Gradishar William, Johnson KariAnne, Brown Krystal, Mundt Erin, Manley Susan
Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA.
Oncologist. 2017 Jul;22(7):797-803. doi: 10.1634/theoncologist.2016-0431. Epub 2017 Apr 13.
There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, the well-documented limitations of these databases call into question how often clinicians will encounter discordant variant classifications that may introduce uncertainty into patient management. Here, we evaluate discordance in and variant classifications between a single commercial testing laboratory and a public database commonly consulted in clinical practice.
and variant classifications were obtained from ClinVar and compared with the classifications from a reference laboratory. Full concordance and discordance were determined for variants whose ClinVar entries were of the same pathogenicity (pathogenic, benign, or uncertain). Variants with conflicting ClinVar classifications were considered partially concordant if ≥1 of the listed classifications agreed with the reference laboratory classification.
Four thousand two hundred and fifty unique and variants were available for analysis. Overall, 73.2% of classifications were fully concordant and 12.3% were partially concordant. The remaining 14.5% of variants had discordant classifications, most of which had a definitive classification (pathogenic or benign) from the reference laboratory compared with an uncertain classification in ClinVar (14.0%).
Here, we show that discrepant classifications between a public database and single reference laboratory potentially account for 26.7% of variants in and . The time and expertise required of clinicians to research these discordant classifications call into question the practicality of checking all test results against a database and suggest that discordant classifications should be interpreted with these limitations in mind.
With the increasing use of clinical genetic testing for hereditary cancer risk, accurate variant classification is vital to ensuring appropriate medical management. There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, we show that up to 26.7% of variants in and have discordant classifications between ClinVar and a reference laboratory. The findings presented in this paper serve as a note of caution regarding the utility of database consultation.
在从临床实验室收到基因检测结果后,查阅公共数据库的行为日益增多;然而,这些数据库中记载详尽的局限性让人质疑临床医生遇到可能给患者管理带来不确定性的不一致变异分类的频率。在此,我们评估了单个商业检测实验室与临床实践中常用的一个公共数据库之间在 和 变异分类方面的不一致情况。
从ClinVar获取 和 变异分类,并与参考实验室的分类进行比较。对于ClinVar条目中致病性相同(致病、良性或不确定)的变异,确定完全一致和不一致的情况。如果列出的分类中≥1个与参考实验室分类一致,则ClinVar分类相互冲突的变异被视为部分一致。
有4250个独特的 和 变异可用于分析。总体而言,73.2%的分类完全一致,12.3%部分一致。其余14.5%的变异分类不一致,其中大多数在参考实验室有明确分类(致病或良性),而在ClinVar中为不确定分类(14.0%)。
在此,我们表明公共数据库与单个参考实验室之间的分类差异可能占 和 变异的26.7%。临床医生研究这些不一致分类所需的时间和专业知识让人质疑对照数据库检查所有检测结果的实用性,并表明应在考虑这些局限性的情况下解释不一致的分类。
随着临床基因检测在遗传性癌症风险评估中的使用增加,准确的变异分类对于确保适当的医疗管理至关重要。在从临床实验室收到基因检测结果后,查阅公共数据库的行为日益增多;然而,我们表明ClinVar与参考实验室之间高达26.7%的 和 变异分类不一致。本文的研究结果提醒人们注意数据库咨询的效用。