| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-08-25 |
| タイトル |
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|
タイトル |
Post-marketing surveillance of anticancer drugs using natural language processing of electronic medical records |
| 言語 |
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|
言語 |
eng |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Adverse effects |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Drug regulation |
| 資源タイプ |
|
|
資源タイプ |
journal article |
| アクセス権 |
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|
アクセス権 |
open access |
| 著者 |
Kawazoe, Yoshimasa
Shimamoto, Kiminori
Seki, Tomohisa
Tsuchiya, Masami
Shinohara, Emiko
矢田, 竣太郎
若宮, 翔子
Imai, Shungo
Hori, Satoko
荒牧, 英治
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
This study demonstrates that adverse events (AEs) extracted using natural language processing (NLP) from clinical texts reflect the known frequencies of AEs associated with anticancer drugs. Using data from 44,502 cancer patients at a single hospital, we identified cases prescribed anticancer drugs (platinum, PLT; taxane, TAX; pyrimidine, PYA) and compared them to non-treatment (NTx) group using propensity score matching. Over 365 days, AEs (peripheral neuropathy, PN; oral mucositis, OM; taste abnormality, TA; appetite loss, AL) were extracted from clinical text using an NLP tool. The hazard ratios (HRs) for the anticancer drugs were: PN, 1.15–1.95; OM, 3.11–3.85; TA, 3.48-4.71; and AL, 1.98–3.84; the HRs were significantly higher than that of the NTx group. Sensitivity analysis revealed that the HR for TA may have been underestimated; however, the remaining three types of AEs extracted from clinical text by NLP were consistently associated with the three anticancer drugs. |
| 書誌情報 |
en : npj Digital Medicine
巻 7,
号 1,
ページ数 19,
発行日 2024-11-09
|
| 出版者 |
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出版者 |
Nature Research |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2398-6352 |
| 出版者版DOI |
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|
関連タイプ |
isReplacedBy |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.1038/s41746-024-01323-1 |
| 出版者版URI |
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|
関連タイプ |
isReplacedBy |
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|
識別子タイプ |
URI |
|
|
関連識別子 |
https://www.nature.com/articles/s41746-024-01323-1 |
| 権利 |
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|
権利情報Resource |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
権利情報 |
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. |
| 著者版フラグ |
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|
出版タイプ |
NA |
| 助成情報 |
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|
助成機関名 |
Japan Science and Technology Agency (JST) |
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|
研究課題番号 |
JPMJCR22N1 |
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|
研究課題番号URI |
https://projectdb.jst.go.jp/grant/JST-PROJECT-22717060/ |
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|
研究課題名 |
リアルワールドテキスト処理の深化によるデータ駆動型探薬 |
| 助成情報 |
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|
助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
|
|
研究課題番号 |
23H03492 |
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研究課題番号URI |
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23K28182/ |
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|
研究課題名 |
医療用語のエンティティリンキングに向けた実践的医療用語辞書の開発 |
| 助成情報 |
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|
助成機関名 |
National Center for Global Health and Medicine (NCGM) |
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|
研究課題番号 |
JPJ012425 |
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|
研究課題名 |
Integrated Health Care System |
