A Continuous Registry of Medical Record, Patient Input, and Epidemiological Data of Patients With Ulcerative Colitis: a Multicentre, Prospective, Observational Clinical Registry Study in Japan

日本溃疡性结肠炎患者病历、患者信息和流行病学数据的连续登记:一项多中心、前瞻性、观察性临床登记研究

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Abstract

BACKGROUND: This registry aims to allow for a prospective non-interventional observational study of ulcerative colitis. This will facilitate monitoring of the current state of ulcerative colitis in Japan and improving the long-term disease course and adverse events associated with current treatment options. METHODS: Inclusion of patients from five centres in Japan is planned. The study is expected to take place from July 15, 2020, to November 30, 2024. Background, demographics, and medical history/information will be collected from electronic medical records at enrolment. Medical information including medications, laboratory data, and disease activity will be collected automatically from electronic medical records throughout the study. Patient-reported quality of life data will be collected directly from patients via smartphone. Efficacy endpoints (clinical remission rate, clinical improvement rate, and endoscopic healing rate) and safety endpoints (incidence of adverse events and specific ulcerative colitis-related events) will be collected according to treatment administered. Treatment categories include no treatment, 5-aminosalicylic acids, corticosteroids, immunomodulators, immunosuppressants, anti-tumour necrosis alpha agents, cytapheresis, Janus kinase inhibitors, anti-integrin antibodies, and anti-interleukin-12/23 antibodies. CONCLUSIONS: The dataset will include cross-sectional and longitudinal data and is expected to capture the state of ulcerative colitis in Japan. Patients will be included on a large scale, and the registry will be established automatically from electronic medical records and direct patient input, facilitating the accurate recording of medical information for patients with ulcerative colitis in Japan and minimizing limitations intrinsic to databases that require manual data entry, such as the burden on participating investigators and entry of data with errors/typos.

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