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Four-Year Laboratory Performance of the First College of American Pathologists In Silico Next-Generation Sequencing Bioinformatics Proficiency Testing Surveys.

Authors :
Furtado LV
Souers RJ
Vasalos P
Halley JG
Aisner DL
Nagarajan R
Voelkerding KV
Merker JD
Konnick EQ
Source :
Archives of pathology & laboratory medicine [Arch Pathol Lab Med] 2023 Feb 01; Vol. 147 (2), pp. 137-142.
Publication Year :
2023

Abstract

Context.—: In 2016, the College of American Pathologists (CAP) launched the first next-generation sequencing (NGS) in silico bioinformatics proficiency testing survey to evaluate the performance of clinical laboratory bioinformatics pipelines for the detection of oncology-associated variants at varying allele fractions. This survey focused on 2 commonly used oncology panels, the Illumina TruSeq Amplicon Cancer Panel and the Thermo Fisher Ion AmpliSeq Cancer Hotspot v2 Panel.<br />Objective.—: To review the analytical performance of laboratories participating in the CAP NGS bioinformatics (NGSB) surveys, comprising NGSB1 for Illumina users and NGSB2 for Thermo Fisher Ion Torrent users, between 2016 and 2019.<br />Design.—: Responses from 78 laboratories were analyzed for accuracy and associated performance characteristics.<br />Results.—: The analytical sensitivity was 90.0% (1901 of 2112) for laboratories using the Illumina platform and 94.8% (2153 of 2272) for Thermo Fisher Ion Torrent users. Variant type and variant allele fraction were significantly associated with performance. False-negative results were seen mostly for multi-nucleotide variants and variants engineered at variant allele fractions of less than 25%. Analytical specificity for all participating laboratories was 99.8% (9303 of 9320). There was no statistically significant association between deletion-insertion length and detection rate.<br />Conclusions.—: These results demonstrated high analytical sensitivity and specificity, supporting the feasibility and utility of using in silico mutagenized NGS data sets as a supplemental challenge to CAP surveys for oncology-associated variants based on physical samples. This program demonstrates the opportunity and challenges that can guide future surveys inclusive of customized in silico programs.

Details

Language :
English
ISSN :
1543-2165
Volume :
147
Issue :
2
Database :
MEDLINE
Journal :
Archives of pathology & laboratory medicine
Publication Type :
Academic Journal
Accession number :
35671151
Full Text :
https://doi.org/10.5858/arpa.2021-0384-CP