FRAX is a robust predictor of baseline vertebral fractures in multiple myeloma patients Conference Paper uri icon

abstract

  • FRAX is a commonly used tool to evaluate patient fracture risk based on individual patient models that integrate the risks associated with clinical risk factors with or without bone mineral density (BMD) at the femoral neck. Retrospectively, factors identified by the FRAX scoring algorithm were used to predict the risk for vertebral compression fractures at baseline in newly diagnosed multiple myeloma patients. The data were derived from myeloma patients enrolled in Total Therapy Protocols (TT4 & TT5) between 8/2008 and 9/2017. FRAX scores were calculated and baseline PET and MRI imaging obtained. Univariate and multivariate logistic regression analyses determined the association between FRAX components and the existence of vertebral compression fractures, both pathologic and osteoporotic. The patient population had a median age of 61 years (43-76), 37% female, and 87% white. The median major osteoporotic score (MOS) and Hip fracture scores (HFS) for TT4 patients (low-risk myeloma) were 5.6 and 0.5, respectively, while median MOS and HFS for TT5 (high risk myeloma) patients were 6.2 and 0.7, respectively. The odds ratio for fracture at diagnosis in patients with elevated MOS (>2), and HFS (>4.5) was significant OR (1.48, 95% confidence interval (1.35,1.62)) and OR (1.61, 95% confidence interval (1.42, 1.81)), respectively. In sum, an elevated baseline FRAX score was highly predictive of baseline vertebral fractures in MM patients at presentation. In addition, patients with higher FRAX scores had significantly shorter survival in the low-risk (TT4) group but this survival effect was not seen in the high-risk (TT5) group. These findings suggest that FRAX assessment of baseline fracture risk is beneficial in MM patients to identify an individual patients' risk of vertebral fracture.

altmetric score

  • 1

author list (cited authors)

  • Atrash, S., Dua, I., Buros, A. F., Van Rhee, F., Suva, L. J., Thanendrarajan, S., ... Zangari, M.

citation count

  • 1

publication date

  • September 2018

published in