Analysis of risk factors and predictive efficacy of senile osteoporosis fracture based on biochemical indicators of bone metabolism

Predictive Factors for Senile Osteoporosis Fractures

  • Yufang Mao Sports Medicine, Zhuzhou People's Hospital
  • Kanghua Li
  • Bing Zhu
  • Jiang Long
Keywords: Bone metabolism, Osteoporotic fracture in the elderly, Risk prediction, Predictive efficacy

Abstract


Background: Osteoporosis is characterized by low bone mass and altered bone microarchitecture. Patients with osteoporosis are at significantly increased risk for fragility fractures, which ultimately suffer fractures. The occurrence and development of osteoporotic fractures are significantly associated with high mortality, reduced quality of life as well as comorbidities. Biochemical indicators of bone metabolism are important for assessing the risk of fracture occurrence. In this study, we aimed to investigate the risk factors for osteoporotic fracture in the elderly based on bone metabolism biochemical indexes and to analyze their predictive efficacy through relevant bone metabolism biochemical indexes.

Methods: A total of 254 elderly osteoporosis (OS) patients diagnosed and treated in our hospital during May 2019 to April 2022 was randomly picked, of which 100 patients were finally chosen for subsequent analysis following the inclusion and exclusion criteria. Patients were divided into OS fracture group and non-fracture group according to whether they had OS fracture. The contents of bone mineral density (BMD) and bone metabolism biochemical indexes, including Dickkopf-1 (DKK-1), sclerostin (SOST), osteoprotegerin (OPG), osteopontin (OPN), osteocalcin (BGP) and 25 hydroxyvitamin d (25 (OH) D) were detected in lumbar L2~4 and left femoral greater trochanter. The correlation between bone metabolism and BMD was evaluated using Pearson analysis. The risk factors of OS fracture were analyzed using Multivariate logistic regression analysis. The predictive value of biochemical indexes of bone metabolism on the risk of OS fracture was analyzed using ROC curve.

Results: The proportion of patients with age and lack of sunlight in the OS fracture group was significantly higher than that in the non-fracture group (P < 0.05). The BMD in lumbar L2~4 and left femoral greater trochanter of patients in the OS fracture group was lower than that of patients in the non-fracture group (P < 0.05). At 14 weeks and 16 weeks after surgery, the levels of DKK-1, SOST and OPN in the OS fracture group were higher than these in the non-fracture group, and the levels of OPG, BGP and 25 (OH) D were lower than these in the non-fracture group (P < 0.05). BMD in lumbar L2~4, BMD in femoral greater trochanter, OPG, BGP and 25 (OH) D were the protective factors (P < 0.05), and the age, lack of sunlight, DKK-1, SOST and OPN were the risk factors affecting OS fractures (P < 0.05). BMD in lumbar L2~4 was negatively correlated with DKK-1, SOST and OPN (P < 0.05), and positively correlated with BGP and 25 (OH) D (P < 0.05). 25 (OH) D was positively correlated with femoral greater trochanter BMD (P < 0.05). OPG, OPN, BGP and 25 (OH) D had certain predictive value for the occurrence of OS fracture with the areas under the curve (AUC) of 0.709, 0.761, 0.720 and 0.730 respectively. The combined detection of all indicators had the AUC of 0.940 (P < 0.05), which had a high predictive value for OS fracture.

Conclusion: Biochemical indicators of bone metabolism were closely correlated with the risk of OS fracture and had a high predictive value as influencing factors for the occurrence of OS fracture. Therefore, an accurate combination of biochemical indices could reduce the risk of fracture in the elderly, thus facilitating the development of targeted treatment plans for elderly fracture patients.

References

1.        Johnston CB, Dagar M. Osteoporosis in Older Adults. Med Clin N Am 2020; 104(5): 873-84.


2.        Noh JY, Yang Y, Jung H. Molecular Mechanisms and Emerging Therapeutics for Osteoporosis. Int J Mol Sci 2020; 21(20): 7623.


