Details of a Researcher - Tsuchiya, Masami

Papers - Tsuchiya, Masami

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Changes in the trend and quality of adverse drug reaction reports in the Japanese Adverse Drug Event Report database and the impact of COVID-19-related reports

2025.09

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Natural Language Processing-Based Approach to Detect Common Adverse Events of Anticancer Agents from Unstructured Clinical Notes: A Time-to-Event Analysis.

Masami Tsuchiya, Kiminori Shimamoto, Yoshimasa Kawazoe, Emiko Shinohara, Shuntaro Yada, Shoko Wakamiya, Shungo Imai, Hayato Kizaki, Satoko Hori, Eiji Aramaki

Studies in health technology and informatics 329 703 - 707 2025.08

Lead author, Accepted

This study assessed the effectiveness of natural language processing (NLP) in detecting adverse events (AEs) from anticancer agents by analyzing data from over 39,000 cancer patients. A specialized machine learning model identified known AEs from anticancer agents like capecitabine, oxaliplatin, and anthracyclines, revealing a significantly higher incidence in the treatment groups compared to non-users. While the NLP approach effectively detected most symptomatic AEs requiring manual review, it struggled with rarely documented conditions and commonly used clinical terms. Overall, the method shows promise for automated AE detection in medical records, particularly for symptoms without laboratory markers or diagnosis codes.

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Elucidating Celecoxib's Preventive Effect in Capecitabine-Induced Hand-Foot Syndrome Using Medical Natural Language Processing.

Masami Tsuchiya, Yoshimasa Kawazoe, Kiminori Shimamoto, Tomohisa Seki, Shungo Imai, Hayato Kizaki, Emiko Shinohara, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki, Satoko Hori

JCO clinical cancer informatics 9 e2500096 2025.08

ISSN 2473-4276

PURPOSE: Capecitabine, an oral anticancer agent, frequently causes hand-foot syndrome (HFS), affecting patients' quality of life and treatment adherence. However, such symptomatic toxicities are often difficult to detect in structured electronic health record (EHR) data. This study primarily aimed to validate a natural language processing (NLP) approach to identifying capecitabine-induced HFS from unstructured clinical text and demonstrate its application in evaluating medication-associated adverse event trends in real-world settings. METHODS: We conducted a retrospective cohort study using EHRs from the University of Tokyo Hospital (2004-2021). HFS cases were identified using the MedNERN-CR-JA NLP model. After propensity score matching, we compared capecitabine users with and without celecoxib and assessed time to HFS onset using Cox proportional hazards models. NLP-based HFS detection was validated through manual annotation of aggregated clinical notes. Negative control and sensitivity analyses ensured robustness. RESULTS: Among 44,502 patients with cancer, 669 capecitabine users were analyzed. HFS incidence was significantly higher among capecitabine users (hazard ratio [HR], 1.93 [95% CI, 1.48 to 2.52]; P < .001) compared with nonusers. Celecoxib use showed a suggestive association with a reduced HFS risk (HR, 0.51 [95% CI, 0.24 to 1.07]; P = .073). The NLP model demonstrated high accuracy in identifying HFS, achieving a precision of 0.875, recall of 1.000, and F1 score of 0.933, based on manual annotation of patient-level clinical notes. Outcome trends remained consistent when using manually annotated HFS case labels instead of NLP-detected events, supporting the method's robustness. CONCLUSION: These findings demonstrate the effectiveness of NLP in detecting HFS from real-world clinical records. The application to celecoxib-HFS detection illustrates the potential utility of this approach for retrospective safety analysis. Further work is needed to evaluate generalizability across diverse clinical settings.

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Work styles and career development of hospital pharmacists in Japan: a cross-sectional questionnaire survey

Masami Tsuchiya, Hitoshi Kawazoe, Hirotake Ohashi, Akemi Ogasawara, Yukiko Miyoshi, Manabu Sasuga, Kumiko Kasashi

BMJ Leader 2025.07

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A patient-centered approach to developing and validating a natural language processing model for extracting patient-reported symptoms

Satoshi Watabe, Yuki Yanagisawa, Kyoko Sayama, Sakura Yokoyama, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Hayato Kizaki, Masami Tsuchiya, Shungo Imai, Satoko Hori

Scientific Reports (Springer Science and Business Media LLC) 15 ( 1 ) 2025.07

Accepted, ISSN 2045-2322

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Analysis of factors affecting difficulty in handling oral medicine using electronic medication notebook-based personal health records.

