Masami Tsuchiya

Purpose: To characterize cancer treatment during pregnancy and maternal and infant outcomes among women with cancer identified during pregnancy in Japan. Methods: In this descriptive cohort study, we used mother‐infant linkage data from the JMDC claims database from 2005 to 2024. Live‐birth pregnancies were considered eligible when a malignant neoplasm (ICD‐10 C00–C97) was recorded between the estimated pregnancy onset and delivery. Exposure was defined as at least one anticancer agent prescribed between the diagnosis and delivery; surgery and radiation therapy were also identified. The outcomes were preterm delivery and major congenital malformation at 6 months of age. Pregnancies without a diagnosis of malignant neoplasms constituted the internal reference group. Results: Of the 500 pregnancies with cancer identified during pregnancy, 16 (3.2%) had an anticancer agent prescribed, 46 (9.2%) underwent surgery for malignant tumors, and none underwent radiation therapy. Cancer was identified in the second trimester in 10 of the 16 pregnancies with exposure (62.5%) and in 128 of the 484 pregnancies without exposure (26.4%). All eight pregnancies with breast cancer received an anthracycline with cyclophosphamide. The frequencies in the reference group ( n = 236 002), without exposure, and with exposure were 12.0%, 20.9%, and 37.5% for preterm delivery and 6.1%, 9.1%, and 12.5% for major congenital malformation, respectively. Conclusions: Cancer identified during pregnancy was treated in a minority of women, and anticancer agents were most often prescribed when cancer was identified in the second trimester. Outcomes were recorded more often in pregnancies with cancer but cannot be attributed to anticancer agent exposure.

Vancomycin (VCM) is essential for treating methicillin‐resistant Staphylococcus aureus infections, but its use is limited by vancomycin‐induced nephrotoxicity (VIN). Although preclinical and small clinical studies suggest a protective role for vitamin E, real‐world evidence remains limited. We conducted a retrospective cohort study using a large‐scale Japanese electronic medical record database including adult patients who received intravenous VCM between 1996 and 2022. VIN was defined according to Kidney Disease Improving Global Outcomes criteria. The association between concomitant vitamin E use and VIN was evaluated using propensity score matching based on logistic regression and light gradient boosting machine models, followed by Kaplan–Meier analysis and Cox proportional hazards regression. Robustness was examined using three analytical strategies, including adjustment for concomitant medications. Among 12 411 eligible patients, 2267 (18.3%) developed VIN and 116 (0.9%) received vitamin E. After matching, vitamin E use was associated with a 10% lower incidence of VIN. Kaplan–Meier analysis showed significantly lower cumulative incidence in the vitamin E group in two approaches. Across 63 Cox models, vitamin E consistently demonstrated a protective trend. These findings support the potential preventive role of vitamin E in maintaining VCM therapy.

Pneumocystis jirovecii pneumonia (PCP) remains a life-threatening opportunistic infection in patients receiving chemotherapy and other immunosuppressive cancer treatments. Accurate identification of true PCP cases within real-world electronic health record (EHR) databases is essential for epidemiological research and optimization of prophylactic strategies in oncology practice. The aim of this study was to develop and validate a practical, EHR-based algorithm for reliably identifying PCP cases. This retrospective, single-center validation study used EHR data from a Japanese university hospital between April 2022 and March 2024. Adult patients (≧20 years) who were assigned an ICD-10 code for PCP were extracted, and true cases were confirmed by a detailed review of the patient records. Seven candidate algorithms combining diagnostic codes, therapeutic-dose anti-PCP prescriptions, laboratory testing, chemotherapy exposure, and prescription duration were evaluated. The positive predictive value (PPV) and capture rate were then calculated using chart-confirmed PCP as the reference standard. Among 617 ICD-coded patients, 11 (1.8%) were confirmed as true PCP cases. The PPV of diagnostic codes alone was 1.8%. A prescription-enhanced algorithm (A1) identified 12 patients, including 11 true cases (PPV=91.7%; capture rate 100%). Algorithms incorporating β-D-glucan or PCR testing achieved PPVs of 100% with lower capture rates (63.6-81.8%). Incorporation of concurrent chemotherapy also resulted in a PPV of 100% with reduced capture. An algorithm requiring therapeutic-dose prescription for ≥21 days showed equivalent performance to A1. Prescription-based algorithms substantially improve the accuracy of PCP case identification in EHR data compared with diagnostic codes alone. This straightforward, scalable approach offers a robust framework for real-world oncology research, enabling a more reliable evaluation of PCP incidence and informing future prophylaxis strategies for patients receiving anticancer treatment.

