the PSSA design as a pharmacovigilance tool with a particular focus on the breadth of identified signals and advances in PSSA methodology.
We searched Embase, PubMed/Medline, Google Scholar, Web of Science and grey literature to identify studies that used the PSSA methodology. Two reviewers independently extracted relevant data for each included article. Study characteristics including signals identified, exposure time window, stratified analyses, and use of controls were extracted.
We identified 53 studies which reported original results obtained using PSSA methodology or quantified the validity of components of the PSSA design. Of those, nine studies provided validation metrics showing reasonable sensitivity and high specificity of PSSA to identify prescribing cascade signals. We identified 340 unique index drug - marker drug signals published in the PSSA literature, representing 281 unique index - marker pharmacological class dyads (i.e., unique fourth-level Anatomical Therapeutic Chemical [ATC] classification dyads). Commonly observed signals were identified for index drugs acting upon the nervous system (34%), cardiovascular system (21%), and blood and blood-forming organs (15%), and many marker drugs were related to the nervous system (25%), alimentary tract and metabolism (23%), cardiovascular system (17%), and genitourinary system and sex hormones (14%). Negative controls and positive controls were utilized in 21% and 13% of studies, respectively.
The PSSA methodology has been used in 53 studies worldwide to detect and evaluate over 300 unique prescribing cascades signals. Researchers should consider sensitivity analyses incorporating negative and/or positive controls and additional time windows to evaluate time-varying biases when designing PSSA studies.
（处方）序列对称分析（PSSA）设计已被用于通过评估相对于假定治疗由索引药物引起的不良药物事件的标记药物的索引药物的处方序列来识别潜在的处方级联信号。
本综述旨在探讨 PSSA 设计作为一种药物警戒工具的用途，特别是在确定的信号的广度和 PSSA 方法学的进展方面。
我们在 Embase、PubMed/Medline、Google Scholar、Web of Science 和灰色文献中进行了检索，以确定使用 PSSA 方法学的研究。两位评审员独立地为每个纳入的文章提取相关数据。提取了研究特征，包括确定的信号、暴露时间窗、分层分析和对照的使用。
我们确定了 53 项研究，这些研究报告了使用 PSSA 方法学获得的原始结果或量化了 PSSA 设计的组成部分的有效性。其中，有 9 项研究提供了验证指标，表明 PSSA 识别处方级联信号具有合理的敏感性和高特异性。我们在 PSSA 文献中确定了 340 个独特的索引药物-标记药物信号，代表了 281 个独特的索引-标记药物药理学类别对偶（即独特的第四级解剖治疗化学[ATC]分类对偶）。观察到的常见信号是作用于神经系统的索引药物（34%）、心血管系统（21%）和血液和造血器官（15%），许多标记药物与神经系统（25%）、消化道和新陈代谢（23%）、心血管系统（17%）和泌尿生殖系统和性激素（14%）有关。阴性对照和阳性对照分别在 21%和 13%的研究中使用。
PSSA 方法已在全球范围内用于检测和评估 300 多个独特的处方级联信号。研究人员在设计 PSSA 研究时，应考虑纳入阴性和/或阳性对照以及额外的时间窗进行敏感性分析，以评估时变偏倚。
