Fragility fractures occur 9 million times per year worldwide [1], lead to significant disability and excessive mortality [1,2], and cost $19 billion per year in the United States alone [3]. Fragility fractures are projected to increase substantially as the population ages [3,4], making them a significant public health issue. Concurrently, there have been precipitous decreases in osteoporosis screening and treatment. These decreases are likely related to a multitude of factors, including poor implementation of fracture risk assessment tools, media attention of rare side effects of bisphosphonate therapies, and reduced dual energy absorptiometry (DXA) reimbursement rates [5]. However, this combination of an aging population and unacceptably low rates of osteoporosis screening and therapy has been deemed a "crisis in osteoporosis care" and could have devastating consequences to the U.S. population if not adequately addressed [5].

One dreaded side effect of antiresorptive osteoporosis therapy is atypical femur fracture (AFF). Atypical femur fractures have been described with long-term bisphosphonate and denosumab therapy. They have specific radiologic characteristics, including sub-trochanteric location, transverse or short oblique (rather than spiral) orientation, and non-comminution [6]. While these fractures are rare (less than 1 in 1,000 with 5 years of bisphosphonate use), patients often read about them and decline to be treated due to concerns about experiencing them.

Few studies have examined AFFs, but the most clear risk factors are years on antiresorptive therapy, Asian race/ethnicity, and glucocorticoids. Drug holidays are protective. Very few Black patients were reported to have AFF in the largest study from California, so it is possible this is a protective factor [7]. However, these risk and protective factors are insufficient to identify patients at high or low risk of this side effect, and more individualized information for practicing clinicians is needed.

Recently, advances in 3D modeling have allowed for the measurement of trabecular and cortical parameters from DXA images. This technique uses a 3D shape and bone density statistical model that is registered onto the proximal femur DXA scan to obtain a subject-specific model of the patient's bone in 3D [8]. This technique, referred to as 3D-DXA, provides structural measurements that correlate well with QCT. It is possible that this technique may demonstrate differences in bone structure in patients with high AFF risk.

Thus, the purpose of this study is to identify a cohort of patients from the University of Chicago who have had AFFs and compare them to controls matched on age, sex, BMI, race, and previous exposure to antiresorptive medicines.

For the Pritzker Summer Research Program: The ideal student will have an interest in either internal medicine, radiology, or orthopedics.

References

1. Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int. 2006;17:1726-33.

2. Johnell O, Kanis JA, Oden A, et al. Mortality after osteoporotic fractures. Osteoporos Int. 2004;15:38-42.

3. Burge R, Dawson-Hughes B, Solomon DH, et al. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005-2025. J Bone Miner Res. 2007;22:465-75.

4. Gullberg B, Johnell O, Kanis JA. World-wide projections for hip fracture. Osteoporos Int. 1997;7:407-13.

5. Khosla S, Shane E. A crisis in the treatment of osteoporosis. J Bone Miner Res. 2016;31:1485-7.

6. Shane E, Burr D, Abrahamsen B, et al. Atypical subtrochanteric and diaphyseal femoral fractures: second report of a task force of the American Society for Bone and Mineral Research. J Bone Miner Res. 2014;29:123.

7. Black DM, Geiger EJ, Eastell R, et al. Atypical femur fracture risk versus fragility fracture prevention with bisphosphonates. N Engl J Med. 2020;383:743;53.

8. Humbert L, Martelli Y, Fonolla R, et al. 3D-DXA: assessing the femoral shape, the trabecular macrostructure and the cortex in 3D from DXA images. IEEE Trans Med Imaging. 2016;36:27-39.

1. Characterize demographics and comorbidities of multiracial patients with atypical femur fractures

2. For patients with prior bone density scan, compare 3D-DXA imaging characteristics to controls matched by age, sex, BMI, race, and antiresorptive exposure

Summary: Potential subjects with atypical femur fractures will be identified using ICD codes; however, the ICD codes are not sensitive enough to identify these fractures, which have specific radiologic features. Thus, clinical course and imaging description/review is needed of potential fractures. Thus, the student will review charts of subjects and review imaging, description of fracture, trauma, prior exposure to osteoporosis medication, and overall course after fracture. The student will capture images for faculty to review if available. PI and other faculty will review images to verify the fracture meets the definition of an AFF.

Additionally, the PI will be matching cases to controls, and the student may review the controls to review and verify characteristics. Depending on the timeline of the project, the student can become involved with statistical analysis.

Epic access will be needed for the project.