Accepted for/Published in: JMIR Medical Informatics
Date Submitted: May 15, 2019
Open Peer Review Period: May 21, 2019 - Jul 16, 2019
Date Accepted: Feb 7, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Next-Generation Sequencing–Based Cancer Panel Data Conversion Using International Standards to Implement a Clinical Next-Generation Sequencing Research System: Single-Institution Study
Background:
The analytical capacity and speed of next-generation sequencing (NGS) technology have been improved. Many genetic variants associated with various diseases have been discovered using NGS. Therefore, applying NGS to clinical practice results in precision or personalized medicine. However, as clinical sequencing reports in electronic health records (EHRs) are not structured according to recommended standards, clinical decision support systems have not been fully utilized. In addition, integrating genomic data with clinical data for translational research remains a great challenge.
Objective:
To apply international standards to clinical sequencing reports and to develop a clinical research information system to integrate standardized genomic data with clinical data.
Methods:
We applied the recently published ISO/TS 20428 standard to 367 clinical sequencing reports generated by panel (91 genes) sequencing in EHRs and implemented a clinical NGS research system by extending the clinical data warehouse to integrate the necessary clinical data for each patient. We also developed a user interface with a clinical research portal and an NGS result viewer.
Results:
A single clinical sequencing report with 28 items was restructured into four database tables and 49 entities. As a result, 367 patients’ clinical sequencing data were connected with clinical data in EHRs, such as diagnosis, surgery, and death information. This system can support the development of cohort or case-control datasets as well.
Conclusions:
The standardized clinical sequencing data are not only for clinical practice and could be further applied to translational research.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.