Development and Validation of a Novel and HIV-Relevant Prediction Model for Fracture

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ABSTRACT Fragility fractures (fractures) among persons with HIV (PWH) account for $99 million in excess costs each year in the United States. Our prior research has shown a significantly higher annual rate of fractures among PWH – most of whom are middle-aged – compared with uninfected individuals (2.0% vs 1.4%). Such fractures are associated with increased rates of hospitalization and nursing home admissions, long-term physical disability, social isolation, and death. Because middle-age is a time when people are most economically and socially productive, fractures at this time of life set the stage for economic hardship and poorer health outcomes as these individuals grow older. Highly effective methods exist for preventing fragility fractures, reducing rates by 25%-50%. However, there are no risk prediction models that reliably identify PWH at greatest risk. The Fracture Risk Assessment Tool (FRAX) is the most widely used model for predicting fractures in the general population. It incorporates demographics (age, sex, race) and key risk factors (body mass index, previous fracture, parental fracture, current smoking, glucocorticoid use, rheumatoid arthritis, secondary osteoporosis, and hazardous alcohol use). For settings where dual-energy x-ray absorptiometry is available, sensitivity of FRAX can be improved by adding bone mineral density (BMD) to the algorithm. However, our prior studies suggest that FRAX underperforms among PWH, exhibiting poor discrimination (C statistic 0.59) and sensitivity (0.06). We believe this is because FRAX does not account for risk factors that are important to PWH. For example, FRAX does not account for falls, hepatitis C and B viruses, substance use disorder, multimorbidity, polypharmacy, use of other medications associated with fractures, or physiologic frailty – all of which have been associated with fractures among PWH. Finally, FRAX does not account for antiretroviral therapy (ART) use. Individual ART as well as ART classes have been independently associated with fracture. Leveraging an outstanding team of collaborators and research platforms, we will develop, validate and disseminate a Fracture Risk Assessment Calculator based on FRAX but that incorporates HIV-relevant risk factors (FRAC-HIV) to calculate the probability of a fracture among PWH in the next year. We have extensive experience working with the Veterans Aging Cohort Study (VACS), the largest cohort of PWH in North America, which will serve as our development cohort. To assess generalizability, we will externally validate the model using electronic health record data from Yale New Haven Healthcare System and Boston Medical Center. Our final aim sets the stage for the implementation of this predictive model via the development of a web-based fracture risk prediction calculator, which will be directly informed by insights from providers who care for PWH. FRAC-HIV will reconceptualize and facilitate clinical decision-making for fracture prevention in PWH by emphasizing the role of clinically modifiable risk factors. Our findings will lay the foundation for future intervention trials that will incorporate FRAC-HIV into clinical care algorithms to prevent fractures among PWH.