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CLIR分析后工具与二线检测对丙酸、蛋氨酸和钴胺素代谢紊乱新生儿筛查性能的综合影响

The Combined Impact of CLIR Post-Analytical Tools and Second Tier Testing on the Performance of Newborn Screening for Disorders of Propionate, Methionine, and Cobalamin Metabolism.

作者信息

Gavrilov Dimitar K, Piazza Amy L, Pino Gisele, Turgeon Coleman, Matern Dietrich, Oglesbee Devin, Raymond Kimiyo, Tortorelli Silvia, Rinaldo Piero

机构信息

Biochemical Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA;

出版信息

Int J Neonatal Screen. 2020 Apr 10;6(2):33. doi: 10.3390/ijns6020033. eCollection 2020 Jun.

Abstract

The expansion of the recommend uniform screening panel to include more than 50 primary and secondary target conditions has resulted in a substantial increase of false positive results. As an alternative to subjective manipulation of cutoff values and overutilization of molecular testing, here we describe the performance outcome of an algorithm for disorders of methionine, cobalamin, and propionate metabolism that includes: (1) first tier screening inclusive of the broadest available spectrum of markers measured by tandem mass spectrometry; (2) integration of all results into a score of likelihood of disease for each target condition calculated by post-analytical interpretive tools created byCollaborative Laboratory Integrated Reports (CLIR), a multivariate pattern recognition software; and (3) further evaluation of abnormal scores by a second tier test measuring homocysteine, methylmalonic acid, and methylcitric acid. This approach can consistently reduce false positive rates to a <0.01% level, which is the threshold of precision newborn screening. We postulate that broader adoption of this algorithm could lead to substantial savings in health care expenditures. More importantly, it could prevent the stress and anxiety experienced by many families when faced with an abnormal newborn screening result that is later resolved as a false positive outcome.

摘要

推荐统一筛查项目扩展至涵盖50多种一级和二级目标疾病后,假阳性结果大幅增加。作为主观调整临界值和过度使用分子检测的替代方法,我们在此描述一种针对蛋氨酸、钴胺素和丙酸代谢紊乱的算法的性能结果,该算法包括:(1)一级筛查,涵盖串联质谱法检测的最广泛可用标志物谱;(2)将所有结果整合为通过协作实验室综合报告(CLIR)创建的分析后解释工具计算的每种目标疾病的疾病可能性评分,CLIR是一种多变量模式识别软件;(3)通过检测同型半胱氨酸、甲基丙二酸和甲基柠檬酸的二级检测对异常评分进行进一步评估。这种方法可将假阳性率持续降低至<0.01%的水平,这是精准新生儿筛查的阈值。我们推测,更广泛地采用该算法可大幅节省医疗保健支出。更重要的是,它可以防止许多家庭在面对后来被判定为假阳性结果的异常新生儿筛查结果时所经历的压力和焦虑。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f30/7423003/5f5fc5c3997b/IJNS-06-00033-g001.jpg

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