Evidence map›Paper›PMID 32329738›Full record

ArticleJMIR medical informatics2020

Next-Generation Sequencing-Based Cancer Panel Data Conversion Using International Standards to Implement a Clinical Next-Generation Sequencing Research System: Single-Institution Study.

Phillip Park, Soo-Yong Shin, Seog Yun Park, Jeonghee Yun, Chulmin Shin, Jipmin Jung, Kui Son Choi, Hyo Soung Cha

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 58% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Phillip Park *Cancer Data Center, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0002-8769-6383
Soo-Yong Shin *Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-2410-6120
Seog Yun ParkDepartment of Pathology, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0002-5704-646X
Jeonghee YunDepartment of Pathology, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0003-3192-6044
Chulmin ShinCancer Data Center, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0002-7131-5902
Jipmin JungCancer Data Center, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0002-2901-9333
Kui Son ChoiCancer Data Center, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0001-5336-3874
Hyo Soung ChaCancer Data Center, National Cancer Center, Goyang, Republic of Korea.ORCID https://orcid.org/0000-0003-0537-8355
National Cancer Center · KRSamsung (South Korea) · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectiveTo apply international standards to clinical sequencing reports and to develop a clinical research information system to integrate standardized genomic data with clinical data.

methodsWe 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.

resultsA 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.

conclusionsThe standardized clinical sequencing data are not only for clinical practice and could be further applied to translational research.

Indexed as

clinical sequencing datadata standardizationnext-generation sequencingtranslational research information system

Identifiers

PMID32329738
PMCPMC7210491
OpenAlexW3004640216

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.