Evidence map›Paper›PMID 31383922›Full record

ArticleScientific reports2019

A comparative study of curated contents by knowledge-based curation system in cancer clinical sequencing.

Kazuko Sakai, Masayuki Takeda, Shigeki Shimizu, Takayuki Takahama, Takeshi Yoshida, Satomi Watanabe, Tsutomu Iwasa, Kimio Yonesaka, Shinichiro Suzuki, Hidetoshi Hayashi and 9 more

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
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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

19 authors.

Kazuko SakaiDepartment of Genome Biology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Masayuki TakedaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Shigeki ShimizuDepartment of Pathology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Takayuki TakahamaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Takeshi YoshidaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Satomi WatanabeDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Tsutomu IwasaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Kimio YonesakaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.ORCID http://orcid.org/0000-0002-0816-5315
Shinichiro SuzukiDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Hidetoshi HayashiDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Hisato KawakamiDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.ORCID http://orcid.org/0000-0002-3280-4850
Yoshikane NonagaseDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Kaoru TanakaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Junji TsurutaniDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Kazumasa SaigohDepartment of Clinical Genetics, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.ORCID http://orcid.org/0000-0002-0905-5935
Akihiko ItoDepartment of Pathology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Tetsuya MitsudomiDepartment of Thoracic Surgery, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.
Kazuhiko NakagawaDepartment of Medical Oncology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan.ORCID http://orcid.org/0000-0003-1284-9776
Kazuto NishioDepartment of Genome Biology, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, 589-8511, Japan. knishio@med.kindai.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical oncologists are challenged to personalize medicine with scientific evidence, drug approvals, and treatment guidelines based on sequencing of clinical samples using next generation sequencer (NGS). Knowledge-based curation systems have the potential to help address this challenge. We report here the results of examining the level of evidence regarding treatment approval and clinical trials between recommendations made by Watson for Genomics (WfG), QIAGEN Clinical Insight Interpret (QCII), and Oncomine knowledge-based reporter (OKR). The tumor samples obtained from the solid cancer patients between May to June 2018 at Kindai University Hospital. The formalin-fixed paraffin-embedded tumor samples (n = 31) were sequenced using Oncomine Comprehensive Assay v3. Variants including copy number alteration and gene fusions identified by the Ion reporter software were used commonly on three curation systems. Curation process of data were provided for 25 solid cancers using three curation systems independently. Concordance and distribution of curated evidence levels of variants were analyzed. As a result of sequencing analysis, nonsynonymous mutation (n = 58), gene fusion (n = 2) or copy number variants (n = 12) were detected in 25 cases, and subsequently subjected to knowledge-based curation systems (WfG, OKR, and QCII). The number of curated information in any systems was 51/72 variants. Concordance of evidence levels was 65.3% between WfG and OKR, 56.9% between WfG and QCII, and 66.7% between OKR and QCII. WfG provided great number of clinical trials for the variants. The annotation of resistance information was also observed. Larger differences were observed in clinical trial matching which could be due to differences in the filtering process among three curation systems. This study demonstrates knowledge-based curation systems (WfG, OKR, and QCII) could be helpful tool for solid cancer treatment decision making. Difference in non-concordant evidence levels was observed between three curation systems, especially in the information of clinical trials. This point will be improved by standardized filtering procedure and enriched database of clinical trials in Japan.

Indexed as

DNA Copy Number VariationsGene FusionGenomicsHigh-Throughput Nucleotide SequencingHumansKnowledge BasesMutationNeoplasms

Identifiers

PMID31383922
PMCPMC6683116

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Registered trials

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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.