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将商业药物遗传学检测结果以及抗抑郁药的建议与既定的CPIC指南进行比较。

Comparing commercial pharmacogenetic testing results and recommendations for antidepressants with established CPIC guidelines.

作者信息

Nguyen Tiffany T, Leary Emili J W, Lee Joshua T, Shukla Sanjay K, Griesbach Sara A

机构信息

Clinical Pharmacy Services, Marshfield Clinic Health System, Marshfield, WI, United States.

Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, WI, United States.

出版信息

Front Pharmacol. 2024 Nov 25;15:1500235. doi: 10.3389/fphar.2024.1500235. eCollection 2024.

Abstract

INTRODUCTION

Increasingly, pharmacogenetic testing helps providers with medication selection based upon patient-specific DNA results. While several government-funded organizations work towards consensus and standardization for testing and interpretation, compliance to these best practices remains inconsistent. Pharmacogenetic testing companies often develop proprietary practices for interpreting and reporting, which can lead to incongruency of reported results among companies and potential discrepancies in interpretation.

METHODS

To identify the differences of commercial pharmacogenetic testing vendors' interpretation of genotype-to-phenotype translations and medication recommendations from the Clinical Pharmacogenetic Implementation Consortium (CPIC) guidelines, a retrospective manual chart review was completed in a large rural healthcare system that utilizes two institution-approved pharmacogenetic vendors. One hundred patients were evaluated: 50 who completed testing through Company A and 50 who completed testing through Company B. Genes of interest for genotype-to-phenotype translation included , , and . Comparison of medication recommendations for drug-gene pairs sertraline ( and/or , escitalopram (), and paroxetine () were compared with recommendations from CPIC, with consideration of the CPIC Serotonin Reuptake Inhibitor Antidepressants (SSRI) guideline 2023 update. This was accomplished via a novel binning process to enable comparison of company-provided binned medication recommendations with CPIC guideline recommendations. Briefly, the binning system included three categorizations based upon the relevant CPIC guideline recommendations-no action needed (green), recommend monitoring (yellow) and therapeutic intervention or alternative recommended (red).

RESULTS

There were 32/250 (12.8%) genotype-to-phenotype translation discrepancies from CPIC guidelines, all from Company A. Of 266 evaluated binned medication recommendations, there were 114 (42.9%) discrepancies between the pharmacogenetic testing companies (Company A: 93 discrepancies, Company B: 21 discrepancies) and CPIC's guideline based upon comparison with the novel binning system.

DISCUSSION

Significant differences were observed between testing companies' interpretations and recommendations, which is concerning as these discrepancies could lead to providers making medication decisions that are not supported by CPIC's clinical practice guidelines. This may result in suboptimal outcomes for patients, leading to patient and provider dissatisfaction and erosion of trust with pharmacogenetic testing. A proposed resolution for the discrepancies in company-to-company interpretation is adherence to the CPIC guidelines and transparency in interpretation practices.

摘要

引言

药物遗传学检测越来越有助于医疗服务提供者根据患者特定的DNA结果进行药物选择。虽然有几个政府资助的组织致力于检测和解读的共识与标准化,但对这些最佳实践的遵守情况仍然参差不齐。药物遗传学检测公司通常会制定专有的解读和报告方法,这可能导致公司之间报告结果的不一致以及解读上的潜在差异。

方法

为了确定商业药物遗传学检测供应商对基因型到表型转化的解读以及药物推荐与临床药物遗传学实施联盟(CPIC)指南之间的差异,在一个大型农村医疗系统中完成了一项回顾性人工图表审查,该系统使用了两家机构批准的药物遗传学供应商。对100名患者进行了评估:50名通过A公司完成检测,50名通过B公司完成检测。用于基因型到表型转化的感兴趣基因包括 、 和 。将舍曲林( 和/或 )、艾司西酞普兰( )和帕罗西汀( )药物 - 基因对的药物推荐与CPIC指南进行比较,并考虑CPIC 2023年更新的5-羟色胺再摄取抑制剂抗抑郁药(SSRI)指南。这是通过一个新颖的分类过程完成的,以便能够将公司提供的分类药物推荐与CPIC指南推荐进行比较。简而言之,分类系统包括基于相关CPIC指南推荐的三种分类 - 无需采取行动(绿色)、建议监测(黄色)和建议进行治疗干预或选择替代方案(红色)。

结果

与CPIC指南存在32/250(12.8%)的基因型到表型转化差异,均来自A公司。在266项评估的分类药物推荐中,根据与新颖分类系统的比较,药物遗传学检测公司(A公司:93项差异,B公司:21项差异)与CPIC指南之间存在114项(42.9%)差异。

讨论

在检测公司的解读和推荐之间观察到了显著差异,这令人担忧,因为这些差异可能导致医疗服务提供者做出CPIC临床实践指南不支持的药物决策。这可能会给患者带来不理想的结果,导致患者和医疗服务提供者不满,并削弱对药物遗传学检测的信任。针对公司间解读差异提出的一个解决方案是遵守CPIC指南并在解读实践中保持透明。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1395/11626124/55a30b206e96/fphar-15-1500235-g001.jpg

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