Yuri Shimizu, Masami Tsuchiya, Masaki Asano, Shungo Imai, Hayato Kizaki, Yukiko Ito, Makoto Tsuchiya, Ryoko Kuriyama, Nao Yoshida, Masanori Shimada, Takanori Sando, Tomo Ishijima, Satoko Hori

Scientific reports 15 ( 1 ) 26867 - 26867 2025.07

Accepted, ISSN 2045-2322

Tablets and capsules are widely used forms of oral medication, but some patients experience difficulty handling them, which can reduce medication adherence and affect health outcomes. This study aimed to identify factors contributing to perceived handling difficulty, using data from harmo®, a nationwide electronic medication notebook system. A questionnaire was distributed to adult users who had been prescribed oral medications, and the responses were linked with personal health records to analyze medication characteristics and patient backgrounds. Among the 1,230 respondents, 24% reported difficulty with small tablets or capsules. A size threshold was identified: a combined long and short diameter of 13.3 mm or less was most associated with handling problems (ROC-AUC = 0.834). Binomial logistic regression analysis revealed that difficulty in applying force with the hands (OR = 2.64), prescription of small tablets or capsules (OR = 2.52), and medical histories of hypertension (OR = 1.69) and osteoporosis (OR = 4.99) were significantly associated with reported difficulty. These results suggest that both the physical characteristics of formulations and individual patient factors influence medication usability. Our results provide evidence to inform more patient-centered approaches to oral formulation design and prescribing practices, ultimately supporting better adherence and medication safety.

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Validation of Risk Prediction System for Denosumab-Induced Hypocalcemia with an External Clinical Dataset

Keisuke Ikegami, Masami Tsuchiya, Shungo Imai, Yukiyoshi Fujita, Osamu Yasumuro, Hayato Kizaki, Ryohkan Funakoshi, Yasunori Sato, Satoko Hori

Biological and Pharmaceutical Bulletin (Pharmaceutical Society of Japan) 48 ( 6 ) 860 - 863 2025.06

ISSN 0918-6158

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Impact of renal function on non-hematologic toxicities in mCRC patients treated with TAS-102: a post-hoc analysis of the JASCC-CINV2001 study.

Hironori Fujii, Masami Tsuchiya, Daichi Watanabe, Miki Chin, Daisuke Hirate, Katsuyuki Takahashi, Makiko Go, Toshihiro Kudo, Kazuhiro Shimomura, Yosuke Ando, Shinya Tani, Takao Takahashi, Katsuhisa Hayashi, Hironobu Hashimoto, Naomi Matsunami, Masaya Takahashi, Akiko Hasegawa, Takashi Uchida, Akiko Kubo, Nobuhisa Matsuhashi, Akio Suzuki, Junichi Nishimura, Naoki Inui, Hirotoshi Iihara

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer 33 ( 6 ) 469 - 469 2025.05

ISSN 0941-4355

PURPOSE: Although the efficacy of trifluridine/tipiracil hydrochloride (TAS-102) in treating metastatic colorectal cancer (mCRC) is well established, its non-hematologic toxicities in relation to renal function remain unclear. This study aimed to assess the impact of creatinine clearance (Ccr) on non-hematologic toxicities, including nausea and vomiting, in patients with mCRC treated with TAS-102. METHODS: This study was conducted as a post-hoc analysis of the JASCC-CINV2001 study, a multicenter observational study of mCRC patients. Using a Cox proportional hazards model, we assessed the relationship between Ccr and nausea or vomiting, and used a generalized estimating equations (GEE) logistic regression model to analyze the association between Ccr and additional toxicities, including fatigue, constipation, diarrhea, insomnia, and dysgeusia. Toxicities were evaluated at weekly intervals over four weeks. RESULTS: Among 100 patients, median Ccr was 80.5 ml/min. The primary analysis showed no significant association between Ccr and nausea or vomiting. However, the secondary analysis revealed a significant link between lower Ccr and the incidence of diarrhea (P = 0.02). CONCLUSION: These results suggest that although TAS-102-induced nausea and vomiting are not strongly influenced by renal function, decreased renal function increases the risk of diarrhea. Enhanced antiemetic measures may not be necessary for TAS-102 patients with impaired renal function, but monitoring for diarrhea is recommended.

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Accuracy of Diagnostic Coding for Acute Kidney Injury in Japan—Analysis of a Japanese Hospital‐Based Database

Satoru Mitsuboshi, Shungo Imai, Masami Tsuchiya, Hayato Kizaki, Satoko Hori

Pharmacoepidemiology and Drug Safety (Wiley) 34 ( 4 ) 2025.04

ISSN 1053-8569

ABSTRACT

Purpose

To evaluate the accuracy of diagnostic coding for acute kidney injury (AKI) in Japan.

