Estimating the 10-year fracture risk among persons with HIV and person without HIV: A comparative study - Pramukti, S.Kp., MsC, Iqbal; Ibrahim, Kusman; Lukman, Mamat; Harun, Hasniatisari; Nugraha, Andri; Lin, Chung-Ying (Faculty of Nursing Universitas Padjadjaran, 2025)
Background: The risk of osteoporotic fracture among persons with HIV was higher than the persons without HIV. Traditional factors are also found as the risk factor affecting fracture risk among persons with HIV and general population. Predicting the fracture risk among the high-risk group is important to develop a comprehensive fracture prevention program. Purpose: This study aimed to compare the estimation of the 10-year fracture risk between persons with HIV and persons without HIV using the FRAX™ algorithm. Methods: This study recruited 245 participants from August to November 2023, while 221 participants agreed to participate. The participants consist of 107 persons with HIV and 114 persons without HIV. The estimation of the ten-year probability of major osteoporotic and hip fractures was calculated using the FRAX™ algorithm. The participant's characteristics related to osteoporotic fracture risk was analyzed using a Chi-Square analysis. Results: The overall mean score of 10-year probability of major osteoporotic fracture (MOF) was 3.1% (SD 1.9) for the HIV group and 2.7% (SD 2.3) for non-HIV. For the 10-year probability, hip fracture (HF) risk was 0.5% (SD 0.5) for the HIV group and 0.6% (SD 0.9) for non-HIV. For MOF, HIV persons with fracture history showed a lower score (3.5%) compared to persons without HIV (5.3%). Smoker HIV persons showed the same MOF score (4.6% vs. 4.6%) but lower HF score (0.8% vs. 1.6%) when comparing to persons without HIV, respectively. HIV persons with glucocorticoid use showed a higher MOF probability score than persons without HIV (2.8% vs 2.7%). Conclusions: The 10-year fracture risk was higher among persons with HIV compared to persons without HIV. Fracture history, smoking behavior, and glucocorticoid use were identified as the potential factors associated with the risk. Further analysis using multivariate regression analysis may require to confirm the factors associated with high fracture risk.