de Germay Sibylle, Conte Cécile, Micallef Joëlle, Bouquet Emilie, Chouchana Laurent, Lafaurie Margaux, Pariente Antoine
University of Bordeaux, Inserm U1219, Bordeaux Population Health Research Center, Team AHead, Department of Medical Pharmacology, CHU de Bordeaux, 33000 Bordeaux, France.
Department of Clinical Pharmacology, CIC 1436, Team PEPSS (Pharmacologie en Population, Cohortes, Biobanques), Inserm, Toulouse University Hospital, 31000 Toulouse, France.
Therapie. 2023 Nov-Dec;78(6):691-703. doi: 10.1016/j.therap.2023.01.010. Epub 2023 Jan 29.
The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendationswhen using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.
名为SNDS的法国健康保险数据仓库是世界上最大的医疗管理数据库之一,它基于前瞻性收集的真实数据,可进行强大的药物流行病学研究。除了强有力的药理学依据这一绝对必要条件外,人们还认为有必要提出一些建议来提高药物流行病学研究的质量。这些指南强调了准确界定研究人群、结局和暴露因素的重要性,尤其是对于在医疗管理数据库上开展的研究。由于SNDS的结构和所记录数据的性质,在利用该数据库开展研究时,要遵循某些指南,特别是那些关于确定特定人群或结局以及界定风险期或暴露期的指南,可能会存在困难。鉴于SNDS的特殊性,本文旨在根据相关建议,为利用该数据库开展药物流行病学研究提供指导。要从这个丰富但复杂的数据仓库中开展可靠的研究,需要研究人员具备在SNDS和药理学推理方面有深入知识的专业技能。