A prospective nationwide COVID-19 healthcare outcomes registry-based cohort study in Japan: ANCHOR study
Year: 2025
Type: article
Abstract: Introduction: The coronavirus disease 2019 (COVID-19) pandemic highlighted the need for real-world evidence on treatment effectiveness and postinfection outcomes. In Japan, comprehensive prospective real-world data remain limited, particularly for oral antiviral treatments and post-COVID-19 conditions. This nationwide registry and cohort study aims to prospectively collect data on COVID-19 patients to address this gap and to evaluate treatment effectiveness and outcomes using cohort analyses. Methods and analysis: This large-scale, prospective registry-based cohort study will be conducted at acute care hospitals across Japan and will enroll COVID-19 outpatients and inpatients aged ≥ 12 years with symptom onset within 5 days prior to consent. The study will establish a comprehensive COVID-19 registry and will concurrently serve as a cohort study to assess treatment patterns, effectiveness, and clinical outcomes. Outcome measures, broadly defined for the overall study population, will be collected from electronic health records and patient-reported outcomes via an electronic PRO system at baseline, Day 28, and Day 84. Outcomes include patient characteristics, acute-phase and post-infection symptoms, treatment patterns, clinical outcomes (including severe events), healthcare utilization, work productivity and activity impairment, and safety of anti-severe acute respiratory syndrome coronavirus 2 drugs. However, an interim analysis showed lower-than-expected enrollment, which resulted in insufficient statistical power to assess severe outcomes. To increase statistical power and ensure that the study can evaluate severe outcomes as originally intended, the registration period has been extended to October 31, 2025. Summary statistics will be calculated for all outcome measures, and detailed analysis methods will be prespecified in a separate statistical analysis plan.
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7117312496