Real-world evaluation of osteoporotic fractures using the Japan Medical Data Vision database

In Japanese patients who experienced an osteoporotic fracture, 10.8% and 18.6% had a subsequent fracture within 1 and 2 years of follow-up, respectively. Although the burden of hip and vertebral fractures has been reported widely, we found that patients with non-hip non-vertebral (NHNV) fractures had a 26% higher risk of subsequent fracture than patients with hip fractures; therefore, NHNV fractures should also be considered an important risk factor for subsequent fracture.

To investigate imminent risk and odds of subsequent osteoporotic fractures and associated risk factors in patients who experienced an initial osteoporotic fracture.

Patients aged ≥ 50 years with ≥ 1 osteoporotic fracture were analyzed from Japan's Medical Data Vision (MDV) database of claims from acute-care hospitals (January 2012-January 2017). Multivariable models were constructed to explore the impact of key comorbidities and medications on the subsequent fracture risk: Cox proportional hazards model for time to subsequent fracture and logistic regression models for odds of subsequent fracture within 1 and 2 years from index fracture.

In total, 32,926 patients were eligible with a median follow-up duration of 12.3 months. The percentage of patients experiencing subsequent fractures was 14.1% across the study duration, and 10.8% and 18.6% in patients with 1 and 2 years of follow-up, respectively. In the Cox proportional hazards model, patients with vertebral or NHNV index fractures had a higher subsequent fracture risk than patients with a hip index fracture (adjusted hazard ratio [aHR] 1.11 and 1.26, respectively); subsequent fracture risk was lower in males than females (aHR 0.89). Patients with baseline claims for tranquilizers and glucocorticoids had a higher subsequent fracture risk than those without (aHR 1.14 and 1.08, respectively). Additionally, baseline claims for anti-Parkinson's medications, alcoholism, and stage 4/5 chronic kidney disease were significantly associated with higher odds of subsequent fracture in the logistic regression models.

Several clinical and demographic factors were associated with a higher risk and odds of subsequent fracture. This may help to identify patients who should be prioritized for osteoporosis treatment.