Osteoporosis treatment considerations based upon fracture history, fracture risk assessment, vertebral fracture assessment, and bone density in Canada

The role and place of the FRAX calculator in initiation osteoporosis treatment: an analysis of the osteoporosis center registry

Background: The growing frequency of fractures associated with osteoporosis, the significant costs of their treatment, disability and increased mortality make it an important and urgent task to optimize the diagnosis and treatment of osteoporosis in the Russian Federation.

Aim: The aim of this study was analyzed of using modern diagnostic criteria for osteoporosis by specialists when they making a clinical decision to initiate treatment for osteoporosis, including an estimate of the 10-year probability of fractures according to FRAX.

Materials and methods: The study was conducted in the city consultative and diagnostic center for the prevention of osteoporosis, St. Petersburg. The register of the osteoporosis center for 2018–2021 was used to select patients for the study. Based on the analysis of registry data, a sample of 362 patients with newly diagnosed osteoporosis was obtained. In the resulting sample, the existing FRAX value was assessed on the therapeutic intervention threshold graph, all of them analyzed the primary medical documentation, as well as the available DXA densitometry data.

Results: In this study, we assessed the place of FRAX 10-year risk of major osteoporotic fractures in the clinical decision of an osteoporosis specialist to start anti-osteoporosis therapy, in this case taken as the «gold standard». The study found that a positive FRAX score had a high predictive value of 100%. In contrast, the negative predictive value was very low (19.5%): a FRAX value below the intervention threshold did not guarantee a truly low fracture risk and no need to start osteoporosis treatment.

Conclusion: Despite the fact that both densitometry and FRAX have significant limitations in use, and cannot identify all patients with a high risk of fractures, their combined use increases the prognostic value of the methods. FRAX technology in routine practice allows, in addition to clinical and instrumental methods for diagnosing high-risk fractures, to identify candidates for the treatment of osteoporosis, and should be used in accordance with clinical recommendations.

Comparison of screening tools for optimizing fracture prevention in Canada

The best screening strategy to identify treatment qualification based upon indicators of high fracture risk (low-trauma fractures of the hip, spine, or multiple fracture episodes at other sites; high fracture probability with the Canadian fracture risk assessment [FRAX®] tool major osteoporotic fracture [MOF] computed with bone mineral density [BMD] > 20%; or vertebral fracture on vertebral fracture assessment [VFA]) was FRAX-MOF without BMD using a cutoff of ≥ 10%.

PURPOSE

To inform clinical practice guidelines in Canada, we compared multiple screening tools using the population-based Manitoba BMD Program registry.

METHODS

The study populations consisted of (a) 28,906 individuals > 50 years or older, and (b) 15,429 women age > 65 years undergoing baseline BMD assessment (2010-2018). We considered two treatment qualifications: Treatment Approach 1: prior high-risk fracture, high fracture probability (FRAX-MOF with BMD > 20%), or vertebral fracture on VFA; Treatment Approach 2: Approach 1 or an osteoporotic BMD T score. Candidate screening tools were FRAX-MOF without BMD, age alone, weight alone, SCORE, ORAI, SOFSURF, OSIRIS, ABONE, and OST. Healthcare records were assessed for the presence of incident fracture diagnoses.

RESULTS

Among all individuals, FRAX-MOF without BMD demonstrated the best ability to identify those satisfying Treatment Approach 1 (area under the curve [AUC 0.863]) and was significantly better than all other screening tools (P < 0.001). For identification of individuals satisfying Treatment Approach 2, FRAX-MOF without BMD showed moderate stratification (AUC 0.735), slightly lower than OSIRIS (AUC 0.752, P < 0.05), similar to SCORE (AUC 0.739, P > 0.05) and significantly better than all other screening tools (P < 0.05). For prediction of incident MOF, FRAX-MOF without BMD achieved the highest performance (AUC 0.652), and was significantly better than all other screening tools except OSIRIS. AUCs among women age > 65 years tended to be greater with a similar ranking, and no tool outperformed FRAX-MOF without BMD. Based upon a summary score, the highest ranked strategy was FRAX-MOF without BMD using a cutoff of 10%.

CONCLUSIONS

All screening tools show some ability to identify individuals qualifying for treatment and stratify risk for incident fracture. For treatment based upon indicators of high fracture risk, the best performing strategy was FRAX-MOF without BMD using a cutoff of ≥ 10%.