Elsevier

Bone

Volume 121, April 2019, Pages 134-138
Bone

Full Length Article
FRAX is a robust predictor of baseline vertebral fractures in multiple myeloma patients

https://doi.org/10.1016/j.bone.2018.09.013Get rights and content

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.

Introduction

It is estimated that approximately 30,280 new patients are diagnosed with multiple myeloma in annually [1]. Bone pathophysiology plays a key role in increasing morbidity in these patients, with osteolytic lesions being one of the major presenting features of the disease. In line with the extensive bone loss observed in myeloma patients, hip fractures, vertebral fractures and osteoporosis are serious and disabling complications [2].

Indeed, multiple myeloma is a plasma cell neoplasm in which the bone and bone marrow microenvironment has a been shown to exert major impact on the course of plasma cell survival [3]. For many years, the standard of care has involved a detailed musculoskeletal survey, considered essential for evaluating patients with bone fractures as well as to determine the extent of osteolytic lesions [4]. In 2014, the international myeloma working group included advanced imaging to aid in the assessment of bone lesions for newly diagnosed myeloma patients [5]. Those recommendations included bone MRI (magnetic resonance imaging) and PET (positron emission tomography) based on the premise that advanced imaging technology would be able to differentiate smoldering myeloma from active myeloma [5].

The early identification of bone disease in multiple myeloma is an important addition, as the extent of bone disease changes treatment course and guides the efficacy of preventive treatment interventions. In particular, prognosis is significantly worse for patients with more than three focal lesions post induction as detected by PET scan [6]. In this early identification scenario, there is a continued need to identify additional factors that may aid and/or enhance the earlier detection of bone disease. The FRAX score is a population-based computerized scoring system for predicting the 10 years risk of hip fracture and osteoporosis [7]. This scoring system was developed from population-based studies and uses common variables such as patient's age, weight, height, smoking status, alcohol consumption, and previous bone scan results when available [8].

At our Institution, Total Therapy (TT) protocols included ample information from frequent MRI's and PET scans. However, these advanced imaging resources is not available in routine oncology practice. Therefore, we propose that using a simple scoring system (FRAX) may be helpful for assessing the risk of fracture and provide insight into bone health for myeloma patients.

In this analysis, the baseline FRAX score of newly diagnosed myeloma patients was used to predict the future risk of fracture in newly diagnosed myeloma patients.

Section snippets

Methodology

With IRB approval, data from patients treated at the University of Arkansas for Medical Sciences (UAMS) Myeloma Institute for Research and Therapy (MIRT), between 8/2008 and 9/2017, under the Total Therapy protocol 4 (TT4) [9], and the Total Therapy protocol 5 (TT5) the details of which have been presented elsewhere [10] were interrogated. The TT4 protocol enrolled newly diagnosed transplant eligible patients with low risk multiple myeloma defined by gene expression profile (low GEP score

Results

In this analysis, 432 patients were identified (median age, 61 years old range (43–76); 37% female, median height 173 cm, median weight 93 kg and 87% are white. In the cohort, fractures were identified in 203 patients at baseline. Median MOS and HFS for TT4 patients were 5.6 and 0.5, respectively, while median MOS and HFS for TT5 patients were 6.2 and 0.7, respectively. Multivariate logistic regression confirmed age, race, sex, BMI, major osteoporotic score, and hip fracture score did not

Discussion

Previous studies have demonstrated a fundamental role for altered bone pathology in myeloma bone disease and progression [3]. Asynchronous bone turnover (in which there is an increased osteoclastic activity without a proportional increase in osteoblastic activity,) is commonly encountered in multiple myeloma. Osteoclastogenesis and bone resorption are hyper stimulated predominantly due to the dysregulation of three TNF family members: RANK, its ligand (RANKL), and decoy receptor osteoprotegerin

Acknowledgements

These studies were supported in part by NIH R01CA166060 (LJS).

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