| アブストラクト | BACKGROUND: Comparative evidence on the effectiveness of romosozumab and teriparatide in preventing osteoporotic fractures remains limited. This study evaluated their effectiveness in fracture prevention. METHODS: This observational new-user cohort study used the DeSC Healthcare database, a nationwide claims database in Japan. Patients aged >/=40 years with osteoporosis, defined by International Classification of Diseases, 10th Revision codes or prior fragility fractures, who newly initiated romosozumab or teriparatide between March 2019 and August 2021 were included. The primary outcome was the major osteoporotic fractures within 1 year. Secondary outcomes included 2-years fracture incidence and individual fracture types. Cox proportional hazards models, weighted by inverse probability-of-treatment derived from propensity scores, were used to estimate hazard ratios (HRs) with 95 % confidence intervals (CIs), accounting for patient- and facility-level confounders. RESULTS: Among 35,547 observations (romosozumab: 9603; teriparatide: 25,944), the mean ages were 80.3 and 80.0 years, 85.2 % and 81.3 % were women, and 64.4 % and 71.9 % had a history of fragility fracture, respectively. The 1-year incidences of major osteoporotic fractures were 10.14 per 100 person-years (teriparatide) and 7.01 per 100 person-years (romosozumab) (HR: 0.80, 95 % CI: 0.71, 0.89). Romosozumab was also associated with lower rates of composite fractures over 2 years (HR: 0.81, 95 % CI: 0.72, 0.90); vertebral fractures over 1 and 2 years; and proximal humeral, distal forearm, and proximal femoral fractures over 1 year. CONCLUSIONS: In this nationwide Japanese cohort, romosozumab use was associated with a lower incidence of major osteoporotic fractures compared to teriparatide over both 1- and 2-year follow-up periods among high-risk patients with osteoporosis. |
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| 組織名 | Department of Clinical Epidemiology, Graduate School of Medicine, Fukushima;Medical University, Fukushima City, Fukushima, Japan; Iwai Orthopaedic Hospital,;Edogawa-ku, Tokyo, Japan.;Medical University, Fukushima City, Fukushima, Japan; Data Science and AI;Innovation Research Promotion Centre, Shiga University, Hikone City, Shiga,;Japan; Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto;City, Kyoto, Japan.;Department of Data Science, Graduate School of Data Science, Yokohama City;University, Yokohama City, Kanagawa, Japan.;Medical University, Fukushima City, Fukushima, Japan.;Medical University, Fukushima City, Fukushima, Japan; Department of General;Internal Medicine and Family Medicine, Fukushima Medical University, Fukushima;City, Fukushima, Japan.;Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto City,;Kyoto, Japan; Department of Health Data Science, Graduate School of Medicine,;Tokyo Medical University, Shinjuku-ku, Tokyo, Japan.;Medical University, Fukushima City, Fukushima, Japan; Department of Research,;Patient Driven Academic League (PeDAL), Chuo-ku, Tokyo, Japan; Section of;Clinical Epidemiology, Department of Community Medicine, Graduate School of;Medicine, Kyoto University, Kyoto City, Kyoto, Japan.;Medical University, Fukushima City, Fukushima, Japan; Department of Innovative;Research and Education for Clinicians and Trainees (DiRECT), Fukushima Medical;University Hospital, Fukushima City, Fukushima, Japan. Electronic address:;kuritanoriaki@gmail.com.;Department of Health Data Science, Graduate School of Medicine, Tokyo Medical;University, Shinjuku-ku, Tokyo, Japan. |
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