3.        Yoon BH, Yu W. Clinical Utility of Biochemical Marker of Bone Turnover: Fracture Risk Prediction and Bone Healing. J Bone Metab 2018; 25(2): 73-8.


4.        Peng J, Dong Z, Hui Z, Aifei W, Lianfu D, Youjia X. Bone Sclerostin and Dickkopf-related protein-1 are positively correlated with bone mineral density, bone microarchitecture, and bone strength in postmenopausal osteoporosis. Bmc Musculoskel Dis 2021; 22(1): 480.


5.        Kanis JA, Cooper C, Rizzoli R, Reginster JY. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporosis Int 2019; 30(1): 3-44.


6.        Aspray TJ, Hill TR. Osteoporosis and the Ageing Skeleton. Subcell Biochem 2019; 91: 453-76.


7.        Anam AK, Insogna K. Update on Osteoporosis Screening and Management. Med Clin N Am 2021; 105(6): 1117-34.


8.        Black DM, Cauley JA, Wagman R, Ensrud K, Fink HA, Hillier TA, et al. The Ability of a Single BMD and Fracture History Assessment to Predict Fracture Over 25 Years in Postmenopausal Women: The Study of Osteoporotic Fractures. J Bone Miner Res 2018; 33(3): 389-95.


9.        Holloway-Kew KL, Marijanovic N, De Abreu L, Sajjad MA, Pasco JA, Kotowicz MA. Bone mineral density in diabetes and impaired fasting glucose. Osteoporosis Int 2019; 30(9): 1799-806.


10.    Vasiliadis ES, Evangelopoulos DS, Kaspiris A, Vlachos C, Pneumaticos SG. Sclerostin and Its Involvement in the Pathogenesis of Idiopathic Scoliosis. J Clin Med 2021; 10(22): 5286.


11.    Tsentidis C, Gourgiotis D, Kossiva L, Marmarinos A, Doulgeraki A, Karavanaki K. Increased levels of Dickkopf-1 are indicative of Wnt/beta-catenin downregulation and lower osteoblast signaling in children and adolescents with type 1 diabetes mellitus, contributing to lower bone mineral density. Osteoporosis Int 2017; 28(3): 945-53.


12.    Udagawa N, Koide M, Nakamura M, Nakamichi Y, Yamashita T, Uehara S, et al. Osteoclast differentiation by RANKL and OPG signaling pathways. J Bone Miner Metab 2021; 39(1): 19-26.


13.    Jiang J, Xiao S, Xu X, Ma H, Feng C, Jia X. Isomeric flavonoid aglycones derived from Epimedii Folium exerted different intensities in anti-osteoporosis through OPG/RANKL protein targets. Int Immunopharmacol 2018; 62: 277-86.


14.    Fusaro M, Gallieni M, Aghi A, Iervasi G, Rizzo MA, Stucchi A, et al. Cigarette Smoking is Associated with Decreased Bone Gla-protein (BGP) Levels in Hemodialysis Patients. Curr Vasc Pharmacol 2018; 16(6): 603-9.


15.    Zhou Y, Yang Y, Liu Y, Chang H, Liu K, Zhang X, et al. Irp2 Knockout Causes Osteoporosis by Inhibition of Bone Remodeling. Calcified Tissue Int 2019; 104(1): 70-8.


16.    Si J, Wang C, Zhang D, Wang B, Zhou Y. Osteopontin in Bone Metabolism and Bone Diseases. Med Sci Monitor 2020; 26: e919159.


17.    Bouillon R, Marcocci C, Carmeliet G, Bikle D, White JH, Dawson-Hughes B, et al. Skeletal and Extraskeletal Actions of Vitamin D: Current Evidence and Outstanding Questions. Endocr Rev 2019; 40(4): 1109-51.

Published
2024/01/04
Section
Original paper