| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-10-03 |
| タイトル |
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タイトル |
Identifying Adverse Events in Outpatients With Prostate Cancer Using Pharmaceutical Care Records in Community Pharmacies: Application of Named Entity Recognition |
| 言語 |
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言語 |
eng |
| キーワード |
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主題Scheme |
Other |
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主題 |
natural language processing |
| キーワード |
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主題Scheme |
Other |
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主題 |
pharmaceutical care records |
| キーワード |
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主題Scheme |
Other |
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主題 |
androgen receptor axis-targeting agents |
| キーワード |
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主題Scheme |
Other |
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主題 |
adverse events |
| キーワード |
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主題Scheme |
Other |
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主題 |
outpatient care |
| 資源タイプ |
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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 |
Yanagisawa, Yuki
Watabe, Satoshi
Yokoyama, Sakura
Sayama, Kyoko
Kizaki, Hayato
Tsuchiya, Masami
Imai, Shungo
Someya, Mitsuhiro
Taniguchi, Ryoo
矢田, 竣太郎
荒牧, 英治
Hori, Satoko
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Background: Androgen receptor axis-targeting reagents (ARATs) have become key drugs for patients with castration-resistant prostate cancer (CRPC). ARATs are taken long term in outpatient settings, and effective adverse event (AE) monitoring can help prolong treatment duration for patients with CRPC. Despite the importance of monitoring, few studies have identified which AEs can be captured and assessed in community pharmacies, where pharmacists in Japan dispense medications, provide counseling, and monitor potential AEs for outpatients prescribed ARATs. Therefore, we anticipated that a named entity recognition (NER) system might be used to extract AEs recorded in pharmaceutical care records generated by community pharmacists. Objective: This study aimed to evaluate whether an NER system can effectively and systematically identify AEs in outpatients undergoing ARAT therapy by reviewing pharmaceutical care records generated by community pharmacists, focusing on assessment notes, which often contain detailed records of AEs. Additionally, the study sought to determine whether outpatient pharmacotherapy monitoring can be enhanced by using NER to systematically collect AEs from pharmaceutical care records. Methods: We used an NER system based on the widely used Japanese medical term extraction system MedNER-CR-JA, which uses Bidirectional Encoder Representations from Transformers (BERT). To evaluate its performance for pharmaceutical care records by community pharmacists, the NER system was first applied to 1008 assessment notes in records related to anticancer drug prescriptions. Three pharmaceutically proficient researchers compared the results with the annotated notes assigned symptom tags according to annotation guidelines and evaluated the performance of the NER system on the assessment notes in the pharmaceutical care records. The system was then applied to 2193 assessment notes for patients prescribed ARATs. Results: The F1-score for exact matches of all symptom tags between the NER system and annotators was 0.72, confirming the NER system has sufficient performance for application to pharmaceutical care records. The NER system automatically assigned 1900 symptom tags for the 2193 assessment notes from patients prescribed ARATs; 623 tags (32.8{\%}) were positive symptom tags (symptoms present), while 1067 tags (56.2{\%}) were negative symptom tags (symptoms absent). Positive symptom tags included ARAT-related AEs such as ``pain,'' ``skin disorders,'' ``fatigue,'' and ``gastrointestinal symptoms.'' Many other symptoms were classified as serious AEs. Furthermore, differences in symptom tag profiles reflecting pharmacists' AE monitoring were observed between androgen synthesis inhibition and androgen receptor signaling inhibition. Conclusions: The NER system successfully extracted AEs from pharmaceutical care records of patients prescribed ARATs, demonstrating its potential to systematically track the presence and absence of AEs in outpatients. Based on the analysis of a large volume of pharmaceutical medical records using the NER system, community pharmacists not only detect potential AEs but also actively monitor the absence of severe AEs, offering valuable insights for the continuous improvement of patient safety management. |
| 書誌情報 |
en : JMIR Cancer
巻 11,
ページ数 11,
発行日 2025-03-11
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| 出版者 |
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出版者 |
JMIR Publications |
| 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 |
2369-1999 |
| 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/10.2196/69663 |
| 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 |
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関連識別子 |
https://cancer.jmir.org/2025/1/e69663 |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by/4.0/ |
|
権利情報 |
©Yuki Yanagisawa, Satoshi Watabe, Sakura Yokoyama, Kyoko Sayama, Hayato Kizaki, Masami Tsuchiya, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori. Originally published in JMIR Cancer (https://cancer.jmir.org), 11.03.2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cancer, is properly cited. The complete bibliographic information, a link to the original publication on https://cancer.jmir.org/, as well as this copyright and license information must be included. |
| 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 |