Methods

The data analyzed were obtained from the JMDC hospital‐based administrative claims database from cases registered between April 2014 and August 2022. Only patients who underwent serum creatinine measurements two or more times with intervals of 7 days or less were eligible for inclusion. AKIs were identified by International Classification of Diseases 10th Revision (ICD‐10) codes N14 and N17. These were assessed according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria.

Results

A total of 467 019 patients (median age, 74 [range, 20–99] years; male, 50.9%) were eligible for inclusion. Among these patients, 1849 (0.4%) were assigned ICD‐10 codes for AKI. Among these 1849 patients, the code was assigned within 7 days of the occurrence of AKI (as defined by the KDIGO criteria) in 212 patients, within 14 days in 294 patients, and within 30 days in 386 patients. The positive predictive values and 95% confidence intervals of the ICD‐10 code for AKI at these timepoints were as follows: within 7 days, 11.5% (10.1%–13.0%); within 14 days, 15.9% (14.3%–17.6%); and within 30 days, 20.9% (19.1%–22.8%).

Conclusions

The ICD‐10 codes for AKI showed poor positive predictive values for AKI as defined by the KDIGO criteria, suggesting that it may be difficult to identify AKI using ICD‐10 codes alone in the Japanese context.

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Identifying Adverse Events in Outpatients With Prostate Cancer Using Pharmaceutical Care Records in Community Pharmacies: Application of Named Entity Recognition

Yuki Yanagisawa, Satoshi Watabe, Sakura Yokoyama, Kyoko Sayama, Hayato Kizaki, Masami Tsuchiya, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori

JMIR Cancer (JMIR Publications Inc.) 11 e69663 - e69663 2025.03

Accepted, ISSN 2369-1999

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.

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Natural language processing of electronic medical records identifies cardioprotective agents for anthracycline induced cardiotoxicity.

Yoshimasa Kawazoe, Masami Tsuchiya, Kiminori Shimamoto, Tomohisa Seki, Emiko Shinohara, Shuntaro Yada, Shoko Wakamiya, Shungo Imai, Eiji Aramaki, Satoko Hori

Scientific reports 15 ( 1 ) 6678 - 6678 2025.02

ISSN 2045-2322

In this retrospective observational study, we aimed to investigate the potential of natural language processing (NLP) for drug repositioning by analyzing the preventive effects of cardioprotective drugs against anthracycline-induced cardiotoxicity (AIC) using electronic medical records. We evaluated the effects of angiotensin II receptor blockers/angiotensin-converting enzyme inhibitors (ARB/ACEIs), beta-blockers (BBs), statins, and calcium channel blockers (CCBs) on AIC using signals extracted from clinical texts via NLP. The study included 2935 patients prescribed anthracyclines at a single hospital, with concomitant prescriptions of ARB/ACEIs, BBs, statins, and CCBs. Upon propensity score matching, groups with and without these medications were compared, and expressions suggestive of cardiotoxicity, extracted via NLP, were considered as the outcome. The hazard ratios for ARB/ACEIs, BBs, statins, and CCBs were 0.58 [95% CI: 0.38-0.88], 0.71 [95% CI: 0.35-1.44], 0.60 [95% CI 0.38-0.95], and 0.63 [95% CI: 0.45-0.88], respectively. ARB/ACEIs, statins, and CCBs significantly suppressed AIC, whereas BBs did not demonstrate statistical significance, possibly due to limited statistical power. NLP-extracted signals from clinical texts reflected the known effects of these medications, demonstrating the feasibility of NLP-based drug repositioning. Further investigation is needed to determine if similar results can be replicated using electronic medical records from other institutions.

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A cross-sectional study of the relationship between the number of hospital beds/pharmacist and reimbursement for infection prevention in Japan

Shiro Hatakeyama, Yuichi Tasaka, Takeshi Uchikura, Daisuke Kikuchi, Masami Tsuchiya, Ryohkan Funakoshi, Taku Obara

Journal of Drug Interaction Research 49 ( 1 ) 8 - 17 2025.02

Accepted

Effect of Concomitant Metformin Use on Hematologic Adverse Events in Non-Small-Cell Lung Cancer Patients Undergoing Pemetrexed-Based Chemotherapy: A Study Using a Japanese Claims Database

Masahiro Hayafune, Shungo Imai, Hayato Kizaki, Masami Tsuchiya, Satoko Hori

YAKUGAKU ZASSHI (Pharmaceutical Society of Japan) 145 ( 1 ) 61 - 70 2025.01

ISSN 0031-6903

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Factors Affecting Delayed Recovery from Neutropenia in Patients with Pancreatic Cancer Receiving Gemcitabine plus Nab-Paclitaxel

