Anna Bollinger, Céline K Stäuble, Chiara Jeiziner, Florine M Wiss, Kurt E Hersberger, Markus L Lampert, Henriette E Meyer Zu Schwabedissen, Samuel S Allemann
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The aim of the study was to identify the drugs that are most frequently object of drug-gene-interactions (DGI) in the study population.</p><p><strong>Patients and methods: </strong>In out-patient and in-patient settings, we recruited 142 patients experiencing adverse drug reaction (ADR) and/or therapy failure (TF). Collected anonymized data from the individual patient was harmonized and transferred to a structured database.</p><p><strong>Results: </strong>The majority of the patients had a main diagnosis of a mental or behavioral disorder (ICD-10: F, 61%), of musculoskeletal system and connective tissue diseases (ICD-10: M, 21%), and of the circulatory system (ICD-10: I, 11%). The number of prescribed medicines reached a median of 7 per person, resulting in a majority of patients with polypharmacy (≥5 prescribed medicines, 65%). In total, 559 suspected DGI were identified in 142 patients. 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引用次数: 0
摘要
目的:药物遗传学(PGx)是个性化医疗的一个新兴方面,具有提高药物治疗有效性和安全性的潜力。然而,PGx检测仍未常规纳入临床实践。我们进行了一项观察性病例系列研究,将来自涵盖30个基因的市售面板测试的PGx信息整合到药物评价中。该研究的目的是确定在研究人群中最常成为药物-基因相互作用(DGI)对象的药物。患者和方法:在门诊和住院环境中,我们招募了142名出现药物不良反应(ADR)和/或治疗失败(TF)的患者。从个别患者收集的匿名数据被协调并转移到结构化数据库。结果:大多数患者的主要诊断为精神或行为障碍(ICD-10: F, 61%)、肌肉骨骼系统和结缔组织疾病(ICD-10: M, 21%)和循环系统疾病(ICD-10: I, 11%)。处方药物数量中位数达到每人7种,导致大多数患者使用多种药物(处方药物≥5种,65%)。142例患者中共发现559例疑似DGI。基因检测后,141例患者中64种不同药物和21种不同基因引起的324例疑似DGI(58%)与至少一种遗传变异相关。6个月后,62%的研究人群记录了基于pgx的药物调整,从而在亚组中确定了差异。结论:本研究的数据分析为PGx背景下的进一步研究重点提供了有价值的见解。结果表明,我们样本中的大多数患者代表了临床实践中PGx面板检测的合适目标群体,特别是那些服用精神或行为障碍、循环系统疾病、免疫疾病、疼痛相关疾病的患者,以及服用多种药物的患者。
Genotyping of Patients with Adverse Drug Reaction or Therapy Failure: Database Analysis of a Pharmacogenetics Case Series Study.
Purpose: Pharmacogenetics (PGx) is an emerging aspect of personalized medicine with the potential to increase efficacy and safety of pharmacotherapy. However, PGx testing is still not routinely integrated into clinical practice. We conducted an observational case series study where PGx information from a commercially available panel test covering 30 genes was integrated into medication reviews. The aim of the study was to identify the drugs that are most frequently object of drug-gene-interactions (DGI) in the study population.
Patients and methods: In out-patient and in-patient settings, we recruited 142 patients experiencing adverse drug reaction (ADR) and/or therapy failure (TF). Collected anonymized data from the individual patient was harmonized and transferred to a structured database.
Results: The majority of the patients had a main diagnosis of a mental or behavioral disorder (ICD-10: F, 61%), of musculoskeletal system and connective tissue diseases (ICD-10: M, 21%), and of the circulatory system (ICD-10: I, 11%). The number of prescribed medicines reached a median of 7 per person, resulting in a majority of patients with polypharmacy (≥5 prescribed medicines, 65%). In total, 559 suspected DGI were identified in 142 patients. After genetic testing, an association with at least one genetic variation was confirmed for 324 suspected DGI (58%) caused by 64 different drugs and 21 different genes in 141 patients. After 6 months, PGx-based medication adjustments were recorded for 62% of the study population, whereby differences were identified in subgroups.
Conclusion: The data analysis from this study provides valuable insights for the main focus of further research in the context of PGx. The results indicate that most of the selected patients in our sample represent suitable target groups for PGx panel testing in clinical practice, notably those taking drugs for mental or behavioral disorder, circulatory diseases, immunological diseases, pain-related diseases, and patients experiencing polypharmacy.
期刊介绍:
Pharmacogenomics and Personalized Medicine is an international, peer-reviewed, open-access journal characterizing the influence of genotype on pharmacology leading to the development of personalized treatment programs and individualized drug selection for improved safety, efficacy and sustainability.
In particular, emphasis will be given to:
Genomic and proteomic profiling
Genetics and drug metabolism
Targeted drug identification and discovery
Optimizing drug selection & dosage based on patient''s genetic profile
Drug related morbidity & mortality intervention
Advanced disease screening and targeted therapeutic intervention
Genetic based vaccine development
Patient satisfaction and preference
Health economic evaluations
Practical and organizational issues in the development and implementation of personalized medicine programs.