Benchmark Database for Process Optimization and Quality Control of Clinical Cancer Panel Sequencing

Seong, Donghyeong; Chung, Jongsuk; Lee, Kiwook; Kim, Sook-Young; Kim, Byung-Suk; Song, Jung-Keun; Jung, Sungwon; Lee, Taeseob; Park, Donghyun; Yi, Byoung-Kee; Park, Woong-Yang; Son, Dae‐Soon

doi:10.1007/s12257-019-0202-7

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…Samsung Medical Center (SMC) has developed and utilized a cancer panel sequencing pipeline, namely CancerSCAN, to determine effective treatment methods for patients based on data from more than 15,000 panel sequencing studies since 2014 [ 17 , 42 , 43 ]. The SMC received clinical laboratory accreditation by the MFDS in 2017, and CancerSCAN is clinically used for the diagnosis and prognosis of cancer patients [ 17 ]. For this study, approximately 1000 data entries were collected from CancerSCAN.…”

Section: Resultsmentioning

confidence: 99%

“…For the legitimacy of clinical NGS genomic testing, the quality information from the process of producing the genomic data should be included within the test results [ 15 - 17 ]. The demand for genomic testing of small tissue samples and needle biopsies is increasing [ 18 ], and it remains challenging to determine the reliability of the genomic test results.…”

Section: Introductionmentioning

confidence: 99%

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Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study

Seong¹,

Jung²,

Bae³

et al. 2021

J Med Internet Res

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Background Next-generation sequencing (NGS) technology has been rapidly adopted in clinical practice, with the scope extended to early diagnosis, disease classification, and treatment planning. As the number of requests for NGS genomic testing increases, substantial efforts have been made to deliver the testing results clearly and unambiguously. For the legitimacy of clinical NGS genomic testing, quality information from the process of producing genomic data should be included within the results. However, most reports provide insufficient quality information to confirm the reliability of genomic testing owing to the complexity of the NGS process. Objective The goal of this study was to develop a Fast Healthcare Interoperability Resources (FHIR)–based web app, NGS Quality Reporting (NGS-QR), to report and manage the quality of the information obtained from clinical NGS genomic tests. Methods We defined data elements for the exchange of quality information from clinical NGS genomic tests, and profiled a FHIR genomic resource to enable information exchange in a standardized format. We then developed the FHIR-based web app and FHIR server to exchange quality information, along with statistical analysis tools implemented with the R Shiny server. Results Approximately 1000 experimental data entries collected from the targeted sequencing pipeline CancerSCAN designed by Samsung Medical Center were used to validate implementation of the NGS-QR app using real-world data. The user can share the quality information of NGS genomic testing and verify the quality status of individual samples in the overall distribution. Conclusions This study successfully demonstrated how quality information of clinical NGS genomic testing can be exchanged in a standardized format. As the demand for NGS genomic testing in clinical settings increases and genomic data accumulate, quality information can be used as reference material to improve the quality of testing. This app could also motivate laboratories to perform diagnostic tests to provide high-quality genomic data.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study

Seong¹,

Jung²,

Bae³

et al. 2021

J Med Internet Res

Self Cite

View full text Add to dashboard Cite

show abstract

“…For the legitimacy of clinical NGS genomic testing, the quality information from the process of producing the genomic data should be included within the test results [15][16][17]. The demand for genomic testing of small tissue samples and needle biopsies is increasing [18], and it remains challenging to determine the reliability of the genomic test results.…”

Section: Introductionmentioning

confidence: 99%

Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study (Preprint)

Seong¹,

Jung²,

Bae³

et al. 2020

Preprint

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BACKGROUND Next Generation Sequencing (NGS) technology has been rapidly adopted in clinical practice, and the scope of clinical NGS applications has been extended to early diagnosis, disease classification, and treatment planning. As the number of requests for NGS genomic testing increases, substantial efforts have been made to deliver the testing results clearly and unambiguously. For the legitimacy of clinical NGS genomic testing, quality information from the process of producing genomic data should be included within the results. However, most reports provide insufficient quality information to confirm the reliability of genomic testing due to the complexity of the NGS process. OBJECTIVE The goal of this study was to develop an NGS Quality Reporting (NGS-QR) app, a Fast Healthcare Interoperability Resources (FHIR) based web application, to report and manage the quality information of clinical NGS genomic tests. METHODS We defined data elements for the exchange of quality information from clinical NGS genomic tests, and profiled a FHIR genomic resource to exchange in a standardized method. Then, we developed a FHIR-based web application and FHIR server to exchange quality information and implemented the R Shiny server to provide statistical analysis in the application. RESULTS Approximately 1,000 experimental data were collected from the targeted sequencing platform CancerSCAN designed by the Samsung Medical Center. Herein, we demonstrated the NGS-QR app using real-world data. The user can share the quality information of NGS genomic testing and verify the quality status of individual samples in the overall distribution. CONCLUSIONS This study successfully demonstrated how quality information of clinical NGS genomic testing can be exchanged in a standardized method. As the demand for NGS genomic testing increases and genomic data accumulates, quality information can be used as reference materials to improve the quality of testing. It could also motivate laboratories to perform diagnostic tests to provide high-quality genomic data.

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Benchmark Database for Process Optimization and Quality Control of Clinical Cancer Panel Sequencing

Cited by 2 publications

References 15 publications

Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study

Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study

Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study (Preprint)

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