Yoshida, N; Imai, S; Kawakami, K; Yokokawa, T; Nakamura, M; Aoyama, T; Shimizu, H; Naito, R; Teramae, M; Tsuchiya, M; Kizaki, H; Ozaka, M; Sasahira, N; Yamaguchi, M; Hori, S

JOURNAL OF CANCER 16 ( 5 ) 1413 - 1419 2025

ISSN 1837-9664

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Analysis of Overdose-related Posts on Social Media

Ryuya Sato, Masami Tsuchiya, Rintaro Ichiyama, Soma Hisamura, Satoshi Watabe, Yuki Yanagisawa, Tomohiro Nishiyama, Shuntaro Yada, Eiji Aramaki, Hayato Kizaki, Shungo Imai, Satoko Hori

YAKUGAKU ZASSHI (Pharmaceutical Society of Japan) 144 ( 12 ) 1125 - 1135 2024.12

Accepted, ISSN 0031-6903

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Actual Status of Pharmacy Education Related to Adverse Drug Event Reports in Pharmacy Schools across Japan

Satoko Hori, Masami Tsuchiya, Hayato Kizaki, Masayuki Hashiguchi, Michihiro Satoh, Hirohito Metoki, Taku Obara, Nariyasu Mano

Japanese Journal of Drug Informatics 26 ( 3 ) 128 - 135 2024.12

Accepted

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Exploring the factors associated with difficulties in extracting tablets or capsules from press‐through‐package sheets

Masami Tsuchiya, Shungo Imai, Masaki Asano, Yuri Shimizu, Hayato Kizaki, Yukiko Ito, Makoto Tsuchiya, Ryoko Kuriyama, Nao Yoshida, Masanori Shimada, Takanori Sando, Tomo Ishijima, Satoko Hori

British Journal of Clinical Pharmacology 91 ( 2 ) 479 - 484 2024.11

ISSN 0306-5251

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Post-marketing surveillance of anticancer drugs using natural language processing of electronic medical records

Yoshimasa Kawazoe, Kiminori Shimamoto, Tomohisa Seki, Masami Tsuchiya, Emiko Shinohara, Shuntaro Yada, Shoko Wakamiya, Shungo Imai, Satoko Hori, Eiji Aramaki

npj Digital Medicine (Springer Science and Business Media LLC) 7 ( 1 ) 2024.11

Accepted, ISSN 2398-6352

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Association Between Docetaxel-induced Hand-foot Syndrome and Patients’ Living Environment: A Case Series

Takashi UCHIDA, Masami TSUCHIYA, Katsuhisa HAYASHI, Tatsuro FUKUHARA, Yasuko MURAKAWA, Yoichiro KAKUGAWA, Kyoko INOOKA

Journal of Drug Interaction Research 48 ( 3 ) 44 - 53 2024.11

Accepted

Trend analysis of pharmacist involvement in cancer care in Japan from 2015 to 2020: A nationwide survey study on hospital pharmacy practice

Masami Tsuchiya, Daisuke Kikuchi, Shiro Hatakeyama, Yuichi Tasaka, Takeshi Uchikura, Ryohkan Funakoshi, Taku Obara

Journal of Oncology Pharmacy Practice (SAGE Publications) 31 ( 5 ) 803 - 809 2024.07

ISSN 1078-1552

Introduction

Pharmacists are needed as members of oncology teams. The Japanese Society of Hospital Pharmacists (JSHP) conducts a nationwide survey annually to analyze the actual situation and generate fundamental information about hospital pharmacy practice in Japan. Using data from this large-scale survey, we described pharmacists’ involvement in cancer chemotherapy. We explored the factors related to the acceleration of pharmacists’ tasks or involvement in clinical practice, primarily in oncology.

Methods

Data were obtained from annual surveys conducted by JSHP from 2015 to 2020. All variables were expressed as categorical variables and tabulated. The Chi-square and Fisher's exact tests were used to compare the categorical variables. The Cochran–Armitage trend test was used to identify significant trends.

Results

From 2015 to 2020, 22,362 responses were recorded. After applying the exclusion criteria, 20,906 were analyzed. The proportion of hospitals enrolling pharmacists with oncology-related certifications significantly increased in all hospitals providing cancer care. Multivariable logistic regression analysis indicated that a smaller number of beds per pharmacist significantly correlated with additional fees for outpatient pharmacy services ( p = 0.0002 for trend).

Conclusion

Hospitals charging increased fees for outpatient oncology pharmacy services were associated with a smaller number of beds per pharmacist, regardless of hospital size. A balance between the number of beds and pharmacists, particularly certified oncology pharmacists, is crucial for safe and high-quality cancer treatment.

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