Purpose: Urothelial carcinoma (UC) is a common malignant tumor of the urinary tract, with bladder cancer as the most frequent type. Radical cystectomy (RC) is the standard treatment for muscle-invasive bladder cancer (MIBC), and perioperative chemotherapy is recommended in addition to RC in guidelines. However, no established evidence defines the optimal regimen and number of cycles, and treatment varies by institution. Therefore, this study aimed to clarify perioperative treatment patterns for MIBC using a hospital-based claims database. Methods: Patients with claims records for bladder cancer recorded during the case-identification window (2012–2020) were identified using the Medical Data Vision Co., Ltd. database. The database spans April 2008 to July 2021, enabling longitudinal assessment. Patient characteristics and prescribed perioperative chemotherapy regimens were analyzed. Factors associated with neoadjuvant chemotherapy (NAC) were examined using univariable analysis and an exploratory multivariable logistic regression model. Results: Among 6,723 patients, 78.5% were men, with a median diagnosis age of 71 years. The treatment groups included 2,324 patients who received NAC, 598 who received adjuvant chemotherapy (AC), 364 who received NAC and AC, and 3,437 who underwent RC-only. NAC utilization rate increased over time ( P for trend < 0.0001). Gemcitabine plus cisplatin was the most frequently administered regimen. Univariable analysis revealed an association between clinical stage 3 or higher and the NAC administration. In contrast, older age and comorbidities were associated with non-administration of NAC. Furthermore, the hospital size and cancer hospital designation influenced NAC administration. Conclusion: Perioperative chemotherapy utilization for MIBC has increased annually. Patient characteristics and treatment facility factors influence NAC administration.

Purpose: Pharmacotherapy during pregnancy should be approached with caution due to the potential risk of adverse effects, including birth defects, in the fetus. Appropriate post‐marketing surveillance and perinatal pharmacoepidemiology are essential to ensure the safety of pharmacotherapy during pregnancy. However, due to limited research infrastructure in pharmacoepidemiology, collecting reliable data on drug safety in pregnant women and infants remains a challenge in Japan. Thus, we examined the suitability (fitness for purpose) of Japanese medical databases for perinatal studies to establish infrastructure in this field. Methods: We assessed seven available databases in Japan: the DeSC database, EBM provider, Japanese Adverse Drug Event Report database, JMDC claims database, MDV analyzer, the National Database of Health Insurance Claims, and Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study (TMM BirThree Cohort Study). To assess the quality of databases for maternal studies, we evaluated the content of each mother‐infant linkable database based on the core data elements recommended for perinatal pharmacoepidemiology. Results: Three of the databases were found to be mother‐infant linkable: the DeSC database, JMDC claims database, and the TMM BirThree Cohort Study. The coverage of core data elements in perinatal pharmacoepidemiology was 73.5% in the DeSC and JMDC claims databases and 92.9% in the TMM BirThree Cohort Study. Conclusion: Some representative medical databases in Japan are well suited for use in perinatal pharmacoepidemiologic research on infant outcomes.

Objectives: This study aimed to identify the impact of the coronavirus disease 2019 (COVID-19) pandemic on changes in the trend and quality of adverse drug reaction (ADR) reports in the Japanese Adverse Drug Events Report (JADER) database using the vigiGrade completeness score as an indicator. Methods: A JADER dataset consisting of ADR reports from April 2004 to March 2025 was used. VigiGrade completeness scores were determined for ADR reports, and the quality of the reports was assessed as ‘well documented’ or not, depending on the score obtained. Key findings: Of 969 520 ADR reports, 393 168 submitted between the fourth quarter of 2018 and the fourth quarter of 2024 were included. The number of ADR reports declined in the first quarter of 2020 but peaked in the second quarter of 2021. The proportion of ‘well-documented’ reports remained between ~20% and 30% during most quarters, but increased to ~40% in the first and second quarters of 2021, during which COVID-19 vaccine-related reports accounted for 29.0% and 39.2% of all reports, respectively. This surge in vaccine-related submissions coincided with a temporary improvement in documentation quality. Conclusions: The COVID-19 pandemic and the increase in ADR reports related to COVID-19 vaccines have affected the trends and quality of reporting in the JADER database. Notably, a substantial increase in vaccine-related ADRs during mass immunization corresponded with a temporary rise in reporting quality. These findings highlight the importance of maintaining robust pharmacovigilance systems that can adapt to large-scale public health interventions and sustain data quality during future emergencies.

Aims: Spontaneous reporting of adverse drug reactions (ADR) after a product has reached the market is essential for drug safety. This study analysed patient ADR reports and compared them with reports from the Japanese Adverse Drug Event Report (JADER) database to identify differences and trends. Methods: ADR reports from the Pharmaceuticals and Medical Devices Agency website, including patient reports from March 2019 to March 2024, and JADER reports from January 2019 to March 2024, were utilized. Information on demographics, drugs, ADR types and outcomes was analysed. Frequencies and comparisons between the two reporting groups were performed. Results: A total of 2913 patient reports and 343 894 JADER reports were analysed. Patients were often younger (30–50 years) and mostly female, whereas JADER reports included older patients (60–80 years) and mostly male. Patients reported subjective symptoms, such as fatigue and headache, often associated with drugs targeting the central nervous system. In contrast, JADER reports focused on serious conditions, such as interstitial lung disease and pneumonia, which are commonly associated with anticancer drugs. Patient and professional ADR reports differed in focus. Patients highlighted quality‐of‐life‐related symptoms, whereas professionals reported more serious medical conditions. Differences in demographics and reporting methods indicate that these systems are complementary. Offering more reporting options, such as telephone‐based submissions, can make the system more inclusive. Conclusions: The study highlights how patient ADR reports provide valuable insights into drug safety. Although differences exist, patient and professional reports improve monitoring after drug approval.

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.