@Article{info:doi/10.2196/35464，作者=“Lee, Suehyun and Lee, Jeong Hoon and Kim, Grace Juyun and Kim, Jong-Yeup and Shin, Hyunah and Ko, Inseok and Choe, Seon and Kim, Ju Han”，标题=“一种数据驱动的药物不良反应(RS-ADR)信号评估参考标准:开发与验证”，期刊=“J Med Internet Res”，年=“2022”，月=“10”，日=“6”，卷=“24”，数=“10”，页=“e35464”，关键词=“药物不良反应;美国存托凭证;现实世界的数据;RWD;真实的证据;RWE;药物警戒;光伏;参考标准;药理学; drug reaction", abstract="Background: Pharmacovigilance using real-world data (RWD), such as multicenter electronic health records (EHRs), yields massively parallel adverse drug reaction (ADR) signals. However, proper validation of computationally detected ADR signals is not possible due to the lack of a reference standard for positive and negative associations. Objective: This study aimed to develop a reference standard for ADR (RS-ADR) to streamline the systematic detection, assessment, and understanding of almost all drug-ADR associations suggested by RWD analyses. Methods: We integrated well-known reference sets for drug-ADR pairs, including Side Effect Resource, Observational Medical Outcomes Partnership, and EU-ADR. We created a pharmacovigilance dictionary using controlled vocabularies and systematically annotated EHR data. Drug-ADR associations computed from MetaLAB and MetaNurse analyses of multicenter EHRs and extracted from the Food and Drug Administration Adverse Event Reporting System were integrated as ``empirically determined'' positive and negative reference sets by means of cross-validation between institutions. Results: The RS-ADR consisted of 1344 drugs, 4485 ADRs, and 6,027,840 drug-ADR pairs with positive and negative consensus votes as pharmacovigilance reference sets. After the curation of the initial version of RS-ADR, novel ADR signals such as ``famotidine--hepatic function abnormal'' were detected and reasonably validated by RS-ADR. Although the validation of the entire reference standard is challenging, especially with this initial version, the reference standard will improve as more RWD participate in the consensus voting with advanced pharmacovigilance dictionaries and analytic algorithms. One can check if a drug-ADR pair has been reported by our web-based search interface for RS-ADRs. Conclusions: RS-ADRs enriched with the pharmacovigilance dictionary, ADR knowledge, and real-world evidence from EHRs may streamline the systematic detection, evaluation, and causality assessment of computationally detected ADR signals. ", issn="1438-8871", doi="10.2196/35464", url="//www.mybigtv.com/2022/10/e35464", url="https://doi.org/10.2196/35464", url="http://www.ncbi.nlm.nih.gov/pubmed/36201386" }